>>Hello and welcome today's cube presentation of eight of us startup showcase. I'm john for your host highlighting the hottest companies and devops data analytics and cloud management lisa martin and David want are here to kick it off. We've got a great program for you again. This is our, our new community event model where we're doing every quarter, we have every new episode, this is quarter three this year or episode three, season one of the hottest cloud startups and we're gonna be featured. Then we're gonna do a keynote package and then 15 countries will present their story, Go check them out and then have a closing keynote with a practitioner and we've got some great lineups, lisa Dave, great to see you. Thanks for joining me. Hey >>guys, great to be here. >>So David got to ask you, you know, back in events last night we're at the 14 it's event where they had the golf PGA championship with the cube Now we got the hybrid model, This is the new normal. We're in, we got these great companies were showcasing them. What's your take? >>Well, you're right. I mean, I think there's a combination of things. We're seeing some live shows. We saw what we did with at mobile world Congress. We did the show with AWS storage day where it was, we were at the spheres, there was no, there was a live audience, but they weren't there physically. It was just virtual and yeah, so, and I just got pained about reinvent. Hey Dave, you gotta make your flights. So I'm making my flights >>were gonna be at the amazon web services, public sector summit next week. At least a lot, a lot of cloud convergence going on here. We got many companies being featured here that we spoke with the Ceo and their top people cloud management, devops data, nelson security. Really cutting edge companies, >>yes, cutting edge companies who are all focused on acceleration. We've talked about the acceleration of digital transformation the last 18 months and we've seen a tremendous amount of acceleration in innovation with what these startups are doing. We've talked to like you said, there's, there's C suite, we've also talked to their customers about how they are innovating so quickly with this hybrid environment, this remote work and we've talked a lot about security in the last week or so. You mentioned that we were at Fortinet cybersecurity skills gap. What some of these companies are doing with automation for example, to help shorten that gap, which is a big opportunity for the >>job market. Great stuff. Dave so the format of this event, you're going to have a fireside chat with the practitioner, we'd like to end these programs with a great experienced practitioner cutting edge in data february. The beginning lisa are gonna be kicking off with of course Jeff bar to give us the update on what's going on AWS and then a special presentation from Emily Freeman who is the author of devops for dummies, she's introducing new content. The revolution in devops devops two point oh and of course jerry Chen from Greylock cube alumni is going to come on and talk about his new thesis castles in the cloud creating moats at cloud scale. We've got a great lineup of people and so the front ends can be great. Dave give us a little preview of what people can expect at the end of the fireside chat. >>Well at the highest level john I've always said we're entering that sort of third great wave of cloud. First wave was experimentation. The second big wave was migration. The third wave of integration, Deep business integration and what you're going to hear from Hello Fresh today is how they like many companies that started early last decade. They started with an on prem Hadoop system and then of course we all know what happened is S three essentially took the knees out from, from the on prem Hadoop market lowered costs, brought things into the cloud and what Hello Fresh is doing is they're transforming from that legacy Hadoop system into its running on AWS but into a data mess, you know, it's a passionate topic of mine. Hello Fresh was scaling they realized that they couldn't keep up so they had to rethink their entire data architecture and they built it around data mesh Clements key and christoph Soewandi gonna explain how they actually did that are on a journey or decentralized data measure >>it and your posts have been awesome on data measure. We get a lot of traction. Certainly you're breaking analysis for the folks watching check out David Landes, Breaking analysis every week, highlighting the cutting edge trends in tech Dave. We're gonna see you later, lisa and I are gonna be here in the morning talking about with Emily. We got Jeff Barr teed up. Dave. Thanks for coming on. Looking forward to fireside chat lisa. We'll see you when Emily comes back on. But we're gonna go to Jeff bar right now for Dave and I are gonna interview Jeff. Mm >>Hey Jeff, >>here he is. Hey, how are you? How's it >>going really well. >>So I gotta ask you, the reinvent is on, everyone wants to know that's happening right. We're good with Reinvent. >>Reinvent is happening. I've got my hotel and actually listening today, if I just remembered, I still need to actually book my flights. I've got my to do list on my desk and I do need to get my flights. Uh, really looking forward to it. >>I can't wait to see the all the announcements and blog posts. We're gonna, we're gonna hear from jerry Chen later. I love the after on our next event. Get your reaction to this castle and castles in the cloud where competitive advantages can be built in the cloud. We're seeing examples of that. But first I gotta ask you give us an update of what's going on. The ap and ecosystem has been an incredible uh, celebration these past couple weeks, >>so, so a lot of different things happening and the interesting thing to me is that as part of my job, I often think that I'm effectively living in the future because I get to see all this really cool stuff that we're building just a little bit before our customers get to, and so I'm always thinking okay, here I am now, and what's the world going to be like in a couple of weeks to a month or two when these launches? I'm working on actually get out the door and that, that's always really, really fun, just kind of getting that, that little edge into where we're going, but this year was a little interesting because we had to really significant birthdays, we had the 15 year anniversary of both EC two and S three and we're so focused on innovating and moving forward, that it's actually pretty rare for us at Aws to look back and say, wow, we've actually done all these amazing things in in the last 15 years, >>you know, it's kind of cool Jeff, if I may is is, you know, of course in the early days everybody said, well, a place for startup is a W. S and now the great thing about the startup showcases, we're seeing the startups that are very near, or some of them have even reached escape velocity, so they're not, they're not tiny little companies anymore, they're in their transforming their respective industries, >>they really are and I think that as they start ups grow, they really start to lean into the power of the cloud. They as they start to think, okay, we've we've got our basic infrastructure in place, we've got, we were serving data, we're serving up a few customers, everything is actually working pretty well for us. We've got our fundamental model proven out now, we can invest in publicity and marketing and scaling and but they don't have to think about what's happening behind the scenes. They just if they've got their auto scaling or if they're survivalists, the infrastructure simply grows to meet their demand and it's it's just a lot less things that they have to worry about. They can focus on the fun part of their business which is actually listening to customers and building up an awesome business >>Jeff as you guys are putting together all the big pre reinvented, knows a lot of stuff that goes on prior as well and they say all the big good stuff to reinvent. But you start to see some themes emerged this year. One of them is modernization of applications, the speed of application development in the cloud with the cloud scale devops personas, whatever persona you want to talk about but basically speed the speed of of the app developers where other departments have been slowing things down, I won't say name names, but security group and I t I mean I shouldn't have said that but only kidding but no but seriously people want in minutes and seconds now not days or weeks. You know whether it's policy. What are some of the trends that you're seeing around this this year as we get into some of the new stuff coming out >>So Dave customers really do want speed and for we've actually encapsulate this for a long time in amazon in what we call the bias for action leadership principle where we just need to jump in and move forward and and make things happen. A lot of customers look at that and they say yes this is great. We need to have the same bias fraction. Some do. Some are still trying to figure out exactly how to put it into play. And they absolutely for sure need to pay attention to security. They need to respect the past and make sure that whatever they're doing is in line with I. T. But they do want to move forward. And the interesting thing that I see time and time again is it's not simply about let's adopt a new technology. It's how do we how do we keep our workforce engaged? How do we make sure that they've got the right training? How do we bring our our I. T. Team along for this. Hopefully new and fun and exciting journey where they get to learn some interesting new technologies they've got all this very much accumulated business knowledge they still want to put to use, maybe they're a little bit apprehensive about something brand new and they hear about the cloud, but there by and large, they really want to move forward. They just need a little bit of help to make it happen real >>good guys. One of the things you're gonna hear today, we're talking about speed traditionally going fast. Oftentimes you meant you have to sacrifice some things on quality and what you're going to hear from some of the startups today is how they're addressing that to automation and modern devoPS technologies and sort of rethinking that whole application development approach. That's something I'm really excited to see organization is beginning to adopt so they don't have to make that tradeoff anymore. >>Yeah, I would never want to see someone sacrifice quality, but I do think that iterating very quickly and using the best of devoPS principles to be able to iterate incredibly quickly and get that first launch out there and then listen with both ears just as much as you can, Everything. You hear iterate really quickly to meet those needs in, in hours and days, not months, quarters or years. >>Great stuff. Chef and a lot of the companies were featuring here in the startup showcase represent that new kind of thinking, um, systems thinking as well as you know, the cloud scale and again and it's finally here, the revolution of deVOps is going to the next generation and uh, we're excited to have Emily Freeman who's going to come on and give a little preview for her new talk on this revolution. So Jeff, thank you for coming on, appreciate you sharing the update here on the cube. Happy >>to be. I'm actually really looking forward to hearing from Emily. >>Yeah, it's great. Great. Looking forward to the talk.

(upbeat music) >> Okay, welcome back everyone. CUBE's coverage of re:MARS, here in Las Vegas, in person. I'm John Furrier, host of theCUBE. This is the analyst panel wrap up analysis of the keynote, the show, past one and a half days. We got two great guests here. We got Andy Thurai, Vice President, Principal Consultant, Constellation Research. Larry Carvalho, Principal Consultant at RobustCloud LLC. Congratulations going out on your own. >> Thank you. >> Andy, great to see you. >> Great to see you as well. >> Guys, thanks for coming out. So this is the session where we break down and analyze, you guys are analysts, industry analysts, you go to all the shows, we see each other. You guys are analyzing the landscape. What does this show mean to you guys? 'Cause this is not obvious to the normal tech follower. The insiders see the confluence of robotics, space, automation and machine learning. Obviously, it's IoTs, industrials, it's a bunch of things. But there's some dots to connect. Let's start with you, Larry. What do you see here happening at this show? >> So you got to see how Amazon started, right? When AWS started. When AWS started, it primarily took the compute storage, networking of Amazon.com and put it as a cloud service, as a service, and started selling the heck out of it. This is a stage later now that Amazon.com has done a lot of physical activity, and using AIML and the robotics, et cetera, it's now the second phase of innovation, which is beyond digital transformation of back office processes, to the transformation of physical processes where people are now actually delivering remotely and it's an amazing area. >> So back office's IT data center kind of vibe. >> Yeah. >> You're saying front end, industrial life. >> Yes. >> Life as we know it. >> Right, right. I mean, I just stopped at a booth here and they have something that helps anybody who's stuck in the house who cannot move around. But with Alexa, order some water to bring them wherever they are in the house where they're stuck in their bed. But look at the innovation that's going on there right at the edge. So I think those are... >> John: And you got the Lunar, got the sex appeal of the space, Lunar Outpost interview, >> Yes. >> those guys. They got Rover on Mars. They're going to have be colonizing the moon. >> Yes. >> I made a joke, I'm like, "Well, I left a part back on earth, I'll be right back." (Larry and Andy laugh) >> You can't drive back to the office. So a lot of challenges. Andy, what's your take of the show? Take us your analysis. What's the vibe, what's your analysis so far? >> It's a great show. So, as Larry was saying, one of the thing was that when Amazon started, right? So they were more about cloud computing. So, which means is they try to commoditize more of data center components or compute components. So that was working really well for what I call it as a compute economy, right? >> John: Mm hmm. >> And I call the newer economy as more of a AIML-based data economy. So when you move from a compute economy into a data economy, there are things that come into the forefront that never existed before, never popular before. Things like your AIML model creation, model training, model movement, model influencing, all of the above, right? And then of course the robotics has come long way since then. And then some of what they do at the store, or the charging, the whole nine yards. So, the whole concept of all of these components, when you put them on re:Invent, such a big show, it was getting lost. So that's why they don't have it for a couple of years. They had it one year. And now all of a sudden they woke up and say, "You know what? We got to do this!" >> John: Yeah. >> To bring out this critical components that we have, that's ripe, mature for the world to next component. So that's why- I think they're pretty good stuff. And some of the robotics things I saw in there, like one of them I posted on my Twitter, it's about the robot dog, sniffing out the robot rover, which I thought was pretty hilarious. (All laugh) >> Yeah, this is the thing. You're seeing like the pandemic put everything on hold on the last re:Mars, and then the whole world was upside down. But a lot of stuff pulled forward. You saw the call center stuff booming. You saw the Zoomification of our workplace. And I think a lot of people got to the realization that this hybrid, steady-state's here. And so, okay. That settles that. But the digital transformation of actually physical work? >> Andy: Yeah. >> Location, the walk in and out store right over here we've seen that's the ghost store in Seattle. We've all been there. In fact, I was kind of challenged, try to steal something. I'm like, okay- (Larry laughs) I'm pulling all my best New Jersey moves on everyone. You know? >> Andy: You'll get charged for it. >> I couldn't get away with it. Two double packs, drop it, it's smart as hell. Can't beat the system. But, you bring that to where the AI machine learning, and the robotics meet, robots. I mean, we had robots here on theCUBE. So, I think this robotics piece is a huge IoT, 'cause we've been covering industrial IoT for how many years, guys? And you could know what's going on there. Huge cyber threats. >> Mm hmm. >> Huge challenges, old antiquated OT technology. So I see a confluence in the collision between that OT getting decimated, to your point. And so, do you guys see that? I mean, am I just kind of seeing mirage? >> I don't see it'll get decimated, it'll get replaced with a newer- >> John: Dave would call me out on that. (Larry laughs) >> Decimated- >> Microsoft's going to get killed. >> I think it's going to have to be reworked. And just right now, you want do anything in a shop floor, you have to have a physical wire connected to it. Now you think about 5G coming in, and without a wire, you get minute details, you get low latency, high bandwidth. And the possibilities are endless at the edge. And I think with AWS, they got Outposts, they got Snowcone. >> John: There's a threat to them at the edge. Outpost is not doing well. You talk to anyone out there, it's like, you can't find success stories. >> Larry: Yeah. >> I'm going to get hammered by Amazon people, "Oh, what're you're saying that?" You know, EKS for example, with serverless is kicking ass too. So, I mean I'm not saying Outpost was wrong answer, it was a right at the time, what, four years ago that came out? >> Yeah. >> Okay, so, but that doesn't mean it's just theirs. You got Dell Technologies want some edge action. >> Yeah. >> So does HPE. >> Yes. >> So you got a competitive edge situation. >> I agree with that and I think that's definitely not Amazon's strong point, but like everything, they try to make it easy to use. >> John: Yeah. >> You know, you look at the AIML and they got Canvas. So Canvas says, hey, anybody can do AIML. If they can do that for the physical robotic processes, or even like with Outpost and Snowcone, that'll be good. I don't think they're there yet, and they don't have the presence in the market, >> John: Yeah. >> like HPE and, >> John: Well, let me ask you guys this question, because I think this brings up the next point. Will the best technology win or will the best solution win? Because if cloud's a platform and all software's open source, which you can make those assumptions, you then say, hey, they got this killer robotics thing going on with Artemis and Moonshot, they're trying to colonize the moon, but oh, they discovered a killer way to solve a big problem. Does something fall out of this kind of re:Mars environment, that cracks the code and radically changes and disrupts the IoT game? That's my open question. I don't know the answer. I'd love to get your take on what might be possible, what wild card's out there around, disrupting the edge. >> So one thing I see the way, so when IoT came into the world of play, it's when you're digitizing the physical world, it's IoT that does digitalization part of that actually, right? >> But then it has its own set of problems. >> John: Yeah. >> You're talking about you installing sensor everywhere, right? And not only installing your own sensor, but also you're installing competitor sensors. So in a given square feet how many sensors can you accommodate? So there are physical limitations on liabilities of bandwidth and networking all of that. >> John: And integration. >> As well. >> John: Your point. >> Right? So when that became an issue, this is where I was talking to the robotic guys here, a couple of companies, and one of the use cases they were talking about, which I thought was pretty cool, is, rather than going the sensor route, you go the robot route. So if you have either a factor that you want to map out, you put as many sensors on your robot, whatever that is, and then you make it go around, map the whole thing, and then you also do a surveillance in the whole nine yards. So, you can either have a fixed sensors or you can have moving sensors. So you can have three or four robots. So initially, when I was asking them about the price of it, when they were saying about a hundred thousand dollars, I was like, "Who would buy that?" (John and Larry laugh) >> When they then explained that, this is the use case, oh, that makes sense, because if you had to install, entire factory floor sensors, you're talking about millions of dollars. >> John: Yeah. >> But if you do the moveable sensors in this way, it's a lot cheaper. >> John: Yeah, yeah. >> So it's based on your use case, what are your use cases? What are you trying to achieve? >> The general purpose is over. >> Yeah. >> Which you're getting at, and that the enablement, this is again, this is the cloud scale open question- >> Yep. >> it's, okay, the differentiations isn't going to be open source software. That's open. >> It's going to be in the, how you configure it. >> Yes. >> What workflows you might have, the data streams. >> I think, John, you're bringing up a very good point about general purpose versus special purpose. Yesterday Zoox was on the stage and when they talked about their vehicle, it's made just for self-driving. You walk around in Vegas, over here, you see a bunch of old fashioned cars, whether they're Ford or GM- >> and they put all these devices around it, but you're still driving the same car. >> John: Yeah, exactly. >> You can retrofit those, but I don't think that kind of IoT is going to work. But if you redo the whole thing, we are going to see a significant change in how IoT delivers value all the way from the industrial to home, to healthcare, mining, agriculture, it's going to have to redo. I'll go back to the OT question. There are some OT guys, I know Rockwell and Siemens, some of them are innovating faster. The ones who innovate faster to keep up with the IT side, as well as the MLAI model are going to be the winners on that one. >> John: Yeah, I agree. Andy, your thoughts on manufacturing, you brought up the sensor thing. Robotics ultimately is, end of the day, an opportunity there. Obviously machine learning, we know what that does. As we move into these more autonomous builds, what does that look like? And is Amazon positioned well there? Obviously they have big manufacturers. Some are saying that they might want to get out of that business too, that Jassy's evaluating that some are saying. So, where does this all lead for that robotics manufacturing lifestyle, walk in, grab my food? 'Cause it's all robotics and AI at the end of the day, I got sensors, I got cameras, I got non-humans moving heavy lifting stuff, fixing the moon will be done by robots, not humans. So it's all coming. What's your analysis? >> Well, so, the point about robotics is on how far it has come, it is unbelievable, right? Couple of examples. One was that I was just talking to somebody, was explaining to them, to see that robot dog over there at the Boston Dynamics one- >> John: Yeah. >> climbing up and down the stairs. >> Larry: Yeah. >> That's more like the dinosaur movie opening the doors scene. (John and Larry laugh) It's like that for me, because the coordinated things, it is able to go walk up and down, that's unbelievable. But okay, it does that, and then there was also another video which is going on viral on the internet. This guy kicks the dog, robot dog, and then it falls down and it gets back up, and the sentiment that people were feeling for the dog, (Larry laughs) >> you can't, it's a robot, but people, it just comes at that level- >> John: Empathy, for a non-human. >> Yeah. >> But you see him, hey you, get off my lawn, you know? It's like, where are we? >> It has come to that level that people are able to kind of not look at that as a robot, but as more like a functioning, almost like a pet-level, human-level being. >> John: Yeah. >> And you saw that the human-like walking robot there as well. But to an extent, in my view, they are all still in an experimentation, innovation phase. It doesn't made it in the industrial terms yet. >> John: Yeah, not yet, it's coming. >> But, the problem- >> John: It's coming fast. That's what I'm trying to figure out is where you guys see Amazon and the industry relative to what from the fantasy coming reality- >> Right. >> of space in Mars, which is, it's intoxicating, let's face it. People love this. The nerds are all here. The geeks are all here. It's a celebration. James Hamilton's here- >> Yep. >> trying to get him on theCUBE. And he's here as a civilian. Jeff Barr, same thing. I'm here, not for Amazon, I bought a ticket. No, you didn't buy a ticket. (Larry laughs) >> I'm going to check on that. But, he's geeking out. >> Yeah. >> They're there because they want to be here. >> Yeah. >> Not because they have to work here. >> Well, I mean, the thing is, the innovation velocity has increased, because, in the past, remember, the smaller companies couldn't innovate because they don't have the platform. Now Compute is a platform available at the scale you want, AI is available at the scale. Every one of them is available at the scale you want. So if you have an idea, it's easy to innovate. The innovation velocity is high. But where I see most of the companies failing, whether startup or big company, is that you don't find the appropriate use case to solve, and then don't sell it to the right people to buy that. So if you don't find the right use case or don't sell the right value proposition to the actual buyer, >> John: Mm hmm. >> then why are you here? What are you doing? (John laughs) I mean, you're not just an invention, >> John: Eh, yeah. >> like a telephone kind of thing. >> Now, let's get into next talk track. I want to get your thoughts on the experience here at re:Mars. Obviously AWS and the Amazon people kind of combined effort between their teams. The event team does a great job. I thought the event, personally, was first class. The coffee didn't come in late today, I was complaining about that, (Larry laughs) >> people complaining out there, at CUBE reviews. But world class, high bar on the quality of the event. But you guys were involved in the analyst program. You've been through the walkthrough, some of the briefings. I couldn't do that 'cause I'm doing theCUBE interviews. What would you guys learn? What were some of the key walkaways, impressions? Amazon's putting all new teams together, seems on the analyst relations. >> Larry: Yeah. >> They got their mojo booming. They got three shows now, re:Mars, re:inforce, re:invent. >> Andy: Yeah. >> Which will be at theCUBE at all three. Now we got that coverage going, what's it like? What was the experience like? Did you feel it was good? Where do they need to improve? How would you grade the Amazon team? >> I think they did a great job over here in just bringing all the physical elements of the show. Even on the stage, where they had robots in there. It made it real and it's not just fake stuff. And every, or most of the booths out there are actually having- >> John: High quality demos. >> high quality demos. (John laughs) >> John: Not vaporware. >> Yeah, exactly. Not vaporware. >> John: I won't say the name of the company. (all laugh) >> And even the sessions were very good. They went through details. One thing that stood out, which is good, and I cover Low Code/No Code, and Low Code/No Code goes across everything. You know, you got DevOps No Low-Code Low-Code. You got AI Low Code/No Code. You got application development Low Code/No Code. What they have done with AI with Low Code/No Code is very powerful with Canvas. And I think that has really grown the adoption of AI. Because you don't have to go and train people what to do. And then, people are just saying, Hey, let me kick the tires, let me use it. Let me try it. >> John: It's going to be very interesting to see how Amazon, on that point, handles this, AWS handles this data tsunami. It's cause of Snowflake. Snowflake especially running the table >> Larry: Yeah. >> on the old Hadoop world. I think Dave had a great analysis with other colleagues last week at Snowflake Summit. But still, just scratching the surface. >> Larry: Yeah. >> The question is, how shared that ecosystem, how will that morph? 'Cause right now you've got Data Bricks, you've got Snowflake and a handful of others. Teradata's got some new chops going on there and a bunch of other folks. Some are going to win and lose in this downturn, but still, the scale that's needed is massive. >> So you got data growing so much, you were talking earlier about the growth of data and they were talking about the growth. That is a big pie and the pie can be shared by a lot of folks. I don't think- >> John: And snowflake pays AWS, remember that? >> Right, I get it. (John laughs) >> I get it. But they got very unique capabilities, just like Netflix has very unique capabilities. >> John: Yeah. >> They also pay AWS. >> John: Yeah. >> Right? But they're competing on prime. So I really think the cooperation is going to be there. >> John: Yeah. >> The pie is so big >> John: Yeah. >> that there's not going to be losers, but everybody could be winners. >> John: I'd be interested to follow up with you guys after next time we have an event together, we'll get you back on and figure out how do you measure this transitions? You went to IDC, so they had all kinds of ways to measure shipments. >> Larry: Yep. >> Even Gartner had fumbled for years, the Magic Quadrant on IaaS and PaaS when they had the market share. (Larry laughs) And then they finally bundled PaaS and IaaS together after years of my suggesting, thank you very much Gartner. (Larry laughs) But that just performs as the landscape changes so does the scoreboard. >> Yep. >> Right so, how do you measure who's winning and who's losing? How can we be critical of Amazon so they can get better? I mean, Andy Jassy always said to me, and Adam Salassi same way, we want to hear how bad we're doing so we can get better. >> Yeah. >> So they're open-minded to feedback. I mean, not (beep) posting on them, but they're open to critical feedback. What do you guys, what feedback would you give Amazon? Are they winning? I see them number one clearly over Azure, by miles. And even though Azure's kicking ass and taking names, getting back in the game, Microsoft's still behind, by a long ways, in some areas. >> Andy: Yes. In some ways. >> So, the scoreboard's changing. What's your thoughts on that? >> So, look, I mean, at the end of the day, when it comes to compute, right, Amazon is a clear winner. I mean, there are others who are catching up to it, but still, they are the established leader. And it comes with its own advantages because when you're trying to do innovation, when you're trying to do anything else, whether it's a data collection, we were talking about the data sensors, the amount of data they are collecting, whether it's the store, that self-serving store or other innovation projects, what they have going on. The storage compute and process of that requires a ton of compute. And they have that advantage with them. And, as I mentioned in my last article, one of my articles, when it comes to AIML and data programs, there is a rich and there is a poor. And the rich always gets richer because they, they have one leg up already. >> John: Yeah. >> I mean the amount of model training they have done, the billion or trillion dollar trillion parametrization, fine tuning of the model training and everything. They could do it faster. >> John: Yeah. >> Which means they have a leg up to begin with. So unless you are given an opportunity as a smaller, mid-size company to compete at them at the same level, you're going to start at the negative level to begin with. You have a lot of catch up to do. So, the other thing about Amazon is that they, when it comes to a lot of areas, they admit that they have to improve in certain areas and they're open and willing and listen to the people. >> Where are you, let's get critical. Let's do some critical analysis. Where does Amazon Websters need to get better? In your opinion, what criticism would you, in a constructive way, share? >> I think on the open source side, they need to be more proactive in, they are already, but they got to get even better than what they are. They got to engage with the community. They got to be able to talk on the open source side, hey, what are we doing? Maybe on the hardware side, can they do some open-sourcing of that? They got graviton. They got a lot of stuff. Will they be able to share the wealth with other folks, other than just being on an Amazon site, on the edge with their partners. >> John: Got it. >> If they can now take that, like you said, compute with what they have with a very end-to-end solution, the full stack. And if they can extend it, that's going to be really beneficial for them. >> Awesome. Andy, final word here. >> So one area where I think they could improve, which would be a game changer would be, right now, if you look at all of their solutions, if you look at the way they suggest implementation, the innovations, everything that comes out, comes out across very techy-oriented. The persona is very techy-oriented. Very rarely their solutions are built to the business audience or to the decision makers. So if I'm, say, an analyst, if I want to build, a business analyst rather, if I want to build a model, and then I want to deploy that or do some sort of application, mobile application, or what have you, it's a little bit hard. It's more techy-oriented. >> John: Yeah, yeah. >> So, if they could appeal or build a higher level abstraction of how to build and deploy applications for business users, or even build something industry specific, that's where a lot of the legacy companies succeeded. >> John: Yeah. >> Go after manufacturing specific or education. >> Well, we coined the term 'Supercloud' last re:Invent, and that's what we see. And Jerry Chen at Greylock calls it Castles in the Cloud, you can create these moats >> Yep. >> on top of the CapEx >> Yep. >> of Amazon. >> Exactly. >> And ride their back. >> Yep. >> And the difference in what you're paying and what you're charging, if you're good, like a Snowflake or a Mongo. I mean, Mongo's, they're just as big as Snow, if not bigger on Amazon than Snowflake is. 'Cause they use a lot of compute. No one turns off their database. (John laughs) >> Snowflake a little bit different, a little nuanced point, but, this is the new thing. You see Goldman Sachs, you got Capital One. They're building their own kind of, I call them sub clouds, but Dave Vellante says it's a Supercloud. And that essentially is the model. And then once you have a Supercloud, you say, great, I'm going to make sure it works on Azure and Google. >> Andy: Yep. >> And Alibaba if I have to. So, we're kind of seeing a playbook. >> Andy: Mm hmm. >> But you can't get it wrong 'cause it scales. >> Larry: Yeah, yeah. >> You can't scale the wrong answer. >> Andy: Yeah. >> So that seems to be what I'm watching is, who gets it right? Product market fit. Then if they roll it out to the cloud, then it becomes a Supercloud, and that's pure product market fit. So I think that's something that I've seen some people trying to figure out. And then, are you a supplier to the Superclouds? Like a Dell? Or you become an enabler? >> Andy: Yeah. >> You know, what's Dell Technologies do? >> Larry: Yeah. >> I mean, how do the box movers compete? >> Larry: I, the whole thing is now hybrid and you're going to have to see just, you said. (Larry laughs) >> John: Hybrid's a steady-state. I don't need to. >> Andy: I mean, >> By the way we're (indistinct), we can't get the chips, cause Broadcom and Apple bought 'em all. (Larry laughs) I mean there's a huge chip problem going on. >> Yes. I agree. >> Right now. >> I agree. >> I mean all these problems when you attract to a much higher level, a lot of those problems go away because you don't care about what they're using underlying as long as you deliver my solution. >> Larry: Yes. >> Yeah, it could be significantly, a little bit faster than what it used to be. But at the end of the day, are you solving my specific use case? >> John: Yeah. >> Then I'm willing to wait a little bit longer. >> John: Yeah. Time's on our side and now they're getting the right answers. Larry, Andy, thanks for coming on. This great analyst session turned into more of a podcast vibe, but you know what? (Larry laughs) To chill here at re:Mars, thanks for coming on, and we unpacked a lot. Thanks for sharing. >> Both: Thank you. >> Appreciate it. We'll get you back on. We'll get you in the rotation. We'll take it virtual. Do a panel. Do a panel, do some panels around this. >> Larry: Absolutely. >> Andy: Oh this not virtual, this physical. >> No we're live right now! (all laugh) We get back to Palo Alto. You guys are influencers. Thanks for coming on. You guys are moving the market, congratulations. Take a minute, quick minute each to plug any work you're doing for the people watching. Larry, what are you working on? Andy? You go after Larry, what you're working on. >> Yeah. So since I started my company, RobustCloud, since I left IDC about a year ago, I'm focused on edge computing, cloud-native technologies, and Low Code/No Code. And basically I help companies put their business value together. >> All right, Andy, what are you working on? >> I do a lot of work on the AIML areas. Particularly, last few of my reports are in the AI Ops incident management and ML Ops areas of how to generally improve your operations. >> John: Got it, yeah. >> In other words, how do you use the AIML to improve your IT operations? How do you use IT Ops to improve your AIML efficiency? So those are the- >> John: The real hardcore business transformation. >> Yep. >> All right. Guys, thanks so much for coming on the analyst session. We do keynote review, breaking down re:Mars after day two. We got a full day tomorrow. I'm John Furrier with theCUBE. See you next time. (pleasant music)

>>Okay. We're back here in the cube, focusing on the business promise of the cloud democratizing data, making it accessible and enabling everyone to get value from analytics, insights, and data. We're now moving into the eco systems segment the power of many versus the resources of one. And we're pleased to welcome. Barb Hills camp was the senior vice president partners and alliances at Ultrix and a special guest terror do week head of technology alliances at snowflake folks. Welcome. Good to see you. >>Thank you. Thanks for having me. Good to >>See Dave. Great to see you guys. So cloud migration, it's one of the hottest topics. It's the top one of the top initiatives of senior technology leaders. We have survey data with our partner ETR it's number two behind security and just ahead of analytics. So we're hovering around all the hot topics here. Barb, what are you seeing with respect to customer know cloud migration momentum and how does the Ultrix partner strategy fit? >>Yeah, sure. Partners are central, our company's strategy. They always have been, we recognize that our partners have deep customer relationships. And when you connect that with their domain expertise, they're really helping customers on their cloud and business transformation journey. We've been helping customers achieve their desired outcomes with our partner community for quite some time. And our partner base has been growing an average of 30% year over year, that partner, community and strategy now addresses several kinds of partners, spanning solution providers to global size and technology partners, such as snowflake and together, we help our customers realize that business promise of their journey to the cloud. Snowflake provides a scalable storage system altereds provides the business user friendly front end. So for example, it departments depend on snowflake to consolidate data across systems into one data cloud with Altryx business users can easily unlock that data in snowflake solving real business outcomes. Our GSI and solution provider partners are instrumental in providing that end to end benefit of a modern analytic stack in the cloud providing platform guidance, deployment, support, and other professional services. Okay, >>Great. Let's get a little bit more into the relationship between Altrix and in snowflake the partnership, maybe a little bit about the history, you know, what are the critical aspects that we should really focus on? Barb? Maybe you could start an Interra kindly way in as well. >>Yeah, so the relationship started in 2020 and all shirts made a big bag deep with snowflake co-innovating and optimizing cloud use cases together. We are supporting customers who are looking for that modern analytic stack to replace an old one or to implement their first analytic strategy. And our joint customers want to self-serve with data-driven analytics, leveraging all the benefits of the cloud, scalability, accessibility, governance, and optimizing our costs. Altrix proudly achieves highest elite tier and their partner program last year. And to do that, we completed a rigorous third party testing process, which also helped us make some recommended improvements to our joint stack. We wanted customers to have confidence. They would benefit from high quality and performance in their investment with us then to help customers get the most value out of the strength solution. We developed two great assets. One is the Altrix starter kit for snowflake, and we coauthored a joint best practices guide. >>The starter kit contains documentation, business workflows and videos, helping customers to get going more easily with an Alteryx and snowflake solution. And the best practices guide is more of a technical document, bringing together experiences and guidance on how Ultrix and snowflake can be deployed together. Internally. We also built a full enablement catalog resources, right? We wanted to provide our account executives more about the value of the snowflake relationship. How do we engage and some best practices. And now we have hundreds of joint customers such as Juniper and Sainsbury who are actively using our joint solution, solving big business problems, much faster. Cool. >>Tara, can you give us your perspective on the >>Yeah, definitely. Dave. So as Bart mentioned, we've got this standing very successful partnership going back, whereas with hundreds of happy joint customers. And when I look at the beginning, Ultrix has helped pioneer the concept of self-service analytics actually with use cases that we've worked on with, for, for data prep for BI users like Tableau and as Altrix has evolved to now becoming from data prep to now becoming a full end to end data science platform, it's really opened up a lot more opportunities for our partnership. Ultrix has invested heavily over the last two years in areas of deep integration for customers to fully be able to expand their investment, both technologies. And those investments include things like in database pushed down, right? So customers can, can leverage that elastic platform, that being the snowflake data cloud with Alteryx orchestrating the end to end machine learning workflows, Altryx also invested heavily in snow park, a feature we released last year around this concept of data programmability. So all users were regardless of their business analysts, regardless of their data, scientists can use their tools of choice in order to consume and get at data. And now with Altryx cloud, we think it's going to open up even more opportunities. It's going to be a big year for the partnership. >>Yeah. So, you know, Terike, we we've covered snowflake pretty extensively and you initially solve what I used to call the, I still call the snake swallowing the basketball problem and cloud data warehouse changed all that because you had virtually infinite resources. But so that's obviously one of the problems that you guys solved early on, but what are some of the common challenges or patterns or trends that you see with snowflake customers and where does Altryx come in? >>Sure. Dave there's there's handful that I can come up with today. The big challenges or trends for us, and Altrix really helps us across all of them. There are three particular ones I'm going to talk about the first one being self service analytics. If we think about it, every organization is trying to democratize data. Every organization wants to empower all their users, business users, you know, the, the technology users, but the business users, right? I think every, every organization has realized that if everyone has access to data and everyone can do something with data, it's going to make them competitively, give them a competitive advantage with all traits is something we share that vision of putting that power in the hands of everyday users, regardless of the skillsets. So with self-service analytics, with Ultrix designer, they've they started out with self-service analytics as the forefront, and we're just scratching the surface. >>I think there was an analyst report that shows that less than 20% of organizations are truly getting self-service analytics to their end users. Now with Altryx going to Ultrix cloud, we think that's going to be a huge opportunity for us. And then that opens up the second challenge, which is machine learning and AI, every organization is trying to get predictive analytics into every application that they have in order to be competitive in order to be competitive. And with Altryx creating this platform. So they can cater to both the everyday business user, the quote, unquote, citizen data scientists, and making it code friendly for data scientists, to be able to get at their notebooks and all the different tools that they want to use. They fully integrated in our snow park platform, which I talked about before, so that now we get an end to end solution catering to all, all lines of business. >>And then finally this concept of data marketplaces, right? We, we created snowflake from the ground up to be able to solve the data sharing problem, the big data problem, the data sharing problem. And Altryx, if we look at mobilizing your data, getting access to third-party data sets to enrich with your own data sets to enrich with, with your suppliers and with your partners, data sets, that's what all customers are trying to do in order to get a more comprehensive 360 view within their, their data applications. And so with Altryx is we're working on third-party data sets and marketplaces for quite some time. Now we're working on how do we integrate what Altrix is providing with, with the snowflake data marketplace so that we can enrich these workflows, these great rate workflows that Ultrix rating provides. Now we can add third party data into that workflow. So that opens up a ton of opportunities date. So those are three. I see easily that we're going to be able to solve a lot of customer challenges with. >>Excellent. Thank you for that. Terrick so let's stay on cloud a little bit. I mean, Altrix is undergoing a major transformation, big focus on the cloud. How does this cloud launch impact the partnership Terike from snowflakes perspective and then Barb, maybe, please add some color. >>Yeah, sure. Dave snowflake started as a cloud data platform. We saw our founders really saw the challenges that customers are having with becoming data-driven. And the biggest challenge was the complexity of having a managed infrastructure to even be able to, to get applications off the ground. And so we created something to be Claudia. We created to be a SAS managed service. So now that that Altrix is moving into the same model, right? A cloud platform, a SAS managed service, we're just, we're just removing more of the friction. So we're going to be able to start to package these end to end solutions that are SAS based that are fully managed. So customers can, can go faster. They don't have to worry about all of the underlying complexities of, of, of stitching things together. Right? So, so that's, what's exciting from my viewpoint >>And I'll follow up. So as you said, we're investing heavily in the cloud a year ago, we had to pray desktop products. And today we have four cloud products with cloud. We can provide our users with more flexibility. We want to make it easier for the users to leverage their snowflake data in the Alteryx platform, whether they're using our beloved on-premise solution or the new cloud products, we're committed to that continued investment in the cloud, enabling our joint partner solutions to meet customer requirements, wherever they store their data. And we're working with snowflake, we're doing just that. So as customers look for a modern analytic stack, they expect that data to be easily accessible, right within a fast, secure and scalable platform. And the launch of our cloud strategy is a huge leap forward in making Altrix more widely accessible to all users in all types of roles, our GSI and our solution provider partners have asked for these cloud capabilities at scale, and they're excited to better support our customers cloud and analytic ambitions. >>How about you go to market strategy? How would you describe your joint go to market strategy with snowflake? >>Sure. It's simple. We've got to work backwards from our customer's challenges, right? Driving transformation to solve problems, games agencies, or help them save money. So whether it's with snowflake or other GSI, other partner types, we've outlined a joint journey together from recruit solution development, activation enablement, and then strengthening our go to market strategies to optimize our results together. We launched an updated partner program and within that framework, we've created new benefits for our partners around opportunity registration, new role based enablement and training, basically extending everything we do internally for our own go-to-market teams to our partners. We're offering partner, marketing resources and funding to reach new customers together. And as a matter of fact, we recently launched a fantastic video with snowflake. I love this video that very simply describes the path to insights starting with your snowflake data. Right? We do joint customer webinars. We're working on joint hands-on labs and have a wonderful landing page with a lot of assets for our customers. Once we have an interested customer, we engage our respective account managers, collaborating through questions, proof of concepts really showcasing the desired outcome. And when you combine that with our partners technology or domain expertise, it's quite powerful, >>Tara, how do you see it? You'd go to market strategy. >>Yeah. Dave we've. So we initially started selling, we initially sold snowflake as technology, right? Looking at positioning the diff the architectural differentiators and the scale and concurrency. And we noticed as we got up into the larger enterprise customers, we were starting to see how do they solve their business problems using the technology, as well as them coming to us and saying, look, we want to also know how do you, how do you continue to map back to the specific prescriptive business problems we're having? And so we shifted to an industry focus last year, and this is an area where Ultrix has been mature for probably since their inception selling to the line of business, right? Having prescriptive use cases that are particular to an industry like financial services, like retail, like healthcare and life sciences. And so mark talked about these, these starter kits where it's prescriptive, you've got a demo and a way that customers can get off the ground and running, right? >>Because we want to be able to shrink that time to market, the time to value that customers can watch these applications. And we want to be able to, to, to tell them specifically how we can map back to their business initiatives. So I see a huge opportunity to align on these industry solutions. As BARR mentioned, we're already doing that where we've released a few around financial services working on healthcare and retail as well. So that is going to be a way for us to allow customers to go even faster and start to map to lines of business with Altryx >>Great. Thanks Derek, Bob, what can we expect if we're observing this relationship? What should we look for in the coming year? >>A lot specifically with snowflake, we'll continue to invest in the partnership. We're co innovators in this journey, including snow park extensibility efforts, which Derek will tell you more about shortly. We're also launching these great news strategic solution blueprints, and extending that at no charge to our partners with snowflake, we're already collaborating with their retail and CPG team for industry blueprints. We're working with their data marketplace team to highlight solutions, working with that data in their marketplace. More broadly, as I mentioned, we're relaunching the alternative partner program designed to really better support the unique partner types in our global ecosystem, introducing new benefits so that with every partner, achievement or investment with ultra we're providing our partners with earlier access to benefits, I could talk about our program for 30 minutes. I know we don't have time, but the key message here Alteryx is investing in our partner community across the business, recognizing the incredible value that they bring to our customers every day. >>Great Tarik. We'll give you the last word. What should we be looking for from, >>Yeah. Thanks. Thanks, Dave. As BARR mentioned, Ultrix has been the forefront of innovating with us. They've been integrating into making sure again, that customers get the full investment out of snowflake things like in database push down that I talked about before, but extensibility is really what we're excited about. The ability for Altrix to plug into this extensibility framework that we call snow park and to be able to extend out ways that the end users can consume snowflake through, through sequel, which has traditionally been the way that you consume snowflake as well as Java and Scala now Python. So we're excited about those, those capabilities. And then we're also excited about the ability to plug into the data marketplace to provide third party data sets, right? If they're PI day sets and in financial services, third party, data sets and retail. So now customers can build their data applications from end to end using ultrasound snowflake when the comprehensive 360 view of their customers, of their partners, of even their employees. Right. I think it's exciting to see what we're going to be able to do together with these upcoming innovations. >>Great stuff, Bob, Derek, thanks so much for coming on the program. Got to leave it right there in a moment. I'll be back with some closing thoughts in summary, don't go away.

>>Alteryx is a company with a long history that goes all the way back to the late 1990s. Now the one consistent theme over 20 plus years has been that Ultrix has always been a data company early in the big data and Hadoop cycle. It saw the need to combine and prep different data types so that organizations could analyze data and take action Altrix and similar companies played a critical role in helping companies become data-driven. The problem was the decade of big data, brought a lot of complexities and required immense skills just to get the technology to work as advertised this in turn limited, the pace of adoption and the number of companies that could really lean in and take advantage of the cloud began to change all that and set the foundation for today's theme to Zuora of digital transformation. We hear that phrase a ton digital transformation. >>People used to think it was a buzzword, but of course we learned from the pandemic that if you're not a digital business, you're out of business and a key tenant of digital transformation is democratizing data, meaning enabling, not just hypo hyper specialized experts, but anyone business users to put data to work. Now back to Ultrix, the company has embarked on a major transformation of its own. Over the past couple of years, brought in new management, they've changed the way in which it engaged with customers with the new subscription model and it's topgraded its talent pool. 2021 was even more significant because of two acquisitions that Altrix made hyper Ana and trifecta. Why are these acquisitions important? Well, traditionally Altryx sold to business analysts that were part of the data pipeline. These were fairly technical people who had certain skills and were trained in things like writing Python code with hyper Ana Altryx has added a new persona, the business user, anyone in the business who wanted to gain insights from data and, or let's say use AI without having to be a deep technical expert. >>And then Trifacta a company started in the early days of big data by cube alum, Joe Hellerstein and his colleagues at Berkeley. They knocked down the data engineering persona, and this gives Altryx a complimentary extension into it where things like governance and security are paramount. So as we enter 2022, the post isolation economy is here and we do so with a digital foundation built on the confluence of cloud native technologies, data democratization and machine intelligence or AI, if you prefer. And Altryx is entering that new era with an expanded portfolio, new go-to market vectors, a recurring revenue business model, and a brand new outlook on how to solve customer problems and scale a company. My name is Dave Vellante with the cube and I'll be your host today. And the next hour, we're going to explore the opportunities in this new data market. And we have three segments where we dig into these trends and themes. First we'll talk to Jay Henderson, vice president of product management at Ultrix about cloud acceleration and simplifying complex data operations. Then we'll bring in Suresh Vetol who's the chief product officer at Altrix and Adam Wilson, the CEO of Trifacta, which of course is now part of Altrix. And finally, we'll hear about how Altryx is partnering with snowflake and the ecosystem and how they're integrating with data platforms like snowflake and what this means for customers. And we may have a few surprises sprinkled in as well into the conversation let's get started. >>We're kicking off the program with our first segment. Jay Henderson is the vice president of product management Altryx and we're going to talk about the trends and data, where we came from, how we got here, where we're going. We get some launch news. Well, Jay, welcome to the cube. >>Great to be here, really excited to share some of the things we're working on. >>Yeah. Thank you. So look, you have a deep product background, product management, product marketing, you've done strategy work. You've been around software and data, your entire career, and we're seeing the collision of software data cloud machine intelligence. Let's start with the customer and maybe we can work back from there. So if you're an analytics or data executive in an organization, w J what's your north star, where are you trying to take your company from a data and analytics point of view? >>Yeah, I mean, you know, look, I think all organizations are really struggling to get insights out of their data. I think one of the things that we see is you've got digital exhaust, creating large volumes of data storage is really cheap, so it doesn't cost them much to keep it. And that results in a situation where the organization's, you know, drowning in data, but somehow still starving for insights. And so I think, uh, you know, when I talk to customers, they're really excited to figure out how they can put analytics in the hands of every single person in their organization, and really start to democratize the analytics, um, and, you know, let the, the business users and the whole organization get value out of all that data they have. >>And we're going to dig into that throughout this program data, I like to say is plentiful insights, not always so much. Tell us about your launch today, Jay, and thinking about the trends that you just highlighted, the direction that your customers want to go and the problems that you're solving, what role does the cloud play in? What is what you're launching? How does that fit in? >>Yeah, we're, we're really excited today. We're launching the Altryx analytics cloud. That's really a portfolio of cloud-based solutions that have all been built from the ground up to be cloud native, um, and to take advantage of things like based access. So that it's really easy to give anyone access, including folks on a Mac. Um, it, you know, it also lets you take advantage of elastic compute so that you can do, you know, in database processing and cloud native, um, solutions that are gonna scale to solve the most complex problems. So we've got a portfolio of solutions, things like designer cloud, which is our flagship designer product in a browser and on the cloud, but we've got ultra to machine learning, which helps up-skill regular old analysts with advanced machine learning capabilities. We've got auto insights, which brings a business users into the fold and automatically unearths insights using AI and machine learning. And we've got our latest edition, which is Trifacta that helps data engineers do data pipelining and really, um, you know, create a lot of the underlying data sets that are used in some of this, uh, downstream analytics. >>Let's dig into some of those roles if we could a little bit, I mean, you've traditionally Altryx has served the business analysts and that's what designer cloud is fit for, I believe. And you've explained, you know, kind of the scope, sorry, you've expanded that scope into the, to the business user with hyper Anna. And we're in a moment we're going to talk to Adam Wilson and Suresh, uh, about Trifacta and that recent acquisition takes you, as you said, into the data engineering space in it. But in thinking about the business analyst role, what's unique about designer cloud cloud, and how does it help these individuals? >>Yeah, I mean, you know, really, I go back to some of the feedback we've had from our customers, which is, um, you know, they oftentimes have dozens or hundreds of seats of our designer desktop product, you know, really, as they look to take the next step, they're trying to figure out how do I give access to that? Those types of analytics to thousands of people within the organization and designer cloud is, is really great for that. You've got the browser-based interface. So if folks are on a Mac, they can really easily just pop, open the browser and get access to all of those, uh, prep and blend capabilities to a lot of the analysis we're doing. Um, it's a great way to scale up access to the analytics and then start to put it in the hands of really anyone in the organization, not just those highly skilled power users. >>Okay, great. So now then you add in the hyper Anna acquisition. So now you're targeting the business user Trifacta comes into the mix that deeper it angle that we talked about, how does this all fit together? How should we be thinking about the new Altryx portfolio? >>Yeah, I mean, I think it's pretty exciting. Um, you know, when you think about democratizing analytics and providing access to all these different groups of people, um, you've not been able to do it through one platform before. Um, you know, it's not going to be one interface that meets the, of all these different groups within the organization. You really do need purpose built specialized capabilities for each group. And finally, today with the announcement of the alternates analytics cloud, we brought together all of those different capabilities, all of those different interfaces into a single in the end application. So really finally delivering on the promise of providing analytics to all, >>How much of this you've been able to share with your customers and maybe your partners. I mean, I know OD is fairly new, but if you've been able to get any feedback from them, what are they saying about it? >>Uh, I mean, it's, it's pretty amazing. Um, we ran a early access, limited availability program that led us put a lot of this technology in the hands of over 600 customers, um, over the last few months. So we have gotten a lot of feedback. I tell you, um, it's been overwhelmingly positive. I think organizations are really excited to unlock the insights that have been hidden in all this data. They've got, they're excited to be able to use analytics in every decision that they're making so that the decisions they have or more informed and produce better business outcomes. Um, and, and this idea that they're going to move from, you know, dozens to hundreds or thousands of people who have access to these kinds of capabilities, I think has been a really exciting thing that is going to accelerate the transformation that these customers are on. >>Yeah, those are good. Good, good numbers for, for preview mode. Let's, let's talk a little bit about vision. So it's democratizing data is the ultimate goal, which frankly has been elusive for most organizations over time. How's your cloud going to address the challenges of putting data to work across the entire enterprise? >>Yeah, I mean, I tend to think about the future and some of the investments we're making in our products and our roadmap across four big themes, you know, in the, and these are really kind of enduring themes that you're going to see us making investments in over the next few years, the first is having cloud centricity. You know, the data gravity has been moving to the cloud. We need to be able to provide access, to be able to ingest and manipulate that data, to be able to write back to it, to provide cloud solution. So the first one is really around cloud centricity. The second is around big data fluency. Once you have all of the data, you need to be able to manipulate it in a performant manner. So having the elastic cloud infrastructure and in database processing is so important, the third is around making AI a strategic advantage. >>So, uh, you know, getting everyone involved and accessing AI and machine learning to unlock those insights, getting it out of the hands of the small group of data scientists, putting it in the hands of analysts and business users. Um, and then the fourth thing is really providing access across the entire organization. You know, it and data engineers, uh, as well as business owners and analysts. So, um, cloud centricity, big data fluency, um, AI is a strategic advantage and, uh, personas across the organization are really the four big themes you're going to see us, uh, working on over the next few months and, uh, coming coming year. >>That's good. Thank you for that. So, so on a related question, how do you see the data organizations evolving? I mean, traditionally you've had, you know, monolithic organizations, uh, very specialized or I might even say hyper specialized roles and, and your, your mission of course is the customer. You, you, you, you and your customers, they want to democratize the data. And so it seems logical that domain leaders are going to take more responsibility for data, life cycles, data ownerships, low code becomes more important. And perhaps this kind of challenges, the historically highly centralized and really specialized roles that I just talked about. How do you see that evolving and, and, and what role will Altryx play? >>Yeah. Um, you know, I think we'll see sort of a more federated systems start to emerge. Those centralized groups are going to continue to exist. Um, but they're going to start to empower, you know, in a much more de-centralized way, the people who are closer to the business problems and have better business understanding. I think that's going to let the centralized highly skilled teams work on, uh, problems that are of higher value to the organization. The kinds of problems where one or 2% lift in the model results in millions of dollars a day for the business. And then by pushing some of the analytics out to, uh, closer to the edge and closer to the business, you'll be able to apply those analytics in every single decision. So I think you're going to see, you know, both the decentralized and centralized models start to work in harmony and a little bit more about almost a federated sort of a way. And I think, you know, the exciting thing for us at Altryx is, you know, we want to facilitate that. We want to give analytic capabilities and solutions to both groups and types of people. We want to help them collaborate better, um, and drive business outcomes with the analytics they're using. >>Yeah. I mean, I think my take on another one, if you could comment is to me, the technology should be an operational detail and it has been the, the, the dog that wags the tail, or maybe the other way around, you mentioned digital exhaust before. I mean, essentially it's digital exhaust coming out of operationals systems that then somehow, eventually end up in the hand of the domain users. And I wonder if increasingly we're going to see those domain users, users, those, those line of business experts get more access. That's your goal. And then even go beyond analytics, start to build data products that could be monetized, and that maybe it's going to take a decade to play out, but that is sort of a new era of data. Do you see it that way? >>Absolutely. We're actually making big investments in our products and capabilities to be able to create analytic applications and to enable somebody who's an analyst or business user to create an application on top of the data and analytics layers that they have, um, really to help democratize the analytics, to help prepackage some of the analytics that can drive more insights. So I think that's definitely a trend we're going to see more. >>Yeah. And to your point, if you can federate the governance and automate that, then that can happen. I mean, that's a key part of it, obviously. So, all right, Jay, we have to leave it there up next. We take a deep dive into the Altryx recent acquisition of Trifacta with Adam Wilson who led Trifacta for more than seven years. It's the recipe. Tyler is the chief product officer at Altryx to explain the rationale behind the acquisition and how it's going to impact customers. Keep it right there. You're watching the cube. You're a leader in enterprise tech coverage. >>It's go time, get ready to accelerate your data analytics journey with a unified cloud native platform. That's accessible for everyone on the go from home to office and everywhere in between effortless analytics to help you go from ideas to outcomes and no time. It's your time to shine. It's Altryx analytics cloud time. >>Okay. We're here with. Who's the chief product officer at Altryx and Adam Wilson, the CEO of Trifacta. Now of course, part of Altryx just closed this quarter. Gentlemen. Welcome. >>Great to be here. >>Okay. So let me start with you. In my opening remarks, I talked about Altrix is traditional position serving business analysts and how the hyper Anna acquisition brought you deeper into the business user space. What does Trifacta bring to your portfolio? Why'd you buy the company? >>Yeah. Thank you. Thank you for the question. Um, you know, we see, uh, we see a massive opportunity of helping, um, brands, um, democratize the use of analytics across their business. Um, every knowledge worker, every individual in the company should have access to analytics. It's no longer optional, um, as they navigate their businesses with that in mind, you know, we know designer and are the products that Altrix has been selling the past decade or so do a really great job, um, addressing the business analysts, uh, with, um, hyper Rana now kind of renamed, um, Altrix auto. We even speak with the business owner and the line of business owner. Who's looking for insights that aren't real in traditional dashboards and so on. Um, but we see this opportunity of really helping the data engineering teams and it organizations, um, to also make better use of analytics. Um, and that's where the drive factor comes in for us. Um, drive factor has the best data engineering cloud in the planet. Um, they have an established track record of working across multiple cloud platforms and helping data engineers, um, do better data pipelining and work better with, uh, this massive kind of cloud transformation that's happening in every business. Um, and so fact made so much sense for us. >>Yeah. Thank you for that. I mean, you, look, you could have built it yourself would have taken, you know, who knows how long, you know, but, uh, so definitely a great time to market move, Adam. I wonder if we could dig into Trifacta some more, I mean, I remember interviewing Joe Hellerstein in the early days. You've talked about this as well, uh, on the cube coming at the problem of taking data from raw refined to an experience point of view. And Joe in the early days, talked about flipping the model and starting with data visualization, something Jeff, her was expert at. So maybe explain how we got here. We used to have this cumbersome process of ETL and you may be in some others changed that model with ELL and then T explain how Trifacta really changed the data engineering game. >>Yeah, that's exactly right. Uh, David, it's been a really interesting journey for us because I think the original hypothesis coming out of the campus research, uh, at Berkeley and Stanford that really birth Trifacta was, you know, why is it that the people who know the data best can't do the work? You know, why is this become the exclusive purview of the highly technical? And, you know, can we rethink this and make this a user experience, problem powered by machine learning that will take some of the more complicated things that people want to do with data and really help to automate those. So, so a broader set of, of users can, um, can really see for themselves and help themselves. And, and I think that, um, there was a lot of pent up frustration out there because people have been told for, you know, for a decade now to be more data-driven and then the whole time they're saying, well, then give me the data, you know, in the shape that I could use it with the right level of quality and I'm happy to be, but don't tell me to be more data-driven and then, and, and not empower me, um, to, to get in there and to actually start to work with the data in meaningful ways. >>And so, um, that was really, you know, what, you know, the origin story of the company and I think is, as we, um, saw over the course of the last 5, 6, 7 years that, um, you know, uh, real, uh, excitement to embrace this idea of, of trying to think about data engineering differently, trying to democratize the, the ETL process and to also leverage all these exciting new, uh, engines and platforms that are out there that allow for processing, you know, ever more diverse data sets, ever larger data sets and new and interesting ways. And that's where a lot of the push-down or the ELT approaches that, you know, I think it could really won the day. Um, and that, and that for us was a hallmark of the solution from the very beginning. >>Yeah, this is a huge point that you're making is, is first of all, there's a large business, it's probably about a hundred billion dollar Tam. Uh, and the, the point you're making, because we've looked, we've contextualized most of our operational systems, but the big data pipeline is hasn't gotten there. But, and maybe we could talk about that a little bit because democratizing data is Nirvana, but it's been historically very difficult. You've got a number of companies it's very fragmented and they're all trying to attack their little piece of the problem to achieve an outcome, but it's been hard. And so what's going to be different about Altryx as you bring these puzzle pieces together, how is this going to impact your customers who would like to take that one? >>Yeah, maybe, maybe I'll take a crack at it. And Adam will, um, add on, um, you know, there hasn't been a single platform for analytics, automation in the enterprise, right? People have relied on, uh, different products, um, to solve kind of, uh, smaller problems, um, across this analytics, automation, data transformation domain. Um, and, um, I think uniquely Alcon's has that opportunity. Uh, we've got 7,000 plus customers who rely on analytics for, um, data management, for analytics, for AI and ML, uh, for transformations, uh, for reporting and visualization for automated insights and so on. Um, and so by bringing drive factor, we have the opportunity to scale this even further and solve for more use cases, expand the scenarios where it's applied and so multiple personas. Um, and we just talked about the data engineers. They are really a growing stakeholder in this transformation of data and analytics. >>Yeah, good. Maybe we can stay on this for a minute cause you, you you're right. You bring it together. Now at least three personas the business analyst, the end user slash business user. And now the data engineer, which is really out of an it role in a lot of companies, and you've used this term, the data engineering cloud, what is that? How is it going to integrate in with, or support these other personas? And, and how's it going to integrate into the broader ecosystem of clouds and cloud data warehouses or any other data stores? >>Yeah, no, that's great. Uh, yeah, I think for us, we really looked at this and said, you know, we want to build an open and interactive cloud platform for data engineers, you know, to collaboratively profile pipeline, um, and prepare data for analysis. And that really meant collaborating with the analysts that were in the line of business. And so this is why a big reason why this combination is so magic because ultimately if we can get the data engineers that are creating the data products together with the analysts that are in the line of business that are driving a lot of the decision making and allow for that, what I would describe as collaborative curation of the data together, so that you're starting to see, um, uh, you know, increasing returns to scale as this, uh, as this rolls out. I just think that is an incredibly powerful combination and, and frankly, something that the market is not crack the code on yet. And so, um, I think when we, when I sat down with Suresh and with mark and the team at Ultrix, that was really part of the, the, the big idea, the big vision that was painted and got us really energized about the acquisition and about the potential of the combination. >>And you're really, you're obviously writing the cloud and the cloud native wave. Um, and, but specifically we're seeing, you know, I almost don't even want to call it a data warehouse anyway, because when you look at what's, for instance, Snowflake's doing, of course their marketing is around the data cloud, but I actually think there's real justification for that because it's not like the traditional data warehouse, right. It's, it's simplified get there fast, don't necessarily have to go through the central organization to share data. Uh, and, and, and, but it's really all about simplification, right? Isn't that really what the democratization comes down to. >>Yeah. It's simplification and collaboration. Right. I don't want to, I want to kind of just what Adam said resonates with me deeply. Um, analytics is one of those, um, massive disciplines inside an enterprise that's really had the weakest of tools. Um, and we just have interfaces to collaborate with, and I think truly this was all drinks and a superpower was helping the analysts get more out of their data, get more out of the analytics, like imagine a world where these people are collaborating and sharing insights in real time and sharing workflows and getting access to new data sources, um, understanding data models better, I think, um, uh, curating those insights. I boring Adam's phrase again. Um, I think that creates a real value inside the organization because frankly in scaling analytics and democratizing analytics and data, we're still in such early phases of this journey. >>So how should we think about designer cloud, which is from Altrix it's really been the on-prem and the server desktop offering. And of course Trifacta is with cloud cloud data warehouses. Right. Uh, how, how should we think about those two products? Yeah, >>I think, I think you should think about them. And, uh, um, as, as very complimentary right designer cloud really shares a lot of DNA and heritage with, uh, designer desktop, um, the low code tooling and that interface, uh, the really appeals to the business analysts, um, and gets a lot of the things that they do well, we've also built it with interoperability in mind, right. So if you started building your workflows in designer desktop, you want to share that with design and cloud, we want to make it super easy for you to do that. Um, and I think over time now we're only a week into, um, this Alliance with, um, with, um, Trifacta, um, I think we have to get deeper inside to think about what does the data engineer really need? What's the business analysts really need and how to design a cloud, and Trifacta really support both of those requirements, uh, while kind of continue to build on the trifecta on the amazing Trifacta cloud platform. >>You know, >>I think we're just going to say, I think that's one of the things that, um, you know, creates a lot of, uh, opportunity as we go forward, because ultimately, you know, Trifacta took a platform, uh, first mentality to everything that we built. So thinking about openness and extensibility and, um, and how over time people could build things on top of factor that are a variety of analytic tool chain, or analytic applications. And so, uh, when you think about, um, Ultrix now starting to, uh, to move some of its capabilities or to provide additional capabilities, uh, in the cloud, um, you know, Trifacta becomes a platform that can accelerate, you know, all of that work and create, uh, uh, a cohesive set of, of cloud-based services that, um, share a common platform. And that maintains independence because both companies, um, have been, uh, you know, fiercely independent, uh, and, and really giving people choice. >>Um, so making sure that whether you're, uh, you know, picking one cloud platform and other, whether you're running things on the desktop, uh, whether you're running in hybrid environments, that, um, no matter what your decision, um, you're always in a position to be able to get out your data. You're always in a position to be able to cleanse transform shape structure, that data, and ultimately to deliver, uh, the analytics that you need. And so I think in that sense, um, uh, you know, this, this again is another reason why the combination, you know, fits so well together, giving people, um, the choice. Um, and as they, as they think about their analytics strategy and their platform strategy going forward, >>Yeah. I make a chuckle, but one of the reasons I always liked Altrix is cause you kinda did the little end run on it. It can be a blocker sometimes, but that created problems, right? Because the organization said, wow, this big data stuff has taken off, but we need security. We need governance. And it's interesting because you've got, you know, ETL has been complex, whereas the visualization tools, they really, you know, really weren't great at governance and security. It took some time there. So that's not, not their heritage. You're bringing those worlds together. And I'm interested, you guys just had your sales kickoff, you know, what was their reaction like? Uh, maybe Suresh, you could start off and maybe Adam, you could bring us home. >>Um, thanks for asking about our sales kickoff. So we met for the first time and you've got a two years, right. For, as, as it is for many of us, um, in person, uh, um, which I think was a, was a real breakthrough as Qualtrics has been on its transformation journey. Uh, we added a Trifacta to, um, the, the potty such as the tour, um, and getting all of our sales teams and product organizations, um, to meet in person in one location. I thought that was very powerful for other the company. Uh, but then I tell you, um, um, the reception for Trifacta was beyond anything I could have imagined. Uh, we were working out him and I will, when he's so hot on, on the deal and the core hypotheses and so on. And then you step back and you're going to share the vision with the field organization, and it blows you away, the energy that it creates among our sellers out of partners. >>And I'm sure Madam will and his team were mocked, um, every single day, uh, with questions and opportunities to bring them in. But Adam, maybe you should share. Yeah, no, it was, uh, it was through the roof. I mean, uh, uh, the, uh, the amount of energy, the, uh, certainly how welcoming everybody was, uh, uh, you know, just, I think the story makes so much sense together. I think culturally, the company is, are very aligned. Um, and, uh, it was a real, uh, real capstone moment, uh, to be able to complete the acquisition and to, and to close and announced, you know, at the kickoff event. And, um, I think, you know, for us, when we really thought about it, you know, when we ended, the story that we told was just, you have this opportunity to really cater to what the end users care about, which is a lot about interactivity and self-service, and at the same time. >>And that's, and that's a lot of the goodness that, um, that Altryx is, has brought, you know, through, you know, you know, years and years of, of building a very vibrant community of, you know, thousands, hundreds of thousands of users. And on the other side, you know, Trifacta bringing in this data engineering focus, that's really about, uh, the governance things that you mentioned and the openness, um, that, that it cares deeply about. And all of a sudden, now you have a chance to put that together into a complete story where the data engineering cloud and analytics, automation, you know, coming together. And, um, and I just think, you know, the lights went on, um, you know, for people instantaneously and, you know, this is a story that, um, that I think the market is really hungry for. And certainly the reception we got from, uh, from the broader team at kickoff was, uh, was a great indication. >>Well, I think the story hangs together really well, you know, one of the better ones I've seen in, in this space, um, and, and you guys coming off a really, really strong quarter. So congratulations on that jets. We have to leave it there. I really appreciate your time today. Yeah. Take a look at this short video. And when we come back, we're going to dig into the ecosystem and the integration into cloud data warehouses and how leading organizations are creating modern data teams and accelerating their digital businesses. You're watching the cube you're leader in enterprise tech coverage. >>This is your data housed neatly insecurely in the snowflake data cloud. And all of it has potential the potential to solve complex business problems, deliver personalized financial offerings, protect supply chains from disruption, cut costs, forecast, grow and innovate. All you need to do is put your data in the hands of the right people and give it an opportunity. Luckily for you. That's the easy part because snowflake works with Alteryx and Alteryx turns data into breakthroughs with just a click. Your organization can automate analytics with drag and drop building blocks, easily access snowflake data with both sequel and no SQL options, share insights, powered by Alteryx data science and push processing to snowflake for lightning, fast performance, you get answers you can put to work in your teams, get repeatable processes they can share in that's exciting because not only is your data no longer sitting around in silos, it's also mobilized for the next opportunity. Turn your data into a breakthrough Alteryx and snowflake >>Okay. We're back here in the queue, focusing on the business promise of the cloud democratizing data, making it accessible and enabling everyone to get value from analytics, insights, and data. We're now moving into the eco systems segment the power of many versus the resources of one. And we're pleased to welcome. Barb Hills camp was the senior vice president partners and alliances at Ultrix and a special guest Terek do week head of technology alliances at snowflake folks. Welcome. Good to see you. >>Thank you. Thanks for having me. Good to see >>Dave. Great to see you guys. So cloud migration, it's one of the hottest topics. It's the top one of the top initiatives of senior technology leaders. We have survey data with our partner ETR it's number two behind security, and just ahead of analytics. So we're hovering around all the hot topics here. Barb, what are you seeing with respect to customer, you know, cloud migration momentum, and how does the Ultrix partner strategy fit? >>Yeah, sure. Partners are central company's strategy. They always have been. We recognize that our partners have deep customer relationships. And when you connect that with their domain expertise, they're really helping customers on their cloud and business transformation journey. We've been helping customers achieve their desired outcomes with our partner community for quite some time. And our partner base has been growing an average of 30% year over year, that partner community and strategy now addresses several kinds of partners, spanning solution providers to global SIS and technology partners, such as snowflake and together, we help our customers realize the business promise of their journey to the cloud. Snowflake provides a scalable storage system altereds provides the business user friendly front end. So for example, it departments depend on snowflake to consolidate data across systems into one data cloud with Altryx business users can easily unlock that data in snowflake solving real business outcomes. Our GSI and solution provider partners are instrumental in providing that end to end benefit of a modern analytic stack in the cloud providing platform, guidance, deployment, support, and other professional services. >>Great. Let's get a little bit more into the relationship between Altrix and S in snowflake, the partnership, maybe a little bit about the history, you know, what are the critical aspects that we should really focus on? Barb? Maybe you could start an Interra kindly way in as well. >>Yeah, so the relationship started in 2020 and all shirts made a big bag deep with snowflake co-innovating and optimizing cloud use cases together. We are supporting customers who are looking for that modern analytic stack to replace an old one or to implement their first analytic strategy. And our joint customers want to self-serve with data-driven analytics, leveraging all the benefits of the cloud, scalability, accessibility, governance, and optimizing their costs. Um, Altrix proudly achieved. Snowflake's highest elite tier in their partner program last year. And to do that, we completed a rigorous third party testing process, which also helped us make some recommended improvements to our joint stack. We wanted customers to have confidence. They would benefit from high quality and performance in their investment with us then to help customers get the most value out of the destroyed solution. We developed two great assets. One is the officer starter kit for snowflake, and we coauthored a joint best practices guide. >>The starter kit contains documentation, business workflows, and videos, helping customers to get going more easily with an altered since snowflake solution. And the best practices guide is more of a technical document, bringing together experiences and guidance on how Altryx and snowflake can be deployed together. Internally. We also built a full enablement catalog resources, right? We wanted to provide our account executives more about the value of the snowflake relationship. How do we engage and some best practices. And now we have hundreds of joint customers such as Juniper and Sainsbury who are actively using our joint solution, solving big business problems much faster. >>Cool. Kara, can you give us your perspective on the partnership? >>Yeah, definitely. Dave, so as Barb mentioned, we've got this standing very successful partnership going back years with hundreds of happy joint customers. And when I look at the beginning, Altrix has helped pioneer the concept of self-service analytics, especially with use cases that we worked on with for, for data prep for BI users like Tableau and as Altryx has evolved to now becoming from data prep to now becoming a full end to end data science platform. It's really opened up a lot more opportunities for our partnership. Altryx has invested heavily over the last two years in areas of deep integration for customers to fully be able to expand their investment, both technologies. And those investments include things like in database pushed down, right? So customers can, can leverage that elastic platform, that being the snowflake data cloud, uh, with Alteryx orchestrating the end to end machine learning workflows Alteryx also invested heavily in snow park, a feature we released last year around this concept of data programmability. So all users were regardless of their business analysts, regardless of their data, scientists can use their tools of choice in order to consume and get at data. And now with Altryx cloud, we think it's going to open up even more opportunities. It's going to be a big year for the partnership. >>Yeah. So, you know, Terike, we we've covered snowflake pretty extensively and you initially solve what I used to call the, I still call the snake swallowing the basketball problem and cloud data warehouse changed all that because you had virtually infinite resources, but so that's obviously one of the problems that you guys solved early on, but what are some of the common challenges or patterns or trends that you see with snowflake customers and where does Altryx come in? >>Sure. Dave there's there's handful, um, that I can come up with today, the big challenges or trends for us, and Altrix really helps us across all of them. Um, there are three particular ones I'm going to talk about the first one being self-service analytics. If we think about it, every organization is trying to democratize data. Every organization wants to empower all their users, business users, um, you know, the, the technology users, but the business users, right? I think every organization has realized that if everyone has access to data and everyone can do something with data, it's going to make them competitively, give them a competitive advantage with Altrix is something we share that vision of putting that power in the hands of everyday users, regardless of the skillsets. So, um, with self-service analytics, with Ultrix designer they've they started out with self-service analytics as the forefront, and we're just scratching the surface. >>I think there was an analyst, um, report that shows that less than 20% of organizations are truly getting self-service analytics to their end users. Now, with Altryx going to Ultrix cloud, we think that's going to be a huge opportunity for us. Um, and then that opens up the second challenge, which is machine learning and AI, every organization is trying to get predictive analytics into every application that they have in order to be competitive in order to be competitive. Um, and with Altryx creating this platform so they can cater to both the everyday business user, the quote unquote, citizen data scientists, and making a code friendly for data scientists to be able to get at their notebooks and all the different tools that they want to use. Um, they fully integrated in our snow park platform, which I talked about before, so that now we get an end to end solution caring to all, all lines of business. >>And then finally this concept of data marketplaces, right? We, we created snowflake from the ground up to be able to solve the data sharing problem, the big data problem, the data sharing problem. And Altryx um, if we look at mobilizing your data, getting access to third-party datasets, to enrich with your own data sets, to enrich with, um, with your suppliers and with your partners, data sets, that's what all customers are trying to do in order to get a more comprehensive 360 view, um, within their, their data applications. And so with Altryx alterations, we're working on third-party data sets and marketplaces for quite some time. Now we're working on how do we integrate what Altrix is providing with the snowflake data marketplace so that we can enrich these workflows, these great, great workflows that Altrix writing provides. Now we can add third party data into that workflow. So that opens up a ton of opportunities, Dave. So those are three I see, uh, easily that we're going to be able to solve a lot of customer challenges with. >>So thank you for that. Terrick so let's stay on cloud a little bit. I mean, Altrix is undergoing a major transformation, big focus on the cloud. How does this cloud launch impact the partnership Terike from snowflakes perspective and then Barb, maybe, please add some color. >>Yeah, sure. Dave snowflake started as a cloud data platform. We saw our founders really saw the challenges that customers are having with becoming data-driven. And the biggest challenge was the complexity of having imagine infrastructure to even be able to do it, to get applications off the ground. And so we created something to be cloud-native. We created to be a SAS managed service. So now that that Altrix is moving to the same model, right? A cloud platform, a SAS managed service, we're just, we're just removing more of the friction. So we're going to be able to start to package these end to end solutions that are SAS based that are fully managed. So customers can, can go faster and they don't have to worry about all of the underlying complexities of, of, of stitching things together. Right? So, um, so that's, what's exciting from my viewpoint >>And I'll follow up. So as you said, we're investing heavily in the cloud a year ago, we had two pre desktop products, and today we have four cloud products with cloud. We can provide our users with more flexibility. We want to make it easier for the users to leverage their snowflake data in the Alteryx platform, whether they're using our beloved on-premise solution or the new cloud products were committed to that continued investment in the cloud, enabling our joint partner solutions to meet customer requirements, wherever they store their data. And we're working with snowflake, we're doing just that. So as customers look for a modern analytic stack, they expect that data to be easily accessible, right within a fast, secure and scalable platform. And the launch of our cloud strategy is a huge leap forward in making Altrix more widely accessible to all users in all types of roles, our GSI and our solution provider partners have asked for these cloud capabilities at scale, and they're excited to better support our customers, cloud and analytic >>Are. How about you go to market strategy? How would you describe your joint go to market strategy with snowflake? >>Sure. It's simple. We've got to work backwards from our customer's challenges, right? Driving transformation to solve problems, gain efficiencies, or help them save money. So whether it's with snowflake or other GSI, other partner types, we've outlined a joint journey together from recruit solution development, activation enablement, and then strengthening our go to market strategies to optimize our results together. We launched an updated partner program and within that framework, we've created new benefits for our partners around opportunity registration, new role based enablement and training, basically extending everything we do internally for our own go-to-market teams to our partners. We're offering partner, marketing resources and funding to reach new customers together. And as a matter of fact, we recently launched a fantastic video with snowflake. I love this video that very simply describes the path to insights starting with your snowflake data. Right? We do joint customer webinars. We're working on joint hands-on labs and have a wonderful landing page with a lot of assets for our customers. Once we have an interested customer, we engage our respective account managers, collaborating through discovery questions, proof of concepts really showcasing the desired outcome. And when you combine that with our partners technology or domain expertise, it's quite powerful, >>Dark. How do you see it? You'll go to market strategy. >>Yeah. Dave we've. Um, so we initially started selling, we initially sold snowflake as technology, right? Uh, looking at positioning the diff the architectural differentiators and the scale and concurrency. And we noticed as we got up into the larger enterprise customers, we're starting to see how do they solve their business problems using the technology, as well as them coming to us and saying, look, we want to also know how do you, how do you continue to map back to the specific prescriptive business problems we're having? And so we shifted to an industry focus last year, and this is an area where Altrix has been mature for probably since their inception selling to the line of business, right? Having prescriptive use cases that are particular to an industry like financial services, like retail, like healthcare and life sciences. And so, um, Barb talked about these, these starter kits where it's prescriptive, you've got a demo and, um, a way that customers can get off the ground and running, right? >>Cause we want to be able to shrink that time to market, the time to value that customers can watch these applications. And we want to be able to, to tell them specifically how we can map back to their business initiatives. So I see a huge opportunity to align on these industry solutions. As BARR mentioned, we're already doing that where we've released a few around financial services working in healthcare and retail as well. So that is going to be a way for us to allow customers to go even faster and start to map two lines of business with Alteryx. >>Great. Thanks Derek. Bob, what can we expect if we're observing this relationship? What should we look for in the coming year? >>A lot specifically with snowflake, we'll continue to invest in the partnership. Uh, we're co innovators in this journey, including snow park extensibility efforts, which Derek will tell you more about shortly. We're also launching these great news strategic solution blueprints, and extending that at no charge to our partners with snowflake, we're already collaborating with their retail and CPG team for industry blueprints. We're working with their data marketplace team to highlight solutions, working with that data in their marketplace. More broadly, as I mentioned, we're relaunching the ultra partner program designed to really better support the unique partner types in our global ecosystem, introducing new benefits so that with every partner, achievement or investment with ultra score, providing our partners with earlier access to benefits, um, I could talk about our program for 30 minutes. I know we don't have time. The key message here Alteryx is investing in our partner community across the business, recognizing the incredible value that they bring to our customers every day. >>Tarik will give you the last word. What should we be looking for from, >>Yeah, thanks. Thanks, Dave. As BARR mentioned, Altrix has been the forefront of innovating with us. They've been integrating into, uh, making sure again, that customers get the full investment out of snowflake things like in database push down that I talked about before that extensibility is really what we're excited about. Um, the ability for Ultrix to plug into this extensibility framework that we call snow park and to be able to extend out, um, ways that the end users can consume snowflake through, through sequel, which has traditionally been the way that you consume snowflake as well as Java and Scala, not Python. So we're excited about those, those capabilities. And then we're also excited about the ability to plug into the data marketplace to provide third party data sets, right there probably day sets in, in financial services, third party, data sets and retail. So now customers can build their data applications from end to end using ultrasound snowflake when the comprehensive 360 view of their customers, of their partners, of even their employees. Right? I think it's exciting to see what we're going to be able to do together with these upcoming innovations. Great >>Barb Tara, thanks so much for coming on the program, got to leave it right there in a moment, I'll be back with some closing thoughts in a summary, don't go away. >>1200 hours of wind tunnel testing, 30 million race simulations, 2.4 second pit stops make that 2.3. The sector times out the wazoo, whites are much of this velocity's pressures, temperatures, 80,000 components generating 11.8 billion data points and one analytics platform to make sense of it all. When McLaren needs to turn complex data into insights, they turn to Altryx Qualtrics analytics, automation, >>Okay, let's summarize and wrap up the session. We can pretty much agree the data is plentiful, but organizations continue to struggle to get maximum value out of their data investments. The ROI has been elusive. There are many reasons for that complexity data, trust silos, lack of talent and the like, but the opportunity to transform data operations and drive tangible value is immense collaboration across various roles. And disciplines is part of the answer as is democratizing data. This means putting data in the hands of those domain experts that are closest to the customer and really understand where the opportunity exists and how to best address them. We heard from Jay Henderson that we have all this data exhaust and cheap storage. It allows us to keep it for a long time. It's true, but as he pointed out that doesn't solve the fundamental problem. Data is spewing out from our operational systems, but much of it lacks business context for the data teams chartered with analyzing that data. >>So we heard about the trend toward low code development and federating data access. The reason this is important is because the business lines have the context and the more responsibility they take for data, the more quickly and effectively organizations are going to be able to put data to work. We also talked about the harmonization between centralized teams and enabling decentralized data flows. I mean, after all data by its very nature is distributed. And importantly, as we heard from Adam Wilson and Suresh Vittol to support this model, you have to have strong governance and service the needs of it and engineering teams. And that's where the trifecta acquisition fits into the equation. Finally, we heard about a key partnership between Altrix and snowflake and how the migration to cloud data warehouses is evolving into a global data cloud. This enables data sharing across teams and ecosystems and vertical markets at massive scale all while maintaining the governance required to protect the organizations and individuals alike. >>This is a new and emerging business model that is very exciting and points the way to the next generation of data innovation in the coming decade. We're decentralized domain teams get more facile access to data. Self-service take more responsibility for quality value and data innovation. While at the same time, the governance security and privacy edicts of an organization are centralized in programmatically enforced throughout an enterprise and an external ecosystem. This is Dave Volante. All these videos are available on demand@theqm.net altrix.com. Thanks for watching accelerating automated analytics in the cloud made possible by Altryx. And thanks for watching the queue, your leader in enterprise tech coverage. We'll see you next time.

>>Hello and welcome today's cube presentation of eight of us startup showcase. I'm john for your host highlighting the hottest companies and devops data analytics and cloud management lisa martin and David want are here to kick it off. We've got a great program for you again. This is our, our new community event model where we're doing every quarter, we have every new episode, this is quarter three this year or episode three, season one of the hottest cloud startups and we're gonna be featured. Then we're gonna do a keynote package and then 15 countries will present their story, Go check them out and then have a closing keynote with a practitioner and we've got some great lineups, lisa Dave, great to see you. Thanks for joining me. >>Hey guys, >>great to be here. So David got to ask you, you know, back in events last night we're at the 14 it's event where they had the golf PGA championship with the cube Now we got the hybrid model, This is the new normal. We're in, we got these great companies were showcasing them. What's your take? >>Well, you're right. I mean, I think there's a combination of things. We're seeing some live shows. We saw what we did with at mobile world Congress. We did the show with AWS storage day where it was, we were at the spheres, there was no, there was a live audience, but they weren't there physically. It was just virtual and yeah, so, and I just got pained about reinvent. Hey Dave, you gotta make your flights. So I'm making my flights >>were gonna be at the amazon web services, public sector summit next week. At least a lot, a lot of cloud convergence going on here. We got many companies being featured here that we spoke with the Ceo and their top people cloud management, devops data, nelson security. Really cutting edge companies, >>yes, cutting edge companies who are all focused on acceleration. We've talked about the acceleration of digital transformation the last 18 months and we've seen a tremendous amount of acceleration in innovation with what these startups are doing. We've talked to like you said, there's, there's C suite, we've also talked to their customers about how they are innovating so quickly with this hybrid environment, this remote work and we've talked a lot about security in the last week or so. You mentioned that we were at Fortinet cybersecurity skills gap. What some of these companies are doing with automation for example, to help shorten that gap, which is a big opportunity >>for the job market. Great stuff. Dave so the format of this event, you're going to have a fireside chat with the practitioner, we'd like to end these programs with a great experienced practitioner cutting edge in data february. The beginning lisa are gonna be kicking off with of course Jeff bar to give us the update on what's going on AWS and then a special presentation from Emily Freeman who is the author of devops for dummies, she's introducing new content. The revolution in devops devops two point oh and of course jerry Chen from Greylock cube alumni is going to come on and talk about his new thesis castles in the cloud creating moats at cloud scale. We've got a great lineup of people and so the front ends can be great. Dave give us a little preview of what people can expect at the end of the fireside chat. >>Well at the highest level john I've always said we're entering that sort of third great wave of cloud. First wave was experimentation. The second big wave was migration. The third wave of integration, Deep business integration and what you're >>going to hear from >>Hello Fresh today is how they like many companies that started early last decade. They started with an on prem Hadoop system and then of course we all know what happened is S three essentially took the knees out from, from the on prem Hadoop market lowered costs, brought things into the cloud and what Hello Fresh is doing is they're transforming from that legacy Hadoop system into its running on AWS but into a data mess, you know, it's a passionate topic of mine. Hello Fresh was scaling they realized that they couldn't keep up so they had to rethink their entire data architecture and they built it around data mesh Clements key and christoph Soewandi gonna explain how they actually did that are on a journey or decentralized data >>measure it and your posts have been awesome on data measure. We get a lot of traction. Certainly you're breaking analysis for the folks watching check out David Landes, Breaking analysis every week, highlighting the cutting edge trends in tech Dave. We're gonna see you later, lisa and I are gonna be here in the morning talking about with Emily. We got Jeff Barr teed up. Dave. Thanks for coming on. Looking forward to fireside chat lisa. We'll see you when Emily comes back on. But we're gonna go to Jeff bar right now for Dave and I are gonna interview Jeff. Mm >>Hey Jeff, >>here he is. Hey, how are you? How's it going really well. So I gotta ask you, the reinvent is on, everyone wants to know that's happening right. We're good with Reinvent. >>Reinvent is happening. I've got my hotel and actually listening today, if I just remembered, I still need to actually book my flights. I've got my to do list on my desk and I do need to get my >>flights. Uh, >>really looking forward >>to it. I can't wait to see the all the announcements and blog posts. We're gonna, we're gonna hear from jerry Chen later. I love the after on our next event. Get your reaction to this castle and castles in the cloud where competitive advantages can be built in the cloud. We're seeing examples of that. But first I gotta ask you give us an update of what's going on. The ap and ecosystem has been an incredible uh, celebration these past couple weeks, >>so, so a lot of different things happening and the interesting thing to me is that as part of my job, I often think that I'm effectively living in the future because I get to see all this really cool stuff that we're building just a little bit before our customers get to, and so I'm always thinking okay, here I am now, and what's the world going to be like in a couple of weeks to a month or two when these launches? I'm working on actually get out the door and that, that's always really, really fun, just kind of getting that, that little edge into where we're going, but this year was a little interesting because we had to really significant birthdays, we had the 15 year anniversary of both EC two and S three and we're so focused on innovating and moving forward, that it's actually pretty rare for us at Aws to look back and say, wow, we've actually done all these amazing things in in the last 15 years, >>you know, it's kind of cool Jeff, if I may is is, you know, of course in the early days everybody said, well, a place for startup is a W. S and now the great thing about the startup showcases, we're seeing the startups that >>are >>very near, or some of them have even reached escape velocity, so they're not, they're not tiny little companies anymore, they're in their transforming their respective industries, >>they really are and I think that as they start ups grow, they really start to lean into the power of the cloud. They as they start to think, okay, we've we've got our basic infrastructure in place, we've got, we were serving data, we're serving up a few customers, everything is actually working pretty well for us. We've got our fundamental model proven out now, we can invest in publicity and marketing and scaling and but they don't have to think about what's happening behind the scenes. They just if they've got their auto scaling or if they're survivalists, the infrastructure simply grows to meet their demand and it's it's just a lot less things that they have to worry about. They can focus on the fun part of their business which is actually listening to customers and building up an awesome business >>Jeff as you guys are putting together all the big pre reinvented, knows a lot of stuff that goes on prior as well and they say all the big good stuff to reinvent. But you start to see some themes emerged this year. One of them is modernization of applications, the speed of application development in the cloud with the cloud scale devops personas, whatever persona you want to talk about but basically speed the speed of of the app developers where other departments have been slowing things down, I won't say name names, but security group and I t I mean I shouldn't have said that but only kidding but no but seriously people want in minutes and seconds now not days or weeks. You know whether it's policy. What are some of the trends that you're seeing around this this year as we get into some of the new stuff coming out >>So Dave customers really do want speed and for we've actually encapsulate this for a long time in amazon in what we call the bias for action leadership principle >>where >>we just need to jump in and move forward and and make things happen. A lot of customers look at that and they say yes this is great. We need to have the same bias fraction. Some do. Some are still trying to figure out exactly how to put it into play. And they absolutely for sure need to pay attention to security. They need to respect the past and make sure that whatever they're doing is in line with I. T. But they do want to move forward. And the interesting thing that I see time and time again is it's not simply about let's adopt a new technology. It's how do we >>how do we keep our workforce >>engaged? How do we make sure that they've got the right training? How do we bring our our I. T. Team along for this. Hopefully new and fun and exciting journey where they get to learn some interesting new technologies they've got all this very much accumulated business knowledge they still want to put to use, maybe they're a little bit apprehensive about something brand new and they hear about the cloud, but there by and large, they really want to move forward. They just need a little bit of >>help to make it happen >>real good guys. One of the things you're gonna hear today, we're talking about speed traditionally going fast. Oftentimes you meant you have to sacrifice some things on quality and what you're going to hear from some of the startups today is how they're addressing that to automation and modern devoPS technologies and sort of rethinking that whole application development approach. That's something I'm really excited to see organization is beginning to adopt so they don't have to make that tradeoff anymore. >>Yeah, I would >>never want to see someone >>sacrifice quality, >>but I do think that iterating very quickly and using the best of devoPS principles to be able to iterate incredibly quickly and get that first launch out there and then listen with both ears just >>as much >>as you can, Everything. You hear iterate really quickly to meet those needs in, in hours and days, not months, quarters or years. >>Great stuff. Chef and a lot of the companies were featuring here in the startup showcase represent that new kind of thinking, um, systems thinking as well as you know, the cloud scale and again and it's finally here, the revolution of deVOps is going to the next generation and uh, we're excited to have Emily Freeman who's going to come on and give a little preview for her new talk on this revolution. So Jeff, thank you for coming on, appreciate you sharing the update here on the cube. Happy >>to be. I'm actually really looking forward to hearing from Emily. >>Yeah, it's great. Great. Looking forward to the talk. Brand new Premier, Okay, uh, lisa martin, Emily Freeman is here. She's ready to come in and we're going to preview her lightning talk Emily. Um, thanks for coming on, we really appreciate you coming on really, this is about to talk around deVOPS next gen and I think lisa this is one of those things we've been, we've been discussing with all the companies. It's a new kind of thinking it's a revolution, it's a systems mindset, you're starting to see the connections there she is. Emily, Thanks for coming. I appreciate it. >>Thank you for having me. So your teaser video >>was amazing. Um, you know, that little secret radical idea, something completely different. Um, you gotta talk coming up, what's the premise behind this revolution, you know, these tying together architecture, development, automation deployment, operating altogether. >>Yes, well, we have traditionally always used the sclc, which is the software delivery life cycle. Um, and it is a straight linear process that has actually been around since the sixties, which is wild to me um, and really originated in manufacturing. Um, and as much as I love the Toyota production system and how much it has shown up in devops as a sort of inspiration on how to run things better. We are not making cars, we are making software and I think we have to use different approaches and create a sort of model that better reflects our modern software development process. >>It's a bold idea and looking forward to the talk and as motivation. I went into my basement and dusted off all my books from college in the 80s and the sea estimates it was waterfall. It was software development life cycle. They trained us to think this way and it came from the mainframe people. It was like, it's old school, like really, really old and it really hasn't been updated. Where's the motivation? I actually cloud is kind of converging everything together. We see that, but you kind of hit on this persona thing. Where did that come from this persona? Because you know, people want to put people in buckets release engineer. I mean, where's that motivation coming from? >>Yes, you're absolutely right that it came from the mainframes. I think, you know, waterfall is necessary when you're using a punch card or mag tape to load things onto a mainframe, but we don't exist in that world anymore. Thank goodness. And um, yes, so we, we use personas all the time in tech, you know, even to register, well not actually to register for this event, but a lot events. A lot of events, you have to click that drop down. Right. Are you a developer? Are you a manager, whatever? And the thing is personas are immutable in my opinion. I was a developer. I will always identify as a developer despite playing a lot of different roles and doing a lot of different jobs. Uh, and this can vary throughout the day. Right. You might have someone who has a title of software architect who ends up helping someone pair program or develop or test or deploy. Um, and so we wear a lot of hats day to day and I think our discussions around roles would be a better, um, certainly a better approach than personas >>lease. And I've been discussing with many of these companies around the roles and we're hearing from them directly and they're finding out that people have, they're mixing and matching on teams. So you're, you're an S R E on one team and you're doing something on another team where the workflows and the workloads defined the team formation. So this is a cultural discussion. >>It absolutely is. Yes. I think it is a cultural discussion and it really comes to the heart of devops, right? It's people process. And then tools deVOps has always been about culture and making sure that developers have all the tools they need to be productive and honestly happy. What good is all of this? If developing software isn't a joyful experience. Well, >>I got to ask you, I got you here obviously with server list and functions just starting to see this kind of this next gen. And we're gonna hear from jerry Chen, who's a Greylock VC who's going to talk about castles in the clouds, where he's discussing the moats that could be created with a competitive advantage in cloud scale. And I think he points to the snowflakes of the world. You're starting to see this new thing happening. This is devops 2.0, this is the revolution. Is this kind of where you see the same vision of your talk? >>Yes, so DeVOps created 2000 and 8, 2000 and nine, totally different ecosystem in the world we were living in, you know, we didn't have things like surveillance and containers, we didn't have this sort of default distributed nature, certainly not the cloud. Uh and so I'm very excited for jerry's talk. I'm curious to hear more about these moz. I think it's fascinating. Um but yeah, you're seeing different companies use different tools and processes to accelerate their delivery and that is the competitive advantage. How can we figure out how to utilize these tools in the most efficient way possible. >>Thank you for coming and giving us a preview. Let's now go to your lightning keynote talk. Fresh content. Premier of this revolution in Devops and the Freemans Talk, we'll go there now. >>Hi, I'm Emily Freeman, I'm the author of devops for dummies and the curator of 97 things every cloud engineer should know. I am thrilled to be here with you all today. I am really excited to share with you a kind of a wild idea, a complete re imagining of the S DLC and I want to be clear, I need your feedback. I want to know what you think of this. You can always find me on twitter at editing. Emily, most of my work centers around deVOps and I really can't overstate what an impact the concept of deVOPS has had on this industry in many ways it built on the foundation of Agile to become a default a standard we all reach for in our everyday work. When devops surfaced as an idea in 2008, the tech industry was in a vastly different space. AWS was an infancy offering only a handful of services. Azure and G C P didn't exist yet. The majority's majority of companies maintained their own infrastructure. Developers wrote code and relied on sys admins to deploy new code at scheduled intervals. Sometimes months apart, container technology hadn't been invented applications adhered to a monolithic architecture, databases were almost exclusively relational and serverless wasn't even a concept. Everything from the application to the engineers was centralized. Our current ecosystem couldn't be more different. Software is still hard, don't get me wrong, but we continue to find novel solutions to consistently difficult, persistent problems. Now, some of these end up being a sort of rebranding of old ideas, but others are a unique and clever take to abstracting complexity or automating toil or perhaps most important, rethinking challenging the very premises we have accepted as Cannon for years, if not decades. In the years since deVOps attempted to answer the critical conflict between developers and operations, engineers, deVOps has become a catch all term and there have been a number of derivative works. Devops has come to mean 5000 different things to 5000 different people. For some, it can be distilled to continuous integration and continuous delivery or C I C D. For others, it's simply deploying code more frequently, perhaps adding a smattering of tests for others. Still, its organizational, they've added a platform team, perhaps even a questionably named DEVOPS team or have created an engineering structure that focuses on a separation of concerns. Leaving feature teams to manage the development, deployment, security and maintenance of their siloed services, say, whatever the interpretation, what's important is that there isn't a universally accepted standard. Well, what deVOPS is or what it looks like an execution, it's a philosophy more than anything else. A framework people can utilize to configure and customize their specific circumstances to modern development practices. The characteristic of deVOPS that I think we can all agree on though, is that an attempted to capture the challenges of the entire software development process. It's that broad umbrella, that holistic view that I think we need to breathe life into again, The challenge we face is that DeVOps isn't increasingly outmoded solution to a previous problem developers now face. Cultural and technical challenge is far greater than how to more quickly deploy a monolithic application. Cloud native is the future the next collection of default development decisions and one the deVOPS story can't absorb in its current form. I believe the era of deVOPS is waning and in this moment as the sun sets on deVOPS, we have a unique opportunity to rethink rebuild free platform. Even now, I don't have a crystal ball. That would be very handy. I'm not completely certain with the next decade of tech looks like and I can't write this story alone. I need you but I have some ideas that can get the conversation started, I believe to build on what was we have to throw away assumptions that we've taken for granted all this time in order to move forward. We must first step back. Mhm. The software or systems development life cycle, what we call the S. D. L. C. has been in use since the 1960s and it's remained more or less the same since before color television and the touch tone phone. Over the last 60 or so odd years we've made tweaks, slight adjustments, massaged it. The stages or steps are always a little different with agile and deVOps we sort of looped it into a circle and then an infinity loop we've added pretty colors. But the sclc is more or less the same and it has become an assumption. We don't even think about it anymore, universally adopted constructs like the sclc have an unspoken permanence. They feel as if they have always been and always will be. I think the impact of that is even more potent. If you were born after a construct was popularized. Nearly everything around us is a construct, a model, an artifact of a human idea. The chair you're sitting in the desk, you work at the mug from which you drink coffee or sometimes wine, buildings, toilets, plumbing, roads, cars, art, computers, everything. The sclc is a remnant an artifact of a previous era and I think we should throw it away or perhaps more accurately replace it, replace it with something that better reflects the actual nature of our work. A linear, single threaded model designed for the manufacturer of material goods cannot possibly capture the distributed complexity of modern socio technical systems. It just can't. Mhm. And these two ideas aren't mutually exclusive that the sclc was industry changing, valuable and extraordinarily impactful and that it's time for something new. I believe we are strong enough to hold these two ideas at the same time, showing respect for the past while envisioning the future. Now, I don't know about you, I've never had a software project goes smoothly in one go. No matter how small. Even if I'm the only person working on it and committing directly to master software development is chaos. It's a study and entropy and it is not getting any more simple. The model with which we think and talk about software development must capture the multithreaded, non sequential nature of our work. It should embody the roles engineers take on and the considerations they make along the way. It should build on the foundations of agile and devops and represent the iterative nature of continuous innovation. Now, when I was thinking about this, I was inspired by ideas like extreme programming and the spiral model. I I wanted something that would have layers, threads, even a way of visually representing multiple processes happening in parallel. And what I settled on is the revolution model. I believe the visualization of revolution is capable of capturing the pivotal moments of any software scenario. And I'm going to dive into all the discrete elements. But I want to give you a moment to have a first impression, to absorb my idea. I call it revolution because well for one it revolves, it's circular shape reflects the continuous and iterative nature of our work, but also because it is revolutionary. I am challenging a 60 year old model that is embedded into our daily language. I don't expect Gartner to build a magic quadrant around this tomorrow, but that would be super cool. And you should call me my mission with. This is to challenge the status quo to create a model that I think more accurately reflects the complexity of modern cloud native software development. The revolution model is constructed of five concentric circles describing the critical roles of software development architect. Ng development, automating, deploying and operating intersecting each loop are six spokes that describe the production considerations every engineer has to consider throughout any engineering work and that's test, ability, secure ability, reliability, observe ability, flexibility and scalability. The considerations listed are not all encompassing. There are of course things not explicitly included. I figured if I put 20 spokes, some of us, including myself, might feel a little overwhelmed. So let's dive into each element in this model. We have long used personas as the default way to do divide audiences and tailor messages to group people. Every company in the world right now is repeating the mantra of developers, developers, developers but personas have always bugged me a bit because this approach typically either oversimplifies someone's career are needlessly complicated. Few people fit cleanly and completely into persona based buckets like developers and operations anymore. The lines have gotten fuzzy on the other hand, I don't think we need to specifically tailor messages as to call out the difference between a devops engineer and a release engineer or a security administrator versus a security engineer but perhaps most critically, I believe personas are immutable. A persona is wholly dependent on how someone identifies themselves. It's intrinsic not extrinsic. Their titles may change their jobs may differ, but they're probably still selecting the same persona on that ubiquitous drop down. We all have to choose from when registering for an event. Probably this one too. I I was a developer and I will always identify as a developer despite doing a ton of work in areas like devops and Ai Ops and Deverell in my heart. I'm a developer I think about problems from that perspective. First it influences my thinking and my approach roles are very different. Roles are temporary, inconsistent, constantly fluctuating. If I were an actress, the parts I would play would be lengthy and varied, but the persona I would identify as would remain an actress and artist lesbian. Your work isn't confined to a single set of skills. It may have been a decade ago, but it is not today in any given week or sprint, you may play the role of an architect. Thinking about how to design a feature or service, developer building out code or fixing a bug and on automation engineer, looking at how to improve manual processes. We often refer to as soil release engineer, deploying code to different environments or releasing it to customers or in operations. Engineer ensuring an application functions inconsistent expected ways and no matter what role we play. We have to consider a number of issues. The first is test ability. All software systems require testing to assure architects that designs work developers, the code works operators, that infrastructure is running as expected and engineers of all disciplines that code changes won't bring down the whole system testing in its many forms is what enables systems to be durable and have longevity. It's what reassures engineers that changes won't impact current functionality. A system without tests is a disaster waiting to happen, which is why test ability is first among equals at this particular roundtable. Security is everyone's responsibility. But if you understand how to design and execute secure systems, I struggle with this security incidents for the most part are high impact, low probability events. The really big disasters, the one that the ones that end up on the news and get us all free credit reporting for a year. They don't happen super frequently and then goodness because you know that there are endless small vulnerabilities lurking in our systems. Security is something we all know we should dedicate time to but often don't make time for. And let's be honest, it's hard and complicated and a little scary def sec apps. The first derivative of deVOPS asked engineers to move security left this approach. Mint security was a consideration early in the process, not something that would block release at the last moment. This is also the consideration under which I'm putting compliance and governance well not perfectly aligned. I figure all the things you have to call lawyers for should just live together. I'm kidding. But in all seriousness, these three concepts are really about risk management, identity, data, authorization. It doesn't really matter what specific issue you're speaking about, the question is who has access to what win and how and that is everyone's responsibility at every stage site reliability engineering or sorry, is a discipline job and approach for good reason. It is absolutely critical that applications and services work as expected. Most of the time. That said, availability is often mistakenly treated as a synonym for reliability. Instead, it's a single aspect of the concept if a system is available but customer data is inaccurate or out of sync. The system is not reliable, reliability has five key components, availability, latency, throughput. Fidelity and durability, reliability is the end result. But resiliency for me is the journey the action engineers can take to improve reliability, observe ability is the ability to have insight into an application or system. It's the combination of telemetry and monitoring and alerting available to engineers and leadership. There's an aspect of observe ability that overlaps with reliability, but the purpose of observe ability isn't just to maintain a reliable system though, that is of course important. It is the capacity for engineers working on a system to have visibility into the inner workings of that system. The concept of observe ability actually originates and linear dynamic systems. It's defined as how well internal states of a system can be understood based on information about its external outputs. If it is critical when companies move systems to the cloud or utilize managed services that they don't lose visibility and confidence in their systems. The shared responsibility model of cloud storage compute and managed services require that engineering teams be able to quickly be alerted to identify and remediate issues as they arise. Flexible systems are capable of adapting to meet the ever changing needs of the customer and the market segment, flexible code bases absorb new code smoothly. Embody a clean separation of concerns. Are partitioned into small components or classes and architected to enable the now as well as the next inflexible systems. Change dependencies are reduced or eliminated. Database schemas accommodate change well components, communicate via a standardized and well documented A. P. I. The only thing constant in our industry is change and every role we play, creating flexibility and solutions that can be flexible that will grow as the applications grow is absolutely critical. Finally, scalability scalability refers to more than a system's ability to scale for additional load. It implies growth scalability and the revolution model carries the continuous innovation of a team and the byproducts of that growth within a system. For me, scalability is the most human of the considerations. It requires each of us in our various roles to consider everyone around us, our customers who use the system or rely on its services, our colleagues current and future with whom we collaborate and even our future selves. Mhm. Software development isn't a straight line, nor is it a perfect loop. It is an ever changing complex dance. There are twirls and pivots and difficult spins forward and backward. Engineers move in parallel, creating truly magnificent pieces of art. We need a modern model for this modern era and I believe this is just the revolution to get us started. Thank you so much for having me. >>Hey, we're back here. Live in the keynote studio. I'm john for your host here with lisa martin. David lot is getting ready for the fireside chat ending keynote with the practitioner. Hello! Fresh without data mesh lisa Emily is amazing. The funky artwork there. She's amazing with the talk. I was mesmerized. It was impressive. >>The revolution of devops and the creative element was a really nice surprise there. But I love what she's doing. She's challenging the status quo. If we've learned nothing in the last year and a half, We need to challenge the status quo. A model from the 1960s that is no longer linear. What she's doing is revolutionary. >>And we hear this all the time. All the cube interviews we do is that you're seeing the leaders, the SVP's of engineering or these departments where there's new new people coming in that are engineering or developers, they're playing multiple roles. It's almost a multidisciplinary aspect where you know, it's like going into in and out burger in the fryer later and then you're doing the grill, you're doing the cashier, people are changing roles or an architect, their test release all in one no longer departmental, slow siloed groups. >>She brought up a great point about persona is that we no longer fit into these buckets. That the changing roles. It's really the driver of how we should be looking at this. >>I think I'm really impressed, really bold idea, no brainer as far as I'm concerned, I think one of the things and then the comments were off the charts in a lot of young people come from discord servers. We had a good traction over there but they're all like learning. Then you have the experience, people saying this is definitely has happened and happening. The dominoes are falling and they're falling in the direction of modernization. That's the key trend speed. >>Absolutely with speed. But the way that Emily is presenting it is not in a brash bold, but it's in a way that makes great sense. The way that she creatively visually lined out what she was talking about Is amenable to the folks that have been doing this for since the 60s and the new folks now to really look at this from a different >>lens and I think she's a great setup on that lightning top of the 15 companies we got because you think about sis dig harness. I white sourced flamingo hacker one send out, I oh, okay. Thought spot rock set Sarah Ops ramp and Ops Monte cloud apps, sani all are doing modern stuff and we talked to them and they're all on this new wave, this monster wave coming. What's your observation when you talk to these companies? >>They are, it was great. I got to talk with eight of the 15 and the amount of acceleration of innovation that they've done in the last 18 months is phenomenal obviously with the power and the fuel and the brand reputation of aws but really what they're all facilitating cultural shift when we think of devoPS and the security folks. Um, there's a lot of work going on with ai to an automation to really kind of enabled to develop the develops folks to be in control of the process and not have to be security experts but ensuring that the security is baked in shifting >>left. We saw that the chat room was really active on the security side and one of the things I noticed was not just shift left but the other groups, the security groups and the theme of cultural, I won't say war but collision cultural shift that's happening between the groups is interesting because you have this new devops persona has been around Emily put it out for a while. But now it's going to the next level. There's new revolutions about a mindset, a systems mindset. It's a thinking and you start to see the new young companies coming out being funded by the gray locks of the world who are now like not going to be given the we lost the top three clouds one, everything. there's new business models and new technical architecture in the cloud and that's gonna be jerry Chen talk coming up next is going to be castles in the clouds because jerry chant always talked about moats, competitive advantage and how moats are key to success to guard the castle. And then we always joke, there's no more moz because the cloud has killed all the boats. But now the motor in the cloud, the castles are in the cloud, not on the ground. So very interesting thought provoking. But he's got data and if you look at the successful companies like the snowflakes of the world, you're starting to see these new formations of this new layer of innovation where companies are growing rapidly, 98 unicorns now in the cloud. Unbelievable, >>wow, that's a lot. One of the things you mentioned, there's competitive advantage and these startups are all fueled by that they know that there are other companies in the rear view mirror right behind them. If they're not able to work as quickly and as flexibly as a competitor, they have to have that speed that time to market that time to value. It was absolutely critical. And that's one of the things I think thematically that I saw along the eighth sort of that I talked to is that time to value is absolutely table stakes. >>Well, I'm looking forward to talking to jerry chan because we've talked on the queue before about this whole idea of What happens when winner takes most would mean the top 3, 4 cloud players. What happens? And we were talking about that and saying, if you have a model where an ecosystem can develop, what does that look like and back in 2013, 2014, 2015, no one really had an answer. Jerry was the only BC. He really nailed it with this castles in the cloud. He nailed the idea that this is going to happen. And so I think, you know, we'll look back at the tape or the videos from the cube, we'll find those cuts. But we were talking about this then we were pontificating and riffing on the fact that there's going to be new winners and they're gonna look different as Andy Jassy always says in the cube you have to be misunderstood if you're really going to make something happen. Most of the most successful companies are misunderstood. Not anymore. The cloud scales there. And that's what's exciting about all this. >>It is exciting that the scale is there, the appetite is there the appetite to challenge the status quo, which is right now in this economic and dynamic market that we're living in is there's nothing better. >>One of the things that's come up and and that's just real quick before we bring jerry in is automation has been insecurity, absolutely security's been in every conversation, but automation is now so hot in the sense of it's real and it's becoming part of all the design decisions. How can we automate can we automate faster where the keys to automation? Is that having the right data, What data is available? So I think the idea of automation and Ai are driving all the change and that's to me is what these new companies represent this modern error where AI is built into the outcome and the apps and all that infrastructure. So it's super exciting. Um, let's check in, we got jerry Chen line at least a great. We're gonna come back after jerry and then kick off the day. Let's bring in jerry Chen from Greylock is he here? Let's bring him in there. He is. >>Hey john good to see you. >>Hey, congratulations on an amazing talk and thesis on the castles on the cloud. Thanks for coming on. >>All right, Well thanks for reading it. Um, always were being put a piece of workout out either. Not sure what the responses, but it seemed to resonate with a bunch of developers, founders, investors and folks like yourself. So smart people seem to gravitate to us. So thank you very much. >>Well, one of the benefits of doing the Cube for 11 years, Jerry's we have videotape of many, many people talking about what the future will hold. You kind of are on this early, it wasn't called castles in the cloud, but you were all I was, we had many conversations were kind of connecting the dots in real time. But you've been on this for a while. It's great to see the work. I really think you nailed this. I think you're absolutely on point here. So let's get into it. What is castles in the cloud? New research to come out from Greylock that you spearheaded? It's collaborative effort, but you've got data behind it. Give a quick overview of what is castle the cloud, the new modes of competitive advantage for companies. >>Yeah, it's as a group project that our team put together but basically john the question is, how do you win in the cloud? Remember the conversation we had eight years ago when amazon re event was holy cow, Like can you compete with them? Like is it a winner? Take all? Winner take most And if it is winner take most, where are the white spaces for Some starts to to emerge and clearly the past eight years in the cloud this journey, we've seen big companies, data breaks, snowflakes, elastic Mongo data robot. And so um they spotted the question is, you know, why are the castles in the cloud? The big three cloud providers, Amazon google and Azure winning. You know, what advantage do they have? And then given their modes of scale network effects, how can you as a startup win? And so look, there are 500 plus services between all three cloud vendors, but there are like 500 plus um startups competing gets a cloud vendors and there's like almost 100 unicorn of private companies competing successfully against the cloud vendors, including public companies. So like Alaska, Mongo Snowflake. No data breaks. Not public yet. Hashtag or not public yet. These are some examples of the names that I think are winning and watch this space because you see more of these guys storm the castle if you will. >>Yeah. And you know one of the things that's a funny metaphor because it has many different implications. One, as we talk about security, the perimeter of the gates, the moats being on land. But now you're in the cloud, you have also different security paradigm. You have a different um, new kinds of services that are coming on board faster than ever before. Not just from the cloud players but From companies contributing into the ecosystem. So the combination of the big three making the market the main markets you, I think you call 31 markets that we know of that probably maybe more. And then you have this notion of a sub market, which means that there's like we used to call it white space back in the day, remember how many whites? Where's the white space? I mean if you're in the cloud, there's like a zillion white spaces. So talk about this sub market dynamic between markets and that are being enabled by the cloud players and how these sub markets play into it. >>Sure. So first, the first problem was what we did. We downloaded all the services for the big three clowns. Right? And you know what as recalls a database or database service like a document DB and amazon is like Cosmo dB and Azure. So first thing first is we had to like look at all three cloud providers and you? Re categorize all the services almost 500 Apples, Apples, Apples # one number two is you look at all these markets or sub markets and said, okay, how can we cluster these services into things that you know you and I can rock right. That's what amazon Azure and google think about. It is very different and the beauty of the cloud is this kind of fat long tail of services for developers. So instead of like oracle is a single database for all your needs. They're like 20 or 30 different databases from time series um analytics, databases. We're talking rocks at later today. Right. Um uh, document databases like Mongo search database like elastic. And so what happens is there's not one giant market like databases, there's a database market And 30, 40 sub markets that serve the needs developers. So the Great News is cloud has reduced the cost and create something that new for developers. Um also the good news is for a start up you can find plenty of white speeds solving a pain point, very specific to a different type of problem >>and you can sequence up to power law to this. I love the power of a metaphor, you know, used to be a very thin neck note no torso and then a long tail. But now as you're pointing out this expansion of the fat tail of services, but also there's big tam's and markets available at the top of the power law where you see coming like snowflake essentially take on the data warehousing market by basically sitting on amazon re factoring with new services and then getting a flywheel completely changing the economic unit economics completely changing the consumption model completely changing the value proposition >>literally you >>get Snowflake has created like a storm, create a hole, that mode or that castle wall against red shift. Then companies like rock set do your real time analytics is Russian right behind snowflakes saying, hey snowflake is great for data warehouse but it's not fast enough for real time analytics. Let me give you something new to your, to your parallel argument. Even the big optic snowflake have created kind of a wake behind them that created even more white space for Gaza rock set. So that's exciting for guys like me and >>you. And then also as we were talking about our last episode two or quarter two of our showcase. Um, from a VC came on, it's like the old shelf where you didn't know if a company's successful until they had to return the inventory now with cloud you if you're not successful, you know it right away. It's like there's no debate. Like, I mean you're either winning or not. This is like that's so instrumented so a company can have a good better mousetrap and win and fill the white space and then move up. >>It goes both ways. The cloud vendor, the big three amazon google and Azure for sure. They instrument their own class. They know john which ecosystem partners doing well in which ecosystems doing poorly and they hear from the customers exactly what they want. So it goes both ways they can weaponize that. And just as well as you started to weaponize that info >>and that's the big argument of do that snowflake still pays the amazon bills. They're still there. So again, repatriation comes back, That's a big conversation that's come up. What's your quick take on that? Because if you're gonna have a castle in the cloud, then you're gonna bring it back to land. I mean, what's that dynamic? Where do you see that compete? Because on one hand is innovation. The other ones maybe cost efficiency. Is that a growth indicator slow down? What's your view on the movement from and to the cloud? >>I think there's probably three forces you're finding here. One is the cost advantage in the scale advantage of cloud so that I think has been going for the past eight years, there's a repatriation movement for a certain subset of customers, I think for cost purposes makes sense. I think that's a tiny handful that believe they can actually run things better than a cloud. The third thing we're seeing around repatriation is not necessary against cloud, but you're gonna see more decentralized clouds and things pushed to the edge. Right? So you look at companies like Cloudflare Fastly or a company that we're investing in Cato networks. All ideas focus on secure access at the edge. And so I think that's not the repatriation of my own data center, which is kind of a disaggregated of cloud from one giant monolithic cloud, like AWS east or like a google region in europe to multiple smaller clouds for governance purposes, security purposes or legacy purposes. >>So I'm looking at my notes here, looking down on the screen here for this to read this because it's uh to cut and paste from your thesis on the cloud. The excellent cloud. The of the $38 billion invested this quarter. Um Ai and ml number one, um analytics. Number two, security number three. Actually, security number one. But you can see the bubbles here. So all those are data problems I need to ask you. I see data is hot data as intellectual property. How do you look at that? Because we've been reporting on this and we just started the cube conversation around workflows as intellectual property. If you have scale and your motives in the cloud. You could argue that data and the workflows around those data streams is intellectual property. It's a protocol >>I believe both are. And they just kind of go hand in hand like peanut butter and jelly. Right? So data for sure. I. P. So if you know people talk about days in the oil, the new resource. That's largely true because of powers a bunch. But the workflow to your point john is sticky because every company is a unique snowflake right? Like the process used to run the cube and your business different how we run our business. So if you can build a workflow that leverages the data, that's super sticky. So in terms of switching costs, if my work is very bespoke to your business, then I think that's competitive advantage. >>Well certainly your workflow is a lot different than the cube. You guys just a lot of billions of dollars in capital. We're talking to all the people out here jerry. Great to have you on final thought on your thesis. Where does it go from here? What's been the reaction? Uh No, you put it out there. Great love the restart. Think you're on point on this one. Where did we go from here? >>We have to follow pieces um in the near term one around, you know, deep diver on open source. So look out for that pretty soon and how that's been a powerful strategy a second. Is this kind of just aggregation of the cloud be a Blockchain and you know, decentralized apps, be edge applications. So that's in the near term two more pieces of, of deep dive we're doing. And then the goal here is to update this on a quarterly and annual basis. So we're getting submissions from founders that wanted to say, hey, you missed us or he screwed up here. We got the big cloud vendors saying, Hey jerry, we just lost his new things. So our goal here is to update this every single year and then probably do look back saying, okay, uh, where were we wrong? We're right. And then let's say the castle clouds 2022. We'll see the difference were the more unicorns were there more services were the IPO's happening. So look for some short term work from us on analytics, like around open source and clouds. And then next year we hope that all of this forward saying, Hey, you have two year, what's happening? What's changing? >>Great stuff and, and congratulations on the southern news. You guys put another half a billion dollars into early, early stage, which is your roots. Are you still doing a lot of great investments in a lot of unicorns. Congratulations that. Great luck on the team. Thanks for coming on and congratulations you nailed this one. I think I'm gonna look back and say that this is a pretty seminal piece of work here. Thanks for sharing. >>Thanks john thanks for having us. >>Okay. Okay. This is the cube here and 81 startup showcase. We're about to get going in on all the hot companies closing out the kino lisa uh, see jerry Chen cube alumni. He was right from day one. We've been riffing on this, but he nails it here. I think Greylock is lucky to have him as a general partner. He's done great deals, but I think he's hitting the next wave big. This is, this is huge. >>I was listening to you guys talking thinking if if you had a crystal ball back in 2013, some of the things Jerry saying now his narrative now, what did he have a crystal >>ball? He did. I mean he could be a cuBA host and I could be a venture capital. We were both right. I think so. We could have been, you know, doing that together now and all serious now. He was right. I mean, we talked off camera about who's the next amazon who's going to challenge amazon and Andy Jassy was quoted many times in the queue by saying, you know, he was surprised that it took so long for people to figure out what they were doing. Okay, jerry was that VM where he had visibility into the cloud. He saw amazon right away like we did like this is a winning formula and so he was really out front on this one. >>Well in the investments that they're making in these unicorns is exciting. They have this, this lens that they're able to see the opportunities there almost before anybody else can. And finding more white space where we didn't even know there was any. >>Yeah. And what's interesting about the report I'm gonna dig into and I want to get to him while he's on camera because it's a great report, but He says it's like 500 services I think Amazon has 5000. So how you define services as an interesting thing and a lot of amazon services that they have as your doesn't have and vice versa, they do call that out. So I find the report interesting. It's gonna be a feature game in the future between clouds the big three. They're gonna say we do this, you're starting to see the formation, Google's much more developer oriented. Amazon is much more stronger in the governance area with data obviously as he pointed out, they have such experience Microsoft, not so much their developer cloud and more office, not so much on the government's side. So that that's an indicator of my, my opinion of kind of where they rank. So including the number one is still amazon web services as your long second place, way behind google, right behind Azure. So we'll see how the horses come in, >>right. And it's also kind of speaks to the hybrid world in which we're living the hybrid multi cloud world in which many companies are living as companies to not just survive in the last year and a half, but to thrive and really have to become data companies and leverage that data as a competitive advantage to be able to unlock the value of it. And a lot of these startups that we talked to in the showcase are talking about how they're helping organizations unlock that data value. As jerry said, it is the new oil, it's the new gold. Not unless you can unlock that value faster than your competition. >>Yeah, well, I'm just super excited. We got a great day ahead of us with with all the cots startups. And then at the end day, Volonte is gonna interview, hello, fresh practitioners, We're gonna close it out every episode now, we're going to do with the closing practitioner. We try to get jpmorgan chase data measures. The hottest area right now in the enterprise data is new competitive advantage. We know that data workflows are now intellectual property. You're starting to see data really factoring into these applications now as a key aspect of the competitive advantage and the value creation. So companies that are smart are investing heavily in that and the ones that are kind of slow on the uptake are lagging the market and just trying to figure it out. So you start to see that transition and you're starting to see people fall away now from the fact that they're not gonna make it right, You're starting to, you know, you can look at look at any happens saying how much ai is really in there. Real ai what's their data strategy and you almost squint through that and go, okay, that's gonna be losing application. >>Well the winners are making it a board level conversation >>And security isn't built in. Great to have you on this morning kicking it off. Thanks John Okay, we're going to go into the next set of the program at 10:00 we're going to move into the breakouts. Check out the companies is three tracks in there. We have an awesome track on devops pure devops. We've got the data and analytics and we got the cloud management and just to run down real quick check out the sis dig harness. Io system is doing great, securing devops harness. IO modern software delivery platform, White Source. They're preventing and remediating the rest of the internet for them for the company's that's a really interesting and lumbago, effortless acres land and monitoring functions, server list super hot. And of course hacker one is always great doing a lot of great missions and and bounties you see those success continue to send i O there in Palo alto changing the game on data engineering and data pipe lining. Okay. Data driven another new platform, horizontally scalable and of course thought spot ai driven kind of a search paradigm and of course rock set jerry Chen's companies here and press are all doing great in the analytics and then the cloud management cost side 80 operations day to operate. Ops ramps and ops multi cloud are all there and sunny, all all going to present. So check them out. This is the Cubes Adria's startup showcase episode three.

(bouncy techno music) >> Thank you, Adam. It's great working with you all week in the studio. We're here, live in Barcelona. TheCUBE's continuous coverage of Cloud City, it's unbelievable. Darragh Grealish is here, he's the chief technology officer and co-founder of 56K.Cloud. I love that name, we're going to talk about that. And Alexander Lerhmann is the director of new business development innovation at Sunrise UPC. Gents, great to see you, welcome to theCUBE. Thanks for coming on. >> Yeah. >> Thanks for having us. >> MWC, you guys made the bet to come here and aren't you glad you did? >> Yeah, we had to go through a lot of processes, but it was totally worth it, you know? >> Yeah, we're going to talk about edge cloud, right, and we're going to talk about developers, and how this whole thing's going to build out. But how do you think about the cloud? You know, we were talking to DR earlier. The cloud, people think it's a place. Increasingly people say, "no, that's actually an experience, it's a development environment." The cloud is expanding to the edge. The data center is just another edge node. How do you guys look at the edge cloud? >> Yeah well, we see the edge cloud as a huge opportunity to monetize on 5G. To bring the understanding, and the features that 5G can deliver into the next generation of developer experience. Because once we address developer experience, we're going to be able to address that next generation of user experience. >> Okay so, let's dig into a little bit about what each of your respective companies does. Tell us about 56K, and I love the name. Maybe a lot of people don't understand it, but y'know. >> Yeah, it's kind of a generation thing. So, I worked for a lot of large companies, all of them super long email addresses. At the same time, I grew up with the 56K modem. The dial-up modem, as you know it. >> Speaker: Right. >> And the transition from dial-up to broadband was massive. I mean, in terms of user experience on the web, you know. The impact on that technology that did, meant that finally you could control the user experience. You had some predictability, and we thought it was a catchy name. People relate to it. I used to work in test automations, so user experience was an important thing. And so, we kind of combine now, cloud and the 56k kind of understanding, so experience. And it's all about addressing that user experience. >> It's a game changer from a consumer experience at that time. >> Exactly. >> And that's obviously the metaphor you're using. Alexander, tell us more about Sunrise UPC, what their relationship is with 56K. >> Yeah, so Sunrise UPC obviously is a telecommunications provider. #2 largest private telecommunication provider in Switzerland. And in terms of partnership with 56K.Cloud, business started the conversation of how we can bring our world together with what 56K.Cloud is doing. We see a lot of things that we can do to kind of improve the offer from our end, to our customers in the wider community as well. >> Yeah so, this is a good example, right? Because we see, we always talk about the global telco industry, but there's a lot of localization, right? >> Alexander: Right. >> There's a lot of public policy that has to be considered. So let's get into the "Cloud" portion of your name. >> Darragh: Yeah. >> You think about things like wavelength. Which is essentially, it's really the outpost for 5G, if you think about it, right. They're not satellites, it's a platform for the development. Tell us about wavelength in 5G, the intersection there, why it's important. >> Yeah so, the edge cloud solution from Amazon, as you've heard of it, it's not just solving existing use cases or problems, it's actually creating new opportunities by combining the technologies of 5G network slicing, network exposed functions, and multiple access edge compute, you know, it's actually the platform. So, what we're trying to do is bring that developer experience at tuning that is dominated in this large ecosystem in the public cloud, stretched into the network because we need to start to see developers to see the network as an asset. Once they realize that speed, bandwidth, and latency, they're not fighting against this to deliver the best user experience. They can orchestrate this. They can be part of the challenge. And once we can get those developers to see the network as a value proposition, and this is the kind of minimum components that would build that next generation, you know, the next opportunities. So you know, you had an interview recently with Jeff Barr from AWS, and he referred to AWS waveband as, "this is not just solving existing issues." He said, "this is an opportunity," you know, combining 5G. 5G is not just 4G plus one, it's a whole stack of capabilities. And once operators realize that, they restack on public cloud, their telco stack. That's modernizing 5G, going to 5G standalone. And then once they're on public cloud, you know, dogfooding, you start to take those technologies, and you bring them to your subscriber base. But the developers that are in that subscriber base, once you address their need, they can have their creativity process, and building those super apps, like DATRON. Once they address that, then you're going to get that ultimate user experience. >> So, as a telco in the local region, you've got an advantage because you've got your presence at the edge, and you're leaning into next-gen, cloud-native, container, sort of developers. We've always said, "developers are going to win the edge." And you don't typically, most telcos anyway, we don't think of them as developer centric. You guys are different. So, can you talk about how you envision leveraging wavelength, and what the role of developers will be in your country? >> Yeah, I think for us first, it's essentially very important to kind of look at new stuff in many ways. You know, my role at the company is to look at innovative things, and to kind of think a little bit ahead, what's coming down the line, and not necessarily being revenue generating today, but maybe something that's coming, >> Dave: Right. >> sometime down the road. And I think that whole area has so much potential, it just plays into so many fields that are relevant for a telco. And it opens a new channel in many ways because, you know, we'll be able to not just sell connectivity, business, connectivity, mobile, all those products to our customers, but we actually take a more sophisticated route by working with a developer community, then I kind of augment the offering, but then we'll hit the customer. >> So we've seen CDNs and over-the-top providers come in, use your network, thank you, >> Darragh: Yes. >> for building out all that great infrastructure. It sounds like this is different. You're actually facilitating the development of new apps. >> Alexander: Yes. What's different, what kind of apps are we talking about here that you can monetize? >> I mean, it's from small to large, literally everything. I think what we've learned with the rollout of 5G is that it actually touches all industries. Maybe there's some others that shine a bit more than others, but fundamentally, it's such a big shift in terms of what we, as a telco, provides. It's not just this smartphone centric world any longer. It's much more like a building customized solution for particular customer segments, and help them in the industry. So, one thing, when I mentioned in particular was we are from Switzerland. Smart farming. Agriculture, right. And we can do a lot of good things there, if you bring all these technologies together and solve problems that this vertical has had in the past, which was literally increase food production, and be sustainable. Now you can do that, you know, in the old days that wasn't possible. >> So you're talking drones, stream data, and 5G enables that. >> Exactly. >> Yeah. I mean, that's a whole new world, and that is a great monetization opportunity. Who owns the data in that example? Is that a discussion that's going on, or? >> Well, who owns the data? The customer owns the data, right. If it's his or hers. >> Dave: Yeah good, right answer. (all laugh) >> How about when you think about 5G features, network slicing, other capabilities. How do you see 56K taking advantage of those, and working with the developer community to really exploit them? >> Yeah so, we've been more than four years already, working in public clouds, primarily on AWS. And what we've done is, you know, a lot of that cloud native migrations we've done, you know, we've seen those technologies. So what we're trying to do is remap that. And how we're doing this is we're going to be launching the 5G developer platform. It's going to be global ecosystem, open ecosystem, you can go and check it out, it's 5g.dev, literally. And in there, what we want to do is expose these new features of 5G, not just in telco language. So we're launching these kind of networks that slice as code, so that you have this infrastructure as code, in the public cloud domain. This is what resonates with developers. You want to stretch that, and like I mentioned earlier, make that network slices code. So search features, and network slicing dynamic narrative slicing is enhanced mobile broadband, geofence ways, speed, bandwidth, ultra reliable low-latency. I've seen it with my own eyes. You can single digit milliseconds. It's ridiculous how accurate it can be. And then there is the massive IOT. So as you see in IOT, but actually bringing narrowband IOT really at scale, and not just you needing technical boundaries, or contractual boundaries to access that, the developer has the same experiences as in public cloud. And so we want to monetize this to a global 5G. >> Single digit latency, right? So I mean, you know what's going to happen. I think that's why I love the name so much, right. And what happened is people being the consumer at first it was like, "oh my gosh!" And then what happened is the developer community said, "look at all the great data apps we can push in." And then now it's just orders of magnitude more that we can do. And we saw video in the early days of video, it was jittery. And so, it's very exciting times. I think about the data center, and how virtualization occurred there. And, it was almost like force fitting an old model into a new model, where the cloud was setting the definition of that new model. And now they're kind of catching up. Telcos are in a similar situation, right? They've got very purpose-built infrastructure. You guys obviously are more forward-thinking in regard, but is there a parallel there with the old sort of virtualization days, and how you're modernizing the network? What's the state of the network today, and where do you see it going? >> Yeah, we've always looked at the network as our prime differentiator, and we had to be on top of new things, and make sure that it is top notch. That's sort of an indisputable- >> Dave: Table stakes. >> Table stakes, exactly. And so I guess from that point alone, you need to continue to look at how can you improve it? How can you make it more efficient? How can we make it more stable? I mean, frictionless is for us, a key word in that context. And I think with those new technologies, there's just more that we can do. And now we can actually, and this is the beauty of it that comes with 5G and all these new cloud technologies. We can actually make the network our offering again, by delivering network enabled services, which is something that comes with 5G that wasn't there with 4G. >> Yeah, those value added services are key. And it's almost like, I think about the virtualization days, but now we're bringing cloud-native containerization, Kubernetes, Docker, to this new world, and you're doing it on a cloud platform. So that's what's different about the data centers. Data centers were trying to do it on general purpose platforms that were kind of being refactored and forced into it. But the cloud has shown us the way, and it's different, isn't it? >> Yeah, exactly. Well, what has shown to us is that we know we no longer have to sell top down or anything. What we're doing is we have to sell developer to developer. There is multiple avenues, not just SIM cards, with subscribers or large enterprises wanting a thousand SIM cards. It's past that. Now it's developers building those augmented kind of user experiences on the apps, on drones. Like you mentioned too, like chargers and stuff, and aqua tech. In the end, these developers need to become aware that the network can be orchestrated by them. And that we can describe it's never against code, in a familiar way, the way they develop those applications. And we need to extend that developer experience with those applications, and not just be talking about, "no, I have slow speed here, I have fast speed.' I mean, we want to enable some really serious, interesting use cases. >> You used the term network as code infrastructure, as code has been a game changer, >> Darragh: Yup. >> in the technology industry. But, much of the infrastructure is not programmable. And so, what what you're envisioning is a world where, whether it's edge, whether it's data center or cloud, it's the same, right? >> Yeah. >> It's the same experience. The developer experience is the same. The program ability spans, that's the layer that spans all those physical locations. That's the game changer. >> Exactly, yeah. That's why we have to break down those technical boundaries inside the telco industry, and make this familiar to developers and expose them. So that's why we're working with all the major ISVs, the vendors, like you've seen here today in Cloud City. What what we're doing is we're making those never exposed functions, if you call it that way, in a way that the developers can relate to. And why that's really important, is because then they have the same experience on the mobile expert app world. But at the same time we've been here at Cloud City, what we realized is actually, the vendors are also interested in that too, because they want to talk across from each other, and build and be more rapid, and actually in the end, build more competitive, be more competitive in terms of the network implementation. Because right now, there isn't yet this value proposition of why do I need a 5G phone. Why do we need a 5G, 4G is just good enough once I have three out of four bars. (Dave laughs) We need to get that 4G to 5G transition. And the developers are going to drive that. >> Well, when customers see the applications, it's going to shine a light. We've got the mobile network operators, we've got the whole 5G networks licensed capability. We've got this edge cloud coming together, real quick. You got to be excited, Alexander. >> That is an absolutely exciting point in our development and in our evolution as an industry, and it's a huge opportunity, because as again, as I said earlier, it is game changing. It's not just an evolution, but it's really a next major step forward to do things differently. >> Guys, great having you. >> Yup. >> We've got to go, We're going to take it back to Adam Burns in the studio. Thanks for watching.

(bouncy techno music) >> Thank you, Adam. It's great working with you all week in the studio. We're here, live in Barcelona. TheCUBE's continuous coverage of Cloud City, it's unbelievable. Darragh Grealish is here, he's the chief technology officer and co-founder of 56K.Cloud. I love that name, we're going to talk about that. And Alexander Lerhmann is the director of new business development innovation at Sunrise UPC. Gents, great to see you, welcome to theCUBE. Thanks for coming on. >> Yeah. >> Thanks for having us. >> MWC, you guys made the bet to come here and aren't you glad you did? >> Yeah, we had to go through a lot of processes, but it was totally worth it, you know? >> Yeah, we're going to talk about edge cloud, right, and we're going to talk about developers, and how this whole thing's going to build out. But how do you think about the cloud? You know, we were talking to DR earlier. The cloud, people think it's a place. Increasingly people say, "no, that's actually an experience, it's a development environment." The cloud is expanding to the edge. The data center is just another edge node. How do you guys look at the edge cloud? >> Yeah well, we see the edge cloud as a huge opportunity to monetize on 5G. To bring the understanding, and the features that 5G can deliver into the next generation of developer experience. Because once we address developer experience, we're going to be able to address that next generation of user experience. >> Okay so, let's dig into a little bit about what each of your respective companies does. Tell us about 56K, and I love the name. Maybe a lot of people don't understand it, but y'know. >> Yeah, it's kind of a generation thing. So, I worked for a lot of large companies, all of them super long email addresses. At the same time, I grew up with the 56K modem. The dial-up modem, as you know it. >> Speaker: Right. >> And the transition from dial-up to broadband was massive. I mean, in terms of user experience on the web, you know. The impact on that technology that did, meant that finally you could control the user experience. You had some predictability, and we thought it was a catchy name. People relate to it. I used to work in test automations, so user experience was an important thing. And so, we kind of combine now, cloud and the 56k kind of understanding, so experience. And it's all about addressing that user experience. >> It's a game changer from a consumer experience at that time. >> Exactly. >> And that's obviously the metaphor you're using. Alexander, tell us more about Sunrise UPC, what their relationship is with 56K. >> Yeah, so Sunrise UPC obviously is a telecommunications provider. #2 largest private telecommunication provider in Switzerland. And in terms of partnership with 56K.Cloud, business started the conversation of how we can bring our world together with what 56K.Cloud is doing. We see a lot of things that we can do to kind of improve the offer from our end, to our customers in the wider community as well. >> Yeah so, this is a good example, right? Because we see, we always talk about the global telco industry, but there's a lot of localization, right? >> Alexander: Right. >> There's a lot of public policy that has to be considered. So let's get into the "Cloud" portion of your name. >> Darragh: Yeah. >> You think about things like wavelength. Which is essentially, it's really the outpost for 5G, if you think about it, right. They're not satellites, it's a platform for the development. Tell us about wavelength in 5G, the intersection there, why it's important. >> Yeah so, the edge cloud solution from Amazon, as you've heard of it, it's not just solving existing use cases or problems, it's actually creating new opportunities by combining the technologies of 5G network slicing, network exposed functions, and multiple access edge compute, you know, it's actually the platform. So, what we're trying to do is bring that developer experience at tuning that is dominated in this large ecosystem in the public cloud, stretched into the network because we need to start to see developers to see the network as an asset. Once they realize that speed, bandwidth, and latency, they're not fighting against this to deliver the best user experience. They can orchestrate this. They can be part of the challenge. And once we can get those developers to see the network as a value proposition, and this is the kind of minimum components that would build that next generation, you know, the next opportunities. So you know, you had an interview recently with Jeff Barr from AWS, and he referred to AWS waveband as, "this is not just solving existing issues." He said, "this is an opportunity," you know, combining 5G. 5G is not just 4G plus one, it's a whole stack of capabilities. And once operators realize that, they restack on public cloud, their telco stack. That's modernizing 5G, going to 5G standalone. And then once they're on public cloud, you know, dogfooding, you start to take those technologies, and you bring them to your subscriber base. But the developers that are in that subscriber base, once you address their need, they can have their creativity process, and building those super apps, like DATRON. Once they address that, then you're going to get that ultimate user experience. >> So, as a telco in the local region, you've got an advantage because you've got your presence at the edge, and you're leaning into next-gen, cloud-native, container, sort of developers. We've always said, "developers are going to win the edge." And you don't typically, most telcos anyway, we don't think of them as developer centric. You guys are different. So, can you talk about how you envision leveraging wavelength, and what the role of developers will be in your country? >> Yeah, I think for us first, it's essentially very important to kind of look at new stuff in many ways. You know, my role at the company is to look at innovative things, and to kind of think a little bit ahead, what's coming down the line, and not necessarily being revenue generating today, but maybe something that's coming, >> Dave: Right. >> sometime down the road. And I think that whole area has so much potential, it just plays into so many fields that are relevant for a telco. And it opens a new channel in many ways because, you know, we'll be able to not just sell connectivity, business, connectivity, mobile, all those products to our customers, but we actually take a more sophisticated route by working with a developer community, then I kind of augment the offering, but then we'll hit the customer. >> So we've seen CDNs and over-the-top providers come in, use your network, thank you, >> Darragh: Yes. >> for building out all that great infrastructure. It sounds like this is different. You're actually facilitating the development of new apps. >> Alexander: Yes. What's different, what kind of apps are we talking about here that you can monetize? >> I mean, it's from small to large, literally everything. I think what we've learned with the rollout of 5G is that it actually touches all industries. Maybe there's some others that shine a bit more than others, but fundamentally, it's such a big shift in terms of what we, as a telco, provides. It's not just this smartphone centric world any longer. It's much more like a building customized solution for particular customer segments, and help them in the industry. So, one thing, when I mentioned in particular was we are from Switzerland. Smart farming. Agriculture, right. And we can do a lot of good things there, if you bring all these technologies together and solve problems that this vertical has had in the past, which was literally increase food production, and be sustainable. Now you can do that, you know, in the old days that wasn't possible. >> So you're talking drones, stream data, and 5G enables that. >> Exactly. >> Yeah. I mean, that's a whole new world, and that is a great monetization opportunity. Who owns the data in that example? Is that a discussion that's going on, or? >> Well, who owns the data? The customer owns the data, right. If it's his or hers. >> Dave: Yeah good, right answer. (all laugh) >> How about when you think about 5G features, network slicing, other capabilities. How do you see 56K taking advantage of those, and working with the developer community to really exploit them? >> Yeah so, we've been more than four years already, working in public clouds, primarily on AWS. And what we've done is, you know, a lot of that cloud native migrations we've done, you know, we've seen those technologies. So what we're trying to do is remap that. And how we're doing this is we're going to be launching the 5G developer platform. It's going to be global ecosystem, open ecosystem, you can go and check it out, it's 5g.dev, literally. And in there, what we want to do is expose these new features of 5G, not just in telco language. So we're launching these kind of networks that slice as code, so that you have this infrastructure as code, in the public cloud domain. This is what resonates with developers. You want to stretch that, and like I mentioned earlier, make that network slices code. So search features, and network slicing dynamic narrative slicing is enhanced mobile broadband, geofence ways, speed, bandwidth, ultra reliable low-latency. I've seen it with my own eyes. You can single digit milliseconds. It's ridiculous how accurate it can be. And then there is the massive IOT. So as you see in IOT, but actually bringing narrowband IOT really at scale, and not just you needing technical boundaries, or contractual boundaries to access that, the developer has the same experiences as in public cloud. And so we want to monetize this to a global 5G. >> Single digit latency, right? So I mean, you know what's going to happen. I think that's why I love the name so much, right. And what happened is people being the consumer at first it was like, "oh my gosh!" And then what happened is the developer community said, "look at all the great data apps we can push in." And then now it's just orders of magnitude more that we can do. And we saw video in the early days of video, it was jittery. And so, it's very exciting times. I think about the data center, and how virtualization occurred there. And, it was almost like force fitting an old model into a new model, where the cloud was setting the definition of that new model. And now they're kind of catching up. Telcos are in a similar situation, right? They've got very purpose-built infrastructure. You guys obviously are more forward-thinking in regard, but is there a parallel there with the old sort of virtualization days, and how you're modernizing the network? What's the state of the network today, and where do you see it going? >> Yeah, we've always looked at the network as our prime differentiator, and we had to be on top of new things, and make sure that it is top notch. That's sort of an indisputable- >> Dave: Table stakes. >> Table stakes, exactly. And so I guess from that point alone, you need to continue to look at how can you improve it? How can you make it more efficient? How can we make it more stable? I mean, frictionless is for us, a key word in that context. And I think with those new technologies, there's just more that we can do. And now we can actually, and this is the beauty of it that comes with 5G and all these new cloud technologies. We can actually make the network our offering again, by delivering network enabled services, which is something that comes with 5G that wasn't there with 4G. >> Yeah, those value added services are key. And it's almost like, I think about the virtualization days, but now we're bringing cloud-native containerization, Kubernetes, Docker, to this new world, and you're doing it on a cloud platform. So that's what's different about the data centers. Data centers were trying to do it on general purpose platforms that were kind of being refactored and forced into it. But the cloud has shown us the way, and it's different, isn't it? >> Yeah, exactly. Well, what has shown to us is that we know we no longer have to sell top down or anything. What we're doing is we have to sell developer to developer. There is multiple avenues, not just SIM cards, with subscribers or large enterprises wanting a thousand SIM cards. It's past that. Now it's developers building those augmented kind of user experiences on the apps, on drones. Like you mentioned too, like chargers and stuff, and aqua tech. In the end, these developers need to become aware that the network can be orchestrated by them. And that we can describe it's never against code, in a familiar way, the way they develop those applications. And we need to extend that developer experience with those applications, and not just be talking about, "no, I have slow speed here, I have fast speed.' I mean, we want to enable some really serious, interesting use cases. >> You used the term network as code infrastructure, as code has been a game changer, >> Darragh: Yup. >> in the technology industry. But, much of the infrastructure is not programmable. And so, what what you're envisioning is a world where, whether it's edge, whether it's data center or cloud, it's the same, right? >> Yeah. >> It's the same experience. The developer experience is the same. The program ability spans, that's the layer that spans all those physical locations. That's the game changer. >> Exactly, yeah. That's why we have to break down those technical boundaries inside the telco industry, and make this familiar to developers and expose them. So that's why we're working with all the major ISVs, the vendors, like you've seen here today in Cloud City. What what we're doing is we're making those never exposed functions, if you call it that way, in a way that the developers can relate to. And why that's really important, is because then they have the same experience on the mobile expert app world. But at the same time we've been here at Cloud City, what we realized is actually, the vendors are also interested in that too, because they want to talk across from each other, and build and be more rapid, and actually in the end, build more competitive, be more competitive in terms of the network implementation. Because right now, there isn't yet this value proposition of why do I need a 5G phone. Why do we need a 5G, 4G is just good enough once I have three out of four bars. (Dave laughs) We need to get that 4G to 5G transition. And the developers are going to drive that. >> Well, when customers see the applications, it's going to shine a light. We've got the mobile network operators, we've got the whole 5G networks licensed capability. We've got this edge cloud coming together, real quick. You got to be excited, Alexander. >> That is an absolutely exciting point in our development and in our evolution as an industry, and it's a huge opportunity, because as again, as I said earlier, it is game changing. It's not just an evolution, but it's really a next major step forward to do things differently. >> Guys, great having you. >> Yup. >> We've got to go, We're going to take it back to Adam Burns in the studio. Thanks for watching.

>> Hi, I'm Natalie Ehrlich and welcome to the AWS startup showcase presented by The Cube. We have an amazing lineup of great guests who will share their insights on the latest innovations and solutions and leveraging cloud scale data in AI, security and life sciences. And now we're joined by the co-founders and co-CEOs of The Cube, Dave Vellante and John Furrier. Thank you gentlemen for joining me. >> Hey Natalie. >> Hey Natalie. >> How are you doing. Hey John. >> Well, I'd love to get your insights here, let's kick it off and what are you looking forward to. >> Dave, I think one of the things that we've been doing on the cube for 11 years is looking at the signal in the marketplace. I wanted to focus on this because AI is cutting across all industries. So we're seeing that with cybersecurity and life sciences, it's the first time we've had a life sciences track in the showcase, which is amazing because it shows that growth of the cloud scale. So I'm super excited by that. And I think that's going to showcase some new business models and of course the keynotes Ali Ghodsi, who's the CEO Data bricks pushing a billion dollars in revenue, clear validation that startups can go from zero to a billion dollars in revenues. So that should be really interesting. And of course the top venture capitalists coming in to talk about what the enterprise dynamics are all about. And what about you, Dave? >> You know, I thought it was an interesting mix and choice of startups. When you think about, you know, AI security and healthcare, and I've been thinking about that. Healthcare is the perfect industry, it is ripe for disruption. If you think about healthcare, you know, we all complain how expensive it is not transparent. There's a lot of discussion about, you know, can everybody have equal access that certainly with COVID the staff is burned out. There's a real divergence and diversity of the quality of healthcare and you know, it all results in patients not being happy, and I mean, if you had to do an NPS score on the patients and healthcare will be pretty low, John, you know. So when I think about, you know, AI and security in the context of healthcare in cloud, I ask questions like when are machines going to be able to better meet or make better diagnoses than doctors? And that's starting. I mean, it's really in assistance putting into play today. But I think when you think about cheaper and more accurate image analysis, when you think about the overall patient experience and trust and personalized medicine, self-service, you know, remote medicine that we've seen during the COVID pandemic, disease tracking, language translation, I mean, there are so many things where the cloud and data, and then it can help. And then at the end of it, it's all about, okay, how do I authenticate? How do I deal with privacy and personal information and tamper resistance? And that's where the security play comes in. So it's a very interesting mix of startups. I think that I'm really looking forward to hearing from... >> You know Natalie one of the things we talked about, some of these companies, Dave, we've talked a lot of these companies and to me the business model innovations that are coming out of two factors, the pandemic is kind of coming to an end so that accelerated and really showed who had the right stuff in my opinion. So you were either on the wrong side or right side of history when it comes to the pandemic and as we look back, as we come out of it with clear growth in certain companies and certain companies that adopted let's say cloud. And the other one is cloud scale. So the focus of these startup showcases is really to focus on how startups can align with the enterprise buyers and create the new kind of refactoring business models to go from, you know, a re-pivot or refactoring to more value. And the other thing that's interesting is that the business model isn't just for the good guys. If you look at say ransomware, for instance, the business model of hackers is gone completely amazing too. They're kicking it but in terms of revenue, they have their own they're well-funded machines on how to extort cash from companies. So there's a lot of security issues around the business model as well. So to me, the business model innovation with cloud-scale tech, with the pandemic forcing function, you've seen a lot of new kinds of decision-making in enterprises. You seeing how enterprise buyers are changing their decision criteria, and frankly their existing suppliers. So if you're an old guard supplier, you're going to be potentially out because if you didn't deliver during the pandemic, this is the issue that everyone's talking about. And it's kind of not publicized in the press very much, but this is actually happening. >> Well thank you both very much for joining me to kick off our AWS startup showcase. Now we're going to go to our very special guest Ali Ghodsi and John Furrier will seat with him for a fireside chat and Dave and I will see you on the other side. >> Okay, Ali great to see you. Thanks for coming on our AWS startup showcase, our second edition, second batch, season two, whatever we want to call it it's our second version of this new series where we feature, you know, the hottest startups coming out of the AWS ecosystem. And you're one of them, I've been there, but you're not a startup anymore, you're here pushing serious success on the revenue side and company. Congratulations and great to see you. >> Likewise. Thank you so much, good to see you again. >> You know I remember the first time we chatted on The Cube, you weren't really doing much software revenue, you were really talking about the new revolution in data. And you were all in on cloud. And I will say that from day one, you were always adamant that it was cloud cloud scale before anyone was really talking about it. And at that time it was on premises with Hadoop and those kinds of things. You saw that early. I remember that conversation, boy, that bet paid out great. So congratulations. >> Thank you so much. >> So I've got to ask you to jump right in. Enterprises are making decisions differently now and you are an example of that company that has gone from literally zero software sales to pushing a billion dollars as it's being reported. Certainly the success of Data bricks has been written about, but what's not written about is the success of how you guys align with the changing criteria for the enterprise customer. Take us through that and these companies here are aligning the same thing and enterprises want to change. They want to be in the right side of history. What's the success formula? >> Yeah. I mean, basically what we always did was look a few years out, the how can we help these enterprises, future proof, what they're trying to achieve, right? They have, you know, 30 years of legacy software and, you know baggage, and they have compliance and regulations, how do we help them move to the future? So we try to identify those kinds of secular trends that we think are going to maybe you see them a little bit right now, cloud was one of them, but it gets more and more and more. So we identified those and there were sort of three or four of those that we kind of latched onto. And then every year the passes, we're a little bit more right. Cause it's a secular trend in the market. And then eventually, it becomes a force that you can't kind of fight anymore. >> Yeah. And I just want to put a plug for your clubhouse talks with Andreessen Horowitz. You're always on clubhouse talking about, you know, I won't say the killer instinct, but being a CEO in a time where there's so much change going on, you're constantly under pressure. It's a lonely job at the top, I know that, but you've made some good calls. What was some of the key moments that you can point to, where you were like, okay, the wave is coming in now, we'd better get on it. What were some of those key decisions? Cause a lot of these startups want to be in your position, and a lot of buyers want to take advantage of the technology that's coming. They got to figure it out. What was some of those key inflection points for you? >> So if you're just listening to what everybody's saying, you're going to miss those trends. So then you're just going with the stream. So, Juan you mentioned that cloud. Cloud was a thing at the time, we thought it's going to be the thing that takes over everything. Today it's actually multi-cloud. So multi-cloud is a thing, it's more and more people are thinking, wow, I'm paying a lot's to the cloud vendors, do I want to buy more from them or do I want to have some optionality? So that's one. Two, open. They're worried about lock-in, you know, lock-in has happened for many, many decades. So they want open architectures, open source, open standards. So that's the second one that we bet on. The third one, which you know, initially wasn't sort of super obvious was AI and machine learning. Now it's super obvious, everybody's talking about it. But when we started, it was kind of called artificial intelligence referred to robotics, and machine learning wasn't a term that people really knew about. Today, it's sort of, everybody's doing machine learning and AI. So betting on those future trends, those secular trends as we call them super critical. >> And one of the things that I want to get your thoughts on is this idea of re-platforming versus refactoring. You see a lot being talked about in some of these, what does that even mean? It's people trying to figure that out. Re-platforming I get the cloud scale. But as you look at the cloud benefits, what do you say to customers out there and enterprises that are trying to use the benefits of the cloud? Say data for instance, in the middle of how could they be thinking about refactoring? And how can they make a better selection on suppliers? I mean, how do you know it used to be RFP, you deliver these speeds and feeds and you get selected. Now I think there's a little bit different science and methodology behind it. What's your thoughts on this refactoring as a buyer? What do I got to do? >> Well, I mean let's start with you said RFP and so on. Times have changed. Back in the day, you had to kind of sign up for something and then much later you're going to get it. So then you have to go through this arduous process. In the cloud, would pay us to go model elasticity and so on. You can kind of try your way to it. You can try before you buy. And you can use more and more. You can gradually, you don't need to go in all in and you know, say we commit to 50,000,000 and six months later to find out that wow, this stuff has got shelf where it doesn't work. So that's one thing that has changed it's beneficial. But the second thing is, don't just mimic what you had on prem in the cloud. So that's what this refactoring is about. If you had, you know, Hadoop data lake, now you're just going to have an S3 data lake. If you had an on-prem data warehouse now you just going to have a cloud data warehouse. You're just repeating what you did on prem in the cloud, architected for the future. And you know, for us, the most important thing that we say is that this lake house paradigm is a cloud native way of organizing your data. That's different from how you would do things on premises. So think through what's the right way of doing it in the cloud. Don't just try to copy paste what you had on premises in the cloud. >> It's interesting one of the things that we're observing and I'd love to get your reaction to this. Dave a lot** and I have been reporting on it is, two personas in the enterprise are changing their organization. One is I call IT ops or there's an SRE role developing. And the data teams are being dismantled and being kind of sprinkled through into other teams is this notion of data, pipelining being part of workflows, not just the department. Are you seeing organizational shifts in how people are organizing their resources, their human resources to take advantage of say that the data problems that are need to being solved with machine learning and whatnot and cloud-scale? >> Yeah, absolutely. So you're right. SRE became a thing, lots of DevOps people. It was because when the cloud vendors launched their infrastructure as a service to stitch all these things together and get it all working you needed a lot of devOps people. But now things are maturing. So, you know, with vendors like Data bricks and other multi-cloud vendors, you can actually get much higher level services where you don't need to necessarily have lots of lots of DevOps people that are themselves trying to stitch together lots of services to make this work. So that's one trend. But secondly, you're seeing more data teams being sort of completely ubiquitous in these organizations. Before it used to be you have one data team and then we'll have data and AI and we'll be done. ' It's a one and done. But that's not how it works. That's not how Google, Facebook, Twitter did it, they had data throughout the organization. Every BU was empowered. It's sales, it's marketing, it's finance, it's engineering. So how do you embed all those data teams and make them actually run fast? And you know, there's this concept of a data mesh which is super important where you can actually decentralize and enable all these teams to focus on their domains and run super fast. And that's really enabled by this Lake house paradigm in the cloud that we're talking about. Where you're open, you're basing it on open standards. You have flexibility in the data types and how they're going to store their data. So you kind of provide a lot of that flexibility, but at the same time, you have sort of centralized governance for it. So absolutely things are changing in the market. >> Well, you're just the professor, the masterclass right here is amazing. Thanks for sharing that insight. You're always got to go out of date and that's why we have you on here. You're amazing, great resource for the community. Ransomware is a huge problem, it's now the government's focus. We're being attacked and we don't know where it's coming from. This business models around cyber that's expanding rapidly. There's real revenue behind it. There's a data problem. It's not just a security problem. So one of the themes in all of these startup showcases is data is ubiquitous in the value propositions. One of them is ransomware. What's your thoughts on ransomware? Is it a data problem? Does cloud help? Some are saying that cloud's got better security with ransomware, then say on premise. What's your vision of how you see this ransomware problem being addressed besides the government taking over? >> Yeah, that's a great question. Let me start by saying, you know, we're a data company, right? And if you say you're a data company, you might as well just said, we're a privacy company, right? It's like some people say, well, what do you think about privacy? Do you guys even do privacy? We're a data company. So yeah, we're a privacy company as well. Like you can't talk about data without talking about privacy. With every customer, with every enterprise. So that's obviously top of mind for us. I do think that in the cloud, security is much better because, you know, vendors like us, we're investing so much resources into security and making sure that we harden the infrastructure and, you know, by actually having all of this infrastructure, we can monitor it, detect if something is, you know, an attack is happening, and we can immediately sort of stop it. So that's different from when it's on prem, you have kind of like the separated duties where the software vendor, which would have been us, doesn't really see what's happening in the data center. So, you know, there's an IT team that didn't develop the software is responsible for the security. So I think things are much better now. I think we're much better set up, but of course, things like cryptocurrencies and so on are making it easier for people to sort of hide. There decentralized networks. So, you know, the attackers are getting more and more sophisticated as well. So that's definitely something that's super important. It's super top of mind. We're all investing heavily into security and privacy because, you know, that's going to be super critical going forward. >> Yeah, we got to move that red line, and figure that out and get more intelligence. Decentralized trends not going away it's going to be more of that, less of the centralized. But centralized does come into play with data. It's a mix, it's not mutually exclusive. And I'll get your thoughts on this. Architectural question with, you know, 5G and the edge coming. Amazon's got that outpost stringent, the wavelength, you're seeing mobile world Congress coming up in this month. The focus on processing data at the edge is a huge issue. And enterprises are now going to be commercial part of that. So architecture decisions are being made in enterprises right now. And this is a big issue. So you mentioned multi-cloud, so tools versus platforms. Now I'm an enterprise buyer and there's no more RFPs. I got all this new choices for startups and growing companies to choose from that are cloud native. I got all kinds of new challenges and opportunities. How do I build my architecture so I don't foreclose a future opportunity. >> Yeah, as I said, look, you're actually right. Cloud is becoming even more and more something that everybody's adopting, but at the same time, there is this thing that the edge is also more and more important. And the connectivity between those two and making sure that you can really do that efficiently. My ask from enterprises, and I think this is top of mind for all the enterprise architects is, choose open because that way you can avoid locking yourself in. So that's one thing that's really, really important. In the past, you know, all these vendors that locked you in, and then you try to move off of them, they were highly innovative back in the day. In the 80's and the 90's, there were the best companies. You gave them all your data and it was fantastic. But then because you were locked in, they didn't need to innovate anymore. And you know, they focused on margins instead. And then over time, the innovation stopped and now you were kind of locked in. So I think openness is really important. I think preserving optionality with multi-cloud because we see the different clouds have different strengths and weaknesses and it changes over time. All right. Early on AWS was the only game that either showed up with much better security, active directory, and so on. Now Google with AI capabilities, which one's going to win, which one's going to be better. Actually, probably all three are going to be around. So having that optionality that you can pick between the three and then artificial intelligence. I think that's going to be the key to the future. You know, you asked about security earlier. That's how people detect zero day attacks, right? You ask about the edge, same thing there, that's where the predictions are going to happen. So make sure that you invest in AI and artificial intelligence very early on because it's not something you can just bolt on later on and have a little data team somewhere that then now you have AI and it's one and done. >> All right. Great insight. I've got to ask you, the folks may or may not know, but you're a professor at Berkeley as well, done a lot of great work. That's where you kind of came out of when Data bricks was formed. And the Berkeley basically was it invented distributed computing back in the 80's. I remember I was breaking in when Unix was proprietary, when software wasn't open you actually had the deal that under the table to get code. Now it's all open. Isn't the internet now with distributed computing and how interconnects are happening. I mean, the internet didn't break during the pandemic, which proves the benefit of the internet. And that's a positive. But as you start seeing edge, it's essentially distributed computing. So I got to ask you from a computer science standpoint. What do you see as the key learnings or connect the dots for how this distributed model will work? I see hybrids clearly, hybrid cloud is clearly the operating model but if you take it to the next level of distributed computing, what are some of the key things that you look for in the next five years as this starts to be completely interoperable, obviously software is going to drive a lot of it. What's your vision on that? >> Yeah, I mean, you know, so Berkeley, you're right for the gigs, you know, there was a now project 20, 30 years ago that basically is how we do things. There was a project on how you search in the very early on with Inktomi that became how Google and everybody else to search today. So workday was super, super early, sometimes way too early. And that was actually the mistake. Was that they were so early that people said that that stuff doesn't work. And then 20 years later you were invented. So I think 2009, Berkeley published just above the clouds saying the cloud is the future. At that time, most industry leaders said, that's just, you know, that doesn't work. Today, recently they published a research paper called, Sky Computing. So sky computing is what you get above the clouds, right? So we have the cloud as the future, the next level after that is the sky. That's one on top of them. That's what multi-cloud is. So that's a lot of the research at Berkeley, you know, into distributed systems labs is about this. And we're excited about that. Then we're one of the sky computing vendors out there. So I think you're going to see much more innovation happening at the sky level than at the compute level where you needed all those DevOps and SRE people to like, you know, build everything manually themselves. I can just see the memes now coming Ali, sky net, star track. You've got space too, by the way, space is another frontier that is seeing a lot of action going on because now the surface area of data with satellites is huge. So again, I know you guys are doing a lot of business with folks in that vertical where you starting to see real time data acquisition coming from these satellites. What's your take on the whole space as the, not the final frontier, but certainly as a new congested and contested space for, for data? >> Well, I mean, as a data vendor, we see a lot of, you know, alternative data sources coming in and people aren't using machine learning< AI to eat out signal out of the, you know, massive amounts of imagery that's coming out of these satellites. So that's actually a pretty common in FinTech, which is a vertical for us. And also sort of in the public sector, lots of, lots of, lots of satellites, imagery data that's coming. And these are massive volumes. I mean, it's like huge data sets and it's a super, super exciting what they can do. Like, you know, extracting signal from the satellite imagery is, and you know, being able to handle that amount of data, it's a challenge for all the companies that we work with. So we're excited about that too. I mean, definitely that's a trend that's going to continue. >> All right. I'm super excited for you. And thanks for coming on The Cube here for our keynote. I got to ask you a final question. As you think about the future, I see your company has achieved great success in a very short time, and again, you guys done the work, I've been following your company as you know. We've been been breaking that Data bricks story for a long time. I've been excited by it, but now what's changed. You got to start thinking about the next 20 miles stair when you look at, you know, the sky computing, you're thinking about these new architectures. As the CEO, your job is to one, not run out of money which you don't have to worry about that anymore, so hiring. And then, you got to figure out that next 20 miles stair as a company. What's that going on in your mind? Take us through your mindset of what's next. And what do you see out in that landscape? >> Yeah, so what I mentioned around Sky company optionality around multi-cloud, you're going to see a lot of capabilities around that. Like how do you get multi-cloud disaster recovery? How do you leverage the best of all the clouds while at the same time not having to just pick one? So there's a lot of innovation there that, you know, we haven't announced yet, but you're going to see a lot of it over the next many years. Things that you can do when you have the optionality across the different parts. And the second thing that's really exciting for us is bringing AI to the masses. Democratizing data and AI. So how can you actually apply machine learning to machine learning? How can you automate machine learning? Today machine learning is still quite complicated and it's pretty advanced. It's not going to be that way 10 years from now. It's going to be very simple. Everybody's going to have it at their fingertips. So how do we apply machine learning to machine learning? It's called auto ML, automatic, you know, machine learning. So that's an area, and that's not something that can be done with, right? But the goal is to eventually be able to automate a way the whole machine learning engineer and the machine learning data scientist altogether. >> You know it's really fun and talking with you is that, you know, for years we've been talking about this inside the ropes, inside the industry, around the future. Now people starting to get some visibility, the pandemics forced that. You seeing the bad projects being exposed. It's like the tide pulled out and you see all the scabs and bad projects that were justified old guard technologies. If you get it right you're on a good wave. And this is clearly what we're seeing. And you guys example of that. So as enterprises realize this, that they're going to have to look double down on the right projects and probably trash the bad projects, new criteria, how should people be thinking about buying? Because again, we talked about the RFP before. I want to kind of circle back because this is something that people are trying to figure out. You seeing, you know, organic, you come in freemium models as cloud scale becomes the advantage in the lock-in frankly seems to be the value proposition. The more value you provide, the more lock-in you get. Which sounds like that's the way it should be versus proprietary, you know, protocols. The protocol is value. How should enterprises organize their teams? Is it end to end workflows? Is it, and how should they evaluate the criteria for these technologies that they want to buy? >> Yeah, that's a great question. So I, you know, it's very simple, try to future proof your decision-making. Make sure that whatever you're doing is not blocking your in. So whatever decision you're making, what if the world changes in five years, make sure that if you making a mistake now, that's not going to bite you in about five years later. So how do you do that? Well, open source is great. If you're leveraging open-source, you can try it out already. You don't even need to talk to any vendor. Your teams can already download it and try it out and get some value out of it. If you're in the cloud, this pay as you go models, you don't have to do a big RFP and commit big. You can try it, pay the vendor, pay as you go, $10, $15. It doesn't need to be a million dollar contract and slowly grow as you're providing value. And then make sure that you're not just locking yourself in to one cloud or, you know, one particular vendor. As much as possible preserve your optionality because then that's not a one-way door. If it turns out later you want to do something else, you can, you know, pick other things as well. You're not locked in. So that's what I would say. Keep that top of mind that you're not locking yourself into a particular decision that you made today, that you might regret in five years. >> I really appreciate you coming on and sharing your with our community and The Cube. And as always great to see you. I really enjoy your clubhouse talks, and I really appreciate how you give back to the community. And I want to thank you for coming on and taking the time with us today. >> Thanks John, always appreciate talking to you. >> Okay Ali Ghodsi, CEO of Data bricks, a success story that proves the validation of cloud scale, open and create value, values the new lock-in. So Natalie, back to you for continuing coverage. >> That was a terrific interview John, but I'd love to get Dave's insights first. What were your takeaways, Dave? >> Well, if we have more time I'll tell you how Data bricks got to where they are today, but I'll say this, the most important thing to me that Allie said was he conveyed a very clear understanding of what data companies are outright and are getting ready. Talked about four things. There's not one data team, there's many data teams. And he talked about data is decentralized, and data has to have context and that context lives in the business. He said, look, think about it. The way that the data companies would get it right, they get data in teams and sales and marketing and finance and engineering. They all have their own data and data teams. And he referred to that as a data mesh. That's a term that is your mock, the Gany coined and the warehouse of the data lake it's merely a node in that global message. It meshes discoverable, he talked about federated governance, and Data bricks, they're breaking the model of shoving everything into a single repository and trying to make that the so-called single version of the truth. Rather what they're doing, which is right on is putting data in the hands of the business owners. And that's how true data companies do. And the last thing you talked about with sky computing, which I loved, it's that future layer, we talked about multi-cloud a lot that abstracts the underlying complexity of the technical details of the cloud and creates additional value on top. I always say that the cloud players like Amazon have given the gift to the world of 100 billion dollars a year they spend in CapEx. Thank you. Now we're going to innovate on top of it. Yeah. And I think the refactoring... >> Hope by John. >> That was great insight and I totally agree. The refactoring piece too was key, he brought that home. But to me, I think Data bricks that Ali shared there and why he's been open and sharing a lot of his insights and the community. But what he's not saying, cause he's humble and polite is they cracked the code on the enterprise, Dave. And to Dave's points exactly reason why they did it, they saw an opportunity to make it easier, at that time had dupe was the rage, and they just made it easier. They was smart, they made good bets, they had a good formula and they cracked the code with the enterprise. They brought it in and they brought value. And see that's the key to the cloud as Dave pointed out. You get replatform with the cloud, then you refactor. And I think he pointed out the multi-cloud and that really kind of teases out the whole future and landscape, which is essentially distributed computing. And I think, you know, companies are starting to figure that out with hybrid and this on premises and now super edge I call it, with 5G coming. So it's just pretty incredible. >> Yeah. Data bricks, IPO is coming and people should know. I mean, what everybody, they created spark as you know John and everybody thought they were going to do is mimic red hat and sell subscriptions and support. They didn't, they developed a managed service and they embedded AI tools to simplify data science. So to your point, enterprises could buy instead of build, we know this. Enterprises will spend money to make things simpler. They don't have the resources, and so this was what they got right was really embedding that, making a building a managed service, not mimicking the kind of the red hat model, but actually creating a new value layer there. And that's big part of their success. >> If I could just add one thing Natalie to that Dave saying is really right on. And as an enterprise buyer, if we go the other side of the equation, it used to be that you had to be a known company, get PR, you fill out RFPs, you had to meet all the speeds. It's like going to the airport and get a swab test, and get a COVID test and all kinds of mechanisms to like block you and filter you. Most of the biggest success stories that have created the most value for enterprises have been the companies that nobody's understood. And Andy Jazz's famous quote of, you know, being misunderstood is actually a good thing. Data bricks was very misunderstood at the beginning and no one kind of knew who they were but they did it right. And so the enterprise buyers out there, don't be afraid to test the startups because you know the next Data bricks is out there. And I think that's where I see the psychology changing from the old IT buyers, Dave. It's like, okay, let's let's test this company. And there's plenty of ways to do that. He illuminated those premium, small pilots, you don't need to go on these big things. So I think that is going to be a shift in how companies going to evaluate startups. >> Yeah. Think about it this way. Why should the large banks and insurance companies and big manufacturers and pharma companies, governments, why should they burn resources managing containers and figuring out data science tools if they can just tap into solutions like Data bricks which is an AI platform in the cloud and let the experts manage all that stuff. Think about how much money in time that saves enterprises. >> Yeah, I mean, we've got 15 companies here we're showcasing this batch and this season if you call it. That episode we are going to call it? They're awesome. Right? And the next 15 will be the same. And these companies could be the next billion dollar revenue generator because the cloud enables that day. I think that's the exciting part. >> Well thank you both so much for these insights. Really appreciate it. AWS startup showcase highlights the innovation that helps startups succeed. And no one knows that better than our very next guest, Jeff Barr. Welcome to the show and I will send this interview now to Dave and John and see you just in the bit. >> Okay, hey Jeff, great to see you. Thanks for coming on again. >> Great to be back. >> So this is a regular community segment with Jeff Barr who's a legend in the industry. Everyone knows your name. Everyone knows that. Congratulations on your recent blog posts we have reading. Tons of news, I want to get your update because 5G has been all over the news, mobile world congress is right around the corner. I know Bill Vass was a keynote out there, virtual keynote. There's a lot of Amazon discussion around the edge with wavelength. Specifically, this is the outpost piece. And I know there is news I want to get to, but the top of mind is there's massive Amazon expansion and the cloud is going to the edge, it's here. What's up with wavelength. Take us through the, I call it the power edge, the super edge. >> Well, I'm really excited about this mostly because it gives a lot more choice and flexibility and options to our customers. This idea that with wavelength we announced quite some time ago, at least quite some time ago if we think in cloud years. We announced that we would be working with 5G providers all over the world to basically put AWS in the telecom providers data centers or telecom centers, so that as their customers build apps, that those apps would take advantage of the low latency, the high bandwidth, the reliability of 5G, be able to get to some compute and storage services that are incredibly close geographically and latency wise to the compute and storage that is just going to give customers this new power and say, well, what are the cool things we can build? >> Do you see any correlation between wavelength and some of the early Amazon services? Because to me, my gut feels like there's so much headroom there. I mean, I was just riffing on the notion of low latency packets. I mean, just think about the applications, gaming and VR, and metaverse kind of cool stuff like that where having the edge be that how much power there. It just feels like a new, it feels like a new AWS. I mean, what's your take? You've seen the evolutions and the growth of a lot of the key services. Like EC2 and SA3. >> So welcome to my life. And so to me, the way I always think about this is it's like when I go to a home improvement store and I wander through the aisles and I often wonder through with no particular thing that I actually need, but I just go there and say, wow, they've got this and they've got this, they've got this other interesting thing. And I just let my creativity run wild. And instead of trying to solve a problem, I'm saying, well, if I had these different parts, well, what could I actually build with them? And I really think that this breadth of different services and locations and options and communication technologies. I suspect a lot of our customers and customers to be and are in this the same mode where they're saying, I've got all this awesomeness at my fingertips, what might I be able to do with it? >> He reminds me when Fry's was around in Palo Alto, that store is no longer here but it used to be back in the day when it was good. It was you go in and just kind of spend hours and then next thing you know, you built a compute. Like what, I didn't come in here, whether it gets some cables. Now I got a motherboard. >> I clearly remember Fry's and before that there was the weird stuff warehouse was another really cool place to hang out if you remember that. >> Yeah I do. >> I wonder if I could jump in and you guys talking about the edge and Jeff I wanted to ask you about something that is, I think people are starting to really understand and appreciate what you did with the entrepreneur acquisition, what you do with nitro and graviton, and really driving costs down, driving performance up. I mean, there's like a compute Renaissance. And I wonder if you could talk about the importance of that at the edge, because it's got to be low power, it has to be low cost. You got to be doing processing at the edge. What's your take on how that's evolving? >> Certainly so you're totally right that we started working with and then ultimately acquired Annapurna labs in Israel a couple of years ago. I've worked directly with those folks and it's really awesome to see what they've been able to do. Just really saying, let's look at all of these different aspects of building the cloud that were once effectively kind of somewhat software intensive and say, where does it make sense to actually design build fabricate, deploy custom Silicon? So from putting up the system to doing all kinds of additional kinds of security checks, to running local IO devices, running the NBME as fast as possible to support the EBS. Each of those things has been a contributing factor to not just the power of the hardware itself, but what I'm seeing and have seen for the last probably two or three years at this point is the pace of innovation on instance types just continues to get faster and faster. And it's not just cranking out new instance types because we can, it's because our awesomely diverse base of customers keeps coming to us and saying, well, we're happy with what we have so far, but here's this really interesting new use case. And we needed a different ratio of memory to CPU, or we need more cores based on the amount of memory, or we needed a lot of IO bandwidth. And having that nitro as the base lets us really, I don't want to say plug and play, cause I haven't actually built this myself, but it seems like they can actually put the different elements together, very very quickly and then come up with new instance types that just our customers say, yeah, that's exactly what I asked for and be able to just do this entire range of from like micro and nano sized all the way up to incredibly large with incredible just to me like, when we talk about terabytes of memory that are just like actually just RAM memory. It's like, that's just an inconceivably large number by the standards of where I started out in my career. So it's all putting this power in customer hands. >> You used the term plug and play, but it does give you that nitro gives you that optionality. And then other thing that to me is really exciting is the way in which ISVs are writing to whatever's underneath. So you're making that, you know, transparent to the users so I can choose as a customer, the best price performance for my workload and that that's just going to grow that ISV portfolio. >> I think it's really important to be accurate and detailed and as thorough as possible as we launch each one of these new instance types with like what kind of processor is in there and what clock speed does it run at? What kind of, you know, how much memory do we have? What are the, just the ins and outs, and is it Intel or arm or AMD based? It's such an interesting to me contrast. I can still remember back in the very very early days of back, you know, going back almost 15 years at this point and effectively everybody said, well, not everybody. A few people looked and said, yeah, we kind of get the value here. Some people said, this just sounds like a bunch of generic hardware, just kind of generic hardware in Iraq. And even back then it was something that we were very careful with to design and optimize for use cases. But this idea that is generic is so, so, so incredibly inaccurate that I think people are now getting this. And it's okay. It's fine too, not just for the cloud, but for very specific kinds of workloads and use cases. >> And you guys have announced obviously the performance improvements on a lamb** does getting faster, you got the per billing, second billings on windows and SQL server on ECE too**. So I mean, obviously everyone kind of gets that, that's been your DNA, keep making it faster, cheaper, better, easier to use. But the other area I want to get your thoughts on because this is also more on the footprint side, is that the regions and local regions. So you've got more region news, take us through the update on the expansion on the footprint of AWS because you know, a startup can come in and these 15 companies that are here, they're global with AWS, right? So this is a major benefit for customers around the world. And you know, Ali from Data bricks mentioned privacy. Everyone's a privacy company now. So the huge issue, take us through the news on the region. >> Sure, so the two most recent regions that we announced are in the UAE and in Israel. And we generally like to pre-announce these anywhere from six months to two years at a time because we do know that the customers want to start making longer term plans to where they can start thinking about where they can do their computing, where they can store their data. I think at this point we now have seven regions under construction. And, again it's all about customer trice. Sometimes it's because they have very specific reasons where for based on local laws, based on national laws, that they must compute and restore within a particular geographic area. Other times I say, well, a lot of our customers are in this part of the world. Why don't we pick a region that is as close to that part of the world as possible. And one really important thing that I always like to remind our customers of in my audience is, anything that you choose to put in a region, stays in that region unless you very explicitly take an action that says I'd like to replicate it somewhere else. So if someone says, I want to store data in the US, or I want to store it in Frankfurt, or I want to store it in Sao Paulo, or I want to store it in Tokyo or Osaka. They get to make that very specific choice. We give them a lot of tools to help copy and replicate and do cross region operations of various sorts. But at the heart, the customer gets to choose those locations. And that in the early days I think there was this weird sense that you would, you'd put things in the cloud that would just mysteriously just kind of propagate all over the world. That's never been true, and we're very very clear on that. And I just always like to reinforce that point. >> That's great stuff, Jeff. Great to have you on again as a regular update here, just for the folks watching and don't know Jeff he'd been blogging and sharing. He'd been the one man media band for Amazon it's early days. Now he's got departments, he's got peoples on doing videos. It's an immediate franchise in and of itself, but without your rough days we wouldn't have gotten all the great news we subscribe to. We watch all the blog posts. It's essentially the flow coming out of AWS which is just a tsunami of a new announcements. Always great to read, must read. Jeff, thanks for coming on, really appreciate it. That's great. >> Thank you John, great to catch up as always. >> Jeff Barr with AWS again, and follow his stuff. He's got a great audience and community. They talk back, they collaborate and they're highly engaged. So check out Jeff's blog and his social presence. All right, Natalie, back to you for more coverage. >> Terrific. Well, did you guys know that Jeff took a three week AWS road trip across 15 cities in America to meet with cloud computing enthusiasts? 5,500 miles he drove, really incredible I didn't realize that. Let's unpack that interview though. What stood out to you John? >> I think Jeff, Barr's an example of what I call direct to audience a business model. He's been doing it from the beginning and I've been following his career. I remember back in the day when Amazon was started, he was always building stuff. He's a builder, he's classic. And he's been there from the beginning. At the beginning he was just the blog and it became a huge audience. It's now morphed into, he was power blogging so hard. He has now support and he still does it now. It's basically the conduit for information coming out of Amazon. I think Jeff has single-handedly made Amazon so successful at the community developer level, and that's the startup action happened and that got them going. And I think he deserves a lot of the success for AWS. >> And Dave, how about you? What is your reaction? >> Well I think you know, and everybody knows about the cloud and back stop X** and agility, and you know, eliminating the undifferentiated, heavy lifting and all that stuff. And one of the things that's often overlooked which is why I'm excited to be part of this program is the innovation. And the innovation comes from startups, and startups start in the cloud. And so I think that that's part of the flywheel effect. You just don't see a lot of startups these days saying, okay, I'm going to do something that's outside of the cloud. There are some, but for the most part, you know, if you saw in software, you're starting in the cloud, it's so capital efficient. I think that's one thing, I've throughout my career. I've been obsessed with every part of the stack from whether it's, you know, close to the business process with the applications. And right now I'm really obsessed with the plumbing, which is why I was excited to talk about, you know, the Annapurna acquisition. Amazon bought and a part of the $350 million, it's reported, you know, maybe a little bit more, but that isn't an amazing acquisition. And the reason why that's so important is because Amazon is continuing to drive costs down, drive performance up. And in my opinion, leaving a lot of the traditional players in their dust, especially when it comes to the power and cooling. You have often overlooked things. And the other piece of the interview was that Amazon is actually getting ISVs to write to these new platforms so that you don't have to worry about there's the software run on this chip or that chip, or x86 or arm or whatever it is. It runs. And so I can choose the best price performance. And that's where people don't, they misunderstand, you always say it John, just said that people are misunderstood. I think they misunderstand, they confused, you know, the price of the cloud with the cost of the cloud. They ignore all the labor costs that are associated with that. And so, you know, there's a lot of discussion now about the cloud tax. I just think the pace is accelerating. The gap is not closing, it's widening. >> If you look at the one question I asked them about wavelength and I had a follow up there when I said, you know, we riff on it and you see, he lit up like he beam was beaming because he said something interesting. It's not that there's a problem to solve at this opportunity. And he conveyed it to like I said, walking through Fry's. But like, you go into a store and he's a builder. So he sees opportunity. And this comes back down to the Martine Casada paradox posts he wrote about do you optimize for CapEx or future revenue? And I think the tell sign is at the wavelength edge piece is going to be so creative and that's going to open up massive opportunities. I think that's the place to watch. That's the place I'm watching. And I think startups going to come out of the woodwork because that's where the action will be. And that's just Amazon at the edge, I mean, that's just cloud at the edge. I think that is going to be very effective. And his that's a little TeleSign, he kind of revealed a little bit there, a lot there with that comment. >> Well that's a to be continued conversation. >> Indeed, I would love to introduce our next guest. We actually have Soma on the line. He's the managing director at Madrona venture group. Thank you Soma very much for coming for our keynote program. >> Thank you Natalie and I'm great to be here and will have the opportunity to spend some time with you all. >> Well, you have a long to nerd history in the enterprise. How would you define the modern enterprise also known as cloud scale? >> Yeah, so I would say I have, first of all, like, you know, we've all heard this now for the last, you know, say 10 years or so. Like, software is eating the world. Okay. Put it another way, we think about like, hey, every enterprise is a software company first and foremost. Okay. And companies that truly internalize that, that truly think about that, and truly act that way are going to start up, continue running well and things that don't internalize that, and don't do that are going to be left behind sooner than later. Right. And the last few years you start off thing and not take it to the next level and talk about like, not every enterprise is not going through a digital transformation. Okay. So when you sort of think about the world from that lens. Okay. Modern enterprise has to think about like, and I am first and foremost, a technology company. I may be in the business of making a car art, you know, manufacturing paper, or like you know, manufacturing some healthcare products or what have you got out there. But technology and software is what is going to give me a unique, differentiated advantage that's going to let me do what I need to do for my customers in the best possible way [Indistinct]. So that sort of level of focus, level of execution, has to be there in a modern enterprise. The other thing is like not every modern enterprise needs to think about regular. I'm competing for talent, not anymore with my peers in my industry. I'm competing for technology talent and software talent with the top five technology companies in the world. Whether it is Amazon or Facebook or Microsoft or Google, or what have you cannot think, right? So you really have to have that mindset, and then everything flows from that. >> So I got to ask you on the enterprise side again, you've seen many ways of innovation. You've got, you know, been in the industry for many, many years. The old way was enterprises want the best proven product and the startups want that lucrative contract. Right? Yeah. And get that beach in. And it used to be, and we addressed this in our earlier keynote with Ali and how it's changing, the buyers are changing because the cloud has enabled this new kind of execution. I call it agile, call it what you want. Developers are driving modern applications, so enterprises are still, there's no, the playbooks evolving. Right? So we see that with the pandemic, people had needs, urgent needs, and they tried new stuff and it worked. The parachute opened as they say. So how do you look at this as you look at stars, you're investing in and you're coaching them. What's the playbook? What's the secret sauce of how to crack the enterprise code today. And if you're an enterprise buyer, what do I need to do? I want to be more agile. Is there a clear path? Is there's a TSA to let stuff go through faster? I mean, what is the modern playbook for buying and being a supplier? >> That's a fantastic question, John, because I think that sort of playbook is changing, even as we speak here currently. A couple of key things to understand first of all is like, you know, decision-making inside an enterprise is getting more and more de-centralized. Particularly decisions around what technology to use and what solutions to use to be able to do what people need to do. That decision making is no longer sort of, you know, all done like the CEO's office or the CTO's office kind of thing. Developers are more and more like you rightly said, like sort of the central of the workflow and the decision making process. So it'll be who both the enterprises, as well as the startups to really understand that. So what does it mean now from a startup perspective, from a startup perspective, it means like, right. In addition to thinking about like hey, not do I go create an enterprise sales post, do I sell to the enterprise like what I might have done in the past? Is that the best way of moving forward, or should I be thinking about a product led growth go to market initiative? You know, build a product that is easy to use, that made self serve really works, you know, get the developers to start using to see the value to fall in love with the product and then you think about like hey, how do I go translate that into a contract with enterprise. Right? And more and more what I call particularly, you know, startups and technology companies that are focused on the developer audience are thinking about like, you know, how do I have a bottom up go to market motion? And sometime I may sort of, you know, overlap that with the top down enterprise sales motion that we know that has been going on for many, many years or decades kind of thing. But really this product led growth bottom up a go to market motion is something that we are seeing on the rise. I would say they're going to have more than half the startup that we come across today, have that in some way shape or form. And so the enterprise also needs to understand this, the CIO or the CTO needs to know that like hey, I'm not decision-making is getting de-centralized. I need to empower my engineers and my engineering managers and my engineering leaders to be able to make the right decision and trust them. I'm going to give them some guard rails so that I don't find myself in a soup, you know, sometime down the road. But once I give them the guard rails, I'm going to enable people to make the decisions. People who are closer to the problem, to make the right decision. >> Well Soma, what are some of the ways that startups can accelerate their enterprise penetration? >> I think that's another good question. First of all, you need to think about like, Hey, what are enterprises wanting to rec? Okay. If you start off take like two steps back and think about what the enterprise is really think about it going. I'm a software company, but I'm really manufacturing paper. What do I do? Right? The core thing that most enterprises care about is like, hey, how do I better engage with my customers? How do I better serve my customers? And how do I do it in the most optimal way? At the end of the day that's what like most enterprises really care about. So startups need to understand, what are the problems that the enterprise is trying to solve? What kind of tools and platform technologies and infrastructure support, and, you know, everything else that they need to be able to do what they need to do and what only they can do in the most optimal way. Right? So to the extent you are providing either a tool or platform or some technology that is going to enable your enterprise to make progress on what they want to do, you're going to get more traction within the enterprise. In other words, stop thinking about technology, and start thinking about the customer problem that they want to solve. And the more you anchor your company, and more you anchor your conversation with the customer around that, the more the enterprise is going to get excited about wanting to work with you. >> So I got to ask you on the enterprise and developer equation because CSOs and CXOs, depending who you talk to have that same answer. Oh yeah. In the 90's and 2000's, we kind of didn't, we throttled down, we were using the legacy developer tools and cloud came and then we had to rebuild and we didn't really know what to do. So you seeing a shift, and this is kind of been going on for at least the past five to eight years, a lot more developers being hired yet. I mean, at FinTech is clearly a vertical, they always had developers and everyone had developers, but there's a fast ramp up of developers now and the role of open source has changed. Just looking at the participation. They're not just consuming open source, open source is part of the business model for mainstream enterprises. How is this, first of all, do you agree? And if so, how has this changed the course of an enterprise human resource selection? How they're organized? What's your vision on that? >> Yeah. So as I mentioned earlier, John, in my mind the first thing is, and this sort of, you know, like you said financial services has always been sort of hiring people [Indistinct]. And this is like five-year old story. So bear with me I'll tell you the firewall story and then come to I was trying to, the cloud CIO or the Goldman Sachs. Okay. And this is five years ago when people were still like, hey, is this cloud thing real and now is cloud going to take over the world? You know, am I really ready to put my data in the cloud? So there are a lot of questions and conversations can affect. The CIO of Goldman Sachs told me two things that I remember to this day. One is, hey, we've got a internal edict. That we made a decision that in the next five years, everything in Goldman Sachs is going to be on the public law. And I literally jumped out of the chair and I said like now are you going to get there? And then he laughed and said like now it really doesn't matter whether we get there or not. We want to set the tone, set the direction for the organization that hey, public cloud is here. Public cloud is there. And we need to like, you know, move as fast as we realistically can and think about all the financial regulations and security and privacy. And all these things that we care about deeply. But given all of that, the world is going towards public load and we better be on the leading edge as opposed to the lagging edge. And the second thing he said, like we're talking about like hey, how are you hiring, you know, engineers at Goldman Sachs Canada? And he said like in hey, I sort of, my team goes out to the top 20 schools in the US. And the people we really compete with are, and he was saying this, Hey, we don't compete with JP Morgan or Morgan Stanley, or pick any of your favorite financial institutions. We really think about like, hey, we want to get the best talent into Goldman Sachs out of these schools. And we really compete head to head with Google. We compete head to head with Microsoft. We compete head to head with Facebook. And we know that the caliber of people that we want to get is no different than what these companies want. If you want to continue being a successful, leading it, you know, financial services player. That sort of tells you what's going on. You also talked a little bit about like hey, open source is here to stay. What does that really mean kind of thing. In my mind like now, you can tell me that I can have from given my pedigree at Microsoft, I can tell you that we were the first embraces of open source in this world. So I'll say that right off the bat. But having said that we did in our turn around and said like, hey, this open source is real, this open source is going to be great. How can we embrace and how can we participate? And you fast forward to today, like in a Microsoft is probably as good as open source as probably any other large company I would say. Right? Including like the work that the company has done in terms of acquiring GitHub and letting it stay true to its original promise of open source and community can I think, right? I think Microsoft has come a long way kind of thing. But the thing that like in all these enterprises need to think about is you want your developers to have access to the latest and greatest tools. To the latest and greatest that the software can provide. And you really don't want your engineers to be reinventing the wheel all the time. So there is something available in the open source world. Go ahead, please set up, think about whether that makes sense for you to use it. And likewise, if you think that is something you can contribute to the open source work, go ahead and do that. So it's really a two way somebody Arctic relationship that enterprises need to have, and they need to enable their developers to want to have that symbiotic relationship. >> Soma, fantastic insights. Thank you so much for joining our keynote program. >> Thank you Natalie and thank you John. It was always fun to chat with you guys. Thank you. >> Thank you. >> John we would love to get your quick insight on that. >> Well I think first of all, he's a prolific investor the great from Madrona venture partners, which is well known in the tech circles. They're in Seattle, which is in the hub of I call cloud city. You've got Amazon and Microsoft there. He'd been at Microsoft and he knows the developer ecosystem. And reason why I like his perspective is that he understands the value of having developers as a core competency in Microsoft. That's their DNA. You look at Microsoft, their number one thing from day one besides software was developers. That was their army, the thousand centurions that one won everything for them. That has shifted. And he brought up open source, and .net and how they've embraced Linux, but something that tele before he became CEO, we interviewed him in the cube at an Xcel partners event at Stanford. He was open before he was CEO. He was talking about opening up. They opened up a lot of their open source infrastructure projects to the open compute foundation early. So they had already had that going and at that price, since that time, the stock price of Microsoft has skyrocketed because as Ali said, open always wins. And I think that is what you see here, and as an investor now he's picking in startups and investing in them. He's got to read the tea leaves. He's got to be in the right side of history. So he brings a great perspective because he sees the old way and he understands the new way. That is the key for success we've seen in the enterprise and with the startups. The people who get the future, and can create the value are going to win. >> Yeah, really excellent point. And just really quickly. What do you think were some of our greatest hits on this hour of programming? >> Well first of all I'm really impressed that Ali took the time to come join us because I know he's super busy. I think they're at a $28 billion valuation now they're pushing a billion dollars in revenue, gap revenue. And again, just a few short years ago, they had zero software revenue. So of these 15 companies we're showcasing today, you know, there's a next Data bricks in there. They're all going to be successful. They already are successful. And they're all on this rocket ship trajectory. Ali is smart, he's also got the advantage of being part of that Berkeley community which they're early on a lot of things now. Being early means you're wrong a lot, but you're also right, and you're right big. So Berkeley and Stanford obviously big areas here in the bay area as research. He is smart, He's got a great team and he's really open. So having him share his best practices, I thought that was a great highlight. Of course, Jeff Barr highlighting some of the insights that he brings and honestly having a perspective of a VC. And we're going to have Peter Wagner from wing VC who's a classic enterprise investors, super smart. So he'll add some insight. Of course, one of the community session, whenever our influencers coming on, it's our beat coming on at the end, as well as Katie Drucker. Another Madrona person is going to talk about growth hacking, growth strategies, but yeah, sights Raleigh coming on. >> Terrific, well thank you so much for those insights and thank you to everyone who is watching the first hour of our live coverage of the AWS startup showcase for myself, Natalie Ehrlich, John, for your and Dave Vellante we want to thank you very much for watching and do stay tuned for more amazing content, as well as a special live segment that John Furrier is going to be hosting. It takes place at 12:30 PM Pacific time, and it's called cracking the code, lessons learned on how enterprise buyers evaluate new startups. Don't go anywhere.

(bright music) >> Welcome back to the CUBE presents the AWS Startup Showcase The Next Big Thing in cloud startups with AI security and life science tracks, 15 hottest growing startups are presented. And we had a great opening keynote with luminaries in the industry. And now our closing keynote is to get a deeper dive on cracking the code in the enterprise, how startups are changing the game and helping companies change. And they're also changing the game of open source. We have a great guest, Katie Drucker, Head of Business Development, Madrona Venture Group. Katie, thank you for coming on the CUBE for this special closing keynote. >> Thank you for having me, I appreciate it. >> So one of the topics we talked about with Soma from Madrona on the opening keynote, as well as Ali from Databricks is how startups are seeing success faster. So that's the theme of the Cloud speed, agility, but the game has changed in the enterprise. And I want to really discuss with you how growth changes and growth strategy specifically. They talk, go to market. We hear things like good sales to enterprise sales, organic, freemium, there's all kinds of different approaches, but at the end of the day, the most successful companies, the ones that might not be known that just come out of nowhere. So the economics are changing and the buyers are thinking differently. So let's explore that topic. So take us through your view 'cause you have a lot of experience. But first talk about your role at Madrona, what you do. >> Absolutely all great points. So my role at Madrona, I think I have personally one of the more enviable jobs and that my job is to... I get the privilege of working with all of these fantastic entrepreneurs in our portfolio and doing whatever we can as a firm to harness resources, knowledge, expertise, connections, to accelerate their growth. So my role in setting up business development is taking a look at all of those tools in the tool chest and partnering with the portfolio to make it so. And in our portfolio, we have a wide range of companies, some rely on enterprise sales, some have other go to markets. Some are direct to consumer, a wide range. >> Talk about the growth strategies that you see evolving because what's clear with the pandemic. And as we come out of it is that there are growth plays happening that don't look a little bit differently, more obvious now because of the Cloud scale, we're seeing companies like Databricks, like Snowflake, like other companies that have been built on the cloud or standalone. What are some of the new growth techniques, or I don't want to say growth hacking, that is a pejorative term, but like just a way for companies to quickly describe their value to an enterprise buyer who's moving away from the old RFP days of vendor selection. The game has changed. So take us through how you see secret key and unlocking that new equation of how to present value to an enterprise and how you see enterprises evaluating startups. >> Yes, absolutely. Well, and that's got a question, that's got a few components nestled in what I think are some bigger trends going on. AWS of course brought us the Cloud first. I think now the Cloud is more and more a utility. And so it's incumbent upon thinking about how an enterprise 'cause using the Cloud is going to go up the value stack and partner with its cloud provider and other service providers. I think also with that agility of operations, you have thinning, if you will, the systems of record and a lot of new entrance into this space that are saying things like, how can we harness AIML and other emerging trends to provide more value directly around work streams that were historically locked into those systems of record? And then I think you also have some price plans that are far more flexible around usage based as opposed to just flat subscription or even these big clunky annual or multi-year RFP type stuff. So all of those trends are really designed in ways that favor the emerging startup. And I think if done well, and in partnership with those underlying cloud providers, there can be some amazing benefits that the enterprise realizes an opportunity for those startups to grow. And I think that's what you're seeing. I think there's also this emergence of a buyer that's different than the CIO or the site the CISO. You have things with low code, no code. You've got other buyers in the organization, other line of business executives that are coming to the table, making software purchase decisions. And then you also have empowered developers that are these citizen builders and developer buyers and personas that really matter. So lots of inroads in places for a startup to reach in the enterprise to make a connection and to bring value. That's a great insight. I want to ask that just if you don't mind follow up on that, you mentioned personas. And what we're seeing is the shift happens. There's new roles that are emerging and new things that are being reconfigured or refactored if you will, whether it's human resources or AI, and you mentioned ML playing a role in automation. These are big parts of the new value proposition. How should companies posture to the customer? Because I don't want to say pivot 'cause that means it's not working but mostly extending our iterating around their positioning because as new things have not yet been realized, it might not be operationalized in a company or maybe new things need to be operationalized, it's a new solution for that. Positioning the value is super important and a lot of companies often struggle with that, but also if they get it right, that's the key. What's your feeling on startups in their positioning? So people will dismiss it like, "Oh, that's marketing." But maybe that's important. What's your thoughts on the great positioning question? >> I've been in this industry a long time. And I think there are some things that are just tried and true, and it is not unique to tech, which is, look, you have to tell a story and you have to reach the customer and you have to speak to the customer's need. And what that means is, AWS is a great example. They're famous for the whole concept of working back from the customer and thinking about what that customer's need is. I think any startup that is looking to partner or work alongside of AWS really has to embody that very, very customer centric way of thinking about things, even though, as we just talked about those personas are changing who that customer really is in the enterprise. And then speaking to that value proposition and meeting that customer and creating a dialogue with them that really helps to understand not only what their pain points are, but how you were offering solves those pain points. And sometimes the customer doesn't realize that that is their pain point and that's part of the education and part of the way in which you engage that dialogue. That doesn't change a lot, just generation to generation. I think the modality of how we have that dialogue, the methods in which we choose to convey that change, but that basic discussion is what makes us human. >> What's your... Great, great, great insight. I want to ask you on the value proposition question again, the question I often get, and it's hard to answer is am I competing on value or am I competing on commodity? And depending on where you're in the stack, there could be different things like, for example, land is getting faster, smaller, cheaper, as an example on Amazon. That's driving down to low cost high value, but it shifts up the stack. You start to see in companies this changing the criteria for how to evaluate. So an enterprise might be struggling. And I often hear enterprises say, "I don't know how to pick who I need. I buy tools, I don't buy many platforms." So they're constantly trying to look for that answer key, if you will, what's your thoughts on the changing requirements of an enterprise? And how to do vendor selection. >> Yeah, so obviously I don't think there's a single magic bullet. I always liked just philosophically to think about, I think it's always easier and frankly more exciting as a buyer to want to buy stuff that's going to help me make more revenue and build and grow as opposed to do things that save me money. And just in a binary way, I like to think which side of the fence are you sitting on as a product offering? And the best ways that you can articulate that, what opportunities are you unlocking for your customer? The problems that you're solving, what kind of growth and what impact is that going to lead to, even if you're one or two removed from that? And again, that's not a new concept. And I think that the companies that have that squarely in mind when they think about their go-to market strategy, when they think about the dialogue they're having, when they think about the problems that they're solving, find a much faster path. And I think that also speaks to why we're seeing so many explosion in the line of business, SAS apps that are out there. Again, that thinning of the systems of record, really thinking about what are the scenarios and work streams that we can have happened that are going to help with that revenue growth and unlocking those opportunities. >> What's the common startup challenge that you see when they're trying to do business development? Usually they build the product first, product led value, you hear that a lot. And then they go, "Okay, we're ready to sell, hire a sales guy." That seems to be shifting away because of the go to markets are changing. What are some of the challenges that startups have? What are some that you're seeing? >> Well, and I think the point that you're making about the changes are really almost a result of the trends that we're talking about. The sales organization itself is becoming... These work streams are becoming instrumented. Data is being collected, insights are being derived off of those things. So you see companies like Clary or Highspot or two examples or tutorial that are in our portfolio that are looking at that action and making the art of sales and marketing far more sophisticated overall, which then leads to the different growth hacking and the different insights that are driven. I think the common mistakes that I see across the board, especially with earlier stage startups, look you got to find product market fit. I think that's always... You start with a thesis or a belief and a passion that you're building something that you think the market needs. And it's a lot of dialogue you have to have to make sure that you do find that. I think once you find that another common problem that I see is leading with an explanation of technology. And again, not focusing on the buyer or the... Sorry, the buyer about solving a problem and focusing on that problem as opposed to focusing on how cool your technology is. Those are basic and really, really simple. And then I think setting a set of expectations, especially as it comes to business development and partnering with companies like AWS. The researching that you need to adequately meet the demand that can be turned on. And then I'm sure you heard about from Databricks, from an organization like AWS, you have to be pragmatic. >> Yeah, Databricks gone from zero a software sales a few years ago to over a billion. Now it looks like a Snowflake which came out of nowhere and they had a great product, but built on Amazon, they became the data cloud on top of Amazon. And now they're growing just whole new business models and new business development techniques. Katie, thank you for sharing your insight here. The CUBE's closing keynote. Thanks for coming on. >> Appreciate it, thank you. >> Okay, Katie Drucker, Head of Business Development at Madrona Venture Group. Premier VC in the Seattle area and beyond they're doing a lot of cloud action. And of course they know AWS very well and investing in the ecosystem. So great, great stuff there. Next up is Peter Wagner partner at Wing.VX. Love this URL first of all 'cause of the VC domain extension. But Peter is a long time venture capitalist. I've been following his career. He goes back to the old networking days, back when the internet was being connected during the OSI days, when the TCP IP open systems interconnect was really happening and created so much. Well, Peter, great to see you on the CUBE here and congratulations with success at Wing VC. >> Yeah, thanks, John. It's great to be here. I really appreciate you having me. >> Reason why I wanted to have you come on. First of all, you had a great track record in investing over many decades. You've seen many waves of innovation, startups. You've seen all the stories. You've seen the movie a few times, as I say. But now more than ever, enterprise wise it's probably the hottest I've ever seen. And you've got a confluence of many things on the stack. You were also an early seed investor in Snowflake, well-regarded as a huge success. So you've got your eye on some of these awesome deals. Got a great partner over there has got a network experience as well. What is the big aha moment here for the industry? Because it's not your classic enterprise startups anymore. They have multiple things going on and some of the winners are not even known. They come out of nowhere and they connect to enterprise and get the lucrative positions and can create a moat and value. Like out of nowhere, it's not the old way of like going to the airport and doing an RFP and going through the stringent requirements, and then you're in, you get to win the lucrative contract and you're in. Not anymore, that seems to have changed. What's your take on this 'cause people are trying to crack the code here and sometimes you don't have to be well-known. >> Yeah, well, thank goodness the game has changed 'cause that old thing was (indistinct) So I for one don't miss it. There was some modernization movement in the enterprise and the modern enterprise is built on data powered by AI infrastructure. That's an agile workplace. All three of those things are really transformational. There's big investments being made by enterprises, a lot of receptivity and openness to technology to enable all those agendas, and that translates to good prospects for startups. So I think as far as my career goes, I've never seen a more positive or fertile ground for startups in terms of penetrating enterprise, it doesn't mean it's easy to do, but you have a receptive audience on the other side and that hasn't necessarily always been the case. >> Yeah, I got to ask you, I know that you're a big sailor and your family and Franks Lubens also has a boat and sailing metaphor is always good to have 'cause you got to have a race that's being run and they have tactics. And this game that we're in now, you see the successes, there's investment thesises, and then there's also actually bets. And I want to get your thoughts on this because a lot of enterprises are trying to figure out how to evaluate startups and starts also can make the wrong bet. They could sail to the wrong continent and be in the wrong spot. So how do you pick the winners and how should enterprises understand how to pick winners too? >> Yeah, well, one of the real important things right now that enterprise is facing startups are learning how to do and so learning how to leverage product led growth dynamics in selling to the enterprise. And so product led growth has certainly always been important consumer facing companies. And then there's a few enterprise facing companies, early ones that cracked the code, as you said. And some of these examples are so old, if you think about, like the ones that people will want to talk about them and talk about Classy and want to talk about Twilio and these were of course are iconic companies that showed the way for others. But even before that, folks like Solar Winds, they'd go to market model, clearly product red, bottom stuff. Back then we didn't even have those words to talk about it. And then some of the examples are so enormous if think about them like the one right in front of your face, like AWS. (laughing) Pretty good PLG, (indistinct) but it targeted builders, it targeted developers and flipped over the way you think about enterprise infrastructure, as a result some how every company, even if they're harnessing relatively conventional sales and marketing motion, and you think about product led growth as a way to kick that motion off. And so it's not really an either word even more We might think OPLJ, that means there's no sales keep one company not true, but here's a way to set the table so that you can very efficiently use your sales and marketing resources, only have the most attractive targets and ones that are really (indistinct) >> I love the product led growth. I got to ask you because in the networking days, I remember the term inevitability was used being nested in a solution that they're just going to Cisco off router and a firewall is one you can unplug and replace with another vendor. Cisco you'd have to go through no switching costs were huge. So when you get it to the Cloud, how do you see the competitiveness? Because we were riffing on this with Ali, from Databricks where the lock-in might be value. The more value provider is the lock-in. Is their nestedness? Is their intimate ability as a competitive advantage for some of these starts? How do you look at that? Because startups, they're using open source. They want to have a land position in an enterprise, but how do they create that sustainable competitive advantage going forward? Because again, this is what you do. You bet on ones that you can see that could establish a model whatever we want to call it, but a competitive advantage and ongoing nested position. >> Sometimes it has to do with data, John, and so you mentioned Snowflake a couple of times here, a big part of Snowflake's strategy is what they now call the data cloud. And one of the reasons you go there is not to just be able to process data, to actually get access to it, exchange with the partners. And then that of course is a great reason for the customers to come to the Snowflake platform. And so the more data it gets more customers, it gets more data, the whole thing start spinning in the right direction. That's a really big example, but all of these startups that are using ML in a fundamental way, applying it in a novel way, the data modes are really important. So getting to the right data sources and training on it, and then putting it to work so that you can see that in this process better and doing this earlier on that scale. That's a big part of success. Another company that I work with is a good example that I call (indistinct) which works in sales technology space, really crushing it in terms of building better sales organizations both at performance level, in terms of the intelligence level, and just overall revenue attainment using ML, and using novel data sources, like the previously lost data or phone calls or Zoom calls as you already know. So I think the data advantages are really big. And smart startups are thinking through it early. >> It's interest-- >> And they're planning by the way, not to ramble on too much, but they're betting that PLG strategy. So their land option is designed not just to be an interesting way to gain usage, but it's also a way to gain access to data that then enables the expand in a component. >> That is a huge call-out point there, I was going to ask another question, but I think that is the key I see. It's a new go to market in a way. product led with that kind of approach gets you a beachhead and you get a little position, you get some data that is a cloud model, it means variable, whatever you want to call it variable value proposition, value proof, or whatever, getting that data and reiterating it. So it brings up the whole philosophical question of okay, product led growth, I love that with product led growth of data, I get that. Remember the old platform versus a tool? That's the way buyers used to think. How has that changed? 'Cause now almost, this conversation throws out the whole platform thing, but isn't like a platform. >> It looks like it's all. (laughs) you can if it is a platform, though to do that you can reveal that later, but you're looking for adoption, so if it's down stock product, you're looking for adoption by like developers or DevOps people or SOEs, and they're trying to solve a problem, and they want rapid gratification. So they don't want to have an architectural boomimg, placed in front of them. And if it's up stock product and application, then it's a user or the business or whatever that is, is adopting the application. And again, they're trying to solve a very specific problem. You need instant and immediate obvious time and value. And now you have a ticket to the dance and build on that and maybe a platform strategy can gradually take shape. But you know who's not in this conversation is the CIO, it's like, "I'm always the last to know." >> That's the CISO though. And they got him there on the firing lines. CISOs are buying tools like it's nobody's business. They need everything. They'll buy anything or you go meet with sand, they'll buy it. >> And you make it sound so easy. (laughing) We do a lot of security investment if only (indistinct) (laughing) >> I'm a little bit over the top, but CISOs are under a lot of pressure. I would talk to the CISO at Capital One and he was saying that he's on Amazon, now he's going to another cloud, not as a hedge, but he doesn't want to focus development teams. So he's making human resource decisions as well. Again, back to what IT used to be back in the old days where you made a vendor decision, you built around it. So again, clouds play that way. I see that happening. But the question is that I think you nailed this whole idea of cross hairs on the target persona, because you got to know who you are and then go to the market. So if you know you're a problem solving and the lower in the stack, do it and get a beachhead. That's a strategy, you can do that. You can't try to be the platform and then solve a problem at the same time. So you got to be careful. Is that what you were getting at? >> Well, I think you just understand what you're trying to achieve in that line of notion. And how those dynamics work and you just can't drag it out. And they could make it too difficult. Another company I work with is a very strategic cloud data platform. It's a (indistinct) on systems. We're not trying to foist that vision though (laughs) or not adopters today. We're solving some thorny problems with them in the short term, rapid time to value operational needs in scale. And then yeah, once they found success with (indistinct) there's would be an opportunity to be increasing the platform, and an obstacle for those customers. But we're not talking about that. >> Well, Peter, I appreciate you taking the time and coming out of a board meeting, I know that you're super busy and I really appreciate you making time for us. I know you've got an impressive partner in (indistinct) who's a former Sequoia, but Redback Networks part of that company over the years, you guys are doing extremely well, even a unique investment thesis. I'd like you to put the plug in for the firm. I think you guys have a good approach. I like what you guys are doing. You're humble, you don't brag a lot, but you make a lot of great investments. So could you take them in to explain what your investment thesis is and then how that relates to how an enterprise is making their investment thesis? >> Yeah, yeah, for sure. Well, the concept that I described earlier that the modern enterprise movement as a workplace built on data powered by AI. That's what we're trying to work with founders to enable. And also we're investing in companies that build the products and services that enable that modern enterprise to exist. And we do it from very early stages, but with a longterm outlook. So we'll be leading series and series, rounds of investment but staying deeply involved, both operationally financially throughout the whole life cycle of the company. And then we've done that a bunch of times, our goal is always the big independent public company and they don't always make it but enough for them to have it all be worthwhile. An interesting special case of this, and by the way, I think it intersects with some of startup showcase here is in the life sciences. And I know you were highlighting a lot of healthcare websites and deals, and that's a vertical where to disrupt tremendous impact of data both new data availability and new ways to put it to use. I know several of my partners are very focused on that. They call it bio-X data. It's a transformation all on its own. >> That's awesome. And I think that the reason why we're focusing on these verticals is if you have a cloud horizontal scale view and vertically specialized with machine learning, every vertical is impacted by data. It's so interesting that I think, first start, I was probably best time to be a cloud startup right now. I really am bullish on it. So I appreciate you taking the time Peter to come in again from your board meeting, popping out. Thanks for-- (indistinct) Go back in and approve those stock options for all the employees. Yeah, thanks for coming on. Appreciate it. >> All right, thank you John, it's a pleasure. >> Okay, Peter Wagner, Premier VC, very humble Wing.VC is a great firm. Really respect them. They do a lot of great investing investments, Snowflake, and we have Dave Vellante back who knows a lot about Snowflake's been covering like a blanket and Sarbjeet Johal. Cloud Influencer friend of the CUBE. Cloud commentator and cloud experience built clouds, runs clouds now invests. So V. Dave, thanks for coming back on. You heard Peter Wagner at Wing VC. These guys have their roots in networking, which networking back in the day was, V. Dave. You remember the internet Cisco days, remember Cisco, Wellfleet routers. I think Peter invested in Arrow Point, remember Arrow Point, that was about in the 495 belt where you were. >> Lynch's company. >> That was Chris Lynch's company. I think, was he a sales guy there? (indistinct) >> That was his first big hit I think. >> All right, well guys, let's wrap this up. We've got a great program here. Sarbjeet, thank you for coming on. >> No worries. Glad to be here todays. >> Hey, Sarbjeet. >> First of all, really appreciate the Twitter activity lately on the commentary, the observability piece on Jeremy Burton's launch, Dave was phenomenal, but Peter was talking about this dynamic and I think ties this cracking the code thing together, which is there's a product led strategy that feels like a platform, but it's also a tool. In other words, it's not mutually exclusive, the old methods thrown out the window. Land in an account, know what problem you're solving. If you're below the stack, nail it, get data and go from there. If you're a process improvement up the stack, you have to much more of a platform longer-term sale, more business oriented, different motions, different mechanics. What do you think about that? What's your reaction? >> Yeah, I was thinking about this when I was listening to some of the startups pitching, if you will, or talking about what they bring to the table in this cloud scale or cloud era, if you will. And there are tools, there are applications and then they're big monolithic platforms, if you will. And then they're part of the ecosystem. So I think the companies need to know where they play. A startup cannot be platform from the get-go I believe. Now many aspire to be, but they have to start with tooling. I believe in, especially in B2B side of things, and then go into the applications, one way is to go into the application area, if you will, like a very precise use cases for certain verticals and stuff like that. And other parties that are going into the platform, which is like horizontal play, if you will, in technology. So I think they have to understand their age, like how old they are, how new they are, how small they are, because when their size matter when you are procuring as a big business, procuring your technology vendors size matters and the economic viability matters and their proximity to other windows matter as well. So I think we'll jump into that in other discussions later, but I think that's key, as you said. >> I would agree with that. I would phrase it in my mind, somewhat differently from Sarbjeet which is you have product led growth, and that's your early phase and you get product market fit, you get product led growth, and then you expand and there are many, many examples of this, and that's when you... As part of your team expansion strategy, you're going to get into the platform discussion. There's so many examples of that. You take a look at Ali Ghodsi today with what's happening at Databricks, Snowflake is another good example. They've started with product led growth. And then now they're like, "Okay, we've got to expand the team." Okta is another example that just acquired zero. That's about building out the platform, versus more of a point product. And there's just many, many examples of that, but you cannot to your point, very hard to start with a platform. Arm did it, but that was like a one in a million chance. >> It's just harder, especially if it's new and it's not operationalized yet. So one of the things Dave that we've observed the Cloud is some of the best known successes where nobody's not known at all, database we've been covering from the beginning 'cause we were close to that movement when they came out of Berkeley. But they still were misunderstood and they just started generating revenue in only last year. So again, only a few years ago, zero software revenue, now they're approaching a billion dollars. So it's not easy to make these vendor selections anymore. And if you're new and you don't have someone to operate it or your there's no department and the departments changing, that's another problem. These are all like enterprisey problems. What's your thoughts on that, Dave? >> Well, I think there's a big discussion right now when you've been talking all day about how should enterprise think about startups and think about most of these startups they're software companies and software is very capital efficient business. At the same time, these companies are raising hundreds of millions, sometimes over a billion dollars before they go to IPO. Why is that? A lot of it's going to promotion. I look at it as... And there's a big discussion going on but well, maybe sales can be more efficient and more direct and so forth. I really think it comes down to the golden rule. Two things really mattered in the early days in the startup it's sales and engineering. And writers should probably say engineering and sales and start with engineering. And then you got to figure out your go to market. Everything else is peripheral to those two and you don't get those two things right, you struggle. And I think that's what some of these successful startups are proving. >> Sarbjeet, what's your take on that point? >> Could you repeat the point again? Sorry, I lost-- >> As cloud scale comes in this whole idea of competing, the roles are changing. So look at IOT, look at the Edge, for instance, you got all kinds of new use cases that no one actually knows is a problem to solve. It's just pure opportunity. So there's no one's operational I could have a product, but it don't know we can buy it yet. It's a problem. >> Yeah, I think the solutions have to be point solutions and the startups need to focus on the practitioners, number one, not the big buyers, not the IT, if you will, but the line of business, even within that sphere, like just focus on the practitioners who are going to use that technology. I talked to, I think it wasn't Fiddler, no, it was CoreLogics. I think that story was great today earlier in how they kind of struggle in the beginning, they were trying to do a big bang approach as a startup, but then they almost stumbled. And then they found their mojo, if you will. They went to Don the market, actually, that's a very classic theory of disruption, like what we study from Harvard School of Business that you go down the market, go to the non-consumers, because if you're trying to compete head to head with big guys. Because most of the big guys have lot of feature and functionality, especially at the platform level. And if you're trying to innovate in that space, you have to go to the practitioners and solve their core problems and then learn and expand kind of thing. So I think you have to focus on practitioners a lot more than the traditional oracle buyers. >> Sarbjeet, we had a great thread last night in Twitter, on observability that you started. And there's a couple of examples there. Chaos searches and relatively small company right now, they just raised them though. And they're part of this star showcase. And they could've said, "Hey, we're going to go after Splunk." But they chose not to. They said, "Okay, let's kind of disrupt the elk stack and simplify that." Another example is a company observed, you've mentioned Jeremy Burton's company, John. They're focused really on SAS companies. They're not going after initially these complicated enterprise deals because they got to get it right or else they'll get churn, and churn is that silent killer of software companies. >> The interesting other company that was on the showcase was Tetra Science. I don't know if you noticed that one in the life science track, and again, Peter Wagner pointed out the life science. That's an under recognized in the press vertical that's exploding. Certainly during the pandemic you saw it, Tetra science is an R&D cloud, Dave, R&D data cloud. So pharmaceuticals, they need to do their research. So the pandemic has brought to life, this now notion of tapping into data resources, not just data lakes, but like real deal. >> Yeah, you and Natalie and I were talking about that this morning and that's one of the opportunities for R&D and you have all these different data sources and yeah, it's not just about the data lake. It's about the ecosystem that you're building around them. And I see, it's really interesting to juxtapose what Databricks is doing and what Snowflake is doing. They've got different strategies, but they play a part there. You can see how ecosystems can build that system. It's not one company is going to solve all these problems. It's going to really have to be connections across these various companies. And that's what the Cloud enables and ecosystems have all this data flowing that can really drive new insights. >> And I want to call your attention to a tweet Sarbjeet you wrote about Splunk's earnings and they're data companies as well. They got Teresa Carlson there now AWS as the president, working with Doug, that should change the game a little bit more. But there was a thread of the neath there. Andy Thry says to replies to Dave you or Sarbjeet, you, if you're on AWS, they're a fine solution. The world doesn't just revolve around AWS, smiley face. Well, a lot of it does actually. So (laughing) nice point, Andy. But he brings up this thing and Ali brought it up too, Hybrid now is a new operating system for what now Edge does. So we got Mobile World Congress happening this month in person. This whole Telco 5G brings up a whole nother piece of the Cloud puzzle. Jeff Barr pointed out in his keynote, Dave. Guys, I want to get your reaction. The Edge now is... I'm calling it the super Edge because it's not just Edge as we know it before. You're going to have these pops, these points of presence that are going to have wavelength as your spectrum or whatever they have. I think that's the solution for Azure. So you're going to have all this new cloud power for low latency applications. Self-driving delivery VR, AR, gaming, Telemetry data from Teslas, you name it, it's happening. This is huge, what's your thoughts? Sarbjeet, we'll start with you. >> Yeah, I think Edge is like bound to happen. And for many reasons, the volume of data is increasing. Our use cases are also expanding if you will, with the democratization of computer analysis. Specialization of computer, actually Dave wrote extensively about how Intel and other chip players are gearing up for that future if you will. Most of the inference in the AI world will happen in the field close to the workloads if you will, that can be mobility, the self-driving car that can be AR, VR. It can be healthcare. It can be gaming, you name it. Those are the few use cases, which are in the forefront and what alarm or use cases will come into the play I believe. I've said this many times, Edge, I think it will be dominated by the hyperscalers, mainly because they're building their Metro data centers now. And with a very low latency in the Metro areas where the population is, we're serving the people still, not the machines yet, or the empty areas where there is no population. So wherever the population is, all these big players are putting their data centers there. And I think they will dominate the Edge. And I know some Edge lovers. (indistinct) >> Edge huggers. >> Edge huggers, yeah. They don't like the hyperscalers story, but I think that's the way were' going. Why would we go backwards? >> I think you're right, first of all, I agree with the hyperscale dying you look at the top three clouds right now. They're all in the Edge, Hardcore it's a huge competitive battleground, Dave. And I think the missing piece, that's going to be uncovered at Mobile Congress. Maybe they'll miss it this year, but it's the developer traction, whoever wins the developer market or wins the loyalty, winning over the market or having adoption. The applications will drive the Edge. >> And I would add the fourth cloud is Alibaba. Alibaba is actually bigger than Google and they're crushing it as well. But I would say this, first of all, it's popular to say, "Oh not everything's going to move into the Cloud, John, Dave, Sarbjeet." But the fact is that AWS they're trend setter. They are crushing it in terms of features. And you'd look at what they're doing in the plumbing with Annapurna. Everybody's following suit. So you can't just ignore that, number one. Second thing is what is the Edge? Well, the edge is... Where's the logical place to process the data? That's what the Edge is. And I think to your point, both Sarbjeet and John, the Edge is going to be won by developers. It's going to be one by programmability and it's going to be low cost and really super efficient. And most of the data is going to stay at the Edge. And so who is in the best position to actually create that? Is it going to be somebody who was taking an x86 box and throw it over the fence and give it a fancy name with the Edge in it and saying, "Here's our Edge box." No, that's not what's going to win the Edge. And so I think first of all it's huge, it's wide open. And I think where's the innovation coming from? I agree with you it's the hyperscalers. >> I think the developers as John said, developers are the kingmakers. They build the solutions. And in that context, I always talk about the skills gravity, a lot of people are educated in certain technologies and they will keep using those technologies. Their proximity to that technology is huge and they don't want to learn something new. So as humans we just tend to go what we know how to use it. So from that front, I usually talk with consumption economics of cloud and Edge. It has to focus on the practitioners. And in this case, practitioners are developers because you're just cooking up those solutions right now. We're not serving that in huge quantity right now, but-- >> Well, let's unpack that Sarbjeet, let's unpack that 'cause I think you're right on the money on that. The consumption of the tech and also the consumption of the application, the end use and end user. And I think the reason why hyperscalers will continue to dominate besides the fact that they have all the resource and they're going to bring that to the Edge, is that the developers are going to be driving the applications at the Edge. So if you're low latency Edge, that's going to open up new applications, not just the obvious ones I did mention, gaming, VR, AR, metaverse and other things that are obvious. There's going to be non-obvious things that are going to be huge that are going to come out from the developers. But the Cloud native aspect of the hyperscalers, to me is where the scales are tipping, let me explain. IT was built to build a supply resource to the businesses who were writing business applications. Mostly driven by IBM in the mainframe in the old days, Dave, and then IT became IT. Telcos have been OT closed, "This is our thing, that's it." Now they have to open up. And the Cloud native technologies is the fastest way to value. And I think that paths, Sarbjeet is going to be defined by this new developer and this new super Edge concept. So I think it's going to be wide open. I don't know what to say. I can't guess, but it's going to be creative. >> Let me ask you a question. You said years ago, data's new development kit, does low code and no code to Sarbjeet's point, change the equation? In other words, putting data in the hands of those OT professionals, those practitioners who have the context. Does low-code and no-code enable, more of those protocols? I know it's a bromide, but the citizen developer, and what impact does that have? And who's in the best position? >> Well, I think that anything that reduces friction to getting stuff out there that can be automated, will increase the value. And then the question is, that's not even a debate. That's just fact that's going to be like rent, massive rise. Then the issue comes down to who has the best asset? The software asset that's eating the world or the tower and the physical infrastructure. So if the physical infrastructure aka the Telcos, can't generate value fast enough, in my opinion, the private equity will come in and take it over, and then refactor that business model to take advantage of the over the top software model. That to me is the big stare down competition between the Telco world and this new cloud native, whichever one yields in valley is going to blink first, if you say. And I think the Cloud native wins this one hands down because the assets are valuable, but only if they enable the new model. If the old model tries to hang on to the old hog, the old model as the Edge hugger, as Sarbjeet says, they'll just going to slowly milk that cow dry. So it's like, it's over. So to me, they have to move. And I think this Mobile World Congress day, we will see, we will be looking for that. >> Yeah, I think that in the Mobile World Congress context, I think Telcos should partner with the hyperscalers very closely like everybody else has. And they have to cave in. (laughs) I usually say that to them, like the people came in IBM tried to fight and they cave in. Other second tier vendors tried to fight the big cloud vendors like top three or four. And then they cave in. okay, we will serve our stuff through your cloud. And that's where all the buyers are congregating. They're going to buy stuff along with the skills gravity, the feature proximity. I've got another term I'll turn a coin. It matters a lot when you're doing one thing and you want to do another thing when you're doing all this transactional stuff and regular stuff, and now you want to do data science, where do you go? You go next to it, wherever you have been. Your skills are in that same bucket. And then also you don't have to write a new contract with a new vendor, you just go there. So in order to serve, this is a lesson for startups as well. You need to prepare yourself for being in the Cloud marketplaces. You cannot go alone independently to fight. >> Cloud marketplace is going to replace procurement, for sure, we know that. And this brings up the point, Dave, we talked about years ago, remember on the CUBE. We said, there's going to be Tier two clouds. I used that word in quotes cause nothing... What does it even mean Tier two. And we were talking about like Amazon, versus Microsoft and Google. We set at the time and Alibaba but they're in China, put that aside for a second, but the big three. They're going to win it all. And they're all going to be successful to a relative terms, but whoever can enable that second tier. And it ended up happening, Snowflake is that example. As is Databricks as is others. So Google and Microsoft as fast as they can replicate the success of AWS by enabling someone to build their business on their cloud in a way that allows the customer to refactor their business will win. They will win most of the lion's share my opinion. So I think that applies to the Edge as well. So whoever can come in and say... Whichever cloud says, "I'm going to enable the next Snowflake, the next enterprise solution." I think takes it. >> Well, I think that it comes back... Every conversation coming back to the data. And if you think about the prevailing way in which we treated data with the exceptions of the two data driven companies in their quotes is as we've shoved all the data into some single repository and tried to come up with a single version of the truth and it's adjudicated by a centralized team, with hyper specialized roles. And then guess what? The line of business, there's no context for the business in that data architecture or data Corpus, if you will. And then the time it takes to go from idea for a data product or data service commoditization is way too long. And that's changing. And the winners are going to be the ones who are able to exploit this notion of leaving data where it is, the point about data gravity or courting a new term. I liked that, I think you said skills gravity. And then enabling the business lines to have access to their own data teams. That's exactly what Ali Ghodsi, he was saying this morning. And really having the ability to create their own data products without having to go bow down to an ivory tower. That is an emerging model. All right, well guys, I really appreciate the wrap up here, Dave and Sarbjeet. I'd love to get your final thoughts. I'll just start by saying that one of the highlights for me was the luminary guests size of 15 great companies, the luminary guests we had from our community on our keynotes today, but Ali Ghodsi said, "Don't listen to what everyone's saying in the press." That was his position. He says, "You got to figure out where the puck's going." He didn't say that, but I'm saying, I'm paraphrasing what he said. And I love how he brought up Sky Cloud. I call it Sky net. That's an interesting philosophy. And then he also brought up that machine learning auto ML has got to be table stakes. So I think to me, that's the highlight walk away. And the second one is this idea that the enterprises have to have a new way to procure and not just the consumption, but some vendor selection. I think it's going to be very interesting as value can be proved with data. So maybe the procurement process becomes, here's a beachhead, here's a little bit of data. Let me see what it can do. >> I would say... Again, I said it was this morning, that the big four have given... Last year they spent a hundred billion dollars more on CapEx. To me, that's a gift. In so many companies, especially focusing on trying to hang onto the legacy business. They're saying, "Well not everything's going to move to the Cloud." Whatever, the narrative should change to, "Hey, thank you for that gift. We're now going to build value on top of the Cloud." Ali Ghodsi laid that out, how Databricks is doing it. And it's clearly what Snowflake's new with the data cloud. It basically a layer that abstracts all that underlying complexity and add value on top. Eventually going out to the Edge. That's a value added model that's enabled by the hyperscalers. And that to me, if I have to evaluate where I'm going to place my bets as a CIO or IT practitioner, I'm going to look at who are the ones that are actually embracing that investment that's been made and adding value on top in a way that can drive my data-driven, my digital business or whatever buzzword you want to throw on. >> Yeah, I think we were talking about the startups in today's sessions. I think for startups, my advice is to be as close as you can be to hyperscalers and anybody who awards them, they will cave in at the end of the day, because that's where the whole span of gravity is. That's what the innovation gravity is, everybody's gravitating towards that. And I would say quite a few times in the last couple of years that the rate of innovation happening in a non-cloud companies, when I talk about non-cloud means are not public companies. I think it's like diminishing, if you will, as compared to in cloud, there's a lot of innovation. The Cloud companies are not paying by power people anymore. They have all sophisticated platforms and leverage those, and also leverage the marketplaces and leverage their buyers. And the key will be how you highlight yourself in that cloud market place if you will. It's like in a grocery store where your product is placed and you have to market around it, and you have to have a good story telling team in place as well after you do the product market fit. I think that's a key. I think just being close to the Cloud providers, that's the way to go for startups. >> Real, real quick. Each of you talk about what it takes to crack the code for the enterprise in the modern era now. Dave, we'll start with you. What's it take? (indistinct) >> You got to have it be solving a problem that is 10X better at one 10th a cost of anybody else, if you're a small company, that rule number one. Number two is you obviously got to get product market fit. You got to then figure out. And I think, and again, you're in your early phases, you have to be almost processed builders, figure out... Your KPIs should all be built around retention. How do I define customer success? How do I keep customers and how do I make them loyal so that I know that my cost of acquisition is going to be at least one-third or lower than my lifetime value of that customer? So you've got to nail that. And then once you nail that, you've got to codify that process in the next phase, which really probably gets into your platform discussion. And that's really where you can start to standardize and scale and figure out your go to market and the relationship between marketing spend and sales productivity. And then when you get that, then you got to move on to figure out your Mot. Your Mot might just be a brand. It might be some secret sauce, but more often than not though, it's going to be the relationship that you build. And I think you've got to think about those phases and in today's world, you got to move really fast. Sarbjeet, real quick. What's the secret to crack the code? >> I think the secret to crack the code is partnership and alliances. As a small company selling to the bigger enterprises, the vendors size will be one of the big objections. Even if they don't say it, it's on the back of their mind, "What if these guys disappear tomorrow what would we do if we pick this technology?" And another thing is like, if you're building on the left side, which is the developer side, not on the right side, which is the operations or production side, if you will, you have to understand the sales cycles are longer on the right side and left side is easier to get to, but that's why we see a lot more startups. And on the left side of your DevOps space, if you will, because it's easier to sell to practitioners and market to them and then show the value correctly. And also understand that on the left side, the developers are very know how hungry, on the right side people are very cost-conscious. So understanding the traits of these different personas, if you will buyers, it will, I think set you apart. And as Dave said, you have to solve a problem, focus on practitioners first, because you're small. You have to solve political problems very well. And then you can expand. >> Well, guys, I really appreciate the time. Dave, we're going to do more of these, Sarbjeet we're going to do more of these. We're going to add more community to it. We're going to add our community rooms next time. We're going to do these quarterly and try to do them as more frequently, we learned a lot and we still got a lot more to learn. There's a lot more contribution out in the community that we're going to tap into. Certainly the CUBE Club as we call it, Dave. We're going to build this actively around Cloud. This is another 20 years. The Edge brings us more life with Cloud, it's really exciting. And again, enterprise is no longer an enterprise, it's just the world now. So great companies here, the next Databricks, the next IPO. The next big thing is in this list, Dave. >> Hey, John, we'll see you in Barcelona. Looking forward to that. Sarbjeet, I know in a second half, we're going to run into each other. So (indistinct) thank you John. >> Trouble has started. Great talking to you guys today and have fun in Barcelona and keep us informed. >> Thanks for coming. I want to thank Natalie Erlich who's in Rome right now. She's probably well past her bedtime, but she kicked it off and emceeing and hosting with Dave and I for this AW startup showcase. This is batch two episode two day. What do we call this? It's like a release so that the next 15 startups are coming. So we'll figure it out. (laughs) Thanks for watching everyone. Thanks. (bright music)

>>mhm Yes, Welcome back to the cubes coverage of red hat summit 2021 virtual, which we were in person this year but we're still remote. We still got the Covid coming around the corner. Soon to be in post. Covid got a great guest here, Clayton Coleman architect that red hat cuba love and I've been on many times expanded role again this year. More cloud, more cloud action. Great, great to see you. Thanks for coming on. >>It's a pleasure >>to be here. So great to see you were just riffing before we came on camera about distributed computing uh and the future of the internet, how it's all evolving, how much fun it is, how it's all changing still. The game is still the same, all that good stuff. But here at Red had some and we're gonna get into that, but I want to just get into the hard news and the real big, big opportunities here you're announcing with red hat new managed cloud services portfolio, take us through that. >>Sure. We're continuing to evolve our open shift managed offerings which has grown now to include um the redhead open shift service on amazon to complement our as your redhead open shift service. Um that means that we have um along with our partnership on IBM cloud and open ship dedicated on both a W S and G C P. We now have um managed open shift on all of the major clouds. And along with that we are bringing in and introducing the first, I think really the first step what we see as uh huh growing and involving the hybrid cloud ecosystem on top of open shift and there's many different ways to slice that, but it's about bringing capabilities on top of open shift in multiple environments and multiple clouds in ways that make developers and operation teams more productive because at the heart of it, that's our goal for open shift. And the broader, open source ecosystem is do what makes all of us safer, more, uh, more productive and able to deliver business value? >>Yeah. And that's a great steak you guys put in the ground. Um, and that's great messaging, great marketing, great value proposition. I want to dig into a little bit with you. I mean, you guys have, I think the only native offering on all the clouds out there that I know of, is that true? I mean, you guys have, it's not just, you know, you support AWS as your and I B M and G C P, but native offerings. >>We do not have a native offering on GCPD offered the same service. And this is actually interesting as we've evolved our approach. You know, everyone, when we talk about hybrid, Hybrid is, um, you know, dealing with the realities of the computing world, We live in, um, working with each of the major clouds, trying to deliver the best immigration possible in a way that drives that consistency across those environments. And so actually are open shift dedicated on AWS service gave us the inspiration a lot of the basic foundations for what became the integrated Native service. And we've worked with amazon very closely to make sure that that does the right thing for customers who have chosen amazon. And likewise, we're trying to continue to deliver the best experience, the best operational reliability that we can so that the choice of where you run your cloud, um, where you run your applications, um, matches the decisions you've already made and where your future investments are gonna be. So we want to be where customers are, but we also want to give you that consistency. That has been a hallmark of um of open shift since the beginning. >>Yeah. And thanks for clarifying, I appreciate that because the manage serves on GCB rest or native. Um let me ask about the application services because Jeff Barr from AWS posted a few weeks ago amazon celebrated their 15th birthday. They're still teenagers uh relatively speaking. But one comment he made that he that was interesting to me. And this applies kind of this cloud native megatrend happening is he says the A. P. I. S are basically the same and this brings up the hybrid environment. You guys are always been into the api side of the management with the cloud services and supporting all that. As you guys look at this ecosystem in open source. How is the role of A PS and these integrations? Because without solid integration all these services could break down and certainly the open source, more and more people are coding. So take me through how you guys look at these applications services because many people are predicting more service is going to be on boarding faster than ever before. >>It's interesting. So um for us working across multiple cloud environments, there are many similarities in those mps, but for every similarity there is a difference and those differences are actually what dr costs and drive complexity when you're integrating. Um and I think a lot of the role of this is, you know, the irresponsible to talk about the role of an individual company in the computing ecosystem moving to cloud native because as many of these capabilities are unlocked by large cloud providers and transformations in the kinds of software that we run at scale. You know, everybody is a participant in that. But then you look at the broad swath of developer and operator ecosystem and it's the communities of people who paper over those differences, who write run books and build um you know, the policies and who build the experience and the automation. Um not just in individual products or an individual clouds, but across the open source ecosystem. Whether it's technologies like answerable or Terror form, whether it's best practices websites around running kubernetes, um every every part of the community is really involved in driving up uh driving consistency, um driving predictability and driving reliability and what we try to do is actually work within those constraints um to take the ecosystem and to push it a little bit further. So the A. P. I. S. May be similar, but over time those differences can trip you up. And a lot of what I think we talked about where the industry is going, where where we want to be is everyone ultimately is going to own some responsibility for keeping their services running and making sure that their applications and their businesses are successful. The best outcome would be that the A. P. R. S are the same and they're open and that both the cloud providers and the open source ecosystem and vendors and partners who drive many of these open source communities are actually all working together to have the most consistent environment to make portability a true strength. But when someone does differentiate and has a true best to bring service, we don't want to build artificial walls between those. I mean, I mean, that's hybrid cloud is you're going to make choices that make sense for you if we tell people that their choices don't work or they can't integrate or, you know, an open source project doesn't support this vendor, that vendor, we're actually leaving a lot of the complexity buried in those organizations. So I think this is a great time to, as we turn over for cloud. Native looking at how we, as much as possible try to drive those ap is closer together and the consistency underneath them is both a community and a vendor. And uh for red hat, it's part of what we do is a core mission is trying to make sure that that consistency is actually real. You don't have to worry about those details when you're ignoring them. >>That's a great point. Before I get into some architectural impact, I want to get your thoughts on um, the, this trends going on, Everyone jumps on the bandwagon. You know, you say, oh yeah, I gotta, I want a data cloud, you know, everything is like the new, you know, they saw Snowflake Apollo, I gotta have some, I got some of that data, You've got streaming data services, you've got data services and native into the, these platforms. But a lot of these companies think it's just, you're just gonna get a data cloud, just, it's so easy. Um, they might try something and then they get stuck with it or they have to re factor, >>how do you look >>at that as an architect when you have these new hot trends like say a data cloud, how should customers be thinking about kicking the tires on services like that And how should they think holistically around architect in that? >>There's a really interesting mindset is, uh, you know, we deal with this a lot. Everyone I talked to, you know, I've been with red hat for 10 years now in an open shift. All 10 years of that. We've gone through a bunch of transformations. Um, and every time I talked to, you know, I've talked to the same companies and organizations over the last 10 years, each point in their evolution, they're making decisions that are the right decision at the time. Um, they're choosing a new capability. So platform as a service is a great example of a capability that allowed a lot of really large organizations to standardize. Um, that ties into digital transformation. Ci CD is another big trend where it's an obvious wind. But depending on where you jumped on the bandwagon, depending on when you adopted, you're going to make a bunch of different trade offs. And that, that process is how do we improve the ability to keep all of the old stuff moving forward as well? And so open api is open standards are a big part of that, but equally it's understanding the trade offs that you're going to make and clearly communicating those so with data lakes. Um, there was kind of the 1st and 2nd iterations of data lakes, there was the uh, in the early days these capabilities were knew they were based around open source software. Um, a lot of the Hadoop and big data ecosystem, you know, started based on some of these key papers from amazon and google and others taking infrastructure ideas bringing them to scale. We went through a whole evolution of that and the input and the output of that basically let us into the next phase, which I think is the second phase of data leak, which is we have this data are tools are so much better because of that first phase that the investments we made the first time around, we're going to have to pay another investment to make that transformation. And so I've actually, I never want to caution someone not to jump early, but it has to be the right jump and it has to be something that really gives you a competitive advantage. A lot of infrastructure technology is you should make the choices that you make one or two big bets and sometimes people say this, you call it using their innovation tokens. You need to make the bets on big technologies that you operate more effectively at scale. It is somewhat hard to predict that. I certainly say that I've missed quite a few of the exciting transformations in the field just because, um, it wasn't always obvious that it was going to pay off to the degree that um, customers would need. >>So I gotta ask you on the real time applications side of it, that's been a big trend, certainly in cloud. But as you look at hybrid hybrid cloud environments, for instance, streaming data has been a big issue. Uh any updates there from you on your managed service? >>That's right. So one of we have to manage services um that are both closely aligned three managed services that are closely aligned with data in three different ways. And so um one of them is redhead open shift streams for Apache Kafka, which is managed cloud service that focuses on bringing that streaming data and letting you run it across multiple environments. And I think that, you know, we get to the heart of what's the purpose of uh managed services is to reduce operational overhead and to take responsibilities that allow users to focus on the things that actually matter for them. So for us, um managed open shift streams is really about the flow of data between applications in different environments, whether that's from the edge to an on premise data center, whether it's an on premise data center to the cloud. And increasingly these services which were running in the public cloud, increasingly these services have elements that run in the public cloud, but also key elements that run close to where your applications are. And I think that bridge is actually really important for us. That's a key component of hybrid is connecting the different locations and different footprints. So for us the focus is really how do we get data moving to the right place that complements our API management service, which is an add on for open ship dedicated, which means once you've brought the data and you need to expose it back out to other applications in the environment, you can build those applications on open shift, you can leverage the capabilities of open shift api management to expose them more easily, both to end customers or to other applications. And then our third services redhead open shift data science. Um and that is a, an integration that makes it easy for data scientists in a kubernetes environment. On open shift, they easily bring together the data to make, to analyze it and to help route it is appropriate. So those three facets for us are pretty important. They can be used in many different ways, but that focus on the flow of data across these different environments is really a key part of our longer term strategy. >>You know, all the customer checkboxes there you mentioned earlier. I mean I'll just summarize that that you said, you know, obviously value faster application velocity time to value. Those are like the checkboxes, Gardner told analysts check those lower complexity. Oh, we do the heavy lifting, all cloud benefits, so that's all cool. Everyone kind of gets that, everyone's been around cloud knows devops all those things come into play right now. The innovation focuses on operations and day to operations, becoming much more specific. When people say, hey, I've done some lift and shift, I've done some Greenfield born in the cloud now, it's like, whoa, this stuff, I haven't seen this before. As you start scaling. So this brings up that concept and then you add in multi cloud and hybrid cloud, you gotta have a unified experience. So these are the hot areas right this year, I would say, you know, that day to operate has been around for a while, but this idea of unification around environments to be fully distributed for developers is huge. >>How do you >>architect for that? This is the number one question I get. And I tease out when people are kind of talking about their environments that challenges their opportunities, they're really trying to architect, you know, the foundation that building to be um future proof, they don't want to get screwed over when they have, they realize they made a decision, they weren't thinking about day to operation or they didn't think about the unified experience across clouds across environments and services. This is huge. What's your take on this? >>So this is um, this is probably one of the hardest questions I think I could get asked, which is uh looking into the crystal ball, what are the aspects of today's environments that are accidental complexity? That's really just a result of the slow accretion of technologies and we all need to make bets when, when the time is right within the business, um and which parts of it are essential. What are the fundamental hard problems and so on. The accidental complexity side for red hat, it's really about um that consistent environment through open shift bringing capabilities, our connection to open source and making sure that there's an open ecosystem where um community members, users vendors can all work together to um find solutions that work for them because there's not, there's no way to solve for all of computing. It's just impossible. I think that is kind of our that's our development process and that's what helps make that accidental complexity of all that self away over time. But in the essential complexity data is tied the location, data has gravity data. Lakes are a great example of because data has gravity. The more data that you bring together, the bigger the scale the tools you can bring, you can invest in more specialized tools. I've almost do that as a specialization centralization. There's a ton of centralization going on right now at the same time that these new technologies are available to make it easier and easier. Whether that's large scale automation um with conflict management technologies, whether that's kubernetes and deploying it in multiple sites in multiple locations and open shift, bringing consistency so that you can run the apps the same way. But even further than that is concentrating, mhm. More of what would have typically been a specialist problem, something that you build a one off around in your organization to work through the problem. We're really getting to a point where pretty soon now there is a technology or a service for everyone. How do you get the data into that service out? How do you secure it? How do you glue it together? Um I think of, you know, some people might call this um you know, the ultimate integration problem, which is we're going to have all of this stuff and all of these places, what are the core concepts, location, security, placement, topology, latency, where data resides, who's accessing that data, We think of these as kind of the building blocks of where we're going next. So for us trying to make investments in, how do we make kubernetes work better across lots of environments. I have a coupon talk coming up this coupon, it's really exciting for me to talk about where we're going with, you know, the evolution of kubernetes, bringing the different pieces more closely together across multiple environments. But likewise, when we talk about our managed services, we've approached the strategy for managed services as it's not just the service in isolation, it's how it connects to the other pieces. What can we learn in the community, in our services, working with users that benefits that connectivity. So I mentioned the open shift streams connecting up environments, we'd really like to improve how applications connect across disparate environments. That's a fundamental property of if you're going to have data uh in one geographic region and you didn't move services closer to that well, those services I need to know and encode and have that behavior to get closer to where the data is, whether it's one data lake or 10. We gotta have that flexibility in place. And so those obstructions are really, and to >>your point about the building blocks where you've got to factor in those building blocks, because you're gonna need to understand the latency impact, that's going to impact how you're gonna handle the compute piece, that's gonna handle all these things are coming into play. So, again, if you're mindful of the building blocks, just as a cloud concept, um, then you're okay. >>We hear this a lot. Actually, there's real challenges in the, the ecosystem of uh, we see a lot of the problems of I want to help someone automate and improved, but the more balkanize, the more spread out, the more individual solutions are in play, it's harder for someone to bring their technology to bear to help solve the problem. So looking for ways that we can um, you know, grease the skids to build the glue. I think open source works best when it's defining de facto solutions that everybody agrees on that openness and the easy access is a key property that makes de facto standards emerged from open source. What can we do to grow defacto standards around multi cloud and application movement and application interconnect I think is a very, it's already happening and what can we do to accelerate it? That's it. >>Well, I think you bring up a really good point. This is probably a follow up, maybe a clubhouse talk or you guys will do a separate session on this. But I've been riffing on this idea of uh, today's silos, tomorrow's component, right, or module. If most people don't realize that these silos can be problematic if not thought through. So you have to kill the silos to bring in kind of an open police. So if you're open, not closed, you can leverage a monolith. Today's monolithic app or full stack could be tomorrow's building block unless you don't open up. So this is where interesting design question comes in, which is, it's okay to have pre existing stuff if you're open about it. But if you stay siloed, you're gonna get really stuck >>and there's going to be more and more pre existing stuff I think, you know, uh even the data lake for every day to lake, there is a huge problem of how to get data into the data lake or taking existing applications that came from the previous data link. And so there's a, there's a natural evolutionary process where let's focus on the mechanisms that actually move that day to get that data flowing. Um, I think we're still in the early phases of thinking about huge amounts of applications. Microservices or you know, 10 years old in the sense of it being a fairly common industry talking point before that we have service oriented architecture. But the difference now is that we're encouraging and building one developer, one team might run several services. They might use three or four different sas vendors. They might depend on five or 10 or 15 cloud services. Those integration points make them easier. But it's a new opportunity for us to say, well, what are the differences to go back to? The point is you can keep your silos, we just want to have great integration in and out of >>those. Exactly, they don't have to you have to break down the silos. So again, it's a tried and true formula integration, interoperability and abstracting away the complexity with some sort of new software abstraction layer. You bring that to play as long as you can paddle with that, you apply the new building blocks, you're classified. >>It sounds so that's so simple, doesn't it? It does. And you know, of course it'll take us 10 years to get there. And uh, you know, after cloud native will be will be galactic native or something like that. You know, there's always going to be a new uh concept that we need to work in. I think the key concepts we're really going after our everyone is trying to run resilient and reliable services and the clouds give us in the clouds take it away. They give us those opportunities to have some of those building blocks like location of geographic hardware resources, but they will always be data that spread. And again, you still have to apply those principles to the cloud to get the service guarantees that you need. I think there's a completely untapped area for helping software developers and software teams understand the actual availability and guarantees of the underlying environment. It's a property of the services you run with. If you're using a disk in a particular availability zone, that's a property of your application. I think there's a rich area that hasn't been mined yet. Of helping you understand what your effective service level goals which of those can be met. Which cannot, it doesn't make a lot of sense in a single cluster or single machine or a single location world the moment you start to talk about, Well I have my data lake. Well what are the ways my data leg can fail? How do we look at your complex web of interdependencies and say, well clearly if you lose this cloud provider, you're going to lose not just the things that you have running there, but these other dependencies, there's a lot of, there's a lot of next steps that we're just learning what happens when a major cloud goes down for a day or a region of a cloud goes down for a day. You still have to design and work around those >>cases. It's distributed computing. And again, I love the space where galactic cloud, you got SpaceX? Where's Cloud X? I mean, you know, space is the next frontier. You know, you've got all kinds of action happening in space. Great space reference there. Clayton, Great insight. Thanks for coming on. Uh, Clayton Coleman architect at red Hat. Clayton, Thanks for coming on. >>Pretty pleasure. >>Always. Great chat. I'm talking under the hood. What's going on in red hats? New managed cloud service portfolio? Again, the world's getting complex, abstract away. The complexities with software Inter operate integrate. That's the key formula with the cloud building blocks. I'm john ferry with the cube. Thanks for watching. Yeah.

(smart gentle music) >> Hey, welcome back everyone to theCUBE's coverage of Red Hat Summit 2021 virtual. I'm John Furrier, host of theCUBE, got two great guests here from AWS, Bob Wise, General Manager of Kubernetes for Amazon Web Services and Peder Ulander, Head of product marketing for the enterprise developer and open-source at AWS. Gentlemen, you guys are the core leaders in the AWS open-source initiatives. Thanks for joining us on theCUBE here for Red Hat Summit. >> Thanks for having us, John. >> Good to be here. >> So the innovation that's come from people building on top of the cloud has just been amazing. You guys, props to Amazon Web Services for constantly adding more and raising the bar on more services every year. You guys do that, and now public cloud has become so popular, and so important that now Hybrid has pushed the Edge. You got outpost with Amazon you see everyone following suit. It's pretty much clear vote of confidence from the customers that, Hybrid is the operating model of the future. And that really is about the Edge. So I want to chat with you about the open-source intersection there, so let's get into it. So we're here at Red Hat Summit. So Red Hat's an open-source company and timing is great for them. Now, part of IBM you guys have had a relationship with Red Hat for some time. Can you tell us about the partnership and how it's working together? >> Yeah, absolutely. Why don't I take that one? AWS and Red Hat have been strategic partners since, shoot, I think it's 2008 or so in the early days of AWS, when engaging with customers, we wanted to ensure that AWS was the best place for enterprises to run their Red Hat workloads. And this is super important when you think about, what Red Hat has accomplished with RHEL in the enterprise, it's running SAP, it's running Oracle's, it's running all different types of core business applications, as well as a lot of the new things that customers are innovating. And so having that relationship to ensure that not only did it work on AWS, but it actually scaled we had integration of services, we had the performance, the price all of the things that were so critical to customers was critical from day one. And we continue to evolve this relationship over time. As you see us coming into Red Hat Summit this year. >> Well, again, to the hard news here also the new service Red Hat OpenShift servers on AWS known as ROSA, the A for Amazon Red Hat OpenShift, A for Amazon Web Services, a clever acronym but really it's on AWS. What exactly is this service? What does it do? And who is it designed for? >> Well, I'll let me jump in on this one. Maybe let's start with the why? Why ROSA? Customers love using OpenShift, but they also want to use AWS. They want the best of both. So they want their peanut butter and their chocolate together in a single confection. A lot of those customers have deployed AWS, have deployed OpenShift on AWS. They want managed service simplified supply chain. We want to be able to streamline moving on premises, OpenShift workloads to AWS, naturally want good integration with AWS services. So as to the, what? Our new service jointly operated is supported by Red Hat and AWS to provide a fully managed to OpenShifts on AWS. So again, like lot of customers have been running OpenShift on AWS before this time, but of course they were managing it themselves typically. And so now they get a fully managed option with also simplified supply chain. Single support channels, single billing. >> You know, were talking before we came on camera about the acronym on AWS and people build on the clouds kind of like it's no big deal to say that, but I know it means something. I want to explain, you guys to explain this on because I know I've been scolded saying things on theCUBE that were kind of misspoken because it's easy to say, Oh yeah, I built that app. We built all this stuff on theCUBE was on AWS, but it's not on AWS. It means something from a designation standpoint what does on AWS mean? 'Cause this is OpenShift servers on AWS, we see this other companies have their products on AWS. This is specific designation. Can you share, please. >> John, when you see the branding of something like Red Hat on AWS, what that basically signals to our customers is that this is joint engineering work. This is the top of the strategic partners where we actually do a lot of joint engineering and work to make sure that we're driving the right integrations and the right experience, make sure that these things are accessible and discoverable in our console. They're treated effectively as a first-class service inside of the AWS ecosystem. So it's, there's not many of the on's, if you will. You think about SAP on VMware cloud, on AWS, and now Red Hat OpenShift on AWS, it really is that signal that helps give customers the confidence of tested, tried, trued, supported and validated service on top of AWS. And we think that's significantly better than anything else. It's easy to run an image on a VM and stuffed it into a cloud service to make it available, but customers want better, customer want tighter experiences. They want to be able to take advantage of all the great things that we have from a scale availability and performance perspective. And that's really what we're pushing towards. >> Yeah. I've seen examples specifically where when partners work with Amazon at that level of joint engineering, deeper partnerships. The results were pretty significant on the business side. So congratulations to you guys working with OpenShift and Red Hat, that's real testament to their product. But I got to ask you guys, pull the Amazon playbook out and challenge you guys, or just, create a new some commentary around the process of working backwards. Every time I talked to Andy Jassy, he always says, we work backwards from the customer and we get the requirements, and we're listening to customers. Okay, great. He loves that, he loves to say that it's true. I know that I've seen that. What is the customer work backwards document look like here? What is the, what was the need and what made this become such an important part of AWS? What was the, and then what are they saying now, now that the products out there? >> Well, OpenShift has a very wide footprint as does AWS. Some working backwards documents kind of write themselves, because now the customer demand is so strong that there's just no avoiding it. Now, it really just becomes about making sure you have a good plan so it becomes much more operational at that point. ROSA's definitely one of those services. We had so much demand and as a result, no surprise that we're getting a lot of enthusiasm for customers because so many of them asked us for it. (crosstalk) >> What's been the reaction in asking demand. That's kind of got the sense of that, but okay. So there's demand now, what's the what's the use cases? What are customers saying? What's the reaction been? >> Lot of the use cases are these Hybrid kind of use cases where a customer has a big OpenShift footprint. What we see from a lot of these customers is a strong demand for consistency in order to reduce IT sprawl. What they really want to do is have the smallest number of simplest environments they can. And so when customers that standardized on OpenShift really wants to be able to standardize OpenShifts, both in their on premises environment and on AWS and get managed service options just to remove the undifferentiated heavy lifting. >> Hey, what's your take on the product marketing side of this, where you got open-source becoming very enterprise specific, Red Hat's been there for a very long time. I've been user of Red Hat since the beginning and following them, and Linux, obviously is Linux where that's come from. But what features specifically jump out in this offering that customers are resonating around? What's the vibe here? >> John, you kind of alluded to it early on, which is I don't know that I'd necessarily call it Hybrid but the reality is our customers have environments that are on premises in the cloud and all the way out to the Edge. Today, when you think of a lot of solutions and services, it's a fractured experience that they have between those three locations. And one of our biggest commitments to our customers, just to make things super simple, remove the complexity do all of the hard work, which means, customers are looking for a consistent experience environment and tooling that spans data center to cloud, to Edge. And that's probably the biggest kind of core asset here for customers who might have standardized on OpenShift in the data centers. They come to the cloud, they want to continue to leverage those skills. I think probably one of the, an interesting one is we headed down in this path, we all know Delta Airlines. Delta is a great example of a customer who, joint customer, who have been doing stuff inside of AWS for a long time. They've been standardizing on Red Hat for a long time and bringing this together just gave them that simple extension to take their investment in Red Hat OpenShift and leverage their experience. And again, the scale and performance of what AWS brings them. >> Next question, what's next for a Red Hat OpenShift on AWS in your work with Red Hat. Where does this go next? What's the big to-do item, what do you guys see as the vision? >> I'm glad you mentioned open-source collaboration at the start there. We're taking to point out is that AWS works on the Kubernetes project upstream as does the Red Hat teams. So one of the ways that we collaborate with the Red Hat team is in open-source. One of those projects is on a new project called ACK. It was on controllers for Kubernetes and this is a kind of Kubernetes friendly way for my customers to use an API to manage AWS services. So that's one of the things that we're looking forward to as that goes GA wobbling out into both ROSA and onto our other services. >> Awesome. I got to ask you guys this while you're here, because it's very rare to get two luminaries within AWS on the open-source side. This has been a huge build-out over the many, many years for AWS, and some people really kind of don't understand kind of the position. So take a minute to clarify the position of AWS on open-source. You guys are very active in a lot of projects. You mentioned upstream with Kubernetes in other areas. I've had many countries with Adrian Cockcroft on this, as well as others within AWS. Huge proponents web services, I mean, you go back to the original Amazon. I mean, Jeff Barr was saying 15 years ago some of those API's are still in play here. API's back in 15 years ago, that was kind of not main stream at that time. So you had open standards, really made Amazon web services successful and you guys are continuing it but as the modern era is very enterprise, like and you see a lot of legacy, you seeing a lot more operations that they're going to be driven by open technologies that you guys are investing in. I'll take a minute to explain what AWS is doing and what you guys care about and your mission? >> Yeah. Well, why don't I start? And then we'll kick it over to Bob 'cause I think Bob can also talk about some of the key contribution sides, but the best way to think about it is kind of in three different pillars. So let's start with the first one, which is, around the fact of ensuring that our customer's favorite open-source projects run best on AWS. Since 2006, we've been helping our customers operationalize their open-source investments and really kind of achieve that scale and focus more on how they use and innovate on the products versus how they set up and run. And for myself being an open-source since the late 90s, the biggest opportunity, yet challenge was the access to the technology, but it still required you as a customer to learn how to set up, configure, operationalized support and sustain. AWS removes that heavy lifting and, again, back to that earlier point from the beginning of AWS, we helped customers scale and implement their Apache services, their database services, all of these different types of open-source projects to make them really work exceptionally well on AWS. And back to that point, make sure that AWS was the best place for their open-source projects. I think the second thing that we do, and you're seeing that today with what we're doing with ROSA and Red Hat is we partner with open-source leaders from Red Hat to Redis and Confluent to a number of different players out there, Grafana, and Prometheus, to even foundations like the LF and the CNCF. We partner with these leaders to ensure that we're working together to grow grow the overall experience and the overall the overall pie, if you will. And this kind of gets into that point you were making John in that, the old world legacy proprietary stuff, there's a huge chance for refresh and new opportunity and rethinking or modernization if you will, as you come into the cloud having the expertise and the partnerships with these key players is as enterprises move in, is so crucial. And then the third piece I'd like to talk about that's important to our open-source strategies is really around contribution. We have a number of projects that we've delivered ourselves. I think the two most recent ones that really come top of mind for me is, what we did with Babel Fish, as well as with OpenSearch. So contributing and driving a true open-source project that helps our customers, take advantage of things like an SQL, a proprietary to open-source SQL conversion tool, or what we're doing to make Elasticsearch, the opportune or the primary open platform for our customers. But it's not just about those services, it's also collaborating with key industry initiatives. Bob's at the forefront of that with what we're doing with the CNCF around things, like Kubernetes and Prometheus et cetera, Bob you want to jump in on some of that? >> Sure, I think the one thing I would add here is that customers love using those open-source projects. The one of the challenges with them frequently is security. And this is job zero to AWS. So a lot of the collaboration work we do, a lot of the work that we do on upstream projects is go specifically around kind of security oriented things because that is what customers expect when they come to get a managed service at AWS. Some of those efforts are somewhat unsung because you generally do more work and less talk, in security oriented things. But projects across AWS, that's always a key contribution focus for us. >> Good way to call out security too. I think that's being built-in to the everything now, that's an operating model. People call it shift-left day two operations. Whatever you want to look at it. You got this nice formation going between under the hood kind of programmability of the infrastructure at scale. And then you have the modern application development which is just beginning, programmable DevSecOps. It's funny, Bob, I'd love to get your take on this because I remember in the 80s and during the Unix generation I used to peddle software under the table. Like, here's a copy of, you just don't tell anyone, people in the younger generation don't get the fact that it wasn't always open. And so now you have open and you have this idea of an enterprise that's going to be a system management system view. So you got engineering and you got computer science kind of coming together, this SRE middle layer. You're hearing that as a, kind of a new discipline. So DevOps kind of has won. I mean, we kind of knew this for many, many years. I said this in 2013 on theCUBE actually at re-inventing. I just recently shared that clip. But okay, now you've got SecOps, DevSecOps. So now you have an era where it's a system thinking and open-source is driving all of that. So can you share your perspective because this is kind of where the puck is going. It's an open to open world. That's going to have to be open and scalable. How does open-source and you guys take it to the next level to give that same scale and reliability? What's your vision? >> The key here is really around automation and what we're seeing you could look at Kubernetes. Kubernetes, is essentially a robot. It was like the early design of it was built around robotics principles. So it's a giant software robot and the world has changed. If you just look at the influx of all kinds of automation to not just the DevOps world but to all industries, you see a similar kind of trend. And so the world of IT operations person is changing from doing the work that the robot did and replacing it with the robot to managing large numbers of robots. And in this case, the robots are like a little early and a little hard to talk to. And so, you end up using languages like YAML and other things, but it turns out robots still just do what you tell them to do. And so one of the things you have to do is be really, really careful because robots will go and do whatever it is you ask them to do. On the other hand, they're really, really good at doing that. So in the security area, they take the research points to the largest single source of security issues, being people making manual mistakes. And a lot of people are still a little bit terrified if human beings aren't touching things on the way to production. In AWS, we're terrified if humans aren't touching it. And that is a super hard chasm to cross and open-source projects have really, are really playing a big role in what's really a IT wide migration to a whole new set of, not just tools, but organizational approaches. >> What's your reaction to that? Because we're talking that essentially software concepts, because if you write bad code, the code will execute what you did. So assuming it compiles left in the old days. Now, if you're going to scale a large scale operations that has dynamic capabilities, services being initiated in terminating tear down up started, you need the automation, but if you really don't design it right, you could be screwed. This is a huge deal. >> This is one reason why we've put so much effort into getops that you can think of it as a more narrowly defined subset of the DevOps world with a specific set of principles around using kind of simplified declarative approaches, along with robots that converge the desired state, converge the system to the desired state. And when you get into large distributed systems, you end up needing to take those kinds of approaches to get it to work at scale. Otherwise you have problems. >> Yeah, just adding to that. And it's funny, you said DevOps has won. I actually think DevOps has won, but DevOps hasn't changed (indistinct) Bob, you were right, the reality is it was founded back what quite a while ago, it was more around CICD in the enterprise and the closed data center. And it was one of those where automation and runbooks took addressed the fact that, every pair of hands between service requests and service delivery recreated or created an issue. So that growth and that mental model of moving from a waterfall, agile to DevOps, you built it, you run it, type of a model, I think is really, really important. But as it comes out into the cloud, you no longer have those controls of the data center and you actually have infinite scale. So back to your point of you got to get this right. You have to architect correctly you have to make sure that your code is good, you have to make sure that you have full visibility. This is where it gets really interesting at AWS. And some of the things that we're tying in. So whether we're talking about getops like what Bob just went through, or what you brought up with DevSecOps, you also have things like, AIOps. And so looking at how we take our machine learning tools to really implement the appropriate types of code reviews to assessing your infrastructure or your choices against well-architected principles and providing automated remediation is key, adding to that is observability, developers, especially in a highly distributed environment need to have better understanding, fidelity and touchpoints of what's going on with our application as it runs in production. And so what we do with regards to the work we have in observability around Grafana and Prometheus projects only accelerate that co-whole concept of continuous monitoring and continuous observability, and then kind of really, adding to that, I think it was last month, we introduce our fault injection simulator, a chaos engineering tool that, again takes advantage of all of this automation and machine learning to really help our developers, our customers operate at scale. And make sure that when they are releasing code, they're releasing code that is not just great in a small sense, it works on my laptop, but it works great in a highly distributed massively scaled environment around the globe. >> You know, this is one of the things that impresses me about Red Hat this year. And I've said this before all the covers events I've covered with them is that they get the cloud scale piece and I think their relationship with you guys shows that I think, DevOps has won, but it's the gift that keeps giving in open-source because what you have here is no longer a conversation about the cloud moving to the cloud. It's the cloud has become the operating model. So the conversation shifts to much more complicated enterprise or, and or intelligent Edge, and whether it's industrial or human or whatever, you got a data problem. So that's about a programmability issue at scale. So what's interesting is that Red Hat is on those bandwagon. It's an operating system. I mean, basically it's a distributed computing paradigm, essentially ala AWS concept as a cloud. Now it goes to the Edge, it's just distributed services via an open-source. So what's your reaction to that? >> Yeah, it's back to the original point, John where I said, any CIO is thinking about their IT environment from data center to cloud, to Edge and the more consistency automation and, kind of tools that they're at their disposal to enable them to create that kind of, I think you started to talk about an infrastructure the whole as code infrastructure's code, it's now, almost everything is code. And that starts with the operating system, obviously. And that's why this is so critical that we're partnering with companies like Red Hat on our vision and their vision, because they aligned to where our customers were ultimately going. Bob, you want to, you want to add to that? >> Bob: No, I think you said it. >> John: You guys are crushing it. Bob, one quick question for you, while I got you here. You mentioned getops, I've heard this before, I kind of understand it. Can you just quickly define from your perspective. What is getops? >> Sure, well, getops is really taking the, I said before it's a kind of narrowed version of DevOps. Sure, it's infrastructure is code. Sure, you're doing things incrementally but the getops principle, it's back to like, what are the good, what are the best practices we are managing large numbers, large numbers of robots. And in this case, it's around this idea of declarative intent. So instead of having systems that reach into production and change things, what you do is you set up the defined declared state of the system that you want and then leave the robots to constantly work to converge the state there. That seems kind of nebulous. Let me give you like a really concrete example from Kubernetes, by the way the entire Kubernetes system design is based on this. You say, I want five pods running in production and that's running my application. So what Kubernetes does is it sits there and it constantly checks, Oh, I'm supposed to have five pods. Do I have five? Well, what happens if the machine running one of those pods goes away. Now, suddenly it goes and checks and says, Oh, I'm supposed to have five pods, but there's four pods. What action do I take to now try to get the system back to the state. So you don't have a system running, reaching out and checking externally to Kubernetes, you let Kubernetes do the heavy lifting there. And so it goes through, goes through a loop of, Oh, I need to start a new pod and then it converges the system state back to running five pods. So it's really taking that kind of declarative intent combined with constant convergence loops to fully production at scale. >> That's awesome. Well, we do a whole segment on state and stateless future, but we don't have time. I do want to summarize real quick. We're here at the Red Hat Summit 2021. You got Red Hat OpenShift on AWS. The big news, Bob and Peder tell us quickly in summary, why AWS? Why Red Hat? Why better together? Give the quick overview, Bob, we'll start with you. >> Bob, you want to kick us off? >> I'm going to repeat peanut butter and chocolate. Customers love OpenShift, they love managed services. They want a simplified operations, simplified supply chain. So you get the best of both worlds. You get the OpenShift that you want fully managed on AWS, where you get all of the security and scale. Yeah, I can't add much to that. Other than saying, Red Hat is powerhouse obviously on data centers it is the operating system of the data center. Bringing together the best in the cloud, with the best in the data center is such a huge benefit to our customers. Because back to your point, John, our customers are thinking about what are they doing from data center to cloud, to Edge and bringing the best of those pieces together in a seamless solution is so, so critical. And that that's why AW. (indistinct) >> Thanks for coming on, I really appreciate it. I just want to give you guys a plug for you and being humble, but you've worked in the CNCF and standards bodies has been well, well known and I'm getting the word out. Congratulations for the commitment to open-source. Really appreciate the community. Thanks you, thank you for your time. >> Thanks, John. >> Okay, Cube coverage here, covering Red Hat Summit 2021. I'm John Ferry, host of theCUBE. Thanks for watching. (smart gentle music)

(upbeat music) >> Welcome to this special cloud virtual event, theCUBE on cloud. This is our continuing editorial series of the most important stories in cloud. We're going to explore the cutting edge most relevant technologies and companies that will impact business and society. We have special guests from Jeff Barr, Michael Liebow, Jerry Chen, Ben Haynes, Michael skulk, Mike Feinstein from AWS all today are presenting the top startups in the AWS ecosystem. This is the AWS showcase of startups. I'm showing with Dave Vellante. Dave great to see you. >> Hey John. Great to be here. Thanks for having me. >> So awesome day today. We're going to feature a 10 grade companies amplitude, auto grid, big ID, cordial Dremio Kong, multicloud, Reltio stardog wire wheel, companies that we've talked to. We've researched. And they're going to present today from 10 for the rest of the day. What's your thoughts? >> Well, John, a lot of these companies were just sort of last decade, they really, were keyer kicker mode, experimentation mode. Now they're well on their way to hitting escape velocity which is very exciting. And they're hitting tens of millions dollars of ARR, many are planning IPO's and it's just it's really great to see what the cloud has enabled and we're going to dig into that very deeply today. So I'm super excited. >> Before we jump into the keynote (mumbles) our non Huff from AWS up on stage Jeremy is the brains behind this program that we're doing. We're going to do this quarterly. Jeremy great to see you, you're in the global startups program at AWS. Your job is to keep the crops growing, keep the startups going and keep the flow of innovation. Thanks for joining us. >> Yeah. Made it to startup showcase day. I'm super excited. And as you mentioned my team the global startup program team, we kind of provide white glove service for VC backed startups and help them with go to market activities. Co-selling with AWS and we've been looking for ways to highlight all the great work they're doing and partnering with you guys has been tremendous. You guys really know how to bring their stories to life. So super excited about all the partner sessions today. >> Well, I really appreciate the vision and working with Amazon this is like truly a bar raiser from theCUBE virtual perspective, using the virtual we can get more content, more flow and great to have you on and bring that the top hot startups around data, data ops. Certainly the most important story in tech is cloud scale with data. You you can't look around and seeing more innovation happening. So I really appreciate the work. Thanks for coming on. >> Yeah, and don't forget, we're making this a quarterly series. So the next one we've already been working on it. The next one is Wednesday, June 16th. So mark your calendars, but super excited to continue doing these showcases with you guys in the future. >> Thanks for coming on Jeremy. I really appreciate it,. Dave so I want to just quick quickly before we get Jeff up here, Jeff Barr who's a luminary guests for us this week who has been in the industry has been there from the beginning of AWS the role of data, and what's happened in cloud. And we've been watching the evolution of Amazon web services from the beginning, from the startup market to dominate in the enterprise. If you look at the top 10 enterprise companies Amazon wasn't on that list in 2010 they weren't even bringing the top 10 Andy Jassy's keynote at reinvent this past year. Highlighted that fact, I think they were number five or four as vendor in just AWS. So interesting to see that you've been reporting and doing a lot of analysis on the role of data. What's your analysis for these startups and as businesses need to embrace the new technologies and be on the right side of history not part of that old guard, incumbent failed model. >> Well, I think again, if you look back on the early days of cloud, it was really about storage and networking and compute infrastructure. And then we collected all this data and now you're seeing the next generation of innovation and value. We're going to talk to Michael Liebow about this is really if you look at all the value points in the leavers, it's all around data and data is going through a massive change in the way that we think about it, that we talk about it. And you hear that a lot. Obviously you talk about the volumes, the giant volumes but there's something else going on as AWS brings the cloud to the edge. And of course it looks at the data centers, just another edge device, data is getting highly decentralized. And what we're seeing is data getting into the hands of business owners and data product builders. I think we're going to see a new parlance emerge and that's where you're seeing the competitive advantage. And if you look at all the real winners these days in the marketplace especially in the digital with COVID, it all comes back to the data. And we're going to talk about that a lot today. >> One of the things that's coming up in all of our cube interviews, certainly we've seen, I mean we've had a great observation space across all the ecosystems, but the clear thing that's coming out of COVID is speed, agility, scale, and data. If you don't have that data you are going to be a non-player. And I think I heard some industry people talking about the future of how the stock market's going to work and that if you're not truly in market with an AI or machine learning data value play you probably will be shorted on the stock market or delisted. I think people are looking at that as a table stakes competitive advantage item, where if you don't have some sort of data competitive strategy you're going to be either delisted or sold short. And that's, I don't think delisted but the point is this table-stakes Dave. >> Well, I think too, I think the whole language the lingua franca of data is changing. We talk about data as an asset all the time, but you think about it now, what do we do with assets? We protect it, we hide it. And we kind of we don't share it. But then on the other hand, everybody talks about sharing the data and that is a huge trend in the marketplace. And so I think that everybody is really starting to rethink the whole concept of data, what it is, its value and how we think about it, talk about it, share it make it accessible, and at the same time, protect it and make it governed. And I think you're seeing, computational governance and automation really hidden. Couldn't do this without the cloud. I mean, that's the bottom line. >> Well, I'm super excited to have Jeff Barr here from AWS as our special keynote guests. I've been following Jeff's career for a long, long time. He's a luminaries, he's a technical, he's in the industry. He's part of the community, he's been there from the beginning AWS just celebrate its 15th birthday as he was blogging hard. He's been a hardcore blogger. I think Jeff, you had one of the original ping service. If I remember correctly, you were part of the web services foundational kind of present at creation. No better guests to have you Jeff thanks for coming up on our stage. >> John and Dave really happy to be here. >> So I got to ask you, you've been blogging hard for the past decade or so, going hard and your job has evolved from blogging about what's new with Amazon. A couple of building blocks a few services to last reinvent them. You must have put out I don't know how many blog posts did you put out last year at every event? I mean, it must have been a zillion. >> Not quite a zillion. I think I personally wrote somewhere between 20 and 25 including quite a few that I did in the month or so run up to reinvent and it's always intense, but it's always really, really fun. >> So I've got to ask you in the past couple of years, I mean I quoted Andy Jassy's keynote where we highlight in 2010 Amazon wasn't even on the top 10 enterprise players. Now in the top five, you've seen the evolution. What is the big takeaway from your standpoint as you look at the enterprise going from Amazon really dominating the start of a year startups today, you're in the cloud, you're born in the cloud. There's advantage to that. Now enterprises are kind of being reborn in the cloud at the same time, they're building these new use cases rejuvenating themselves and having innovation strategy. What's your takeaway? >> So I love to work with our customers and one of the things that I hear over and over again and especially the last year or two is really the value that they're placing on building a workforce that has really strong cloud skills. They're investing in education. They're focusing on this neat phrase that I learned in Australia called upskilling and saying let's take our set of employees and improve their skill base. I hear companies really saying we're going to go cloud first. We're going to be cloud native. We're going to really embrace it, adopt the full set of cloud services and APIs. And I also see that they're really looking at cloud as part of often a bigger picture. They often use the phrase digital transformation, in Amazon terms we'd say they're thinking big. They're really looking beyond where they are and who they are to what they could be and what they could grow into. Really putting a lot of energy and creativity into thinking forward in that way. >> I wonder Jeff, if you could talk about sort of how people are thinking about the future of cloud if you look at where the spending action is obviously you see it in cloud computing. We've seen that as the move to digital, serverless Lambda is huge. If you look at the data it's off the charts, machine learning and AI also up there containers and of course, automation, AWS leads in all of those. And they portend a different sort of programming model a different way of thinking about how to deploy workloads and applications maybe different than the early days of cloud. What's driving that generally and I'm interested in serverless specifically. And how do you see the next several years folding out? >> Well, they always say that the future is the hardest thing to predict but when I talked to our enterprise customers the two really big things that I see is there's this focus that says we need to really, we're not simply like hosting the website or running the MRP. I'm working with one customer in particular where they say, well, we're going to start on the factory floor all the way up to the boardroom effectively from IOT and sensors on the factory floor to feed all the data into machine learning. So they understand that the factory is running really well to actually doing planning and inventory maintenance to putting it on the website to drive the analytics, to then saying, okay, well how do we know that we're building the right product mix? How do we know that we're getting it out through the right channels? How are our customers doing? So they're really saying there's so many different services available to us in the cloud and they're relatively easy and straightforward to deploy. They really don't think in the old days as we talked about earlier that the old days where these multi-year planning and deployment cycles, now it's much more straightforward. It's like let's see what we can do today. And this week and this month, and from idea to some initial results is a much, much shorter turnaround. So they can iterate a lot more quickly which is just always known to produce better results. >> Well, Jeff and the spirit of the 15th birthday of AWS a lot of services have been built from the original three. I believe it was the core building blocks and there's been a lot of history and it's kind of like there was a key decoupling of compute from storage, those innovations what's the most important architectural change if any has happened or built upon those building blocks with AWS that you could share with companies out there as many people are coming into the cloud not just lifting and shifting and having that innovation but really building cloud native and now hybrid full cloud operations, day two operations. However you want to look at it. That's a big thing. What architecturally has changed that's been innovative from those original building blocks? >> Well, I think that the basic architecture has proven to be very, very resilient. When I wrote about the 15 year birthday of Amazon S3 a couple of weeks ago one thing that I thought was really incredible was the fact that the same APIs that you could have used 15 years ago they all still work. The put, the get, the list, the delete, the permissions management, every last one of those were chosen with extreme care. And so they all still work. So one of the things you think about when you put APIs out there is in Amazon terms we always talk about going through a one-way door and a one way door says, once you do it you're committed for the indefinite future. And so you we're very happy to do that but we take those steps with extreme care. And so those basic building blocks so the original S3 APIs, the original EC2 APIs and the model, all those things really worked. But now they're running at this just insane scale. One thing that blows me away I routinely hear my colleagues talking about petabytes and exabytes, and we throw around trillions and quadrillions like they're pennies. It's kind of amazing. Sometimes when you hear the scale of requests per day or request per month, and the orders of magnitude are you can't map them back to reality anymore. They're simply like literally astronomical. >> If I can just jump in real quick Dave before you ask Jeff, I was watching the Jeff Bezos interview in 1999 that's been going around on LinkedIn in a 60 minutes interview. The interviewer says you are reporting that you can store a gigabyte of customer data from all their purchases. What are you going to do with that? He basically nailed the answer. This is in 99. We're going to use that data to create, that was only a gig. >> Well one of the things that is interesting to me guys, is if you look at again, the early days of cloud, of course I always talked about that in small companies like ours John could have now access to information technology that only big companies could get access to. And now you've seen we just going to talk about it today. All these startups rise up and reach viability. But at the same time, Jeff you've seen big companies get the aha moment on cloud and competition drives urgency and that drives innovation. And so now you see everybody is doing cloud, it's a mandate. And so the expectation is a lot more innovation, experimentation and speed from all ends. It's really exciting to see. >> I know this sounds hackneyed and overused but it really, really still feels just like day one. We're 15 plus years into this. I still wake up every morning, like, wow what is the coolest thing that I'm going to get to learn about and write about today? We have the most amazing customers, one of the things that is great when you're so well connected to your customers, they keep telling you about their dreams, their aspirations, their use cases. And we can just take that and say we can actually build awesome things to help you address those use cases from the ground on up, from building custom hardware things like the nitro system, the graviton to the machine learning inferencing and training chips where we have such insight into customer use cases because we have these awesome customers that we can make these incredible pieces of hardware and software to really address those use cases. >> I'm glad you brought that up. This is another big change, right? You're getting the early days of cloud like, oh, Amazon they're just using off the shelf components. They're not buying these big refrigerator sized disc drives. And now you're developing all this custom Silicon and vertical integration in certain aspects of your business. And that's because workload is demanding. You've got to get more specialized in a lot of cases. >> Indeed they do. And if you watch Peter DeSantis' keynote at re-invent he talked about the fact that we're researching ways to make better cement that actually produces less carbon dioxide. So we're now literally at the from the ground on up level of construction. >> Jeff, I want to get a question from the crowd here. We got, (mumbles) who's a good friend of theCUBE cloud Arate from the beginning. He asked you, he wants to know if you'd like to share Amazon's edge aspirations. He says, he goes, I mean, roadmaps. I go, first of all, he's not going to talk about the roadmaps, but what can you share? I mean, obviously the edge is key. Outpost has been all in the news. You obviously at CloudOps is not a boundary. It's a distributed network. What's your response to-- >> Well, the funny thing is we don't generally have technology roadmaps inside the company. The roadmap is always listen really well to customers not just where they are, but the customers are just so great at saying, this is where we'd like to go. And when we hear edge, the customers don't generally come to us and say edge, they say we need as low latency as possible between where the action happens within our factory floors and our own offices and where we might be able to compute, analyze, store make decisions. And so that's resulted in things like outposts where we can put outposts in their own data center or their own field office, wavelength, where we're working with 5G telecom providers to put computing storage in the carrier hubs of the various 5G providers. Again, with reducing latency, we've been doing things like local zones, where we put zones in an increasing number of cities across the country with the goal of just reducing the average latency between the vast majority of customers and AWS resources. So instead of thinking edge, we really think in terms of how do we make sure that our customers can realize their dreams. >> Staying on the flywheel that AWS has built on ship stuff faster, make things faster, smaller, cheaper, great mission. I want to ask you about the working backwards document. I know it's been getting a lot of public awareness. I've been, that's all I've learned in interviewing Amazon folks. They always work backwards. I always mentioned the customer and all the interviews. So you've got a couple of customer references in there check the box there for you. But working backwards has become kind of a guiding principles, almost like a Harvard Business School case study approach to management. As you guys look at this working backwards and ex Amazonians have written books about it now so people can go look at, it's a really good methodology. Take us back to how you guys work back from the customers because here we're featuring 10 startups. So companies that are out there and Andy has been preaching this to customers. You should think about working backwards because it's so fast. These companies are going into this enterprise market your ecosystem of startups to provide value. What things are you seeing that customers need to think about to work backwards from their customer? How do you see that? 'Cause you've been on the community side, you see the tech side customers have to move fast and work backwards. What are the things that they need to focus on? What's your observation? >> So there's actually a brand new book called "Working Backwards," which I actually learned a lot about our own company from simply reading the book. And I think to me, a principal part of learning backward it's really about humility and being able to be a great listener. So you don't walk into a customer meeting ready to just broadcast the latest and greatest that we've been working on. You walk in and say, I'm here from AWS and I simply want to learn more about who you are, what you're doing. And most importantly, what do you want to do that we're not able to help you with right now? And then once we hear those kinds of things we don't simply write down kind of a bullet item of AWS needs to improve. It's this very active listening process. Tell me a little bit more about this challenge and if we solve it in this way or this way which one's a better fit for your needs. And then a typical AWS launch, we might talk to between 50 and 100 customers in depth to make sure that we have that detailed understanding of what they would like to do. We can't always meet all the needs of these customers but the idea is let's see what is the common base that we can address first. And then once we get that first iteration out there, let's keep listening, let's keep making it better and better and better as quickly. >> A lot of people might poopoo that John but I got to tell you, John, you will remember this the first time we ever met Andy Jassy face-to-face. I was in the room, you were on the speaker phone. We were building an app on AWS at the time. And he was asking you John, for feedback. And he was probing and he pulled out his notebook. He was writing down and he wasn't just superficial questions. He was like, well, why'd you do it that way? And he really wanted to dig. So this is cultural. >> Yeah. I mean, that's the classic Amazon. And that's the best thing about it is that you can go from zero startups zero stage startup to traction. And that was the premise of the cloud. Jeff, I want to get your thoughts and commentary on this love to get your opinion. You've seen this grow from the beginning. And I remember 'cause I've been playing with AWS since the beginning as well. And it says as an entrepreneur I remember my first EC2 instance that didn't even have custom domain support. It was the long URL. You seen the startups and now that we've been 15 years in, you see Dropbox was it just a startup back in the day. I remember these startups that when they were coming they were all born on Amazon, right? These big now unicorns, you were there when these guys were just developers and these gals. So what's it like, I mean, you see just the growth like here's a couple of people with them ideas rubbing nickels together, making magic happen who knows what's going to turn into, you've been there. What's it been like? >> It's been a really unique journey. And to me like the privilege of a lifetime, honestly I've like, you always want to be part of something amazing and you aspire to it and you study hard and you work hard and you always think, okay, somewhere in this universe something really cool is about to happen. And if you're really, really lucky and just a million great pieces of luck like lineup in series, sometimes it actually all works out and you get to be part of something like this when it does you don't always fully appreciate just how awesome it is from the inside, because you're just there just like feeding the machine and you are just doing your job just as fast as you possibly can. And in my case, it was listening to teams and writing blog posts about their launches and sharing them on social media, going out and speaking, you do it, you do it as quickly as possible. You're kind of running your whole life as you're doing that as well. And suddenly you just take a little step back and say, wow we did this kind of amazing thing, but we don't tend to like relax and say, okay, we've done it at Amazon. We get to a certain point. We recognize it. And five minutes later, we're like, okay, let's do the next amazingly good thing. But it's been this just unique privilege and something that I never thought I'd be fortunate enough to be a part of. >> Well, then the last few minutes we have Jeff I really appreciate you taking the time to spend with us for this inaugural launch of theCUBE on cloud startup showcase. We are showcasing 10 startups here from your ecosystem. And a lot of people who know AWS for the folks that don't you guys pride yourself on community and ecosystem the global startups program that Jeremy and his team are running. You guys nurture these startups. You want them to be successful. They're vectoring out into the marketplace with growth strategy, helping customers. What's your take on this ecosystem? As customers are out there listening to this what's your advice to them? How should they engage? Why is these sets of start-ups so important? >> Well, I totally love startups and I've spent time in several startups. I've spent other time consulting with them. And I think we're in this incredible time now wheres, it's so easy and straightforward to get those basic resources, to get your compute, to get your storage, to get your databases, to get your machine learning and to take that and to really focus on your customers and to build what you want. And we see this actual exponential growth. And we see these startups that find something to do. They listen to one of their customers, they build that solution. And they're just that feedback cycle gets started. It's really incredible. And I love to see the energy of these startups. I love to hear from them. And at any point if we've got an AWS powered startup and they build something awesome and want to share it with me, I'm all ears. I love to hear about them. Emails, Twitter mentions, whatever I'll just love to hear about all this energy all those great success with our startups. >> Jeff Barr, thank you for coming on. And congratulations, please pass on to Andy Jassy who's going to take over for Jeff Bezos and I saw the big news that he's picking a successor an Amazonian coming back into the fold, Adam. So congratulations on that. >> I will definitely pass on your congratulations to Andy and I worked with Adam in the past when AWS was just getting started and really looking forward to seeing him again, welcoming back and working with him. >> All right, Jeff Barr with AWS guys check out his Twitter and all the social coordinates. He is pumping out all the resources you need to know about if you're a developer or you're an enterprise looking to go to the next level, next generation, modern infrastructure. Thanks Jeff for coming on. Really appreciate it. Our next guests want to bring up stage Michael Liebow from McKinsey cube alumni, who is a great guest who is very timely in his McKinsey role with a paper he and his colleagues put out called cloud's trillion dollar prize up for grabs. Michael, thank you for coming up on stage with Dave and I. >> Hey, great to be here, John. Thank you. >> One of the things I loved about this and why I wanted you to come on was not only is the report awesome. And Dave has got a zillion questions, he want us to drill into. But in 2015, we wrote a story called Andy Jassy trillion dollar baby on Forbes, and then on medium and silken angle where we were the first ones to profile Andy Jassy and talk about this trillion dollar term. And Dave came up with the calculation and people thought we were crazy. What are you talking about trillion dollar opportunity. That was in 2015. You guys have put this together with a serious research report with methodology and you left a lot on the table. I noticed in the report you didn't even have a whole section quantified. So I think just scratching the surface trillion. I'd be a little light, Dave, so let's dig into it, Michael thanks for coming on. >> Well, and I got to say, Michael that John's a trillion dollar baby was revenue. Yours is EBITDA. So we're talking about seven to X, seven to eight X. What we were talking back then, but great job on the report. Fantastic work. >> Thank you. >> So tell us about the report gives a quick lowdown. I got some questions. You guys are unlocking the value drivers but give us a quick overview of this report that people can get for free. So everyone who's registered will get a copy but give us a quick rundown. >> Great. Well the question I think that has bothered all of us for a long time is what's the business value of cloud and how do you quantify it? How do you specify it? Because a lot of people talk around the infrastructure or technical value of cloud but that actually is a big problem because it just scratches the surface of the potential of what cloud can mean. And we focus around the fortune 500. So we had to box us in somewhat. And so focusing on the fortune 500 and fast forwarding to 2030, we put out this number that there's over a trillion dollars worth of value. And we did a lot of analysis using research from a variety of partners, using third-party research, primary research in order to come up with this view. So the business value is two X the technical value of cloud. And as you just pointed out, there is a whole unlock of additional value where organizations can pioneer on some of the newest technologies. And so AWS and others are creating platforms in order to do not just machine learning and analytics and IOT, but also for quantum or mixed reality for blockchain. And so organizations specific around the fortune 500 that aren't leveraging these capabilities today are going to get left behind. And that's the message we were trying to deliver that if you're not doing this and doing this with purpose and with great execution, that others, whether it's others in your industry or upstarts who were motioning into your industry, because as you say cloud democratizes compute, it provides these capabilities and small companies with talent. And that's what the skills can leverage these capabilities ahead of slow moving incumbents. And I think that was the critical component. So that gives you the framework. We can deep dive based on your questions. >> Well before we get into the deep dive, I want to ask you we have startups being showcased here as part of the, it will showcase, they're coming out of the ecosystem. They have a lot of certification from Amazon and they're secure, which is a big issue. Enterprises that you guys talk to McKinsey speaks directly to I call the boardroom CXOs, the top executives. Are they realizing that the scale and timing of this agility window? I mean, you want to go through these key areas that you would break out but as startups become more relevant the boardrooms that are making these big decisions realize that their businesses are up for grabs. Do they realize that all this wealth is shifting? And do they see the role of startups helping them? How did you guys come out of them and report on that piece? >> Well in terms of the whole notion, we came up with this framework which looked at the opportunity. We talked about it in terms of three dimensions, rejuvenate, innovate and pioneer. And so from the standpoint of a board they're more than focused on not just efficiency and cost reduction basically tied to nation, but innovation tied to analytics tied to machine learning, tied to IOT, tied to two key attributes of cloud speed and scale. And one of the things that we did in the paper was leverage case examples from across industry, across-region there's 17 different case examples. My three favorite is one is Moderna. So software for life couldn't have delivered the vaccine as fast as they did without cloud. My second example was Goldman Sachs got into consumer banking is the platform behind the Apple card couldn't have done it without leveraging cloud. And the third example, particularly in early days of the pandemic was Zoom that added five to 6,000 servers a night in order to scale to meet the demand. And so all three of those examples, plus the other 14 just indicate in business terms what the potential is and to convince boards and the C-suite that if you're not doing this, and we have some recommendations in terms of what CEOs should do in order to leverage this but to really take advantage of those capabilities. >> Michael, I think it's important to point out the approach at sometimes it gets a little wonky on the methodology but having done a lot of these types of studies and observed there's a lot of superficial studies out there, a lot of times people will do, they'll go I'll talk to a customer. What kind of ROI did you get? And boom, that's the value study. You took a different approach. You have benchmark data, you talked to a lot of companies. You obviously have a lot of financial data. You use some third-party data, you built models, you bounded it. And ultimately when you do these things you have to ascribe a value contribution to the cloud component because fortunate 500 companies are going to grow even if there were no cloud. And the way you did that is again, you talk to people you model things, and it's a very detailed study. And I think it's worth pointing out that this was not just hey what'd you get from going to cloud before and after. This was a very detailed deep dive with really a lot of good background work going into it. >> Yeah, we're very fortunate to have the McKinsey Global Institute which has done extensive studies in these areas. So there was a base of knowledge that we could leverage. In fact, we looked at over 700 use cases across 19 industries in order to unpack the value that cloud contributed to those use cases. And so getting down to that level of specificity really, I think helps build it from the bottom up and then using cloud measures or KPIs that indicate the value like how much faster you can deploy, how much faster you can develop. So these are things that help to kind of inform the overall model. >> Yeah. Again, having done hundreds, if not thousands of these types of things, when you start talking to people the patterns emerge, I want to ask you there's an exhibit tool in here, which is right on those use cases, retail, healthcare, high-tech oil and gas banking, and a lot of examples. And I went through them all and virtually every single one of them from a value contribution standpoint the unlocking value came down to data large data sets, document analysis, converting sentiment analysis, analytics. I mean, it really does come down to the data. And I wonder if you could comment on that and why is it that cloud is enabled that? >> Well, it goes back to scale. And I think the word that I would use would be data gravity because we're talking about massive amounts of data. So as you go through those kind of three dimensions in terms of rejuvenation one of the things you can do as you optimize and clarify and build better resiliency the thing that comes into play I think is to have clean data and data that's available in multiple places that you can create an underlying platform in order to leverage the services, the capabilities around, building out that structure. >> And then if I may, so you had this again I want to stress as EBITDA. It's not a revenue and it's the EBITDA potential as a result of leveraging cloud. And you listed a number of industries. And I wonder if you could comment on the patterns that you saw. I mean, it doesn't seem to be as simple as Negroponte bits versus Adam's in terms of your ability to unlock value. What are the patterns that you saw there and why are the ones that have so much potential why are they at the top of the list? >> Well, I mean, they're ranked based on impact. So the five greatest industries and again, aligned by the fortune 500. So it's interesting when you start to unpack it that way high-tech oil, gas, retail, healthcare, insurance and banking, right? Top. And so we did look at the different solutions that were in that, tried to decipher what was fully unlocked by cloud, what was accelerated by cloud and what was perhaps in this timeframe remaining on premise. And so we kind of step by step, expert by expert, use case by use case deciphered of the 700, how that applied. >> So how should practitioners within organizations business but how should they use this data? What would you recommend, in terms of how they think about it, how they apply it to their business, how they communicate? >> Well, I think clearly what came out was a set of best practices for what organizations that were leveraging cloud and getting the kind of business return, three things stood out, execution, experience and excellence. And so for under execution it's not just the transaction, you're not just buying cloud you're changing their operating model. And so if the organization isn't kind of retooling the model, the processes, the workflows in order to support creating the roles then they aren't going to be able, they aren't going to be successful. In terms of experience, that's all about hands-on. And so you have to dive in, you have to start you have to apply yourself, you have to gain that applied knowledge. And so if you're not gaining that experience, you're not going to move forward. And then in terms of excellence, and it was mentioned earlier by Jeff re-skilling, up-skilling, if you're not committed to your workforce and pushing certification, pushing training in order to really evolve your workforce or your ways of working you're not going to leverage cloud. So those three best practices really came up on top in terms of what a mature cloud adopter looks like. >> That's awesome. Michael, thank you for coming on. Really appreciate it. Last question I have for you as we wrap up this trillion dollar segment upon intended is the cloud mindset. You mentioned partnering and scaling up. The role of the enterprise and business is to partner with the technologists, not just the technologies but the companies talk about this cloud native mindset because it's not just lift and shift and run apps. And I have an IT optimization issue. It's about innovating next gen solutions and you're seeing it in public sector. You're seeing it in the commercial sector, all areas where the relationship with partners and companies and startups in particular, this is the startup showcase. These are startups are more relevant than ever as the tide is shifting to a new generation of companies. >> Yeah, so a lot of think about an engine. A lot of things have to work in order to produce the kind of results that we're talking about. Brad, you're more than fair share or unfair share of trillion dollars. And so CEOs need to lead this in bold fashion. Number one, they need to craft the moonshot or the Marshot. They have to set that goal, that aspiration. And it has to be a stretch goal for the organization because cloud is the only way to enable that achievement of that aspiration that's number one, number two, they really need a hardheaded economic case. It has to be defined in terms of what the expectation is going to be. So it's not loose. It's very, very well and defined. And in some respects time box what can we do here? I would say the cloud data, your organization has to move in an agile fashion training DevOps, and the fourth thing, and this is where the startups come in is the cloud platform. There has to be an underlying platform that supports those aspirations. It's an art, it's not just an architecture. It's a living, breathing live service with integrations, with standardization, with self service that enables this whole program. >> Awesome, Michael, thank you for coming on and sharing the McKinsey perspective. The report, the clouds trillion dollar prize is up for grabs. Everyone who's registered for this event will get a copy. We will appreciate it's also on the website. We'll make sure everyone gets a copy. Thanks for coming, I appreciate it. Thank you. >> Thanks, Michael. >> Okay, Dave, big discussion there. Trillion dollar baby. That's the cloud. That's Jassy. Now he's going to be the CEO of AWS. They have a new CEO they announced. So that's going to be good for Amazon's kind of got clarity on the succession to Jassy, trusted soldier. The ecosystem is big for Amazon. Unlike Microsoft, they have the different view, right? They have some apps, but they're cultivating as many startups and enterprises as possible in the cloud. And no better reason to change gears here and get a venture capitalist in here. And a friend of theCUBE, Jerry Chen let's bring them up on stage. Jerry Chen, great to see you partner at Greylock making all the big investments. Good to see you >> John hey, Dave it's great to be here with you guys. Happy marks.Can you see that? >> Hey Jerry, good to see you man >> So Jerry, our first inaugural AWS startup showcase we'll be doing these quarterly and we're going to be featuring the best of the best, you're investing in all the hot startups. We've been tracking your careers from the beginning. You're a good friend of theCUBE. Always got great commentary. Why are startups more important than ever before? Because in the old days we've talked about theCUBE before startups had to go through certain certifications and you've got tire kicking, you got to go through IT. It's like going through security at the airport, take your shoes off, put your belt on thing. I mean, all kinds of things now different. The world has changed. What's your take? >> I think startups have always been a great way for experimentation, right? It's either new technologies, new business models, new markets they can move faster, the experiment, and a lot of startups don't work, unfortunately, but a lot of them turned to be multi-billion dollar companies. I thing startup is more important because as we come out COVID and economy is recovery is a great way for individuals, engineers, for companies for different markets to try different things out. And I think startups are running multiple experiments at the same time across the globe trying to figure how to do things better, faster, cheaper. >> And McKinsey points out this use case of rejuvenate, which is essentially retool pivot essentially get your costs down or and the next innovation here where there's Tam there's trillion dollars on unlock value and where the bulk of it is is the innovation, the new use cases and existing new use cases. This is where the enterprises really have an opportunity. Could you share your thoughts as you invest in the startups to attack these new waves these new areas where it may not look the same as before, what's your assessment of this kind of innovation, these new use cases? >> I think we talked last time about kind of changing the COVID the past year and there's been acceleration of things like how we work, education, medicine all these things are going online. So I think that's very clear. The first wave of innovation is like, hey things we didn't think we could be possible, like working remotely, e-commerce everywhere, telemedicine, tele-education, that's happening. I think the second order of fact now is okay as enterprises realize that this is the new reality everything is digital, everything is in the cloud and everything's going to be more kind of electronic relation with the customers. I think that we're rethinking what does it mean to be a business? What does it mean to be a bank? What does it mean to be a car company or an energy company? What does it mean to be a retailer? Right? So I think the rethinking that brands are now global, brands are all online. And they now have relationships with the customers directly. So I think if you are a business now, you have to re experiment or rethink about your business model. If you thought you were a Nike selling shoes to the retailers, like half of Nike's revenue is now digital right all online. So instead of selling sneakers through stores they're now a direct to consumer brand. And so I think every business is going to rethink about what the AR. Airbnb is like are they in the travel business or the experience business, right? Airlines, what business are they in? >> Yeah, theCUBE we're direct to consumer virtual totally opened up our business model. Dave, the cloud premise is interesting now. I mean, let's reset this where we are, right? Andy Jassy always talks about the old guard, new guard. Okay we've been there done that, even though they still have a lot of Oracle inside AWS which we were joking the other day, but this new modern era coming out of COVID Jerry brings this up. These startups are going to be relevant take territory down in the enterprises as new things develop. What's your premise of the cloud and AWS prospect? >> Well, so Jerry, I want to to ask you. >> Jerry: Yeah. >> The other night, last Thursday, I think we were in Clubhouse. Ben Horowitz was on and Martine Casado was laying out this sort of premise about cloud startups saying basically at some point they're going to have to repatriate because of the Amazon VIG. I mean, I'm paraphrasing and I guess the premise was that there's this variable cost that grows as you scale but I kind of shook my head and I went back. You saw, I put it out on Twitter a clip that we had the a couple of years ago and I don't think, I certainly didn't see it that way. Maybe I'm getting it wrong but what's your take on that? I just don't see a snowflake ever saying, okay we're going to go build our own data center or we're going to repatriate 'cause they're going to end up like service now and have this high cost infrastructure. What do you think? >> Yeah, look, I think Martin is an old friend from VMware and he's brilliant. He has placed a lot of insights. There is some insights around, at some point a scale, use of startup can probably run things more cost-effectively in your own data center, right? But I think that's fewer companies more the vast majority, right? At some point, but number two, to your point, Dave going on premise versus your own data center are two different things. So on premise in a customer's environment versus your own data center are two different worlds. So at some point some scale, a lot of the large SaaS companies run their own data centers that makes sense, Facebook and Google they're at scale, they run their own data centers, going on premise or customer's environment like a fortune 100 bank or something like that. That's a different story. There are reasons to do that around compliance or data gravity, Dave, but Amazon's costs, I don't think is a legitimate reason. Like if price is an issue that could be solved much faster than architectural decisions or tech stacks, right? Once you're on the cloud I think the thesis, the conversation we had like a year ago was the way you build apps are very different in the cloud and the way built apps on premise, right? You have assume storage, networking and compute elasticity that's independent each other. You don't really get that in a customer's data center or their own environment even with all the new technologies. So you can't really go from cloud back to on-premise because the way you build your apps look very, very different. So I would say for sure at some scale run your own data center that's why the hyperscale guys do that. On-premise for customers, data gravity, compliance governance, great reasons to go on premise but for vast majority of startups and vast majority of customers, the network effects you get for being in the cloud, the network effects you get from having everything in this alas cloud service I think outweighs any of the costs. >> I couldn't agree more and that's where the data is, at the way I look at it is your technology spend is going to be some percentage of revenue and it's going to be generally flat over time and you're going to have to manage it whether it's in the cloud or it's on prem John. >> Yeah, we had a quote on theCUBE on the conscious that had Jerry I want to get your reaction to this. The executive said, if you don't have an AI strategy built into your value proposition you will be shorted as a stock on wall street. And I even went further. So you'll probably be delisted cause you won't be performing with a tongue in cheek comment. But the reality is that that's indicating that everyone has to have AI in their thing. Mainly as a reality, what's your take on that? I know you've got a lot of investments in this area as AI becomes beyond fashion and becomes table stakes. Where are we on that spectrum? And how does that impact business and society as that becomes a key part of the stack and application stack? >> Yeah, I think John you've seen AI machine learning turn out to be some kind of novelty thing that a bunch of CS professors working on years ago to a funnel piece of every application. So I would say the statement of the sentiment's directionally correct that 20 years ago if you didn't have a web strategy or a website as a company, your company be sure it, right? If you didn't have kind of a internet website, you weren't real company. Likewise, if you don't use AI now to power your applications or machine learning in some form or fashion for sure you'd be at a competitive disadvantage to everyone else. And just like if you're not using software intelligently or the cloud intelligently your stock as a company is going to underperform the rest of the market. And the cloud guys on the startups that we're backing are making AI so accessible and so easy for developers today that it's really easy to use some level of machine learning, any applications, if you're not doing that it's like not having a website in 1999. >> Yeah. So let's get into that whole operation side. So what would you be your advice to the enterprises that are watching and people who are making decisions on architecture and how they roll out their business model or value proposition? How should they look at AI and operations? I mean big theme is day two operations. You've got IT service management, all these things are being disrupted. What's the operational impact to this? What's your view on that? >> So I think two things, one thing that you and Dave both talked about operation is the key, I mean, operations is not just the guts of the business but the actual people running the business, right? And so we forget that one of the values are going to cloud, one of the values of giving these services is you not only have a different technology stack, all the bits, you have a different human stack meaning the people running your cloud, running your data center are now effectively outsource to Amazon, Google or Azure, right? Which I think a big part of the Amazon VIG as Dave said, is so eloquently on Twitter per se, right? You're really paying for those folks like carry pagers. Now take that to the next level. Operations is human beings, people intelligently trying to figure out how my business can run better, right? And that's either accelerate revenue or decrease costs, improve my margin. So if you want to use machine learning, I would say there's two areas to think about. One is how I think about customers, right? So we both talked about the amount of data being generated around enterprise individuals. So intelligently use machine learning how to serve my customers better, then number two AI and machine learning internally how to run my business better, right? Can I take cost out? Can I optimize supply chain? Can I use my warehouses more efficiently my logistics more efficiently? So one is how do I use AI learning to be a more familiar more customer oriented and number two, how can I take cost out be more efficient as a company, by writing AI internally from finance ops, et cetera. >> So, Jerry, I wonder if I could ask you a little different subject but a question on tactical valuations how coupled or decoupled are private company valuations from the public markets. You're seeing the public markets everybody's freaking out 'cause interest rates are going to go up. So the future value of cash flows are lower. Does that trickle in quickly into the private markets? Or is it a whole different dynamic? >> If I could weigh in poly for some private markets Dave I would have a different job than I do today. I think the reality is in the long run it doesn't matter as much as long as you're investing early. Now that's an easy answer say, boats have to fall away. Yes, interest rates will probably go up because they're hard to go lower, right? They're effectively almost zero to negative right now in most of the developed world, but at the end of the day, I'm not going to trade my Twilio shares or Salesforce shares for like a 1% yield bond, right? I'm going to hold the high growth tech stocks because regardless of what interest rates you're giving me 1%, 2%, 3%, I'm still going to beat that with a top tech performers, Snowflake, Twilio Hashi Corp, bunch of the private companies out there I think are elastic. They're going to have a great 10, 15 year run. And in the Greylock portfolio like the things we're investing in, I'm super bullish on from Roxanne to Kronos fear, to true era in the AI space. I think in the long run, next 10 years these things will outperform the market that said, right valuation prices have gone up and down and they will in our careers, they have. In the careers we've been covering tech. So I do believe that they're high now they'll come down for sure. Will they go back up again? Definitely, right? But as long as you're betting these macro waves I think we're all be good. >> Great answer as usual. Would you trade them for NFTs Jerry? >> That $69 million people piece of artwork look, I mean, I'm a longterm believer in kind of IP and property rights in the blockchain, right? And I'm waiting for theCUBE to mint this video as the NFT, when we do this guys, we'll mint this video's NFT and see how much people pay for the original Dave, John, Jerry (mumbles). >> Hey, you know what? We can probably get some good bang for that. Hey it's all about this next Jerry. Jerry, great to have you on, final question as we got this one minute left what's your advice to the people out there that either engaging with these innovative startups, we're going to feature startups every quarter from the in the Amazon ecosystem, they are going to be adding value. What's the advice to the enterprises that are engaging startups, the approach, posture, what's your advice. >> Yeah, when I talk to CIOs and large enterprises, they often are wary like, hey, when do I engage a startup? How, what businesses, and is it risky or low risk? Now I say, just like any career managing, just like any investment you're making in a big, small company you should have a budget or set of projects. And then I want to say to a CIO, Hey, every priority on your wish list, go use the startup, right? I mean, that would be 10 for 10 projects, 10 startups. Probably too much risk for a lot of tech companies. But we would say to most CIOs and executives, look, there are strategic initiatives in your business that you want to accelerate. And I would take the time to invest in one or two startups each quarter selectively, right? Use the time, focus on fewer startups, go deep with them because we can actually be game changers in terms of inflecting your business. And what I mean by that is don't pick too many startups because you can't devote the time, but don't pick zero startups because you're going to be left behind, right? It'd be shorted as a stock by the John, Dave and Jerry hedge fund apparently but pick a handful of startups in your strategic areas, in your top tier three things. These really, these could be accelerators for your career. >> I have to ask you real quick while you're here. We've got a couple minutes left on startups that are building apps. I've seen DevOps and the infrastructure as code movement has gone full mainstream. That's really what we're living right now. That kind of first-generation commercialization of DevOps. Now DevSecOps, what are the trends that you've seen that's different from say a couple of years ago now that we're in COVID around how apps are being built? Is it security? Is it the data integration? What can you share as a key app stack impact (mumbles)? >> Yeah, I think there're two things one is security is always been a top priority. I think that was the only going forward period, right? Security for sure. That's why you said that DevOps, DevSecOps like security is often overlooked but I think increasingly could be more important. The second thing is I think we talked about Dave mentioned earlier just the data around customers, the data on premise or the cloud, and there's a ton of data out there. We keep saying this over and over again like data's new oil, et cetera. It's evolving and not changing because the way we're using data finding data is changing in terms of sources of data we're using and discovering and also speed of data, right? In terms of going from Basser real-time is changing. The speed of business has changed to go faster. So I think these are all things that we're thinking about. So both security and how you use your data faster and better. >> Yeah you were in theCUBE a number of years ago and I remember either John or I asked you about you think Amazon is going to go up the stack and start developing applications and your answer was you know what I think no, I think they're going to enable a new set of disruptors to come in and disrupt the SaaS world. And I think that's largely playing out. And one of the interesting things about Adam Selipsky appointment to the CEO, he comes from Tableau. He really helped Tableau go from that sort of old guard model to an ARR model obviously executed a great exit to Salesforce. And now I see companies like Salesforce and service now and Workday is potential for your scenario to really play out. They've got in my view anyway, outdated pricing models. You look at what's how Snowflake's pricing and the consumption basis, same with Datadog same with Stripe and new startups seem to really be a leading into the consumption-based pricing model. So how do you, what are your thoughts on that? And maybe thoughts on Adam and thoughts on SaaS disruption? >> I think my thesis still holds that. I don't think Selipsky Adam is going to go into the app space aggressively. I think Amazon wants to enable next generation apps and seeing some of the new service that they're doing is they're kind of deconstructing apps, right? They're deconstructing the parts of CRM or e-commerce and they're offering them as services. So I think you're going to see Amazon continue to say, hey we're the core parts of an app like payments or custom prediction or some machine learning things around applications you want to buy bacon, they're going to turn those things to the API and sell those services, right? So you look at things like Stripe, Twilio which are two of the biggest companies out there. They're not apps themselves, they're the components of the app, right? Either e-commerce or messaging communications. So I can see Amazon going down that path. I think Adam is a great choice, right? He was a longterm early AWS exact from the early days latent to your point Dave really helped take Tableau into kind of a cloud business acquired by Salesforce work there for a few years under Benioff the guy who created quote unquote cloud and now him coming home again and back to Amazon. So I think it'll be exciting to see how Adam runs the business. >> And John I think he's the perfect choice because he's got operations chops and he knows how to... He can help the startups disrupt. >> Yeah, and he's been a trusted soldier of Jassy from the beginning, he knows the DNA. He's got some CEO outside experience. I think that was the key he knows. And he's not going to give up Amazon speed, but this is baby, right? So he's got him in charge and he's a trusted lieutenant. >> You think. Yeah, you think he's going to hold the mic? >> Yeah. We got to go. Jerry Chen thank you very much for coming on. Really appreciate it. Great to see you. Thanks for coming on our inaugural cube on cloud AWS startup event. Now for the 10 startups, enjoy the sessions at 12:30 Pacific, we're going to have the closing keynote. I'm John Ferry for Dave Vellante and our special guests, thanks for watching and enjoy the rest of the day and the 10 startups. (upbeat music)

>> What does it take for an entrepreneur to develop a disruptive idea, prove that it works and bring it to market. I can think of a lot of things, but one of the most important is speed. (jet engine roars) This is Dave Vellante from theCUBE inviting you to join me and John Furrier for a special CUBE on cloud startup showcase made possible by AWS. Joining theCUBE will be Michael Lebow of McKinsey. We'll also be joined by Greylock's Jerry Chen. He's going to bring the VC perspective. CIO Ben Haynes is also going to be there to lay down his practical knowledge. We'll also have Jeff Barr of AWS and together we'll feature 10 innovative companies from the AWS Global Startup Program. So if you're a technology practitioner, you'll see some of the innovations that might help transform your business. If you're an investor, you'll get a glimpse of the future and if you're an entrepreneur, you'll see how 10 companies are rocketing toward escape velocity. So join us March, 24th at 9:00 AM Pacific for theCUBE on cloud startup showcase, Innovations with Cloud Data and Cloud Ops. We'll see you there. (upbeat music)

>>Hi, everyone. Welcome to ASML day. My name is Yasmin Joffey. I'm the director of systems engineering for ASML at HPE. Today. We're here and joined by my colleague, Don wake, who is a technical marketing engineer who will talk to us about the date and the life of an it administrator through the lens of ASML container platform. We'll be answering your questions real time. So if you have any questions, please feel free to put your questions in the chat, and we should have some time at the end for some live Q and a. Don wants to go ahead and kick us off. >>All right. Thanks a lot, Yasir. Yeah, my name is Don wake. I'm the tech marketing guy and welcome to asthma all day, day in the life of an it admin and happy St. Patrick's day. At the same time, I hope you're wearing green virtual pinch. If you're not wearing green, don't have to look that up if you don't know what I'm scouting. So we're just going to go through some quick things. Talk about discussion of modern business. It needs to kind of set the stage and go right into a demo. Um, so what is the need here that we're trying to fulfill with, uh, ASML container platform? It's, it's all rooted in analytics. Um, modern businesses are driven by data. Um, they are also application centric and the separation of applications and data has never been more important or, or the relationship between the two applications are very data hungry. >>These days, they consume data in all new ways. The applications themselves are, are virtualized, containerized, and distributed everywhere, and optimizing every decision and every application is, is become a huge problem to tackle for every enterprise. Um, so we look at, um, for example, data science, um, as one big use case here, um, and it's, it's really a team sport and I'm today wearing the hat of perhaps, you know, operations team, maybe software engineer, guy working on, you know, continuous integration, continuous development integration with source control, and I'm supporting these data scientists, data analysts. And I also have some resource control. I can decide whether or not the data science team gets a, a particular cluster of compute and storage so that they can do their work. So this is the solution that I've been given as an it admin, and that is the ASML container platform. >>And just walking through this real quick, at the top, I'm trying to, as wherever possible, not get involved in these guys' lives. So the data engineers, scientists, app developers, dev ops guys, they all have particular needs and they can access their resources and spin up clusters, or just do work with the Jupiter notebook or run spark or Kafka or any of the, you know, popular analytics platforms by just getting in points that we can provide to them web URLs and their self service. But in the backend, I can then as the it guy makes sure the Kubernetes clusters are up and running, I can assign particular access to particular roles. I can make sure the data's well protected and I can connect them. I can import clusters from public clouds. I can, uh, you know, put my like clusters on premise if I want to. >>And I can do all this through this centralized control plane. So today I'm just going to show you I'm supporting some data scientists. So one of our very own guys is actually doing a demo right now as well, called the a day in the life of the data scientist. And he's on the opposite side, not caring about all the stuff I'm doing in the backend and he's training models and registering the models and working with data, uh, inside his, you know, Jupiter notebook, running inferences, running postman scripts. And so I'm in the background here, making sure that he's got access to his cluster storage protected, make sure it's, um, you know, his training models are up, he's got service endpoints, connecting him to, um, you know, his source control and making sure he's got access to all that stuff. So he's got like a taxi ride prediction model that he's working on and he has a Jupiter notebook and models. So why don't we, um, get hands on and I'll just jump right over it. >>It was no container platform. So this is a web UI. So this is the interface into the container platform. Our centralized control plane, I'm using my active directory credentials to log in here. >>And >>When I log in, I've also been assigned a particular role, uh, with regard to how much of the resources I can access. Now, in my case, I'm a site admin you can see right up here in the upper right hand, I'm a site admin and I have access to lots and lots of resources. And the one I'm going to be focusing on today is a Kubernetes cluster. Um, so I have a cluster I can go in here and let's say, um, we have a new data scientists come on board one. I can give him his own resources so he can do whatever he wants, use some GPU's and not affect other clusters. Um, so we have all these other clusters already created here. You can see here that, um, this is a very busy, um, you know, production system. They've got some dev clusters over here. >>I see here, we have a production cluster. So he needs to produce something for data scientists to use. It has to be well protected and, and not be treated like a development resource. So under his production cluster, I decided to create a new Kubernetes cluster. And literally I just push a button, create Kubernetes cluster once I've done that. And I'll just show you some of the screens and this is a live environment. So this is, I could actually do it all my hosts are used up right now, but I wouldn't be able to go in here and give it a name, just select, um, some hosts to use as the primary master controller and some workers answer a few more questions. And then once that's done, I have now created a special, a whole nother Kubernetes cluster, um, that I could also create tenants from. >>So tenants are really Kubernetes. Uh namespaces so in addition to taking hosts and Kubernetes clusters, I can also go to that, uh, to existing clusters and now carve out a namespace from that. So I look at some of the clusters that were already created and, um, let's see, we've got, um, we've got this year is an example of a tenant that I could have created from that production cluster. And to do that here in the namespace, I just hit create and similar to how you create a cluster. You can now carve down from a given cluster and we'll say the production cluster and give it a name and a description. I can even tell it, I want this specific one to be an AI ML project, um, which really is our ML ops license. So at the end of the day, I can say, okay, I'm going to create an ML ops tenant from that cluster that I created. >>And so I've already created it here for this demo. And I'm going to just go into that Kubernetes namespace now that we also call it tenant. I mean, it's like, multitenancy the name essentially means we're carving out resources so that somebody can be isolated from another environment. First thing I typically do. Um, and at this point I could also give access to this tenant and only this tenant to my data scientist. So the first thing I typically do is I go in here and you can actually assign users right here. So right now it's just me. But if I want it to, for example, give this, um, to Terry, I could go in here and find another user and assign him from this lead, from this list, as long as he's got the proper credentials here. So you can see here, all these other users have active directory credentials, and they, uh, when we created the cluster itself, we also made sure it integrated with our active directory, so that only authorized users can get in there. >>Let's say the first thing I want to do is make sure when I do Jupiter notebook work, or when Terry does, I'm going to connect him up straight up to the get hub repository. So he gives me a link to get hub and says, Hey man, this is all of my cluster work that I've been doing. I've got my source control there. My scripts, my Python notebooks, my Jupiter notebooks. So when I create that, I simply give him, you know, he gives me his, I create a configuration. I say, okay, here's a, here's a get repo. Here's the link to it. I can use a token, here's his username. And I can now put in that token. So this is actually a private repo and using a token, you know, standard get interface. And then the cool thing after that, you can go in here and actually copy the authorization secret. >>And this gets into the Kubernetes world. Um, you know, if you want to make sure you have secure integration with things like your source control or perhaps your active directory, that's all maintained in secrets. So you can take that secret. And when I then create his notebook, I can put that secret right in here in this, uh, launch Yammel. And I say, Hey, connect this Jupiter notebook up with this secret so he can log in. And when I've launched this Jupiter notebook cluster, this is actually now, uh, within my, my, uh, Kubernetes tenant. It is now really a pod. And if I want to, I can go right into a terminal for that, uh, Kubernetes tenant and say, coop CTL, these are standard, you know, CNCF certified Kubernetes get pods. And when I do this, it'll tell me all of the active pods and within those positive containers that I'm running. >>So I'm running quite a few pods and containers here in this, uh, artificial intelligence machine learning, um, tenant. So that's kind of cool. Also, if I wanted to, I could go straight and I can download the config for Kubernetes, uh, control. Uh well, and then I can do something like this, where on my own system where I'm more comfortable, perhaps coop CTL get pods. So this is running on my laptop and I just had to do a coop CTL refresh and give the IP address and authorization, um, information in order to connect from my laptop to that end point. So from a CIC D perspective from, you know, an it admin guides, he usually wants to use tools right on his, uh, desktop. So here am I back in my web browser, I'm also here on the dashboard of this, uh, Kubernetes, um, tenant, and I can see how it's doing. >>It looks like it's kind of busy here. I can focus specifically on a pod if I want to. I happen to know this pod is my Jupiter notebook pod. So aren't, I show how, you know, I could enable my data scientists by just giving him the, uh, URL or what we call a notebook service end points or notebook end point. And just by clicking on this URL or copying it, copying, you know, it's a link, uh, and then emailing it to them and say, okay, here's your, uh, you know, here's your duper notebook. And I say, Hey, just log in with your credentials. I've already logged in. Um, and so then he's got his Jupiter notebook here and you can see that he's connected to his GitHub repo directly. He's got all of the files that he needs to run his data science project and within here, and this is really in the data science realm, data scientists realm. >>He can see that he can have access to centralized storage and he can copy the files from his GitHub repo to that centralized storage. And, you know, these, these commands, um, are kind of cool. They're a little Jupiter magic commands, and we've got some of our own that showed that attachment to the cluster. Um, but you can see here if you run these commands, they're actually looking at the shared project repository managed by the container platform. So, you know, just to show you that again, I'll go back to the container platform. And in fact, the data scientist, uh, could do the same thing. Attitude put a notebook back to platform. So here's this project repository. So this is other big point. So now putting on my storage admin hat, you know, I've got this shared, um, storage, um, volume that is managed for me by the ESMO data fabric. >>Um, in, in here, you can see that the data scientist, um, from his get repo is able to through Jupiter notebook directly, uh, copy his code. He was able to run as Jupiter notebook and create this XG boost, uh, model. So this file can then be registered in this AIML tenant. So he can go in here and register his model. So this is, you know, this is really where the data scientist guy can self-service kick off his notebooks, even get a deployment end point so that he can then inference his cluster. So here again, another URL that you could then take this and put it into like a postman rest URL and get answers. Um, but let's say he wants to, um, he's been doing all this work and I want to make sure that his, uh, data's protected, uh, how about creating a mirror. >>So if I want to create a mirror of that data, now I go back to this other, uh, and this is the, the, uh, data fabric embedded in a very special cluster called the Picasso cluster. And it's a version of the ASML data fabric that allows you to launch what was formerly called Matt bar as a Kubernetes cluster. And when you create this special cluster, every other cluster that you create is automatically, uh, gets things like that. Tenant storage. I showed you to create a shared workspace, and it's automatically managed by this, uh, data fabric. Uh, and you're even given an end point to go into the data fabric and then use all of the awesome features of ASML data fabric. So here I can just log in here. And now I'm at the, uh, data fabric, web UI to do some data protection and mirroring. >>So >>Let's go over here. Let's say I want to, uh, create a mirror of that tenant. So I forgot to note what the name of my tenant was. I'm going to go back to my tenant, the name of the volume that I'm playing with here. So in my AIML tenant, I'm going to go to my source, control my project repository that I want to protect. And I see that the ESMO data fabric has created 10 and 30 as a volume. So I'll go back to my, um, data fabric here, and I'm going to look for 10 and 30. And if I want to, I can go into tenant 30, >>Okay. >>Down here, I can look at the usage. I can look at all of the, you know, I've used very little of the, uh, allocated storage that I want, but let's, uh, you know what, let's go ahead and create a volume to mirror that one. So very simple web UI that has said create volume. I go in here and I say, I want to do a, a tenant 30 mirror. And I say, mirror the mirror volume. Um, I want to use my Picasso cluster. I want to use tenant 30. So now that's actually looking up in the data fabric, um, database there's 10 and 30 K. So it knows exactly which one I want to use. I can go in here and I can say, you know, ext HCP, tenant, 30 mirror, you know, I can give it whatever name I want and this path here. >>And that's a whole nother, uh, demo is this could be in Tokyo. This could be mirrored to all kinds of places all over the world, because this is truly a global name, split namespace, which is a huge differentiator for us in this case, I'm creating a local mirror and that can go down here and, um, I can add, uh, audit and encryptions. I can do, um, access control. I can, you know, change permissions, you know, so full service, um, interactivity here. And of course this is using the web UI, but there's also rest API interfaces as well. So that is pretty much the, the brunt of what I wanted to show you in the demo. Um, so we got hands on and I'm just going to throw this up real quick and then come back to Yasser. See if he's got any questions he has received from anybody watching, if you have any new questions. >>Yeah. We've got a few questions. Um, we can, uh, just take some time to go, hopefully answer a few. Um, so it, it does look like you can integrate or incorporate your existing get hub, uh, to be able to, um, extract, uh, shared code or repositories. Correct? >>Yeah. So we have that built in and can either be, um, get hub or bit bucket it's, you know, pretty standard interface. So just like you can go into any given, get hub and do a clone of a, of a repo, pull it into your local environment. We integrated that directly into the gooey so that you can, uh, say to your, um, AIML tenant, uh, to your Jupiter notebook. You know, here's, here's my GitHub repo. When you open up my notebook, just connect me straight up. So it saves you some, some steps there because Jupiter notebook is designed to be integrated with get hub. So we have get hub integrated in as well or bit bucket. Right. >>Um, another question around the file system, um, has the map, our file system that was carried over, been modified in any way to run on top of Kubernetes. >>So yeah, I would say that the map, our file system data fabric, what I showed here is the Kubernetes version of it. So it gives you a lot of the same features, but if you need, um, perhaps run it on bare metal, maybe you have performance, um, concerns, um, you know, you can, uh, you can also deploy it as a separate bare metal instance of data fabric, but this is just one way that you can, uh, use it integrated directly into Kubernetes depends really the needs of, of the, uh, the user and that a fabric has a lot of different capabilities, but this is, um, it has a lot of the core file system capabilities where you can do snapshots and mirrors, and it it's of course, striped across multiple, um, multiple disks and nodes. And, uh, you know, Matt BARR data fabric has been around for years. It's, uh, and it's designed for integration with these, uh, analytic type workloads. >>Great. Um, you showed us how you can manage, um, Kubernetes clusters through the ASML container platform you buy. Um, but the question is, can you, uh, control who accesses, which tenant, I guess, namespace that you created, um, and also can you restrict or, uh, inject resource limitations for each individual namespace through the UI? >>Oh yeah. So that's, that's a great question. Yes. To both of those. So, um, as a site admin, I had lots of authority to create clusters, to go into any cluster I wanted, but typically for like the data scientist example I used, I would give him, I would create a user for him. And there's a couple of ways you can create users. Um, and it's all role-based access control. So I could create a local user and have container platform authenticate him, or I can say integrate directly with, uh, active directory or LDAP, and then even including which groups he has access to. And then in the user interface for the site admin, I could say he gets access to this tenant and only this tenant. Um, another thing you asked about is his limitations. So when you create the tenant to prevent that noisy neighbor problem, you can, um, go in and create quotas. >>So I didn't show the process of actually creating a Quentin, a tenant, but integral to that, um, flow is okay, I've defined which cluster I want to use. I defined how much memory I want to use. So there's a quota right there. You could say, Hey, how many CPU's am I taking from this pool? And that's one of the cool things about the platform is that it abstracts all that away. You don't have to really know exactly which host, um, you know, you can create the cluster and select specific hosts, but once you've created the cluster, it's not just a big pool of resources. So you can say Bob, over here, um, he's only going to get 50 of the a hundred CPU's available and he's only going to get X amount of gigabytes of memory. And he's only going to get this much storage that he can consume. So you can then safely hand off something and know they're not going to take all the resources, especially the GPU's where those will be expensive. And you want to make sure that one person doesn't hog all the resources. And so that absolutely quotas are built in there. >>Fantastic. Well, we, I think we are out of time. Um, we have, uh, a list of other questions that we will absolutely reach out and, um, get all your questions answered, uh, for those of you who ask questions in the chat. Um, Don, thank you very much. Thanks everyone else for joining Don, will this recording be made available for those who couldn't make it today? >>I believe so. Honestly, I'm not sure what the process is, but, um, yeah, it's being recorded so they must've done that for a reason. >>Fantastic. Well, Don, thank you very much for your time and thank everyone else for joining. Thank you.

>> Hello everyone, welcome to the special Cube conversation. I'm John foray with Dave Volante. We're known as theCube guys. We're doing a lot of Cube events over the past year with COVID in a virtual format and we really miss being onsite and being at the events extracting the signal from the noise. Dave, we've got some big news, we're announcing our Cube On Cloud series of virtual events. We're going to do in combination to the hybrid format of theCube when it comes back to, when theCube is coming back which we look like (indistinct), we'll be implementing theCube virtual format. And so Dave, Cube On Cloud Startups is our first inaugural event coming up this month. >> Well, I'm really excited John, because of course as you well know, in the early days of Cloud, we really doubled down on our content focus. And I think if you're a customer, firmly I believe CIO, CTOs, you have to have a portion of your portfolio that is really driven toward innovation and that really comes from startups. And that's really what we're going to feature today. We're talking about startups from tens of millions to hundreds of millions of ARR. I think if you're an investor, there's some great opportunities here. If you're a technologist, you might be trying to figure out, okay, "where's the next great place that I want to work?" And I think really it's all enabled by the Cloud and the Cloud is changing John, right? It's evolving from what was just core infrastructure storage servers, networking to really now driving transformative business value. And that's what this event is going to be all about. >> And what's exciting Dave, I want to share with the folks out there, you see theCube. you've seen us on all the channels, Twitter, Facebook, LinkedIn, all over the internet. Now with the virtual, we going to bring that together. And every quarter we're going to do a quarterly startup hot Cuban Cloud Startup event every quarter, four times a year. So, join us, we want to be part of our community. Be part of the conversation, theCube 365 virtual format is interactive, it's engaging. It's our own clubhouse, it's our own place to engage with you. If you want to engage with us, this is the time to do it. Or if you want to sit back and consume some of the great content, do that. Our first event on the 24th is with aWS and their sponsored showcase startups. We're going to be featuring 10 of the hottest Cloud startups obviously all around data and machine learning. And we're going to feature those 10, we're going to introduce the world to them, unpack them, talk to the founders and this top management of teams and understand their secret sauce, their competitive advantage and how they're going to be successful in the enterprise in Cloud. But we've also got a great keynote program to kick it off. We're going to have Jeff Barr who's legendary in the developer and Cloud community. He's with aWS. He does a lot of their developer. He writes all the blog posts announcing all the great products at aWS. If you're in the Cloud, visit, you know who Jeff Barr is. He's a legend. We got Jerry chin, Cube alumni. He's a partner at Greylock, tier one venture capital firm, and Michael Liebow who's a partner at McKinsey. And McKinsey is talking to all the C-suites Dave, they're the ones setting the table. And just recently came out with a Cloud report called, "Trillion Dollar Market Opportunity." Of course, we wrote Trillion Dollar Baby Cloud Ambition for Andy Jassy in 2015. We're going to tie that together. And of course, when you come to the event and join us, you get a free copy of that report. So, Dave-- >> And Don't forget Ben Haynes. He's going to bring the practitioner perspective which we're really excited about. And I'm glad you made that shout out to the Cube community because as you know, it's not just coming to the event and doing some chat. Do that, lay down your knowledge because the next show we're going to have you on live interview, you that's what we're all about. Bringing our community together, bringing you in and interacting with you, not just on chat or email or whatever but actually making you part of the program. >> Yeah, it's not a webinar Dave, these aren't webinars, webinars are old they're dying. Webinars are great for sales tools. You do those every day if you're a sales person or a company. This is different. We're talking about making it an immersive and interactive, engaging, virtually. This is going to be a great compliment. Certainly when the events come back and we're looking forward to it. I can't tell you Dave how many times people want to chat with me on Twitter, I'm not available, time zone around the world. Now, you can come to our events and engage directly with us and consume, but also we'll call you up. We're going to have sessions, maybe have some Ad hoc femoral conversations, set up your own little clubhouse with us and share your knowledge on the Cube. The Cube going virtual. Virtualization Dave, as we were joking during the pandemic is one of the upsides for what happened this year. And I got to say, I'm really, really excited because this brings a new format for us to bring to people. So, I'm really looking forward to it. >> Yeah, me too, John. So give us the details. Date, time, we've got a, I think we've got a screenshot but we'll pull that up and show people. So, there's a site. What's the dates again, John? >> This is on going to happen on March 24th, >> 9: 00 AM Pacific to 1:00 PM, it's a morning program. Again, it's a featured conference with the hot stars. We're going to feature, We're going to do a keynote session and then we're going to have the breakouts with all the startups. So, it can jump into the rooms find the startups you like and talk to them. And then a closing fireside chat with Ben Haynes who's a practitioner, CIO Perspectives, CXL Perspective as well as executives in the industry. So, we're going to wrap that up at the end of the day. So, great program. Good keynote on what ways are happening? What's the top trends and then ending fireside chats. Should be a great day, very cool. And of course it's virtual. So, you can do a fly by, you can come hang out with us and also come back. it's always going to be on 24/7, 365. So, that is the Cube On Cloud startups, March 24th. Join us and join our community, thank you.

>> Hello and welcome to this special CUBE update conversation, I'm John Furrier, host of theCUBE with my partner, Dave Vellante, co-host of theCUBE. Dave, lots of people are asking us what's going on with theCUBE what's happening. Obviously COVID people know that we go out to events to extract the signal from the noise. Number one leading in enterprise tech events, there's been no events. People want to know what's going on with theCUBE, theCUBE virtual. And they want to know when the events are going to come back and when it does what's theCUBE going to look like. >> Well, as you know, for a decade we were on premises at events, tech events, our great sponsors would have us there and let us do our thing. And we'd have editorial there, which is nice and have our own on discussions. But it was always at the host venue, or largely was, we've done some of our own shows but now with the virtual occurring we're driving a lot of our own events, We've got now the time to do that, and here's what I think, John, I really do believe that there's no question that in the second half of the year we're going to start to see some kind of hybrid emerge where you might see VIP's, almost like the Golden Globes, if you saw that, there may be 15, 20 people socially distant, comfortable, maybe a VIP event, 10, 20 CIO's in a room, and I think there's going to be a digital overlay to that, the virtual overlay to get greater reach. And then even in 2022, when physical comes back in a big way, I think virtual is here to stay. People are learning so much. They're learning the value of that long tail, that host event consumption that we've seen in our data and that's going to continue. And people are really learning how to fine tune that playbook. >> You know, I want to get your thoughts on this because I was explaining to someone about our CUBE virtual opportunity and events coming back. And as you know I've been an avid clubhouse user since December 30th and I've been noticing that the engagement is so high in these apps where people are collaborating. So, I want you to explain the dynamics as, as we have these cube virtual, our first event is March 24th, we've got Jerry Chen from Greylock, Michael Liebow from McKinsey, Jeff Barr from AWS, three big names, big individuals in terms of talent and start up power. But the names of the companies, McKinsey, Greylock, AWS, and me and you, you starting to see virtual as a format, Dave, where our community can come together to compliment theCUBE physical events and bring a new venue, a new format to engaging and creating content together. Can you explain what this means for audiences, our community and our sponsors? >> Well, I think a lot of companies are looking at just events in very narrow sense, we do an event, maybe it's a webinar, we're going to do an event, maybe it's small, mid-size, maybe even a large event. And then we're going onto the next one, onto the next one, so it's all about this sort of event cadence. And I think there's a much bigger picture here. And it's really about the content, the arc of content, the community, engaging with that community, over a long period of time, it's not a one-shot deal or they're not disposable, sort of events are kind of disposable in that regard. I think our philosophy is different. We really try to connect, build that community out. And then also bring that community back in, those who want to participate, it's almost like a reward system. If you participate in an event, a community event, the next one you're actually going to be featured, you're going to come on theCUBE, you're going to be participating in the program directly. And I think, John, for sponsors, it really means, we've seen that a lot of the value that the sponsors are getting really has not been replicated from the physical events. And so what we're trying to do here is give those many, many sponsors a platform in order to have their voices heard so that they can engage with broader communities and tap in to other communities. >> Dave, you know, we were just talking the other day about all these event platforms that are out there and we're a media platform and that there's a new dynamic out there where it's not about the number of events that you participated in, it's the audiences that you engage with and create content value together and sponsors that you enable, we enable, can enable to go direct to the consumer. And this is a big trend that we're seeing. Media as a service or direct to the consumer. You seeing companies like Tesla do it, Apple, even venture capital firms like Andreessen Horowitz going direct to the audience and cutting the middlemen out of being disintermediated. This is an interesting opportunity. Can you share your thoughts, because if a customer, our sponsor, is going to try to do that, they need to have media capabilities, not just event software. An event is a moment in time, media is ongoing for engaging. They're two different things but they have to work together. Can you explain what this means in basic terms to customers and audience? Why is this so important this new trend? >> I think it's really simple. The bottom line is that every company has to be in some way, shape or form a media company they're producing content, and everybody wants to control the narrative, control of the audience, except the way you do that is to produce great authentic content. And I will tell you most companies, certainly most companies in the tech business aren't really that good at it. There are a couple of standouts. You mentioned some big names like Tesla, so you see some VC firms doing it, but people are learning, and they're going to get better and better at it. But our basic premise and I think it's right on is that every company has to be a content company, a content producer. So what we want to do is help them do that. Give them tools, give them platforms, give them methodologies to really be able to in an agile fashion, produce high quality content and distribute it through a workflow and then iterate >> Agile Media, that's our opportunity and that's what we're going to try to do. And I think what I'm most excited about Dave is we can help our sponsors with a product that helps them go direct to their customer while we can at the same time increase our serving our audiences with high quality content so that they can work with us, consume or create with us. And I think that's a power dynamic that is a flywheel of innovation. This is kind of what media should be, and this is what we're trynna do. >> Well, that's a mega trend. And the other thing that I think people forget about sometime is that data, there's a data fabric that connects all these different events, all the different webinars, all the content initiatives, the content programs, et cetera, et cetera, et cetera, that data fabric flows in a distributed way throughout the year, throughout the network, throughout the community. And it's got to be a two-way street and it's fundamentally you have to put data at the core of those initiatives. >> And Dave, one of the exciting things we're doing that I'll share is on March 24th, 9:00 Pacific, we're doing theCUBE On Cloud Startups, our virtual event in conjunction with AWS, Amazon Web Services, startup showcase. We're going to showcase 10 of the hottest startups in the Amazon cloud ecosystem around data, data ops, and pre-public, the next UNICORE, the next deca-core, And these are the hottest companies that are going to be hitting the enterprise and emerging technology markets in the next year. We're going to showcase them in our format, this is theCUBE virtual, so check it out, join us, be part of our community. If you want to engage with us, definitely get on the roster. We're going to do these four times a year, and again, we do a lot more of them. And then you'll see us back in person, when the events come back, post pandemic. I'm John Furrier, Dave Vellante, thank you for your time and we'll see you on the 24th, or at our events, thank you.

(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 around the globe it's the cube with digital coverage of Red Hat summit 2020 brought to you by Red Hat welcome back this is the cubes coverage of Red Hat summit 2020 of course this year instead of all gathering together in San Francisco we're getting to talk to red hat executives their partners and their customers where they are around the globe I'm your host Stu minimun and happy to welcome to the program Nick Barr said who is the senior director of Technology Strategy at Red Hat he happens to be on a boat in the Bahamas so Nick thanks so much for joining us hey thank you for inviting me it's a great pleasure to be here and it's a great pleasure to work for a company that has always dealt with remote people so it's really easy for us to kind of thing yeah Nick you know it's interesting I've been saying probably for the last 10 years that the challenge of our time is really distributed systems you know from a software standpoint that's what we talked about and even more so today and number one of course the current situation with the global plan global pandemic but number two the topic we're gonna talk to you about is edge and 5g it's obviously gotten a lot of hype so before we get into that - training Nick you know you came into Red Hat through an acquisition so give us a little bit about your background and what you work on Baretta about five years ago company I was working for involves got acquired by read at and I've been very lucky in that acquisition where I found a perfect home to express my talent I've been free software advocate for the past 20-some years always been working in free software for the past 20 years and Red Hat is really wonderful for that yeah it's addressing me ok yeah I remember back the early days we used to talk about free software now we don't talk free open-source is what we talk about you know dream is a piece of what we're doing but yeah let's talk about you know Ino Vaughn's I absolutely remember the they were a partner of Red Hat talked to them a lot at some of the OpenStack goes so I I'm guessing when we're talking about edge these are kind of the pieces coming together of what red had done for years with OpenStack and with NFB so what what what's the solution set you're talking about Ferguson side how you're helping your customers with these blue well clearly the solution we are trying to put together as to combine what people already have with where they want to go our vision for the future is a vision where openshift is delivering a common service on any platform including hardware at the far edge on a model where both viens and containers can be hosted on the same machine however there is a long road to get there and until we can fulfill all the needs we are going to be using combination of openshift OpenStack and many other product that we have in our portfolio to fulfill the needs of our customer we've seen for example a Verizon starting with OpenStack quite a few years ago now going with us with openshift that they're going to place on up of OpenStack or directly on bare metal we've seen other big telcos use tag in very successful to deploy their party networks there is great capabilities in the existing portfolio we are just expanding that simplifying it because when we are talking about the edge we are talking about managing thousands if not millions of device and simplicity is key if you do not want to have your management box in Crete excellent so you talked a lot about the service providers obviously 5g as a big wave coming a lot of promise as what it will enable both for the service providers as well as the end-users help us understand where that is today and what we should expect to see in the coming years though so in respect of 5g there is two reason why 5g is important one it is B it is important in terms of ad strategy because any person deploying 5g will need to deploy computer resources much closer to the antenna if they want to be able to deliver the promise of 5g and the promise of very low latency the second reason it is important is because it allows to build a network of things which do not need to be interconnected other than through a 5g connection and this simplifies a lot some of the edge application that we are going to see where sensors needs to provide data in a way where you're not necessarily always connected to a physical network and maintaining a Wi-Fi connection is really complex and costly yeah Nick a lot of pieces that sometimes get confused or conflated I want you to help us connect the dots between what you're talking about for edge and what's happening the telcos and the the broader conversation about hybrid cloud or red hat calls at the O the open hybrid cloud because you know there were some articles that were like you know edge is going to kill the cloud I think we all know an IP nothing ever dies everything is all additive so how do these pieces all go together so for us at reddit it's very important to build edge as an extension of our open hybrid cloud strategy clearly what we are trying to build is an environment where developers can develop workloads once and then can the administrator that needs to deploy a workload or the business mode that means to deploy a workload can do it on any footprint and the edge is just one of these footprint as is the cloud as is a private environment so really having a single way to administer all these footprints having a single way to define the workloads running on it is really what we are achieving today and making better and better in the years to come um the the reality of [Music] who process the data as close as possible to where the data is being consumed or generated so you have new footprints - let's say summarize or simplify or analyze the data where it is being used and then you can limit the traffic to a more central site to only the essential of it is clear that we've the current growth of data there won't be enough capacity to have all the data going directly to the central part and this is what the edge is about making sure we have intermediary of points of processing yeah absolutely so Nikki you talked about OpenStack and OpenShift of course there's open source project with with OpenStack openshift the big piece of that is is kubernetes when it comes to edge are there other open source project the parts of the foundations out there that we should highlight when looking at these that's Luke oh there is a tremendous amount of projects that are pertaining to the edge read ad carry's many of these projects in its portfolio the middleware components for example Quercus or our amq mechanism caki are very important components we've got storage solutions that are super important also when you're talking about storing or handling data you've got in our management portfolio two very key tool one called ansible that allows to configure remotely confidence that that is super handy when you need to reconfigure firewall in Mass you've got another tool that he's a central piece of our strategy which is called a CM read at forgot the name of the product now we are using the acronym all the time which is our central management mechanism just delivered to us through IBM so this is a portfolio wide we are making and I forgot the important one which is real that Enterprise Linux which is delivering very soon a new version that is going to enable easier management at the edge yeah well of course we know that well is you know the core foundational piece with most of the solution in a portfolio that's really interesting how you laid that out though as you know some people on the outside look and say ok Red Hat's got a really big portfolio how does it all fit together you just discussed that all of these pieces become really important when when they come together for the edge so maybe uh you know one of the things when we get together summit of course we get to hear a lot from your your your customer so any customers you can talk about that might be a good proof point for these solutions that you're talking about today so right now most of the proof points are in the telco industry because these are the first one that have made the investment in it and when we are talking about their eyes and we are talking about a very large investment that is reinforced in their strategy we've got customers in telco all over the world that are starting to use our products to deploy their 5g networks and we've got lots of customer starting to work with us on creating their tragedy for in other vertical particularly in the industrial and manufacturing sector which is our necks and ever after telco yet yeah well absolutely Verizon a customer I'm well familiar with when it comes to what they've been used with Red Hat I'd interviewed them it opens back few years back when they talked about that those nmv type solutions you brought a manufacturing so that brings up one of the concerns when you talk about edge or specifically about IOT environment when we did some original research looking at the industrial Internet the boundaries between the IT group and the OT which heavily lives lives in manufacturing wouldn't they did they don't necessarily talk or work together so Houser had had to help to make sure that customers you know go through these transitions Plus through those silos and can take advantage of these sorts of new technologies well obviously you you have to look at a problem in entirety you've got to look at the change management aspect and for this you need to understand how people interact together if you intend on modifying the way they work together you also need to ensure that the requirements of one are not impeding the yeah other the man an environment of a manufacturer is really important especially when we are talking about dealing with IOT sensors which have very limited security capability so you need to add in the appropriate security layers to make what is not secure secure and if you don't do that you're going to introduce a friction and you also need to ensure that you can delegate administration of the component to the right people you cannot say Oh from now on all of what you used to be controlling on a manufacturing floor is now controlled centrally and you have to go through this form in order to have anything modified so having the flexibility in our tooling to enable respect of the existing organization and handle a change management the appropriate way is our way to answer this problem right Nick last thing for you obviously this is a maturing space lots of age happening so gives a little bit of a look forward as to what users should be affecting and you know what what what pieces will the industry and RedHat be working on that bring full value out of the edge and find a solution so as always any such changes are driven by the application and what we are seeing is in terms of application a very large predominance of requirements for AI ml and data processing capability so reinforcing all the components around this environment is one of our key addition and that we are making as we speak you can see Chris keynote which is going to demonstrate how we are enabling a manufacturer to process the signal sent from multiple sensors through an AI and during early failure detection you can also expect us to enable more and more complex use case in terms of footprint right now we can do very small data center that are residing on three machine tomorrow we'll be able to handle remote worker nodes that are on a single machine further along we'll be able to deal with disconnected node a single machine acting as a cluster all these are elements that are going to allow us to go further and further in the complication of the use cases it's not the same thing when you have to connect a manufacturer that is on solid grounds with fiber access or when you have to connect the Norway for example or a vote and talk about that too Nick thank you so much for all the updates no there's some really good breakouts I'm sure there's lots on the Red Hat website find out more about edge in five B's the Nick bark set thanks so much for joining us thank you very much for having me all right back with lots more covered from Red Hat summit 2020 I'm stoom in a man and thanks though we for watching the queue [Music]