>>Welcome back. Everyone live here at the I'm John Fur, host of the Cube. We got a special insertion here off the program. Jerry Chen Greylock, 10 years with the Cube coming on. 10 years ago when the cube first came here, Jerry, you were in the hallway. We didn't have any guess list. He was like, Hey, you wanna come up in the cube so much. Now we got three sets. We're gonna do hundreds of interviews already. We're gonna have probably over 200 streaming live. Love it Shorts, Instagram reels, data lake. The cubes expanded. You've been there from the whole >>Time. Its like the, its like the, the mcu, the Marvel Cinematic Universe. The Cube Cinematic universe. You know, it's, its a whole franchise. Congratulations and happy early birthday, John. Thank you very much. Thanks >>For having me. Yeah, you know, I was just graduated high school when I first came to aws. Look, I wanna get your thoughts on, we're gonna do a quick segment here before AMD comes on. Got some great interviews with those guys. You've been here 10 years, you're out in the trenches. Just Andy, Adam Celski, just talked to the VCs, the investment thesis economy. Yeah. This headwinds, tailwinds, depending on which side you're on, you're gonna have a tailwind or headwind. What's the outlook? What's your take of reinvent this year? Aws, the ecosystem and the investment market. >>You know, I think it's, it is a great rebound. The energy's back when it was like pre covid, right? We're saying last year was kind of half the size and you know, be postcode. But I think the show, the energy's great. And Amazon just amazing, right? It's in this economy, what's going on right now in the world. They're still growing, still kicking butt. I think you're gonna see a lot of both enterprise customers and startups start to worry about cost, right? Because I think Amazon's gonna focus like, Hey, how can they help the customers? But the economy for the next year, I think we're gonna see some headwinds. So I think a lot of startups, a lot of customers are gonna worry about cost. >>You're on the board of a lot of startups that are in the cloud, rock sets. One we've covered. I think they're gonna come on here too tomorrow or today. What's your advice on the board level? Go to market. Dial up. Dial down. Sure. What's the strategy marketplace? I mean, how do you give the advice to start? What's the, what's the north star? What's the, what's the advice as the investor? >>Two or three things for most startups, hard roi, like how can you save money? So all the kinda fluffy marketing value you gotta have hard dollar savings, right? Number one, if can save money, you'll do well. Number two, to your point, the marketplace is becoming the channel for startups. These lot of large customers have deals with Amazon through the marketplace. So startup can sell through the marketplace to customers. These lot of CFOs are doing no new vendors, right? It's getting hard, hard to get approved as a startup. So the marketplace become a bigger, bigger deal. >>What about existing ecosystem partners that have been around for the past 10 years? They're independent. They may have their toe in the marketplace, may not, some of them not making their numbers, they're starting to hear things like maybe they'll be re pivoting. People are tooling up. What's the advice for the existing ecosystem partners? Because they're either gonna be like the next data bricks or kind of like maybe >>Everyone's looking for the next data bricks, right? You know, I think for existing partners, you're seeing what's happened. John deals are getting smaller, taking longer to close, right? It's just the reality of what's happening right now. And so for those partners are saying, Hey, focus on the heart roi, be okay with the smaller land and just expand in 23, 24. So just get kind of creative of how you work with customers. And I, like you said, I think Marketplace is is kind of a, a go-to light >>Book. So today, Aruba, the new leader of the, of the partner network, they've merged eight PN with the marketplace. They've now won Coherent organization, not fragmented, I was talking to them last night. They have more startups than ever before coming on board. So the velocity of new venture creation is up, up and to the right still, even in this economy. And as they always say, best time to invest is in a down market. That's like BC 1 0 1, entrepreneurship 1 0 1. What's your advice right now for builders out there looking for that round, trying to get some traction. The agility with the cloud still is there. You can still get time to value. You can still get traction fast. That doesn't go away. What's your advice for the startups? >>Narrow, narrower wedge, right. So I think with like 5,000 startups every single year, there's so much noise. John, look across the floor, a lot of great companies. B, a lot of noise. So I think the more focused wedge you have as a startup and how you can land deliver value, the better land, the very, very sharp wedge expand over time. But just be very specific how you land. >>Awesome. Jerry, great to have you on. I know we wanna make some room on appreciate AMD for squeezing a couple minutes out of their hour and the next hour we're gonna spend with them for your Sage advice final kind of new Insta challenge that Savannah put together, A new host instant challenge, instant challenges. If you had to do an Instagram reel right now, oh, about reinvent this year, what would that Instagram reel be right now? >>I would, I would do the expos scavenger hunt, right? We would have a race of different VCs. You give me a list of five companies, the VCs find the first five companies on the list wins. The wins the race. I think that would be a great challenge. >>All right. What's the most important story this year at Reinvent that you could share with the folks that you could share in terms of what's important, what they should pay attention to, or what's not being told? >>Well, I, I think you talked about your interview with Adam Slosky is the solutions and the what you call the next gen cloud. These high level services. What AWS is doing around these services, it's super interesting. They kind of don't say lead the way, but the responded customers. So they lead the way by kind of following where the customer's going and if, when Slutsky and AWS are doing these solutions, supply chain, et cetera, that tells you kind of where the market's >>Headed. Next Gen Cloud, Jerry, Chad, thanks. Coming on, you're watching The Cube, the leader in high tech coverage. I'm John Furrier. Will be right back with more cube coverages. Day two, day three, here at Reinvent at the short break.

>>Hello, everyone. Welcome to the cubes presentation of the 80, but startup showcases MarTech is the focus. And this is all about the emerging cloud scale customer experience. This is season two, episode three of the ongoing series covering the exciting, fast growing startups from the cloud AWS ecosystem to talk about the future and what's available now, where are the actions? I'm your host John fur. Today. We joined by Cub alumni, Jerry Chen partner at Greylock ventures. Jerry. Great to see you. Thanks for coming on, >>John. Thanks for having me back. I appreciate you welcome there for season two. Uh, as a, as a guest star, >><laugh>, you know, Hey, you know, season two, it's not a one and done it's continued coverage. We, we got the episodic, uh, cube flicks model going >>Here. Well, you know, congratulations, the, the coverage on this ecosystem around AWS has been impressive, right? I think you and I have talked a long time about AWS and the ecosystem building. It just continues to grow. And so the coverage you did last season, all the events of this season is, is pretty amazing from the data security to now marketing. So it's, it's great to >>Watch. And 12 years now, the cube been running. I remember 2013, when we first met you in the cube, we just left VMware just getting into the venture business. And we were just riffing the next 80. No one really kind of knew how big it would be. Um, but we were kinda riffing on. We kind of had a sense now it's happening. So now you start to see every vertical kind of explode with the right digital transformation and disruption where you see new incumbents. I mean, new Newton brands get replaced the incumbent old guard. And now in MarTech, it's ripe for, for disruption because web two has gone on to web 2.5, 3, 4, 5, um, cookies are going away. You've got more governance and privacy challenges. There's a slew of kind of ad tech baggage, but yet lots of new data opportunities. Jerry, this is a huge, uh, thing. What's your take on this whole MarTech cloud scale, uh, >>Market? I, I think, I think to your point, John, that first the trends are correct and the bad and the good or good old days, the battle days MarTech is really about your webpage. And then email right there. There's, there's the emails, the only channel and the webpage was only real estate and technology to care about fast forward, you know, 10 years you have webpages, mobile apps, VR experiences, car experiences, your, your, your Alexa home experiences. Let's not even get to web three web 18, whatever it is. Plus you got text messages, WhatsApp, messenger, email, still great, et cetera. So I think what we've seen is both, um, explosion and data, uh, explosion of channel. So sources of data have increases and the fruits of the data where you can reach your customers from text, email, phone calls, etcetera have exploded too. So the previous generation created big company responses, Equa, you know, that exact target that got acquired by Oracle or, or, um, Salesforce, and then companies like, um, you know, MailChimp that got acquired as well, but into it, you're seeing a new generation companies for this new stack. So I, I think it's exciting. >>Yeah. And you mentioned all those things about the different channels and stuff, but the key point is now the generation shifts going on, not just technical generation, uh, and platform and tools, it's the people they're younger. They don't do email. They have, you know, proton mail accounts, zillion Gmail accounts, just to get the freebie. Um, they're like, they're, they'll do subscriptions, but not a lot. So the generational piece on the human side is huge. Okay. And then you got the standards, bodies thrown away, things like cookies. Sure. So all this is makes it for a complicated, messy situation. Um, so out of this has to come a billion dollar startup in my mind, >>I, I think multiple billion dollars, but I think you're right in the sense that how we want engage with the company branch, either consumer brands or business brands, no one wants to pick a phone anymore. Right? Everybody wants to either chat or DM people on Twitter. So number one, the, the way we engage is different, both, um, where both, how like chat or phone, but where like mobile device, but also when it's the moment when we need to talk to a company or brand be it at the store, um, when I'm shopping in real life or in my car or at the airport, like we want to reach the brands, the brands wanna reach us at the point of decision, the point of support, the point of contact. And then you, you layer upon that the, the playing field, John of privacy security, right? All these data silos in the cloud, the, the, the, the game has changed and become even more complicated with the startup. So the startups are gonna win. Will do, you know, the collect, all the data, make us secure in private, but then reach your customers when and where they want and how they want it. >>So I gotta ask you, because you had a great podcast just this week, published and snowflake had their event going on the data cloud, there's a new kind of SAS platform vibe going on. You're starting to see it play out. Uh, and one of the things I, I noticed on your podcast with the president of Hashi Corp, who was on people should listen to that podcast. It's on gray matter, which is the Greylocks podcast, uh, plug for you guys. He mentioned he mentions the open source dynamic, right? Sure. And, and I like what he, things, he said, he said, software business has changed forever. It's my words. Now he said infrastructure, but I'm saying software in general, more broader infrastructure and software as a category is all open source. One game over no debate. Right. You agree? >>I, I think you said infrastructure specifically starts at open source, but I would say all open source is one more or less because open source is in every bit of software. Right? And so from your operating system to your car, to your mobile phone, open source, not necessarily as a business model or, or, or whatever, we can talk about that. But open source as a way to build software distribute, software consume software has one, right? It is everywhere. So regardless how you make money on it, how you build software, an open source community ha has >>One. Okay. So let's just agree. That's cool. I agree with that. Let's take it to the next level. I'm a company starting a company to sell to big companies who pay. I gotta have a proprietary advantage. There's gotta be a way. And there is, I know you've talked about it, but I have my opinion. There is needs to be a way to be proprietary in a way that allows for that growth, whether it's integration, it's not gonna be on software license or maybe support or new open source model. But how does startups in the MarTech this area in general, when they disrupt or change the category, they gotta get value creation going. What's your take on, on building. >>You can still build proprietary software on top of open source, right? So there's many companies out there, um, you know, in a company called rock set, they've heavily open source technology like Rock's DB under the hood, but they're running a cloud database. That's proprietary snowflake. You talk about them today. You know, it's not open source technology company, but they use open source software. I'm sure in the hoods, but then there's open source companies, data break. So let's not confus the two, you can still build proprietary software. There's just components of open source, wherever we go. So number one is you can still build proprietary IP. Number two, you can get proprietary data sources, right? So I think increasingly you're seeing companies fight. I call this systems intelligence, right, by getting proprietary data, to train your algorithms, to train your recommendations, to train your applications, you can still collect data, um, that other competitors don't have. >>And then it can use the data differently, right? The system of intelligence. And then when you apply the system intelligence to the end user, you can create value, right? And ultimately, especially marketing tech, the highest level, what we call the system of engagement, right? If, if the chat bot the mobile UI, the phone, the voice app, etcetera, if you own the system of engagement, be a slack, or be it, the operating system for a phone, you can also win. So still multiple levels to play John in multiple ways to build proprietary advantage. Um, just gotta own system record. Yeah. System intelligence, system engagement. Easy, right? Yeah. >>Oh, so easy. Well, the good news is the cloud scale and the CapEx funded there. I mean, look at Amazon, they've got a ton of open storage. You mentioned snowflake, but they're getting a proprietary value. P so I need to ask you MarTech in particular, that means it's a data business, which you, you pointed out and we agree. MarTech will be about the data of the workflows. How do you get those workflows what's changing and how these companies are gonna be building? What's your take on it? Because it's gonna be one of those things where it might be the innovation on a source of data, or how you handle two parties, ex handling encrypted data sets. I don't know. Maybe it's a special encryption tool, so we don't know what it is. What's your what's, what's your outlook on this area? >>I, I, I think that last point just said is super interesting, super genius. It's integration or multiple data sources. So I think either one, if it's a data business, do you have proprietary data? Um, one number two with the data you do have proprietary, not how do you enrich the data and do you enrich the data with, uh, a public data set or a party data set? So this could be cookies. It could be done in Brad street or zoom info information. How do you enrich the data? Number three, do you have machine learning models or some other IP that once you collected the data, enriched the data, you know, what do you do with the data? And then number four is once you have, um, you know, that model of the data, the customer or the business, what do you deal with it? Do you email, do you do a tax? >>Do you do a campaign? Do you upsell? Do you change the price dynamically in our customers? Do you serve a new content on your website? So I think that workflow to your point is you can start from the same place, what to do with the data in between and all the, on the out the side of this, this pipeline is where a MarTech company can have then. So like I said before, it was a website to an email go to website. You know, we have a cookie fill out a form. Yeah. I send you an email later. I think now you, you can't just do a website to email, it's a website plus mobile apps, plus, you know, in real world interaction to text message, chat, phone, call Twitter, a whatever, you know, it's >>Like, it's like, they're playing checkers in web two and you're talking 3d chess. <laugh>, I mean, there's a level, there's a huge gap between what's coming. And this is kind of interesting because now you mentioned, you know, uh, machine learning and data, and AI is gonna factor into all this. You mentioned, uh, you know, rock set. One of your portfolios has under the hood, you know, open source and then use proprietary data and cloud. Okay. That's a configuration, that's an architecture, right? So architecture will be important in terms of how companies posture in this market, cuz MarTech is ripe for innovation because it's based on these old technologies, but there's tons of workflows, but you gotta have the data. Right. And so if I have the best journey map from a client that goes to a website, but then they go and they do something in the organic or somewhere else. If I don't have that, what good is it? It's like a blind spot. >>Correct. So I think you're seeing folks with the data BS, snowflake or data bricks, or an Amazon that S three say, Hey, come to my data cloud. Right. Which, you know, Snowflake's advertising, Amazon will say the data cloud is S3 because all your data exists there anyway. So you just, you know, live on S3 data. Bricks will say, S3 is great, but only use Amazon tools use data bricks. Right. And then, but on top of that, but then you had our SaaS companies like Oracle, Salesforce, whoever, and say, you know, use our qua Marketo, exact target, you know, application as a system record. And so I think you're gonna have a battle between, do I just work my data in S3 or where my data exists or gonna work my data, some other application, like a Marketo Ella cloud Z target, um, or, you know, it could be a Twilio segment, right. Was combination. So you'll have this battle between these, these, these giants in the cloud, easy, the castles, right. Versus, uh, the, the, the, the contenders or the, or the challengers as we call >>'em. Well, great. Always chat with the other. We always talk about castles in the cloud, which is your work that you guys put out, just an update on. So check out greylock.com. They have castles on the cloud, which is a great thesis on and a map by the way ecosystem. So you guys do a really good job props to Jerry and the team over at Greylock. Um, okay. Now I gotta ask kind of like the VC private equity sure. Market question, you know, evaluations. Uh, first of all, I think it's a great time to do a startup. So it's a good time to be in the VC business. I think the next two years, you're gonna find some nice gems, but also you gotta have that cleansing period. You got a lot of overvaluation. So what happened with the markets? So there's gonna be a lot of M and a. So the question is what are some of the things that you see as challenges for product teams in particular that might have that killer answer in MarTech, or might not have the runway if there's no cash, um, how do people partner in this modern era, cuz scale's a big deal, right? Mm-hmm <affirmative> you can measure everything. So you get the combination of a, a new kind of M and a market coming, a potential growth market for the right solution. Again, value's gotta be be there. What's your take on this market? >>I, I, I think you're right. Either you need runway, so cash to make it through, through this next, you know, two, three years, whatever you think the market Turmo is or two, you need scale, right? So if you're at a company of scale and you have enough data, you can probably succeed on your own. If not, if you're kind of in between or early to your point, either one focus, a narrower wedge, John, just like we say, just reduce the surface area. And next two years focus on solving one problem. Very, very well, or number two in this MarTech space, especially there's a lot of partnership and integration opportunities to create a complete solution together, to compete against kind of the incumbents. Right? So I think they're folks with the data, they're folks doing data, privacy, security, they're post focusing their workflow or marketing workflows. You're gonna see either one, um, some M and a, but I definitely can see a lot of Coopers in partnership. And so in the past, maybe you would say, I'm just raise another a hundred million dollars and do what you're doing today. You might say, look, instead of raising more money let's partner together or, or merge or find a solution. So I think people are gonna get creative. Yeah. Like said scarcity often is good. Yeah. I think forces a lot more focus and a lot more creativity. >>Yeah. That's a great point. I'm glad you brought that up up. Cause I didn't think you were gonna go there. I was gonna ask that biz dev activity is going to be really fundamental because runway combined with the fact that, Hey, you know, if you know, get real or you're gonna go under is a real issue. So now people become friends. They're like, okay, if we partner, um, it's clearly a good way to go if you can get there. So what advice would you give companies? Um, even most experienced, uh, founders and operators. This is a different market, right? It's a different kind of velocity, obviously architectural data. You mentioned some of those key things. What's the posture to partner. What's your advice? What's the combat man manual to kind of compete in this new biz dev world where some it's a make or break time, either get the funding, get the customers, which is how you get funding or you get a biz dev deal where you combine forces, uh, go to market together or not. What's your advice? >>I, I think that the combat manual is either you're partnering for one or two things, either one technology or two customers or sometimes both. So it would say which partnerships, youre doing for technology EG solution completers. Like you have, you know, this puzzle piece, I have this puzzle piece data and data privacy and let's work together. Um, or number two is like, who can help you with customers? And that's either a, I, they can be channel for you or, or vice versa or can share customers and you can actually go to market together and find customers jointly. So ideally you're partner for one, if not the other, sometimes both. And just figure out where in your life cycle do you need? Um, friends. >>Yeah. Great. My final question, Jerry, first of all, thanks for coming on and sharing your in insight as usual. Always. Awesome final question for the folks watching that are gonna be partnering and buying product and services from these startups. Um, there's a select few great ones here and obviously every other episode as well, and you've got a bunch you're investing in this, it's actually a good market for the ones that are lean companies that are lean and mean have value. And the cloud scale does provide that. So a lot of companies are getting it right, they're gonna break through. So they're clearly gonna be getting customers the buyer side, how should they be looking through the lens right now and looking at companies, what should they look for? Um, and they like to take chances with seeing that. So it's not so much, they gotta be vetted, but you know, how do they know the winners from the pretenders? >>You know, I, I think the customers are always smart. I think in the, in the, in the past in market market tech, especially they often had a budget to experiment with. I think you're looking now the customers, the buyer technologies are looking for a hard ROI, like a return on investment. And before think they might experiment more, but now they're saying, Hey, are you gonna help me save money or increase revenue or some hardcore metric that they care about? So I think, um, the startups that actually have a strong ROI, like save money or increased revenue and can like point empirically how they do that will, will, you know, rise to the top of, of the MarTech landscape. And customers will see that they're they're, the customers are smart, right? They're savvy buyers. They, they, they, they, they can smell good from bad and they're gonna see the strong >>ROI. Yeah. And the other thing too, I like to point out, I'd love to get your reaction real quick is a lot of the companies have DNA, any open source or they have some community track record where communities now, part of the vetting. I mean, are they real good people? >>Yeah. I, I think open stores, like you said, in the community in general, like especially all these communities that move on slack or discord or something else. Right. I think for sure, just going through all those forums, slack communities or discord communities, you can see what's a good product versus next versus bad. Don't go to like the other sites. These communities would tell you who's working. >>Well, we got a discord channel on the cube now had 14,000 members. Now it's down to six, losing people left and right. We need a moderator, um, to get on. If you know anyone on discord, anyone watching wants to volunteer to be the cube discord, moderator. Uh, we could use some help there. Love discord. Uh, Jerry. Great to see you. Thanks for coming on. What's new at Greylock. What's some of the things happening. Give a quick plug for the firm. When you guys working on, I know there's been some cool things happening, new investments, people moving. >>Yeah. Look we're we're Greylock partners, seed series a firm. I focus at enterprise software. I have a team with me that also does consumer investing as well as crypto investing like all firms. So, but we're we're seed series a occasionally later stage growth. So if you're interested, uh, FA me@jkontwitterorjgreylock.com. Thank you, John. >>Great stuff, Jerry. Thanks for coming on. This is the Cube's presentation of the, a startup showcase. MarTech is the series this time, emerging cloud scale customer experience where the integration and the data matters. This is season two, episode three of the ongoing series covering the hottest cloud startups from the ADWS ecosystem. Um, John farrier, thanks for watching.

>> Announcer: From theCUBE studios in Palo Alto in Boston, connecting with thought leaders all around the world, this is theCUBE Conversation. >> Hello everyone, welcome to this CUBE Conversation, I'm John Furrier, host of theCUBE I'm in the Palo Alto CUBE Studios here with the quarantine crew, doing the remote interviews during this time of COVID. Of course, we want to check in with all of our great esteemed guests and CUBE alumni. We're here with Jerry Chen, partner at Greylock. Jerry, great to see you, it's been a while. Hope you're sheltering in place, nice camera, nice set up you got there at home, thanks for coming on. >> Thanks, John. I set up all the cameras are just for you. Everybody needs their quarantine hobbies, and for me, I kind of dust off the audio visual playbook and set this up, just for theCUBE interviews. But it's good to see you. Glad you and the family are healthy and sane as well. >> Yeah, and same to you. Let's just jump into it, obviously, COVID-19 has caused the virtualization trend, virtual everything. You're no stranger to virtualization, and VMware back in the day really changed the game on server virtualization, but the whole world's becoming virtual. And it's very interesting because now people are feeling, but we in the industry have been talking about inside the ropes for a long time, which is, the future is there, it's going to be about interactions online, software, cloud scale, these things just got accelerated, and the disruption, the change of behavior, Zoom fatigue, Webexing, all this stuff that's happening, people are kind of like, "Wow! This is the future." This is a real impact, and it's mainstream, everyone's feeling about business, to personal, your thoughts? >> Yeah, I think Satya Nadella at Microsoft had this quote recently that they've seen two decade's worth of digital acceleration and transformation in just two months, and I think what we've seen the past four months, John is all the kind of first order effects of virtualization events, not just infrastructure, but like virtualization meetings and people, telemedicine, telehealth, online education, delivery of food, all those trends are just accelerated. We're buying stuff on eCommerce, and Amazon, and Instacart before hand, that's just accelerated. We're moving towards virtualized events, online education, online healthcare, that's just accelerated. So I think we're seeing the first order effects of changing not only how we work, how we communicate, but how we shop, interact, and socialize, it compress two decades within two, three months. And so I think that's changing both how you and I interact and how we build relationships, also how companies interact with their customers, and how companies interact with employees. and it's been exciting time, because one, when there's disruption, there's opportunity, but two is giving guys like you and me a chance to kind of dust off or try new skills, and you and I are both figuring out how to exist and thrive in this role where we're now interacting in this virtualized world. >> And it's still the same game personal relationships. Content is now data. This is stuff that we've been preaching on theCUBE. You've been on many times talking about, I going to get your thoughts as a venture capitalist, whether you're making bets on the future for investments, you have a 10 year horizon, and roughly speaking average on VC deals, enterprises and customers who are building a cloud and data centers, they got to make new bets or double down on stuff they've been doing, or cancel stuff that they had going on, and refactoring. So I want to to get your thoughts on one, first on the VC side, how have you guys refactored your thinking, your meetings, and your bets? >> Yeah, so I would say, three areas, one is how we operate as a VC firm what's changed? Number two, I'll talk about what we're investing in what's good or bad, and thirdly is like, what I think changes for our portfolio companies and how startups think. So first and foremost obviously, we've gone all virtual too, with shelter-in-place, our entire team is now working remotely, working from home, but we're still open for business and we're looking to find new investments, we are investing aggressively right now, and we're just doing things over Zoom. And so we're either A, doing video calls as a partnership, or doing video calls with startups that we're meeting and founders, but I'll be honest, one thing I've done John, is I've turned off the screen more or less, I've done more phone calls because I find that a video call is great for the first or second meeting, but with a founder or executive you have relationship with, it's just really nice to actually, go on a virtual walk where me and the founder of both put AirPods or take the phone to walk outside and kind of have a conversation, that's a little of a higher bandwidth. So, I think how we're operating has changed a little bit, but to your point, is the same business, connecting with a person one-on-one, reading the market, reading the founder, and making a bet. So that hasn't changed. I think on the stuff we're investing in, like you said, all the trends around cloud and APIs and SaaS, that's accelerated. So all the trends around the new workplace, SaaS companies, collaboration, going cloud that's accelerated faster, so some of our companies like Cato Networks that does software defined, wide area networks plus cloud security that just accelerated there in this market called secure access serves edge. We've seen kind of a nice tailwind from that, more and more data is going to cloud so companies like Rockset, that's a database company that you had on theCUBE, they're going to see a benefit from that because more and more data is now in the cloud. Then finally for the founders we work with, the way to go to market, the way to sell like no one's flying around selling one-on-one anymore, you're not meeting a CSO, or the CIO over steak dinner, or you're not going to a conference anymore. So a lot of our companies are figuring out how to do more online sales, bottoms ups adoption, that could be an API, that could be open source, we're trying to find a couple more of our line of business entry to the company and sell that way, versus go to a conference or for one-on-one meeting. So it's interesting, everything's moved faster, but then this slight curve ball on how you connect with your customer has changed. And so what's the Darwin line, it's not the strongest that survives, but the most adaptable. So we're seeing the companies that founders that are most adaptable right now, they're going to thrive. >> It's interesting, we've always talked about from a tech standpoint with DevOps and cloud-native, integration or horizontally scalable has been that ethos of value creation, you've talked about moats in the past, but now it's more real life, is becoming immersed into software, and so I want to get your thoughts on this, and we have a phrase here in theCUBE team is that, every company will become a media company, that's something that we believe in, and you starting to see that people are doing more Zooms, doing more digital events, you mentioned some of the other things. Can you see any other examples where a company has to become blank? Because media is just one element of the new realities of life, right? You got to broadcast, and you got to share your stories and formats, that's media, is there other areas we're seeing, that things that weren't on the radar before with COVID, where companies have to become something like, every company will be blank? Fill in the blank. >> I would say, it's trite to say one, one, was every company is a data company, people have been saying that for a while, that's more true than ever. Number two, I'll be honest, every company now is a healthcare company, right? Because be it in health insurance for employees, the current pandemic is making the reality of both physical health, and emotional health, and mental health key for employees. And so if that was a top cost factor for hiring employees, this could be even more important going forward that every company is a health care company. And thirdly, like you said, every company becomes media company, I would say every company is also either one or two things, they're a Fintech company, because every company is now going online with their content. They wanting to create a one-to-one commercial relationship with a customer, right? That could be ads, could be transaction, could be selling something, so you're now doing business directly with your customer, so every company is a Fintech company, and I would say every company's now also, like you said, content company, right? It's the media creating, but also the data you're taking, the value you add on top of the data you're creating, and then how you share that back to your customer. So you as an enterprise company or a consumer company, you collect data from users, you're to use that data to improve your product, and this could be a SaaS offering, this could be an application, but then take that data through real time analytics, then make your product better and so because of that, if you're a data company, real time data, like our database company mentioned earlier, Rockset becomes more important. If you're a Fintech company, so all things around payments or commercial banking and relationship with your customer make sense. And if a you're a healthcare company because all your employees are now caring about healthcare, just thinking about how to make communication of healthcare with employees a lot more efficient, and a part of the reason why to work for theCUBE and work for a startup is important, so I think those three things are top of mind for all employees and all employers. I think things could change the next six or nine months, but right now I see those three being front and center. >> It's interesting. I wonder if you can add real estate company to that because if you look at the work from home, it's dynamic. >> Yeah >> I had a friend who was a fellow dad with my son's lacrosse team, he lives in Los Gatos, he's been involved in Google, Tesla, building up their facilities, and he had an interesting guest post on SiliconANGLE, and he was saying, it's not just give them some extra pay for their internet access, companies got to rethink the facilities question, right? Because do you pay rent for your employees? Do you provide the VPN, beyond VPN security, for instance? So again, you start to see these new opportunities or challenges, open up new thinking, this is going to be a wave of opportunity. >> Well, that virtualization between work and home has now been blurred like you said earlier, John and so if you're a technology company that enables remote access or distribute access, like Cato Networks when the portfolio comes and Greylock around our road office, home office, that is now how to right? So I had this conversation with Jason of Austin, askSpoke, one of our companies, there's like a mass of hierarchy for working out, and at the base of the mass of hierarchy is like good internet access, right? That's the how to, you need security, right? Because if you don't have secure access, you can't work, and then you have information management, knowledge management, how to communicate, right? And then collaboration, so, you have now this new hierarchy of what is required you to work in this new world, but also the tools and the technologies, be it secured access service edge like CATO or IT Helpdesk for all employees like askSpoke, both of those things become dial tone for any remote work. Just like videoconferencing, we couldn't do this in the same way, 10, 15 years ago, that's become kind of a must have, and so I think it'd be fascinating how we went from the office world where I gave you a laptop, or a computer, or a desk to this home office world, where maybe you now I have to pay for my fancy camera setup and my VPN. >> Well certainly you're getting good ROI on your setup and sure Greylock will take care of that plenty of dough big, billions of dollars under management. And by the way, must have hire things in our houses, ping and internet access, so we fight for that ping time, I got 12 I'm like what's going on? Who's gaming? We have to get the kids off of Twitch, and whatnot. but in all seriousness, this is what the reality is. So now for the average person out there, there's a lot of discussion around mental health, you mentioned taking it off the video conferencing and going for a walk, or just talking on the phone, this speaks to the humanization aspect of what's going on, mental health, social interaction, we're social creatures, collaboration has to be re-imagined. What's your view on all this? >> I think absolutely, look, humans are social creatures by nature, and I think part of the reason why I had this conversation with my founders early during COVID-19, that it's both a healthcare crisis. It's an economic crisis with all the million and millions of people unemployed, but it's also an emotional crisis because one, we're not connected to family, friends, and loved ones, and we're sheltering home with either ourselves or just a handful of people. And so we're trying to figure out ways to like, recreate social connections, and that's a phone call, it's a video call, it's Zoom dinners, it's Zoom dinners, the Zoom parties, is key. I think, going on socially just in walks is another thing to kind of like, play and experience things together. But my two cents is if you're a startup, right now, it can help connect people work-wise or socially, that's just going to be super critical for the new experience. And I think people are discovering new ways to use technology, so Zoom was never meant to be used the way it is today, I think that's amazing. I think how people think about voice video, and email, and chat are changing as well. So I'll finding new ways to like, play games online with my nieces, or communicate with them. And I think as an employer in these companies, like HR software, and how you like manage, and coach, and lead your employees is going to change as well. And so, you have this world where we're all in one building, and think about how you as a CEO, or as a leader now can actually coach, develop, and enable your employees across the world. >> I want to get your thoughts on cloud, we've had many conversations around cloud computing as to rise of AWS, I remember one it was a big Twitter conversation, I think about last year where what enabled Amazon and I think one of the things that came out of it was virtualization enabled them to have all these different servers. What do you see coming out of this virtualization of our lives with the COVID-19, as people start to figure out beyond the triage of stabilization, and as they get foundationally set up in COVID, coming out of it, companies and people have to have a growth strategy, whether it's life or business, people want to come out of this on the upside, whether it's emotional or with their business, what do you see being enabled? What needs to be in place? What kind of scale? What kind of environment? Because this is where I think the entrepreneurs are really going to sharpen their energy on their creativities looking at the expectations and experience needed coming out of this, it may look completely different than what we were talking about a year ago. What's your thoughts? >> Well, I think individually, people can use this time to prove their skills in different ways. So I think as an employee, as CEO, as a founder, you take the time to like invest in new skills, and that could be, "Hey, how do our community collaborate and manage my team remotely?" So I think CEOs and founders that can understand how to motivate, educate, train their employees in this new world, well, those are skills going forward. So communication has always been a great skill John, for any leader, any founder, it's 10X more important in this new virtualized work role, communication, motivation, and leading people over remote work is going to be a new skill that people have. Managing remote teams, managing fully distributed teams or half distributed, half headquarters, so understanding how to organize and lead your team in this kind of half in the office half out of the office role, that's going to be a challenge as well. So any tools, technology and tips there, but I think in terms of the founders that can now hire employees, find customers, sell customers, and manage a distributed team, those three things in this new world, even post COVID-19, we're not going back to the way we were, so the ability to actually use skills around email, creating content, Slack, Zoom, video chat, online conferences, what was that? "Video Killed the Radio Star", the first MTV Video. So, COVID-19, and Zoom, and video collaboration, what's that do to the old skills or the old founders? And what do they enable? So just like TV replaced radio as a medium, and now this virtualized world is going to replace kind of the medium we had beforehand, so, there'll be new generation of founders and investors coming out of this generation that would be for the next 10, 15 years, and I'm excited to be part of that. >> Yeah, and it's super big opportunity, because you have these kind of medium changes, new protocols get developed, new responsibilities and roles emerge, value creation capture, equations change, right? So you're looking at things like online events, for instance, they don't happen anymore, and even when they do come back they'll probably be hybrid anyway. So you got virtual, hybrid, public it sounds like a cloud play to me, public events, hybrid events, and private events, I guess. >> Yeah, virtual private events, but the same thing holds, just like cloud internet increased the reach, right? So all of a sudden, you can reach a bigger audience than just radio, TV, or the newspaper. Now you have these virtualized events like say private events, public events, hybrid events, you as a company or a media property, like theCUBE can now reach a larger audience, right? It's global, you don't have to be there in person, you're going to have the remote audience as a first class citizen, now more than ever, it's just like the internet replacing newspaper and print, people really care about print and newspaper, but really the reach online is always a magnitude larger than print, so all of a sudden you thought more about the print, so the online audience more than print audience. So now going forward, you're going to think about the virtual audience that's remote versus the physical audience. And so you're going to have to create experiences that are their world class or both properties. So just like the cloud, you think about the big three cloud providers, private cloud, as a technology company, you think about all three venues, all three infrastructures as a first class citizen. It's not going to be all one cloud, it's not all going to be one note, if you will. So it forces everyone to think, not just kind of one path, but multiple paths, so like classic problems a lot of founders think, okay, I'm going to do an enterprise private cloud strategy only or I'm going to do a cloud only SaaS strategy. Now founders of this do both the same time, I got to address the private cloud on premise business at the same time as the cloud business, and not just one cloud, three or four clouds around the world. So it forces founders to be able to do more things at one time and the ability for a company to attack multiple venues or multiple territories at the same time, they'll be successful. And the days where I can just do one cloud or one venue, or one audience, those are gone, and so, folks like yourself, John, and what you've built here at theCUBE with everyone else, they can reach multiple audiences at the same time, that's going to be very powerful. >> And we're going to be marketing and doing a lot more online events, like you said, it's going to be easier to tap into our 7000 plus alumni to get people together to create great content. And again, content value to remote audience is interesting. So that shifts into the conversation that everyone talks about the remote worker. Well, what about the remote customer, the remote prospects? So this is going to change how companies have to be change of behaviors. And it's going to be driven by developers, because it's not like one app can solve it, 'cause you got to integrate, you got to have some integration points. So this is the question, are we moving away from that monolithic SaaS app? Or is it going to be some SaaS apps that need to integrate with others? Will there be an abstraction layer of innovation around? Because at the end of the day, these new workloads and new apps going to be built. If you're going to run an event, if I'm a SAP or a big company, I'm not going to rely or may not want to rely on a vendor. In fact, the CEO of SAP said, 'cause their site crashed for their event, "I'm not going to rely on a third party to run my business event." 'Cause their business model is the event, not just a supplier selection for a SaaS app. So interesting kind of new surge of online activity might tip the scales for the supplier side. >> I think you're right John, I think because now the, just like the IT technology is now your business, you're going to basically do one or two things, one, vet the IT technology provider that much higher or harder. But number two to your point, I think the way you sell and you reach companies is going to be through developers and yes, you're going to have these large monolithic SaaS apps before, but almost every SaaS app now has APIs for integration, and so to your point, is that integration and the ability to have multiple companies work together, and share data, and collaborate, that's going to be more important. And so really at Greylock and myself, I've been investing in developer-led technologies and developer-led adoption, or API, or open source-led adoption, for seven plus years now. And the truth of matter is, that's going to be even more powerful going forward. Nassim Taleb would say that's anti-fragile, right? So having one giant app is fragile, but having a bunch of small apps, or a bunch of APIs, or a bunch of developers using your open source technology, or using your API technology to build an application, that's anti-fragile, because at the end of the day, that's going to be more reliable for your customer than a single point of failure, which can be one giant application. So all the big apps like Salesforce, have now other platforms, right? They have APIs, they have extensibility, they understand that there's a long fat tail of solutions needed to build. And all the new startups are doing open source, or API-led adoption 'cause they understand that the fastest route to create value for the customer, is also the most robust technology stack that a customer can build upon. I think that's super insightful, in fact, that is, I think so compelling, because if you think about it, that's the formula for great investments from a startup standpoint. But now, because of COVID, you said, everything's been pulled forward and accelerated at the same time, there's a collision, not all the enterprises are that strong, they're not that developer-led. So I think, to the point about acceleration, now, the enterprises, and we've seen pockets of this with cybersecurity where they have their own, in-house teams doing a variety of different development. The customers have to be developer-led, because that's where the value is, so they have to have a supplier with the right stack and integration frameworks. Now, the customers who haven't really been developer-led, have to be developer-led, what's your take on that? >> Absolutely true. 20 years ago, the CIO of a company that used to be the monopoly supplier technology for the company, they decided what hardware to use, what servers, what stores to use, what applications to buy. And then all of a sudden, like Amazon came around and said, "Well, look, here's a set of APIs, go build what you want." And so the competition for kind of like the centralized decision making became Amazon. And guess what? CIOs reacted, they got better, they got smarter, and those that embrace kind of like an API developer-led adoption, became the CIOs you wanted to have in the company. So I think, CIOs in this cloud mobile era have adopted that philosophy that, look, my job now as the CIO is to enable my developers, my employees, which really the assets of the company is the people, to have the right tools. So you're asked a bunch of cloud APIs, like Rockset or whatever for data, or here's a bunch of resources, or open source technologies for you to pull. So like I invested in a company recently called Chronosphere, it's an open source technology around metrics and monitoring. So, "Hey, use this open source time series database for monitoring your cloud and build upon that," and they're not going to say, "We're going to pick one large vendor that's monolithic," we're going to say, "Here's an open source tech company or a cloud API, go build upon that." And the companies that are embracing that philosophy of API-led or developer-led, John, they're going to be far ahead the better CIOs, the better companies, because the rate of digital adoption has just gone exponential, so we were on this super fast path already, and with quarantine in COVID, we've accelerated all that digital transformation, so every brick-and-mortar retailer now has to be eCommerce retailer. So they're making a slow digital transformation to go from brick-and-mortar stores to online stores. Now like brick-and-mortar retail is pretty much not happening, and probably won't come back to the same levels for a while, they need to accelerate their move towards digital transformation, right? >> And IT certainly exposes the people who haven't really made those investments, because literally action and the mandate, now take action, make those changes, totally want to dig into this developer-led vision, because I think that's very real. And the new decision is going to be made on what to do. I'm happy to see the DevOps thinking, the agile, speed become the table stakes. So with that, this week, Google is having their nine-week digital event of 200 plus sessions, essentially, an asynchronous event, it's going to be sprinkled out, they've kind of pretty much released the videos, most of them today. Over the next eight, nine weeks, you're going to see a lot of videos. Google, one of the big three got AWS, Azure, Google, what's your assessment of the horses on the track relative to the cloud? >> I've been talking about this for seven, eight, nine years, I first met it, like in the first or second Amazon reinvent and what was the forecast? And we said, well, it's not a winner take all, but right now, it's a winner take most. Amazon's clearly the market share leader, Azure coming up quickly behind the enterprise, Google's a third but they're doing some smart things around technology. Google announced a bunch of things today, which I think are very smart. So for example, they announced BigQuery Omni, which is BigQuery that's in query, their kind of a data warehouse, also query data and private cloud Azure or Amazon. And so strategically, if you're the number three player, you're going to push a multi-cloud agenda with BigQuery Omni, or Google Anthos, which is kind of a multi-cloud platform. And for Google, I think is the right strategy. I also think it's the right strategy for most customers to be multi-cloud, because you can't be dependent upon, a single point of failure in your applications. You can't be dependent on a single cloud as well. So I think multi-cloud is probably the direction we're headed as cloud matures. And I think Google's making a bunch of the right choices around embracing multi-cloud, and today they made that choice with BigQuery Omni, and so I think they're playing catch up but they're playing that game. I think Amazon's clue is still in the lead and still it blows my mind, and it's continuing to impress me what they've done over the past 10 years in terms of improving the cloud offering and the cloud services up and down the stack, and I think the past five, six years, what Azure has done, has been super impressive in terms of, Microsoft embracing, open source embracing, cloud as an ethos against their legacy business of operating systems and servers on premise, they've done a great job of embracing the next generation. But I do think, looking around the corner this new developer-led mindset is going to matter, right? So the cloud tomorrow will be APIs, like Stripe for payments, Twilio for communication. So I see the next evolution not just being VMs and containers, but also a bunch of cloud services around data, security, and privacy. And the cloud vendors can build this next generation of database APIs, or privacy APIs, security APIs, that they're going to be in the catbird seat for the next 10 years of applications are going to be built. >> And it'll be interesting to your developer-led position, our conversation around that, if the developer is going to be leading, is it going to be an abstraction layer across multiple clouds? Or do I have to have my Google developers, and my Amazon developers, and my Azure developers? How do you see that playing out? Because I do believe developer-led is the way, the question is, how do you avoid forking resources, right? So you might want to have an (mumbles) I get that, but if I'm going to go double down on say, a cloud, I'm going to go deep, I'm going to hire developers. >> It's interesting, history suggests you have multiple teams remember, we used to have a Unix team or a Sun team inside companies, right? You had a Windows team, you had a kind of a Solaris and Linux team, and there's a Microsoft team, and a non-Microsoft team, in most companies and they didn't really work well together and they had kind of two groups in most companies. I think that was an okay way to get started, but ultimately, to your point, that was not cost effective at all, it was defeating, you see now you had to like have to rethink it, what was my data backup strategy? Okay, I have a Windows backup strategy, and a Unix Solaris backup strategy. So I think we're not going to make the same mistake again, right? I think what will happen, we'll going to have multiple clouds, Amazon, Google, Azure, and then on premise private cloud, so call it, three, four, or five clouds. And then you're going to have a set of tools that can abstract away, not 100% of the clouds, but I think the best developer tools, the best APIs will be multi-cloud. So I can get 80% or 90% of what I want to be done through this developer-led layer of APIs, be it databases or analytics. And then, 10 to 20% of the code, you can write will be able to take care of what's unique to Amazon, what's unique to Azure, what's unique to Google or what's unique to your own private cloud. But I think we're seeing a layer of technology and that's true to all the startups. With back and true to all the startups I see that lets you get most of the way done with a single platform, seamlessly AI technologies, and that's what customers want, right? They don't want to create modal fiefdoms, they want-- >> They want choice. The want choice, but the reality is they don't always get it. I want to go through a throwback to 2010 when Paul Maritz, head of the VMware our first CUBE gig, he said, there's a hardened top. Okay, the hardened top was, you don't worry about what's underneath the top, we're just going to focus on top of the stack that was classic kind of, the stack would develop and you'd had standardization. You mentioned you had Windows teams and Unix teams, but also you could argue that, back then you had Cisco and Wellfleet vendors, but you didn't have two teams of routers, you had one standard that ran the remote interoperability, and OSPF routing, or whatever you had going on, so you had some standardization, how do you view that? Because you want some standardization to have the interoperability, the SLAs and the security, at the same time you want to have flexibility, kind of above what may be called a hardened top, is there a hardened top in multi-cloud? >> I'd say hard top doesn't exist in same way. I think back in the day, you had proprietary technologies, operating systems and firmware, right? So windows was closed, a lot of the network operating systems were closed source. Now you can't get away with that. So you have open source technologies today and public APIs. And so the pressure of both one, competition, two, public APIs that people can read, copy, adjust, three, open source, and it's just customer demand not to be locked into a hard top anymore, that's largely going to go away. So I think most of the major vendors success will try to kind of more or less lock you in and keep you stuck on their platform, their technology, and that's fine, right? Every successful company should be able to do that. But I think the ability to lock you in through proprietary software or operating systems, that's not going to happen anymore. I see through cloud and open source, what we've seen is kind of interoperability, and flexibility is the default, if you can't meet those needs, customers will go other ways. There'll be proprietary technologies, proprietary extensions along the way, but 60, 70% of what you want is going to be compatible with most technologies and most clouds. If you're not going to offer choice and freedom to our customers, they'll go elsewhere. If you don't offer a flexible solution, John, someone else will, and the customers will choose a more flexible solution. >> I would agree with you. Outside of latency, which is laws of physics, value is the lock in, if you're creating value, that's really what the customers want, they get to capture that value. Well, Jerry, great to have you on. I love the new setup. We're going to have to make this more of it. We can bring you in on the podcast when we get Zooms over the weekend, maybe put a panel together. Let's get Carl Eschenbach some VMware alarms to come on, give the perspective, what's going on. And I thank you for taking the time and great to see that you're healthy and doing well. Thanks. >> Me too. Thanks, john. Anytime, I love to be on theCUBE, so I look forward to my next trip. >> All right, Jerry Chen, great CUBE alumni, our first interview over nine years ago, he brought that up. That was at the second reinvent, boy has the world changed, and it's only going to accelerate even faster. Everything's changing new bets are being made, decisions have to be evolving quickly and faster. If you're not fast, you will be in the pile of dead companies and not making it. So, Jerry Chen breaking it down as venture capitalist for Greylock. I'm John Furrier with theCUBE. Thanks for watching. (soft music)

>> Narrator: Live from Las Vegas, it's theCUBE covering AWS reInvent 2019. Brought to you by Amazon Web Services and Intel along with it's Ecosystem partners. >> Well, welcome back, everyone theCUBE's live coverage in Las Vegas for AWS reInvent. It's theCUBE's 10th year of operations, it's our seventh AWS reInvent and every year, it gets better and better and every year, we've had theCUBE at reInvent, Jerry Chen has been on as a guest. He's a VIP, Jerry Chen, now a general partner at Greylock Tier One, one of the leading global Venture capitals at Silicon Valley. Jerry, you've been on the journey with us the whole time. >> I guess I'm your good luck charm. >> (laughs) Well, keep it going. Keep on changing the game. So, thanks for coming on. >> Jerry: Thanks for having me. >> So, now that you're a seasoned partner now at Greylock. You got a lot of investments under your belt. How's it going? >> It's great, I mean look, every single year, I look around the landscape thinking, "What else could be coming? "What if we surprise this year?" What's the new trends? What both macro-trends, also company trends, like, who's going to buy who, who's going to go public? Every year, it just gets busier and busier and bigger and bigger. >> All these new categories are emerging with this new architecture. I call it Cloud 2.0, maybe next gen Cloud, whatever you want to call it, it's clear visibility now into the fact that DevOps is working, Cloud operations, large scale operations with Cloud is certainly a great value proposition. You're seeing now multiple databases, pick the tool, I think Jassy got that right in his keynote, I believe that, but now the data equation comes over the top. So, you got DevOps infrastructure as code, you got data now looking like it's going to go down that same path of data as code where developers don't have to deal with all the different nuances of how data's stored, how it's handled, where is it, warm or cold or at glacier. So, developers still don't have that yet today. Seems to be an area of Amazon. What's your take on all this? >> I think you saw, so what drove DevOps? Speed, right? It's basically how developers shows you operations, merging of two groups. So, we're seeing the same trend DataOps, right? How data engineers and data scientists can now have the same speeds developers had for the past 10 years, DataOps. So, A, what does that mean? Give me the menu of what I want like, Goldilocks, too big, too small, just right. Too hot, too cold, just right. Like, give me the storage tier, the data tier, the size I want, the temperature I want and the speed I want. So, you're seeing DataOps give the same kind of Goldilocks treatment as developers. >> And on terms of like Cloud evolution again, you've seen the movie from the beginning at VM where now through Amazon, seventh year. What jumps out at you, what do you look at as squinting through the trend lines and the fashion of the features, it still seems to be the same old game, compute memory storage and software. >> Well I mean, compute memory storage, there's an atomic building blocks of a compute, right? So, regardless of services these high level frameworks, deep down, you still have compute networking and storage. So, that's the building blocks but I think we're seeing 10th year of reInvent this kind of, it's not one size fits all but this really big fat long tail, small instances, micro-instances, server lists, big instances for like jumbo VMs, bare metal, right? So, you're seeing not one architecture but folks can kind of pick and choose buy compute by the drip, the drop or buy compute by the whole VM or whole server full. >> And a lot of people are like, the builders love that. Amazon owns the builder market. I mean, if anyone who's doing a startup, they pretty much start on Amazon. It's the most robust, you pick your tools, you build, but Steve Malaney was just on before us says, "Enterprise don't want power tools, "they're going to cut their hand off." (laughs) Right so, Microsoft's been winning with this approach of consumable Cloud and it's a nice card to play because they're not yet there with capabilities with Amazon, so it's a good call, they got an Enterprise sales force. Microsoft playing a different game than AWS because they have to. >> Sure I mean, what's football now, you have a running game, you need a passing game, right? So, if you can't beat them with the running game, you go with a passing game and so, Amazon has kind of like the fundamental building blocks or power tools for the builders. There's a large segment of population out there that don't want that level of building blocks but they want us a little bit more prescriptive. Microsoft's been around Enterprise for many many years, they understand prescriptive tools and architectures. So, you're going to become a little bit more prefab, if you will. Here's how you can actually construct the right application, ML apps, AI apps, et cetera. Let me give you the building blocks at a higher level abstraction. >> So, I want to get your take on value creations. >> Jerry: Sure. >> So, if it's still early (mumbles), it's took a lot more growth, you start to see Jassy even admit that in his keynotes that he said quote, "There are two types "of developers and customers. "People want the building blocks "or people who want solutions." Or prefab or some sort of more consumable. >> More prescriptive, yeah. >> So, I think Amazon's going to start going that way but that being said, there's still opportunities for startups. You're an investor, you invest in startups. Where do you see opportunities? If you're looking at the startup landscape, what is the playbook? How should you advise startups? Because ya know, have the best team or whatever but you look at Amazon, it's like, okay, they got large scale. >> Jerry: Yeah. >> I'm going to be a little nervous. Are they going to eat my lunch? Do I take advantage of them? Do I draft off them? There are wide spaces as vertical market's exploding that are available. What's your view on how startups should attack the wealth creation opportunity value creation? >> There, I mean, Amazon's creating a new market, right? So, you look at their list of many services. There's just like 175 services out there, which is basically too many for any one company to win every single service. So, but you look at that menu of services, each one of those services themselves can be a startup or a collection of services can be a startup. So, I look at that as a roadmap for opportunity of companies can actually go in and create value around AI, around data, around security, around observability because Amazon's not going to naturally win all of those markets. What they do have is distribution, right? They have a lot of developer mind share. So, if you're a startup, you play one or three themes. So like, one is how do I pick one area and go deep for IP, right? Like, cheaper, better, faster, own some IP and though, they're going to execute better and that's doable over and over again in different markets. Number two is, we talked about this before, there's not going to be a one Cloud wins all, Amazon's clearly in the lead, they have won most of the Cloud, so far, but it'll be a multi-Cloud world, it'll be On Premise world. So, how do I play a multi-Cloud world, is another angle, so, go deep in IP, go multi-Cloud. Number three is this end to end solution, kind of prescriptive. Amazon can get you 80% of the way there, 70% of the way there but if you're like, an AI developer, you're a CMO, you're a marketing developer, you kind of want this end to end solution. So, how can I put together a full suite of tools from beginning to end that can give me a product that's a better experience. So, either I have something that's a deeper IP play a seam between multiple Clouds or give it end to end solutions around a problem and solve that one problem for our customer. >> And in most cases, the underlay is Amazon or Azure. >> Or Google or Alley Cloud or On Premises. Not going to wait any time soon, right? And so, how do I create a single fabric, if you will that looks similar? >> I want to riff with you in real time here on theCUBE around data. So, data scale is obviously a big discussion that's starting to happen now, data tsunami, we've heard that for years. So, there's two scale benefits, horizontal scale with data and then vertical specialism, vertical scale or ya know, using AI machine learning in apps, having data, so, how do you view that? What's your reaction to the notion of creating the horizontal scale value and vertical specialism value? >> Both are a great place for startups, right? They're not mutually exclusive but I think if you go horizontal, the amount of data being created by your applications, your infrastructure, your sensors, time stories data, ridiculously large amount, right? And that's not going away any time soon. I recently did investment in ChronoSphere, 'cause you guys covered over at CUBEcon a few weeks ago, that's talking about metrics and observability data, time stories data. So, they're going to handle that horizontal amount of data, petabytes and petabytes, how can we quarry this quickly, deeply with a lot of insight? That's one play, right? Cheaper, better, faster at scale. The next play, like you said, is vertical. It's how do I own data or slice the data with more contacts than I know I was going to have? We talked about the virtual cycle of data, right? Just the system of intelligence, as well. If I own a set of data, be it healthcare, government or self-driving car data, that no one else has, I can build a solution end to end and go deep and so either pick a lane or pick a geography, you can go either way. It's hard to do both, though. >> It's hard for startup. >> For a startup. >> Any big company. >> Very few companies can do two things well, startups especially, succeed by doing one thing very well. >> I think my observation is that I think looking at Amazon, is that they want the horizontal and they're leaving offers on the table for our startups, the vertical. >> Yeah, if you look at their strategy, the lower level Amazon gets, the more open-sourced, the more ubiquitous you try to be for containers, server lists, networking, S3, basic sub straits, so, horizontal horizontal, low price. As you get higher up from like, deep mind like, AI technologies, perception, prediction, they're getting a little bit more specialized, right? As you see these solutions around retail, healthcare, voice, so, the higher up in the stack, they can build more narrow solutions because like any startup of any product, you need the right wedge. What's the right wedge in the customers? At the base level of developers, building blocks, ubiquitous. For solutions marketing, healthcare, financial services, retail, how do I find a fine point wedge? >> So, the old Venture business was all enamored with consumers over the years and then, maybe four years ago, Enterprise got hot. We were lowly Enterprise guys where no one-- >> Enterprise has been hot forever in my mind, John but maybe-- >> Well, first of all, we've been hot on Enterprise, we love Enterprise but then all of a sudden, it just seemed like, oh my God, people had an awakening like, and there's real value to be had. The IT spend has been trillions and the stats are roughly 20 or so percent, yet to move to the Cloud or this new next gen architecture that you're investing companies in. So, a big market... that's an investment thesis. So, a huge enterprise market, Steve Malaney of Aviation called it a thousand foot wave. So, there's going to be a massive enterprise money... big bag of money on the table. (laughs) A lot of re-transformations, lot of reborn on the Cloud, lot of action. What's your take on that? Do you see it the same way because look how they're getting in big time, Goldman Sachs on stage here. It's a lot of cash. How do you think it's going to be deployed and who's going to be fighting for it? >> Well, I think, we talked about this in the past. When you look to make an investment, as a startup founder or as a VC, you want to pick a wave bigger than you, bigger than your competitors. Right so, on the consumer side, ya know, the classic example, your Instagram fighting Facebook and photo sharing, you pick the mobile first wave, iPhone wave, right, the first mobile native photo sharing. If you're fighting Enterprise infrastructure, you pick the Cloud data wave, right? You pick the big data wave, you pick the AI waves. So, first as a founder startup, I'm looking for these macro-waves that I see not going away any time soon. So, moving from BaaS data to streaming real time data. That's a wave that's happening, that's inevitable. Dollars are floating from slower BaaS data bases to streaming real time analytics. So, Rocksett, one of the investors we talked about, they're riding that wave from going BaaS to real time, how to do analytics and sequel on real time data. Likewise, time servers, you're going from like, ya know, BaaS data, slow data to massive amounts of time storage data, Chronosphere, playing that wave. So, I think you have to look for these macro-waves of Cloud, which anyone knows but then, you pick these small wavelettes, if that's a word, like a wavelettes or a smaller wave within a wave that says, "Okay, I'm going to "pick this one trend." Ride it as a startup, ride it as an investor and because that's going to be more powerful than my competitors. >> And then, get inside the wave or inside the tornado, whatever metaphor. >> We're going to torch the metaphors but yeah, ride that wave. >> All right, Jerry, great to have you on. Seven years of CUBE action. Great to have you on, congratulations, you're VIP, you've been with us the whole time. >> Congratulations to you, theCUBE, the entire staff here. It's amazing to watch your business grow in the past seven years, as well. >> And we soft launch our CUBE 365, search it, it's on Amazon's marketplace. >> Jerry: Amazing. >> SaaS, our first SaaS offering. >> I love it, I mean-- >> John: No Venture funding. (laughs) Ya know, we're going to be out there. Ya know, maybe let you in on the deal. >> But now, like you broadcast the deal to the rest of the market. >> (laughs) Jerry, great to have you on. Again, great to watch your career at Greylock. Always happy to have ya on, great commentary, awesome time, Jerry Chen, Venture partner, general partner of Greylock. So keep coverage, breaking down the commentary, extracting the signal from the noise here at reInvent 2019, I'm John Furrier, back with more after this short break. (energetic electronic music)

(upbeat music) >> Announcer: Live from San Francisco, celebrating 10 years of high-tech coverage, it's theCUBE, covering VMworld 2019. Brought to you by VMware and its ecosystem partners. >> Welcome back to theCUBE. Two sets, wall-to-wall coverage, our 10th year. We actually call this one the Valley set, over on the other side, it's in the middle of a meadow, and this was in the valley. I'm Stu Miniman. My cohost for this segment is, of course, John Furrier, the founder of SiliconANGLE. And joining us, the quintessential Valley guest that we have, Jerry Chen. Long time participant in the program, climbing up the leaderboard here of theCUBE Times at VMworld. Jerry, thank you so much for joining us. >> Stu, John, thanks for having me back. >> All right, so we knew you back when you worked for VMware. >> Jerry: Right. >> You're now a partner at Greylock. We watched some of your amazing startups, we've had many of them on our program. Just a little bit going on in your world this day, maybe we'll start there. >> Sure, it amazes me, both being at VMworld 10 years since you guys started covering. For me, I joined VMware back in 2003. So I was at the first Vmworld, through every single one of them, and seeing this ecosystem reinvent itself, and juxtapose that with every other conference at Moscone. So Dreamforce, Oracle OpenWorld, VMworld. And I would say five years ago, no one would have thought Dreamforce itself, or Salesforce as an ecosystem big enough for investors. But yes, now they can invest in startups. All they do is sell to the Salesforce ecosystem. You can always invest in a startup. All they sell to is the VMware ecosystem. And for sure, when, you and I, three of us go to Amazon or an event, that ecosystem just continues to grow exponentially year over year. >> And this some of the highlights of Datadog, we were talking before we came on camera. They always had a big booth, they bet on the AWS ecosystem, not a lot of Datadog here, but monitoring turns into observability, a key component, which basically was a white space. I mean, monitoring was boring. A little sector, but because of the nature of the data security auditing, this has become kind of a killer category. >> I think last week you saw SignalFX get acquired by Splunk, which is another huge enterprise company, and Datadog filed their S-1. No one thought monitoring would be a big enough market to support multiple billion plus companies, and what we've learned is making a bet on just cloud-native companies like Datadog did, purely in the Amazon Ecosystem, was a great bet because they've grown super fast, and that market turned out to be very big. In addition, it could be Splunk, and they could bet on logging for mostly on-premise companies. That turned out to be a large market. So I think five, 10 years ago, no one thought that these markets would be so big and so gigantic. The cloud itself, you can have a multi-billion dollar company like Datadog purely on a cloud-native application and cloud-native companies, if you will. >> You know, it's interesting, you're a VC and the enterprise specialist at Greylock. Consumer used to be all the rage in venture. "Oh, we're going to consumer against Facebook," Facebook breaks democracy, all kinds of problems. Being regulated. But enterprise became really hot with the cloud, and then you have an interesting dynamic. Now a thousand flowers are blooming on the startup side, so yes, there's a lot of action in startups, but the buyers of startups and the IPO markets is where the liquidity happens, which you care about, right? So now you have liquidity options for IPO for fast-growing flit scalers as you guys call it, and then the M and A market are buying the companies. So I got to ask you, with seeing Splunk as a great example, where they own the log market, log files, bring SignalFX in, former VMware guys and Facebook guys, comes in, they add some servability piece to it. Splunk's got more power now because of the acquisition. It's not just token acquisition. This is the market, product market slash M and A market. What's your thoughts on that? Because that's a key exit opportunity, and the numbers are pretty sizable when you think about it. >> I think just going back to the opportunity, the market's so big that you have multiple multi-billion dollar companies, so like Splunk's a huge company, great company. We're investors in a company called Sumo Logic. That's going to also be a successful company, and also a big-- >> John: And filed for IPO. >> And a big company that's OZA, Amazon, and Vmworld. So I think what you have here is each of these markets are monitoring, APM, the log, infrastructure, are turning out to be multi multi-billion, and larger than we anticipated. So I think before, to your analogy in the consumer, we always knew consumer markets had huge TAMs. Like how many billion in people are on Facebook? How many billion people are on Twitter? What we're learning now is the market and the TAM for these enterprise software companies, be it SAAS, be it LOG, be it Metrics, be it security, those TAMs are actually bigger than we thought beforehand as well. >> And the driver of that is what? Cloud, transformation, just replatforming, modernization? The businesses are businesses still. >> I think the move to cloud is accelerate, I think your last line, "businesses are businesses," is what's key. Like every business now is being touched by software. They all got to go cloud so I'm an investor in a company called Blend that does mortgage software. So the entire financial services industry, from mortgages to car loans and consumer lending, that's all going digital. That's all going online. Jobs that were like mortgage brokers are going to be an app on your phone now. So finance, retail, healthcare, construction, so all these markets now are going to the cloud, going digital, so these TAMs are expanding exponentially. >> Yeah, Jerry, want to get your take on the ecosystem. You know, we look at VMware, they built a big ecosystem, the end user computing space, you know. You've coined the term Virtual Desktop Infrastructure, from that environment there was an ecosystem around there. I see VMware at a lot of shows, and they have a good presence there, and there's some overlap between the public cloud space. Like when I go to this show, and I walk through the expo hall, oh my gosh. Data protection is everywhere, and all of those companies are at a all of the cloud environment, but do you see a transition from, you know, where VMware is in kind of the cloud-native space? Is there a lot of overlap, or what's your thinking on those kind of dynamics? >> I think all above. I think VMware at Vwworld, and like all these tech companies are constantly reinventing themselves and expanding. So you have, as a VC, say it's this company I'm looking at, when it's two individuals, and a dog, and PowerPoint. Is it a feature, is it a product, or is it a company? It's a feature, it's okay. You know, it's probably not worth the investment, but it's worthwhile. It'll get acquired for something. Is it a product? Some companies are just one killer product, right? And you can ride that product for the arc of the company. But then some startups turn out be companies, multi-product companies. And there always have one or two great products, and then you start adding new things as the market evolves, and VMware has done that. And so, as a result of adding server virtualization, desktop virtualization, Cloud Foundry which I helped build, out in the Kubernetes stuff. So they're adding multiple products to their company. I think the great companies can do that. Look at Amazon. They keep launching 10 new products every single month. Microsoft has done a great job reinventing themselves. So I think the great companies can reinvent, but not transform, they just add to what they have, and just to be a multi-product family. >> Stu: All right, so you mentioned Cloud Foundry. >> Yeah. >> Pivotal, of course, is now back in the mothership where it started there. When Cloud Foundry first started it was, "Well, we're not going to take the hypervisor "and put it all of these places." We needed a slightly different footprint. Well, five years later, we're talking about Kubernetes is going to be baked into Vsphere, and Vsphere is going to be a main piece of VMware's cloud-native strategy. Has the market changed or some of those technology pieces, you know, still a challenge? What's your take there? >> You know, it's a great question because I think what we're seeing is there's never ever in technology as you guys know, on platforms, it's a zero-sum game. It's never always going to all mainframe, all client server, all VMs, all microservers, all Serverless, right? And I think we're seeing is it's also never going to be all Amazon, it's never going to be all Google, it's never going to be all Azure, right? I think we talked about early days, it's not a winner take all. It may be, you know, what one-third, two-thirds, or something, 25-40% market share, but it's not going to be all or nothing. And so we're seeing companies now have architectures on multiple clouds, multiple technologies, and so just like 10 years ago, you had a mainframe team, you had a Windows team, you had a Solaris team. Remember Sun and Spark? And a Linux team. Now you have a Google team, and Azure team, an Amazon team, and an on-prem team. And so you just had these different stacks evolve, and I think what's interesting to see is like, we've kind of had this swing of momentum around Docker, Containers, Kubernetes, Serverless, but at the same time you see a bunch of folks realize, okay, what's happening is I'm choosing how much I want to consume. Like an API, a container, or a whole VM, right? And people realizing, yes, maybe consuming the APIs is our right level of consumption, but quite frankly, Stu, John, buying whole VMs also what I want. So you see a bunch of companies say, I'm just going to build better monolithic applications around VMware, I'm going to build better microservices around Docker and Kubernetes, and then we'll use Serverless where I think I need to use Serverless. >> Yeah, that's a good point. One of the things we hear from customers we talk to, and there's two types of enterprise customers, at least in the enterprise infrastructure side, classic CIOs and then CISOs. Two different spectrums. CIOs, old, traditional, multi-vendor means a good thing, no lock in, I know how to deal with that world. CISOs, they want to build their own stacks, manage their own technology, then push APIs out to the suppliers, and rechange the supplier relationship because security is so important they're forced to the cutting edge. So I look at that a kind of canary in the coal mine, and want to get your thought on that, because we're seeing a trend where enterprises are building software. They're saying, hey, you know, I want a stack internally that we're going to do for a variety of different reasons, security or whatever, and that doesn't really blend well for the multi-cloud team approach, because not everyone can have three killer teams building stacks, so you're seeing some people saying, you know, I'm going to pick a cloud here and go all in on certain things, build the stack, and then have a backup cloud there. And then some CIOs say, hey, you know what? I want all the cloud guys in there negotiating their best price maybe, or whatever. >> I think it's great nuance you pointed out. Even just like we had a Windows team and a Linux team, you still had a single database team that ran across both, or storage teams are ran across both. So I think the nuance here is certain parts of the stack should be Azure, Amazon, VMware. Certain parts of the stack should be, I think that the ultimate expression is just an API with service errors. So one of the companies you guys are familiar with, Roxette, it's a search and Serverless analytics company. It's basically an API in the cloud, multi-cloud, to do search and analytics. And just like you had a database team that's independent across all these stacks, for certain parts of the architecture, you're going to want something like Roxette, that's going to be independent of the architecture stacks. And so it's not all isolated, it's not siloed, it's not all horizontal, depending on the part of the stack, you're going to either want a horizontal cross-cloud solution, or a team that's going to go deep on one. >> So it's really a contextual decision based on what the environment looks like, or business. >> And there's certain areas of technology that we know from history that lends themself to either full stacks versus horizontals. Just like I said, there was a storage team and a database team, right? That's Oracle, or something that ran across Windows and Linux and Sun, you're going to see someone like Roxette become this search and Serverless analytics team across multiple cloud stacks. >> This is why the investment is such a great opportunity for the enterprise VCs right now because, I mean, there's so many dimensions of opportunities for companies to grow and become pretty large, and the markets are shifting so the TAM is pretty big. Michael Dell was just on the other side, I interviewed him. He says, you know, he was getting kind of in Dave's grill saying, "Well, the TAM for enterprise is bigger than cloud TAM." I go, "Well that TAM is going to be replatformized, so like that's going away and moving, shifting, so the numbers are big but they're shifting so tons of opportunities. >> It depends if you're a big company like Dell versus a small startup. Oftentimes, this true that the TAM for enterprise is still much larger than cloud, but your point is what's shifting were the dollars growing fast. >> The TAM for horses was huge at one point, and then, you know, cars came along, right? So you know. >> Every startup, what you want to do, you want to attach to a growing budget. You don't want to attach to a flat to shrinking budget. And so right now, if you're a founder, and say, "Okay, where are the budget dollars flowing to?" Everyone's got a kind of a cloud strategy, just like they had a VMware virtualization strategy, so if I'm like a startup G, metrics, or data analytics, I'm going to try to attach to where the dollars are flowing. That's a cloud strategy, that's an AI application strategy, security strategy. >> So let me ask you one question. So if I'm going to start up, this is a hypothetical startup, startups got an opportunity. It's a SaaS-based startup, they say, "You know what? "This is a feature in the market "that's part of a bigger system, "but I'm going to innovate on that." I think that with the markets shifting, that could evolve into a large TAM to your point about Datadog. What's the strategy, from an investment standpoint, that you would take? Would you say go all in on the single product? Do you want to have one or two features? What's the makeup of that approach, because you want to have some maybe defensibility, is it go all in on the one thing and hope that you return into like a Salesforce, then you bolt stuff on, or do you go in and try to do a little platform play underneath? >> It depends where you are in the startup world. We're in lifecycle. Look, startups succeed because they do one thing better, right? And so focus, focus, focus. And you have to have something that's like 10 times faster, 10 times better, 10 times cheaper, or something different. Something the world hasn't seen before. But if you do that one thing well, either A, you're taking budget dollars from incumbents, or B, you're something net new, the world hasn't seen, people will come to you when they see utility. As an investor I like to see that focus, I like to see, you know, some founders you get say, hey, Stu, think bigger. Some founders like John think smaller. Like what's your wedge? What's that initial entry point to the customer you're going to hit? Because once you land that, you get the right to do the next product, the next feature. >> That's the land, adopt, expand, like Xoom did. Or they picked video, >> Correct, voice, et cetera. >> I mean who the hell thought that was going to be a big market? It's a legacy market but they innovated with the cloud. >> Absolutely. I have all these sayings that I try to say like, "You don't get to play the late innings, "if you don't make it out the early innings," right? You know, and so if you want and have this strategy for this large platform, that's great, and every VC wants to see a path there. But they want to see execute from we're going to land, and we're expand. Now, startups fail because either where they land, they picked incorrectly. Like you decided to storm the wrong beach, right? Or it's either to small, or it's too big. The initial landing spot is too big, and they can't hold that ground. And so part of the art of navigating from Point A to Point B, or where I say, Act one, Act two, Act three of a lifecycle is make sure that you land correctly, earn your keep, show a lot of value, win that first battle, if you will, Act one, and then they move to Act two, Act three, and you can see a company like VMware clearly on their second, third act, right? And they've done a nice job of owning one product category, server virtualization, desktop virtualization, now expanding to other adjacent categories, buying companies like Carbon Black, right? In terms of security. So it doesn't happen overnight. I mean, VMware started in 1998. I was there when there was about 200 employees. People forget Amazon's been, gosh 27, 1998, when Bezos started selling books. Now they're selling books, movies, food, groceries, video, right? >> When did you first use AWS? Was it when the EC2 launched? I mean, everyone kicked the tires on that puppy. >> We all kicked the tires. I was at VMware as a Product Manager, I think it was '06 when they launched, right? And we all kind of kicked the tires on it. And it was a classic innoverse dilemna. We saw this thing that you thought was small and a very narrow surface area. Amazon started with an EC2, >> Two building blocks, storage and EC2. >> S-3, right, that's it. And then they said, "Okay, we're going to give a focus, focus on basic compute and basic object storage," and people were like, "What can you do with S-3? "Nothing," right? It's not a Sand, it's an availability. It's going to fail all the time, but people just started innovating and working their way through it. >> All right, so Jerry, when you look at the overall marketscape out there today, it seems like you still feel pretty confident that it's a good time for startups. Would you say that's true? >> Absolutely. >> All right, I want to get your final word here. 10 years in theCUBE at Vmworld, you know, you've known John for a long time. Did you think we'd make it? Any big memories as to what you've seen as we've changed over the years. >> I've plenty, let's go back to, >> John: Okay, now you can embarrass us. >> 10 year anniversary of VMworld. For your first Vmworld 10 years ago, I was like a Product Manager, and John Furrier, I think I met at a Press dinner, and he's like, "Hey, Chen," walking by, "come here, sit down," and they turn the camera on, and we had no idea what was going on, and he just started asking a bunch of random questions. I'm like, sure, I haven't cleared this with marketing or anyone else, but why not? >> John: Hijack interview, we call that. >> Hijack interview, and then it's been amazing to watch the two of you, Dave, John, everybody, grow SiliconANGLE and theCUBE in particular, and to this, the immediate franchise, in terms of both having a presence at all these shows, like Amazon, Oracle World, DreamForce, Vmworld, etc. But also the content you guys have, right? So now you have 10 years of deep content, and embarrassingly enough, 10 years, I guess, of videos of yours truly, which is always painful to watch, like either what I was saying, or you know, what my hair looked like back then. >> Stu: Jerry, you still have hair though, so. (laughing) >> Well, the beautiful thing is that we can look at the reputation trajectory of what people say and what actually happens. You always had good picks, loved the post you did on MOATs. That turned out to be very timeless content, and yeah, sometimes you miss it, we sometimes cringe. >> We miss a bunch. >> I remember starting one time with no headset on. Lot of great memories, Jerry. Great to have you in the community. Thanks for all your contribution. >> I look forward to the next 10 years of theCUBE, so I got to be here for the 20th anniversary, and now if I walk away, come back on right away, do I get another notch on my CUBE attending list so I can go up and catch Hared in the best? >> If you come on the other set, that counts as another interview. >> Perfect, so I got to catch up with Steve and the rest of the guys. >> Steve just lost it to Eric Herzog just a minute ago. We had a ceremony. It was like a walk through the supermarket, the doors thing, and the confetti came down. 11th time so you got to get to 11 now. So 12 is the high water mark. >> Done, we need t-shirts. (laughing) >> Well Jerry, thanks so much for joining us again. For John Furrier, I'm Stu Miniman, and you can go to theCUBE.net, if you search for Jerry Chen, there's over 16 interviews on there. I know I've gone back and watched some of them. Some great discussions we've had over the years. Thanks so much, and stay tuned for lots more coverage here at Vmworld 2019. Thanks for watching theCUBE. (upbeat music)

>> Live from Las Vegas, it's theCUBE! Covering AWS re:Invent 2018. Brought to you by Amazon web services, Intel, and their ecosystem partners. >> Hey welcome back everyone, here at AWS re:Invent 2018, their sixth year of theCUBE coverage, two sets wall-to-wall coverage here, two more sets in other locations, getting all the content, bringing it in, ingesting it into our video cloud service on AWS, ah, Dave, >> Lot of content, John. >> Lot of people don't know that we have that video cloud service, but we're going to have a lot of fun, ton of content, ton of stories, and a special analyst segment, Jerry Chen, guest here today, CUBE alumni, famous Venture Capitalist and Greylock partners, partnering with Reid Hoffman, the founder of LinkedIn, great set of partners at Greylock , great firm, tier one, doing a lot of great deals, Rockset, recent one. >> Thanks, yeah. >> You're also, on the record, these six years ago, calling the shot of Babe Ruth predicting the future. You've got a good handle on, you've got VM where you have the cloud business, now you're making investments, you're seeing a lot of stuff on the landscape, certainly, as a Venture Capitalist, you're funding projects, what better time now of innovation to actually put money to work, to hit market share, and then the big guys are getting bigger, they're creating more robust platforms, game is changing big-time, want to get your perspective, Dave, so, Jerry, what's your take on the announcements, slew of announcements, which ones jumped out at you? >> I think there's kind of two or three areas, there's definitely the hybrid cloud story with the Outpost, there's a bunch of stuff around ML and AI services, and a bunch of stuff on data and storage, and for me I think what they're doing around the ML services, the prediction, the personalization, the text OCR, what Amazon's doing at that app layer is now creating AI building blocks for modern application, so you want to do forecasts, you want to do personalization, you want to do text analysis, you have a simple API to basically build these modern apowered apps, he's doing to the app infrastructure layer what he's done to the cloud infrastructure layer, by deconstructing these services. >> And API is also the center, that's what web services are, so question for you is, do you see that the core cloud players, Aussie, Amazon, Bigly, Google, Microsoft, others, it's a winner take most, you called that six years ago, and that's true, but as they grow there's going to be now a new cloudification going on for business apps, new entrepreneurs coming to market, who's vulnerable, who wins, who loses, as this evolution continues because it's going to enable a lot of opportunity. >> Yeah, well I mean Amazon in cloud in general is going to create a lot of winners and losers, like you said, so I think you have a shift of dollars from on prem and old legacy vendors, databay storage, compute, to the cloud, so I think there's a shift of dollars, there are winner and losers, but I think what's going to happen is, with all these services around AI, ML, and Cloud as a distribution model, a lot of applications are going to be rebuilt. So I think that the entire application stack from all the big SaaS players to small SaaS companies, you're going to see this kind of a long tale of new SaaS applications being built on top of the Cloud that you didn't see in the past. >> And the ability to get to markets faster, so the question I have for you is, if you're an entrepreneur out there, looking for funding and I can to market quicker, what's the playbook, and two, Jassie talked on stage about a new persona, a new kind of developer, one that can rethink and reimagine and reinvent something that someone else has already done, so if you're an entrepreneur, you got to think to take someone else's territory, so how does an entrepreneur go out and identify whose lunch to eat, so if I want to take down a company, I got to have a strategy, how do I use the cloud to >> I think it's always a combination when a founder in a thing attacks your market it's a combination of where are the dollars, where can I create some advantage IP or advantage angle, and thirdly where do I have a distribution advantage, how can I actually get my product in the hands of the users differently? And so I think those are the three things, you find intersection of a great market, you have a unique angle, and you have a unique route to market, then you have a powerful story. So, you think about cloud changing the game, think about the mobile app you can consist of, for consumers, that is also a new platform, a new distribution method, the mobile app stores, and so what happened, you had a new category of developers, mode developers, creating this long tale, a thousand thousand apps, for everything from groceries to cars to your Fantasy Football score. So I think you're going to see distribution in the cloud, making it easy to get your apps out there, going to see a bunch of new markets open up, because we're seeing verticals like healthcare, construction, financial services, that didn't have special apps beforehand, be disrupted with technology. Autodesk just bought PlanGrid for 800 million dollars, I mean that's unheard of, construction software company. So you can see a bunch of new inverdics like that be opened up, and then I think with this cloud technology, with compute storage network becomes free and you have this AI layer on top of it, you can power these new applications using AI, that I think is pretty damn exciting. >> Yes, you described this sort of, we went from client server to the cloud, brought a whole bunch of new app providers, obviously Salesforce was there but Workday, Service Now, what you described is a set of composeable digital services running on top of a cloud, so that's ripe for disruption, so do I have to own my own data centers if I'm big SaaS company, what happens to those big guys? >> I don't think you have to, well, you don't have to own your own data center as a company, but you could if you wanted to, right, so at some point in scale, a lot of big players build their own data centers, like AirBNB is on Amazon, but Dropbox built their own storage on Amazon early, then their own data center later. Uber has their own data center, right, so you can argue that at some point of scale it makes sense to build your own, so you don't need to be on Amazon or Google as your start, but it does give you a head start. Now the question is, in the future, can you build a SaaS application entirely on Amazon, Azure, or Google, without any custom code, right, can you hide read write call private SaaS, like a single instance of my SaaS application for you, John, or for you, Dave, that's your data, your workflow, your information personalized for you, so instead of this multi-tenet CRM system like Salesforce, I have a custom CRM system just for Dave, just for Jeff, just for Jerry, just for theCUBE, right? >> I think yes, for that, I think that's definitely a trend I would see happening. >> It's what Infor is trying to do, right, Charles Phillips says "Friends don't let friends "build data centers," but they've still got a big loss in legacy there, but it's an interesting model, focused on verticals or microverticals or like the healthcare example that you're giving, and lot of potential for something. >> Well here's why I think I like this because, I think, and I said this before in theCUBE maybe it's not the best way to say it is that, if you look at the benefit of AI, data-driven, the quality of the data and the power of the compute has to be there. AI will work well with all that stuff, but it's also specialized around the application's use case. So you have specialism around the application, but you don't have to build a full stack to do that, you could use a horizontally scalable cloud distribution system in your word, and then only create custom unique workloads for the app, where machine learning's involved, and AI, that's unique to the app, that's differentiation, that could be the business model, or the utility. So, multitenancy could exist in theory, at the scalable level, but unique at the top of the level so yes I would say I'd want that hosted in the most customized, agile, flexible way. So I would argue that that's the scenario. >> I think that's the future, I mean one of my, I think you were saying, Dave, friends don't let friends build data centers anymore, it's you probably don't need to build a data center anymore because you can actually build your own application on top of one of the two or three large cloud providers. So it's interesting to see what happens the next three, four years, we're going to see kind of a thousand flowers bloom of different apps, not everyone's going to make it, not everyone's going to be a huge Salesforce-like outcome, but there'll be a bunch of applications out there. >> And the IoT stuff is interesting to me, so observing a lot of what the IT guys are doing, it reminds me of people trying to make the Windows mobile phone, they're just trying to force IT standards down the IoT, what I've seen from AWS today is more of a bottoms up approach, build applications for operations technology people, which I think is the right way to go, what do you see in an IoT, IoT apps, what's the formula there? >> I think what Amazon announced today with their time series database, right, their Timestream prediction engine, plus their Outpost offering with the Vmware themselves, you're really seeing a combination of IoT and Edge, right, it's the whole idea is, one, there's a bunch of use cases for time series in IoT, because sentry data, cameras, self-driving cars, drones, et cetera, there's more data coming at you, it adds all of that. >> And Splunk has proven that big-time. >> Correct, Splunk's let 18 billion Marcap company, all on time series data, but number two, what's happening is, it's not necessarily centralized data, right, it's happening at the edge, your self-driving car, your cell phone, et cetera, so Outpost is really a way for Amazon to get closer to the edge, by pushing their compute towards your data center, towards remote office, branch office, and get closer to where the data is, so I think that'll be super interesting. >> Well the Elastic Inference engine is critical, now we got elasticity around inference, and then they got the chip set that worked Inferentia, that can work with the elastic service. That's a powerful combination. >> The AI plumbing war between Google and TetraFlow as technology there's like PyTorch, Google TPUs versus what Amazon is doing with inference chips today, versus what I'm sure Microsoft and else is doing, is fascinating to watch in terms of how you had a kind of a Intel Nvidia duopoly for a long time, and now you have Intel, Nvidia, and then everyone from Amazon, Google, Microsoft doing their own soul again, it's pretty fascinating to watch. >> What was the stat, he said 85% of the TensorFlow, cloud TensorFlow's running on AWS? >> Makes a lot of sense, I think he said Aurora's customers logoslide doubled, but let's break down real quick, to end the segment with the key areas that we see going on, at least my perspective, I want to get your reaction. Storage, major disruption, he emphasized a lot of that in the keynote, spent a lot of time on stores, actually I think more than EC2 if you look at it, two, databases, database war, storage rate configuration, and a holy trinity of networking, storage, and compute, that's evolving, databases, SageMaker, machine learning. All there and then over the top, yesterday's announcement of satellite as a service, that essentially kills the edge of the network, cause there is no edge if we have space satellites shooting connectivity to any device the world is now, there's no more edge, it's everywhere. So, your thoughts, those areas. Which one pops out as the most surprising or most relevant? >> I think it's consistent Amazon strategy, on the lowest layer they're trying to draw the cost to zero, so on storage, cheaper cheaper cheaper, they're driving the bottom layer to zero to get all your data. I think the second thing, the database layer, it makes sense, it's not open-source, right, time scale or time series, it's not, Timestream's not their open-source database, it's their own, so open-source, low cost, the lowest layer, their database stuff is mostly their own, Aurora, Dynamo, Timestream, right, because there's some level lock in there, which I think customers are worried about, so that's clever, it's not by accident, that's all proprietary, and then ML Services, on top of that, that's all cares with developers, and it's API locking, so clearly low-cost open-source for the bottom, proprietary data services that they're trying to own, and then API's on top of it. And so the higher up in the stack, the more and more Amazon, you look, the more and more Amazon you have to adopt as kind of a lock in stack, so it's a brilliant strategy the guys have been executing for the past six, seven years as you guys have seen firsthand, I think the most exciting thing, and the most shocking thing to me is this move towards this battle for the AI front, this ML AI front, I think we saw ML's the new sequel, right, that's the new war, right, against Amazon, Google, and Microsoft. >> And that's the future of applications, cause this is >> But you're right on, it's a knife fight for the data, and then you layer on machine intelligence on top of that, and you get cloud scale, and that's the innovation engine for the next 10 years. >> Alright Jerry Chen just unpacked the State of the Union of cloud, of course as an investor I got to ask the final question, how are you investing to take advantage of this wave, versus being on the wrong side of history? >> I have framers for everything, there's a framer on how to attack the cloud vendors, and so I'm looking at a couple things, one, a seams in between the clouds, right, or in between services, because they can't do everything well, and there were kind of these large continents, Amazon, Google, Azure, so I'm looking for seams between the three of them, I'm looking for two, deep areas of IP that they're not going into that you actually have proprietary tap, and then verticals of data, like source of the data, or workflows that these guys aren't great, and then finally kind of cross-data cross-cloud solution, so, something that gives you the ability to run on prem, off prem, Microsoft, Google, Azure. >> Yeah, fill in the white spaces, there are big white spaces, and then hope that could develop into, good. Jerry Chen, partner in Greylock , partners formerly Vmware part of the V Mafia, friend of theCUBE, great guest analysis here, with Dave Vellante and John Furrier, thanks for watching us, stay with us, more live coverage, day two of three days of wall-to-wall coverage at re:Invent, 52,000 people, the whole industry's here, you can see the formations, we're getting all of the data, we're bringing it to you, stay with us.

[Music] we're on welcome to the special cube conversation we're here with some breaking news we got some startup investment news here in the Q studios palo alto I'm John for your host here at Jerry Chen partnered Greylock and the CEO of rock said Venkat Venkat Rahmani welcome to the cube you guys announcing hot news today series a and seed and Series A funding 21 million dollars for your company congratulations thank you Roxette is a data company jerry great this is one of your nest you kept this secret forever it was John was really hard you know over the past two years every time I sat in this seat I'd say and one more thing you know I knew that part of the advantage was rocks I was a special company and we were waiting to announce it and that's right time so it's been about two and half years in the making I gotta give you credit Jerry I just want to say to everyone I try to get the secrets out of you so hard you are so strong and keeping a secret I said you got this hot startup this was two years ago yeah I think the probe from every different angle you can keep it secrets all the entrepreneurs out there Jerry Chen's your guide alright so congratulations let's talk about the startup so you guys got 21 million dollars how much was the seed round this is the series a the seed was three million dollars both Greylock and Sequoia participating and the series a was eighteen point five all right so other investors Jerry who else was in on this I just the two firms former beginning so we teamed up with their French from Sequoia and the seed round and then we over the course of a year and half like this is great we're super excited about the team bank had Andrew bhai belt we love the opportunity and so Mike for an office coin I said let's do this around together and we leaned in and we did it around alright so let's just get into the other side I'm gonna read your your about section of the press release roxette's visions to Korea to build the data-driven future provide a service search and analytics engine make it easy to go from data to applications essentially building a sequel layer on top of the cloud for massive data ingestion I want to jump into it but this is a hot area not a lot of people are doing this at the level you guys are now and what your vision is did this come from what's your background how did you get here did you wake up one Wednesday I'm gonna build this awesome contraction layer and build an operating system around data make this thing scalable how did it all start I think it all started from like just a realization that you know turning useful data to useful apps just requires lots of like hurdles right you have to first figure out what format the data is in you got to prepare the data you gotta find the right specialized you know data database or data management system to load it in and it often requires like weeks to months before useful data becomes useful apps right and finally you know after I you know my tenure at Facebook when I left the first thing I did was I was just talking you know talking to a lot of people with real-world companies and reload problems and I started walking away from moremore of them thinking that this is way too complex I think the the format in which a lot of the data is coming in is not the format in which traditional sequel based databases are optimized for and they were built for like transaction processing and analytical processing not for like real-time streams of data but there's JSON or you know you know parque or or any of these other formats that are very very popular and more and more data is getting produced by one set of applications and getting consumed by other applications but what we saw it was what is this how can we make it simpler why do we need all this complexity right what is a simple what is the most simple and most powerful system we can build and pulled in the hands of as many people as possible and so we very sort of naturally relate to developers and data scientists people who use code on data that's just like you know kind of like our past lives and when we thought about it well why don't we just index the data you know traditional databases were built when every byte mattered every byte of memory every byte on disk now in the cloud the economics are completely different right so when you rethink those things with fresh perspective what we said was like what if we just get all of this data index it in a format where we can directly run very very fast sequel on it how simple would the world be how much faster can people go from ideas to do experiments and experiments to production applications and how do we make it all faster also in the cloud right so that's really the genesis of it well the real inspiration came from actually talking to a lot of people with real-world problems and then figuring out what is the simplest most powerful thing we can build well I want to get to the whole complexity conversation cuz we were talking before we came on camera here about how complexity can kill and why and more complexity on top of more complexity I think there's a simplicity angle here that's interesting but I want to get back to your background of Facebook and I want to tell a story you've been there eight years but you were there during a very interesting time during that time in history Facebook was I think the first generation we've taught us on the cube all the time about how they had to build their own infrastructure at scale while they're scaling so they were literally blitzscaling as reid hoffman and would say and you guys do it the Greylock coverage unlike other companies at scale eBay Microsoft they had old-school one dotto Technology databases Facebook had to kind of you know break glass you know and build the DevOps out from generation one from scratch correct it was a fantastic experience I think when I started in 2007 Facebook had about 40 million monthly actives and I had the privilege of working with some of the best people and a lot of the problems we were very quickly around 2008 when I went and said hey I want to do some infrastructure stuff the mandate that was given to me and my team was we've been very good at taking open source software and customizing it to our needs what would infrastructure built by Facebook for Facebook look like and we then went into this journey that ended up being building the online data infrastructure at Facebook by the time I left the collectively these systems were surveying 5 plus billion requests per second across 25 plus geographical clusters and half a dozen data centers I think at that time and now there's more and the system continues to chug along so it was just a fantastic experience I think all the traditional ways of problem solving just would not work at that scale and when the user base was doubling early in the early days every four months every five months yeah and what's interesting you know you're young and here at the front lines but you're kind of the frog in boiling water and that's because you are you were at that time building the power DevOps equation automating scale growth everything's happening at once you guys were right there building it now fast forward today everyone who's got an enterprise it's it wants to get there they don't they're not Facebook they don't have this engineering staff they want to get scale they see the cloud clearly the value property has got clear visibility but the economics behind who they hire so they have all this data and they get more increasing amount of data they want to be like Facebook but can't be like Facebook so they have to build their own solutions and I think this is where a lot of the other vendors have to rebuild this cherry I want to ask you because you've been looking at a lot of investments you've seen that old guard kind of like recycled database solutions coming to the market you've seen some stuff in open source but nothing unique what was it about Roxette that when you first talk to them that but you saw that this is going to be vectoring into a trend that was going to be a perfect storm yeah I think you nailed it John historic when we have this new problems like how to use data the first thing trying to do you saw with the old technology Oh existing data warehouses akin databases okay that doesn't work and then the next thing you do is like okay you know through my investments in docker and B and the boards or a cloud aerosol firsthand you need kind of this rise of stateless apps but not stateless databases right and then I through the cloud area and a bunch of companies that I saw has an investor every pitch I saw for two or three years trying to solve this data and state problem the cloud dudes add more boxes right here's here's a box database or s3 let me solve it with like Oh another database elastic or Kafka or Mongo or you know Apache arrow and it just got like a mess because if almond Enterprise IT shop there's no way can I have the skill the developers to manage this like as Beckett like to call it Rube Goldberg machination of data pipelines and you know I first met Venkat three years ago and one of the conversations was you know complexity you can't solve complex with more complexity you can only solve complexity with simplicity and Roxette and the vision they had was the first company said you know what let's remove boxes and their design principle was not adding another boxes all a problem but how to remove boxes to solve this problem and you know he and I got along with that vision and excited from the beginning stood to leave the scene ah sure let's go back with you guys now I got the funding so use a couple stealth years to with three million which is good a small team and that goes a long way it certainly 2021 total 18 fresh money it's gonna help you guys build out the team and crank whatnot get that later but what did you guys do in the in those two years where are you now sequel obviously is lingua franca cool of sequel but all this data is doesn't need to be scheming up and built out so were you guys that now so since raising the seed I think we've done a lot of R&D I think we fundamentally believe traditional data management systems that have been ported over to run on cloud Williams does not make them cloud databases I think the cloud economics is fundamentally different I think we're bringing this just scratching the surface of what is possible the cloud economics is you know it's like a simple realization that whether you rent 100 CPUs for one minute or or one CPU 400 minutes it's cost you exactly the same so then if you really ask why is any of my query is slow right I think because your software sucks right so basically what I'm trying to say is if you can actually paralyze that and if you can really exploit the fluidity of the hardware it's not easy it's very very difficult very very challenging but it's possible I think it's not impossible and if you can actually build software ground-up natively in the cloud that simplifies a lot of this stuff and and understands the economics are different now and it's system software at the end of the day is how do I get the best you know performance and efficiency for the price being paid right and the you know really building you know that is really what I think took a lot of time for us we have built not only a ground-up indexing technique that can take raw data without knowing the shape of the data we can turn that and index it in ways and store them maybe in more than one way since for certain types of data and then also have built a distributed sequel engine that is cloud native built by ground up in the cloud and C++ and like really high performance you know technologies and we can actually run distributor sequel on this raw data very very fast my god and this is why I brought up your background on Facebook I think there's a parallel there from the ground this ground up kind of philosophy if you think of sequel as like a Google search results search you know keyword it's the keyword for machines in most database worlds that is the standard so you can just use that as your interface Christ and then you using the cloud goodness to optimize for more of the results crafty index is that right correct yes you can ask your question if your app if you know how to see you sequel you know how to use Roxette if you can frame your the question that you're asking in order to answer an API request it could be a micro service that you're building it could be a recommendation engine that you're that you're building or you could you could have recommendations you know trying to personalize it on top of real time data any of those kinds of applications where it's a it's a service that you're building an application you're building if you can represent ask a question in sequel we will make sure it's fast all right let's get into the how you guys see the application development market because the developers will other winners here end of the day so when we were covering the Hadoop ecosystem you know from the cloud era days and now the important work at the Claire merger that kind of consolidates that kind of open source pool the big complaint that we used to hear from practitioners was its time consuming Talent but we used to kind of get down and dirty the questions and ask people how they're using Hadoop and we had two answers we stood up Hadoop we were running Hadoop in our company and then that was one answer the other answer was we're using Hadoop for blank there was not a lot of those responses in other words there has to be a reason why you're using it not just standing it up and then the Hadoop had the problem of the world grew really fast who's gonna run it yeah management of it Nukem noose new things came in so became complex overnight it kind of had took on cat hair on it basically as we would say so how do you guys see your solution being used so how do you solve that what we're running Roxette oh okay that's great for what what did developers use Roxette for so there are two big personas that that we currently have as users right there are developers and data scientists people who program on data right - you know on one hand developers want to build applications that are making either an existing application better it could be a micro service that you know I want to personalize the recommendations they generated online I mean offline but it's served online but whether it is somebody you know asking shopping for cars on San Francisco was the shopping you know was the shopping for cars in Colorado we can't show the same recommendations based on how do we basically personalize it so personalization IOT these kinds of applications developers love that because often what what you need to do is you need to combine real-time streams coming in semi structured format with structured data and you have no no sequel type of systems that are very good at semi structured data but they don't give you joins they don't give you a full sequel and then traditional sequel systems are a little bit cumbersome if you think about it I new elasticsearch but you can do joins and much more complex correct exactly built for the cloud and with full feature sequel and joins that's how that's the best way to think about it and that's how developers you said on the other side because its sequel now all of a sudden did you know data scientist also loved it they had they want to run a lot of experiments they are the sitting on a lot of data they want to play with it run experiments test hypotheses before they say all right I got something here I found a pattern that I don't know I know I had before which is why when you go and try to stand up traditional database infrastructure they don't know how what indexes to build how do i optimize it so that I can ask you know interrogatory and all that complexity away from those people right from basically provisioning a sandbox if you will almost like a perpetual sandbox of data correct except it's server less so like you don't you never think about you know how many SSDs do I need how many RAM do I need how many hosts do I need what configure your programmable data yes exactly so you start so DevOps for data is finally the interview I've been waiting for I've been saying it for years when's is gonna be a data DevOps so this is kind of what you're thinking right exactly so you know you give us literally you you log in to rocks at you give us read permissions to battle your data sitting in any cloud and more and more data sources we're adding support every day and we will automatically cloudburst will automatically interested we will schematize the data and we will give you very very fast sequel over rest so if you know how to use REST API and if you know how to use sequel you'd literally need don't need to think about anything about Hardware anything about standing up any servers shards you know reindex and restarting none of that you just go from here is a bunch of data here are my questions here is the app I want to build you know like you should be bottleneck by your career and imagination not by what can my data employers give me through a use case real quick island anyway the Jarius more the structural and architectural questions around the marketplace take me through a use case I'm a developer what's the low-hanging fruit use case how would I engage with you guys yeah do I just you just ingest I just point data at you how do you see your market developing from the customer standpoint cool I'll take one concrete example from a from a developer right from somebody we're working with right now so they have right now offline recommendations right or every night they generate like if you're looking for this car or or this particular item in e-commerce these are the other things are related well they show the same thing if you're looking at let's say a car this is the five cars that are closely related this car and they show that no matter who's browsing well you might have clicked on blue cars the 17 out of 18 clicks you should be showing blue cars to them right you may be logging in from San Francisco I may be logging in from like Colorado we may be looking for different kinds of cars with different you know four-wheel drives and other options and whatnot there's so much information that's available that you can you're actually by personalizing it you're adding creating more value to your customer we make it very easy you know live stream all the click stream beta to rock set and you can join that with all the assets that you have whether it's product data user data past transaction history and now if you can represent the joins or whatever personalization that you want to find in real time as a sequel statement you can build that personalization engine on top of Roxanne this is one one category you're putting sequel code into the kind of the workflow of the code saying okay when someone gets down to these kinds of interactions this is the sequel query because it's a blue car kind of go down right so like tell me all the recent cars that this person liked what color is this and I want to like okay here's a set of candidate recommendations I have how do I start it what are the four five what are the top five I want to show and then on the data science use case there's a you know somebody building a market intelligence application they get a lot of third-party data sets it's periodic dumps of huge blocks of JSON they want to combine that with you know data that they have internally within the enterprise to see you know which customers are engaging with them who are the persons churning out what are they doing and they in the in the market and trying to bring they bring it all together how do you do that when you how do you join a sequel table with a with a JSON third party dumb and especially for coming and like in the real-time or periodic in a week or week month or one month literally you can you know what took this particular firm that we're working with this is an investment firm trying to do market intelligence it used age to run ad hoc scripts to turn all of this data into a useful Excel report and that used to take them three to four weeks and you know two people working on one person working part time they did the same thing in two days and Rock said I want to get to back to microservices in a minute and hold that thought I won't go to Jerry if you want to get to the business model question that landscape because micro services were all the world's going to Inc so competition business model I'll see you gets are funded so they said love the thing about monetization to my stay on the core value proposition in light of the red hat being bought by by IBM had a tweet out there kind of critical of the transactions just in terms of you know people talk about IBM's betting the company on RedHat Mike my tweet was don't get your reaction will and tie it to the visible here is that it seems like they're going to macro services not micro services and that the world is the stack is changing so when IBM sell out their stack you have old-school stack thinkers and then you have new-school stack thinkers where cloud completely changes the nature of the stack in this case this venture kind of is an indication that if you think differently the stack is not just a full stack this way it's this way in this way yeah as we've been saying on the queue for a couple of years so you get the old guard trying to get a position and open source all these things but the stacks changing these guys have the cloud out there as a tailwind which is a good thing how do you see the business model evolving do you guys talk about that in terms of you can hey just try to find your groove swing get customers don't worry about the monetization how many charging so how's that how do you guys talk about the business model is it specific and you guys have clear visibility on that what's the story on that I mean I think yeah I always tell Bank had this kind of three hurdles you know you have something worthwhile one well someone listen to your pitch right people are busy you like hey John you get pitched a hundred times a day by startups right will you take 30 seconds listen to it that's hurdle one her will to is we spend time hands on keyboards playing around with the code and step threes will they write you a check and I as a as a enter price offered investor in a former operator we don't overly folks in the revenue model now I think writing a check the biz model just means you're creating value and I think people write you checking screening value but you know the feedback I always give Venkat and the founders work but don't overthink pricing if the first 10 customers just create value like solve their problems make them love the product get them using it and then the monetization the actual specifics the business model you know we'll figure out down the line I mean it's a cloud service it's you know service tactically to many servers in that sentence but it's um it's to your point spore on the cloud the one that economists are good so if it works it's gonna be profitable yeah it's born the cloud multi-cloud right across whatever cloud I wanna be in it's it's the way application architects going right you don't you don't care about VMs you don't care about containers you just care about hey here's my data I just want to query it and in the past you us developer he had to make compromises if I wanted joins in sequel queries I had to use like postgrads if I won like document database and he's like Mongo if I wanted index how to use like elastic and so either one I had to pick one or two I had to use all three you know and and neither world was great and then all three of those products have different business models and with rocks head you actually don't need to make choices right yes this is classic Greylock investment you got sequoia same way go out get a position in the market don't overthink the revenue model you'll funded for grow the company let's scale a little bit and figure out that blitzscale moment I believe there's probably the ethos that you guys have here one thing I would add in the business model discussion is that we're not optimized to sell latte machines who are selling coffee by the cup right so like that's really what I mean we want to put it in the hands of as many people as possible and make sure we are useful to them right and I think that is what we're obsessed about where's the search is a good proxy I mean that's they did well that way and rocks it's free to get started right so right now they go to rocks calm get started for free and just start and play around with it yeah yeah I mean I think you guys hit the nail on the head on this whole kind of data addressability I've been talking about it for years making it part of the development process programming data whatever buzzword comes out of it I think the trend is it looks a lot like that depo DevOps ethos of automation scale you get to value quickly not over thinking it the value proposition and let it organically become part of the operation yeah I think we we the internal KPIs we track are like how many users and applications are using us on a daily and weekly basis this is what we obsess about I think we say like this is what excellence looks like and we pursue that the logos in the revenue would would you know would be a second-order effect yeah and it's could you build that core kernels this classic classic build up so I asked about the multi cloud you mention that earlier I want to get your thoughts on kubernetes obviously there's a lot of great projects going on and CN CF around is do and this new state problem that you're solving in rest you know stateless has been an easy solution VP is but API 2.0 is about state right so that's kind of happening now what's your view on kubernetes why is it going to be impactful if someone asked you you know at a party hey thank you why is what's all this kubernetes what party going yeah I mean all we do is talk about kubernetes and no operating systems yeah hand out candy last night know we're huge fans of communities and docker in fact in the entire rock set you know back-end is built on top of that so we run an AWS but with the inside that like we run or you know their entire infrastructure in one kubernetes cluster and you know that is something that I think is here to stay I think this is the the the programmability of it I think the DevOps automation that comes with kubernetes I think all of that is just like this is what people are going to start taking why is it why is it important in your mind the orchestration because of the statement what's the let's see why is it so important it's a lot of people are jazzed about it I've been you know what's what's the key thing I think I think it makes your entire infrastructure program all right I think it turns you know every aspect of you know for example yeah I'll take it I'll take a concrete example we wanted to build this infrastructure so that when somebody points that like it's a 10 terabytes of data we want to very quickly Auto scale that out and be able to grow this this cluster as quickly as possible and it's like this fluidity of the hardware that I'm talking about and it needs to happen or two levels it's one you know micro service that is ingesting all the data that needs to sort of burst out and also at the second level we need to be able to grow more more nodes that we we add to this cluster and so the programmability nature of this like just imagine without an abstraction like kubernetes and docker and containers and pods imagine doing this right you are building a you know a lots and lots of metrics and monitoring and you're trying to build the state machine of like what is my desired state in terms of server utilization and what is the observed state and everything is so ad hoc and very complicated and kubernetes makes this whole thing programmable so I think it's now a lot of the automation that we do in terms of called bursting and whatnot when I say clock you know it's something we do take advantage of that with respect to stateful services I think it's still early days so our our position on my partner it's a lot harder so our position on that is continue to use communities and continue to make things as stateless as possible and send your real-time streams to a service like Roxette not necessarily that pick something like that very separate state and keep it in a backhand that is very much suited to your micro service and the business logic that needs to live there continue should continue to live there but if you can take a very hard to scale stateful service split it into two and have some kind of an indexing system Roxette is one that you know we are proud of building and have your stateless communal application logic and continue to have that you know maybe use kubernetes scale it in lambdas you know for all we care but you can take something that is very hard to you know manage and scale today break it into the stateful part in the stateless part and the serval is back in like like Roxette will will sort of hopefully give you a huge boost in being able to go from you know an experiment to okay I'm gonna roll it out to a smaller you know set of audience to like I want to do a worldwide you know you can do all of that without having to worry about and think about the alternative if you did it the old way yeah yeah and that's like talent you'd need it would be a wired that's spaghetti everywhere so Jerry this is a kubernetes is really kind of a benefit off your your investment in docker you must be proud and that the industry has gone to a whole nother level because containers really enable all this correct yeah so that this is where this is an example where I think clouds gonna go to a whole nother level that no one's seen before these kinds of opportunities that you're investing in so I got to ask you directly as you're looking at them as a as a knowledgeable cloud guy as well as an investor cloud changes things how does that change how is cloud native and these kinds of new opportunities that have built from the ground up change a company's network network security application era formants because certainly this is a game changer so those are the three areas I see a lot of impact compute check storage check networking early days you know it's it's it's funny it gosh seems so long ago yet so briefly when you know I first talked five years ago when I first met mayor of Essen or docker and it was from beginning people like okay yes stateless applications but stateful container stateless apps and then for the next three or four years we saw a bunch of companies like how do I handle state in a docker based application and lots of stars have tried and is the wrong approach the right approach is what these guys have cracked just suffered the state from the application those are app stateless containers store your state on an indexing layer like rock set that's hopefully one of the better ways saw the problem but as you kind of under one problem and solve it with something like rock set to your point awesome like networking issue because all of a sudden like I think service mesh and like it's do and costs or kind of the technologies people talk about because as these micro services come up and down they're pretty dynamic and partially as a developer I don't want to care about that yeah right that's the value like a Roxanna service but still as they operate of the cloud or the IT person other side of the proverbial curtain I probably care security I matters because also India's flowing from multiple locations multiple destinations using all these API and then you have kind of compliance like you know GDP are making security and privacy super important right now so that's an area that we think a lot about as investors so can I program that into Roxette what about to build that in my nap app natively leveraging the Roxette abstraction checking what's the key learning feature it's just a I'd say I'm a prime agent Ariane gdpr hey you know what I got a website and social network out in London and Europe and I got this gdpr nightmare I don't we don't have a great answer for GDP are we are we're not a controller of the data right we're just a processor so I think for GDP are I think there is still the controller still has to do a lot of work to be compliant with GDP are I think the way we look at it is like we never forget that this ultimately is going to be adding value to enterprises so from day one we you can't store data and Roxette without encrypting it like it's just the on you know on by default the only way and all transit is all or HTTPS and SSL and so we never freaked out that we're building for enterprises and so we've baked in for enterprise customers if they can bring in their own custom encryption key and so everything will be encrypted the key never leaves their AWS account if it's a you know kms key support private VP ceilings like we have a plethora of you know security features so that the the control of the data is still with the data controller with this which is our customer but we will be the the processor and a lot of the time we can process it using their encryption keys if I'm gonna build a GDP our sleeves no security solution I would probably build on Roxette and some of the early developers take around rocks at our security companies that are trying to track we're all ideas coming and going so there the processor and then one of the companies we hope to enable with Roxette is another generation security and privacy companies that in the past had a hard time tracking all this data so I can build on top of rocks crack okay so you can built you can build security a gbbr solution on top rock set because rock set gives you the power to process all the data index all the data and then so one of the early developers you know stolen stealth is they looking at the data flows coming and go he's using them and they'll apply the context right they'll say oh this is your credit card the Social Security is your birthday excetera your favorite colors and they'll apply that but I think to your point it's game-changing like not just Roxette but all the stuff in cloud and as an investor we see a whole generation of new companies either a to make things better or B to solve this new category problems like pricing the cloud and I think the future is pretty bright for both great founders and investors because there's just a bunch of great new companies and it's building up from the ground up this is the thing I brought my mother's red hat IBM thing is that's not the answer at the root level I feel like right now I'd be on I I think's fastenings but it's almost like you're almost doubling down to your your comment on the old stack right it's almost a double down the old stack versus an aggressive bet on kind of what a cloud native stack will look like you know I wish both companies are great people I was doing the best and stuff do well with I think I'd like to do great with OpenStack but again their product company as the people that happen to contribute to open source I think was a great move for both companies but it doesn't mean that that's not we can't do well without a new stack doing well and I think you're gonna see this world where we have to your point oh these old stacks but then a category of new stack companies that are being born in the cloud they're just fun to watch it all it's all big all big investments that would be blitzscaling criteria all start out organically on a wave in a market that has problems yeah and that's growing so I think cloud native ground-up kind of clean sheet of paper that's the new you know I say you're just got a pic pick up you got to pick the right way if I'm oh it's gotta pick a big wave big wave is not a bad wave to be on right now and it's at the data way that's part of the cloud cracked and it's it's been growing bigger it's it's arguably bigger than IBM is bigger than Red Hat is bigger than most of the companies out there and I think that's the right way to bet on it so you're gonna pick the next way that's kind of cloud native-born the cloud infrastructure that is still early days and companies are writing that way we're gonna do well and so I'm pretty excited there's a lot of opportunities certainly this whole idea that you know this change is coming societal change you know what's going on mission based companies from whether it's the NGO to full scale or all the applications that the clouds can enable from data privacy your wearables or cars or health thing we're seeing it every single day I'm pretty sad if you took amazon's revenue and then edit edit and it's not revenue the whole ready you look at there a dybbuk loud revenue so there's like 20 billion run which you know Microsoft had bundles in a lot of their office stuff as well if you took amazon's customers to dinner in the marketplace and took their revenue there clearly would be never for sure if item binds by a long shot so they don't count that revenue and that's a big factor if you look at whoever can build these enabling markets right now there's gonna be a few few big ones I think coming on they're gonna do well so I think this is a good opportunity of gradual ations thank you thank you at 21 million dollars final question before we go what are you gonna spend it on we're gonna spend it on our go-to-market strategy and hiding amazing people as many as we can get good good answer didn't say launch party that I'm saying right yeah okay we're here Rex at SIA and Joe's Jerry Chen cube cube royalty number two all-time on our Keeble um nine list partner and Greylock guy states were coming in I'm Jeffrey thanks for watching this special cube conversation [Music]

>> Voiceover: Live from Las Vegas it's theCUBE covering AWS re:Invent 2017. Presented by AWS, Intel, and our ecosystem of partners. (upbeat techno music) >> Okay, welcome back, everyone. Live here in Las Vegas where Amazon Web Services re:Invent 2017. Our fifth year covering. We missed the first year by one year, 2012. We couldn't make it. We were here 2013 and going forward. Or was it 2012? I don't know. I'm John Furrier with Lisa Martin. Our next guest is CUBE alumni number five in all time on CUBE visits. Famous venture capitalist partner at Greylock, Jerry Chen, former head of cloud at VMware, industry legend. Great to see you. >> Thanks for having me. >> That's quite the intro. >> Always an important guest. >> Oh, no. It's always an important stop at any conference. Like I said, if theCUBE's not there, it's not an event. How's that? >> Well, you're one of our most famous CUBE alumni. So, you're gonna get the credit card in the mail, with the Affinity program and all the benefits the alumni get. >> Thank you. >> John: Almost as good as Stanford. >> Almost as good. >> Okay, Jerry, thanks for coming on. I wanna just reminisce a little bit. 2013, your first time on theCUBE. It was small. We were on the other side over there. >> Jerry: Yeah. >> You were kind of mingling around looking for your first deal at Greylock. >> Jerry: Yeah. And you said, "I'm looking for the next Amazon." There was never a next Amazon, they just kept growing and growing. What a ride it's been. Jerry, your thoughts looking back now. >> Thank you. Well, thanks for having me. Like Moore's Law says, you double every 18 months in compute power. So, the Amazon or the cloud conference is the number of people are tripling every single year we've been here. The number of expos, the number of ecosystem partners has just been doubling, tripling. The number of services on Amazon's cloud has to be more than doubling every single year. So, Moore's Law is taken to the cloud in a different exponential way. >> And scale certainly is a dynamic. I was commenting on my post leading up to here, and my exclusive with Jassy, talking to him, trying to look at him and read the tea leaves. And it's clear to me, this is not him, my observation, the competitive strategy for Amazon is more services, speed, scale. They're raising the bar on the number of services that could be used, thus increasing their total addressable market. As more people use the cloud, more services are available. That's their plan. It's pretty clear. And the speed. Is that a competitive opportunity that blocks out other people? We talked before. You said, it's not a winner take all. It's winner take most. >> Jerry: Yeah. And Amazon's looking good. But you got Microsoft and Google. So, okay, I get that. >> Jerry: Don't forget Alibaba. >> Alibaba, they're number four worldwide. Number seven ... >> Jerry: Yep. Well, number one in China. But here's the deal. There's specialty clouds, there's new intelligent clouds that something Atella talks about. So it's an interesting dynamic, right. And Google, which almost has very little presence outside of North America is considered a new guard. A lot of developers love Google. >> Jerry: Yeah. So, you've got this kind of developer cult going on, that's very like a renaissance. Then you've got the IT. Almost sitting there like, not wondering what to do. Or do they? What's your thoughts? >> I don't know if IT's wondering what to do. So, you said a couple of things that are interesting. It's not a winner take all, or winner take most market. But, Amazon's launching all these new services. And so, what it is, when you have that scale the cost to serve another customer, the cost to lanch an additional service, is low. The marginal cost for yet another API on Amazon is low. So what Amazon has done so well is, there's a long tail of developer features and services that everybody wants. And they just keep adding them. There's only like 1000 developers that care about the service. The cost for Amazon to launch that is so low they can do that and have a positive ROI. So, if you're going to attack Amazon right now, you can't do the breadth of services. You've got to figure out a different vector of attacking. And so, you asked about Google. So Google is definitely taking the approach of two things. One, win developer love. Write a bunch of features around performance, storage, speed, they're doing really well. And number two, they're really doing a concentrated attack around some of their data and ML services. TensorFlow, and what not, that's getting a lot of attention. In contrast, you're going to see, I think, a lot of announcements tomorrow by Amazon or on ML and data services tomorrow. Because they're going to try and win the hearts and minds of the next generation of apps which could be around AI and data. >> And that's not low level parts of the stack. That's around the database layer. I mean, a new kind of middleware ... >> Correct. >> Is developing. >> I think you're seeing Amazon really attack the market in three different ways. One, the lowest level platform, infrastructure. Like storage, security, compute. >> John: Check. >> Check. You know, we see what they're doing there. Next is what I call the system of intelligence, right. It's how do you build AI or data. How to build a system of intelligence on top of that data. And that's where the battle is. The third area for Amazon is really these verticals, right. Their FedCloud, go after healthcare, go after financial services. So there's kind of a good market angle for these guys. So you'll see, I think, Andy and his team announce core infrastructure, system of intelligence tools around AI and data, and then a different good markets around healthcare, Government, financials, et cetera. >> It's interesting, you know, the developer attraction is interesting now. We were debating this on our opening, Lisa, where you know, IT controls the budgets and the enterprise. Certainly Government's the same way. And the old developer model is, join my developer program, here's a bunch of goodness, go build, go in the corner, we're going to tell you what to do, make it work, run the IT pipes, lay down some software applications and we're done. Ship it. QA, done. Now with cloud, the developers are driving the sentiment and now the freedom and the democratization of developers is interesting. So, does developers, this new cult I'm calling it, the new renaissance, are they going to drive the buying decision? It used to be the sales guy from Oracle or Olgar would come in and say, "Hey, I got a deal for you. I'll discount it by a zillion percent." Well, the developers don't want that. So you got this new force with the scale. So, it's interesting to see what we'll see from Amazon. >> Yeah. >> Again, I don't think this is going to be this year, but, this seems to be the trend that we've kind of talked about. Win the developers. Interesting. If you win the developers ... >> The dollars will follow. >> The dollars will follow or be the the new influencer ... >> Correct. >> To the decision maker of the deal. >> Yeah. >> And they've done that so well, I mean, one of the interesting things we're seeing now is advertising from AWS ... >> Jerry: Sure. >> Which we haven't really seen before. There were digital ads at the airport yesterday. They have done such a great job building awareness in the developer community. Really haven't had to advertise. You mention, also, Google getting Stickier binding to developers. The TensorFlow, Cooper Netties. >> Jerry: Correct. >> But, the advertising as a marker kind of speaks to me that are they trying to now go stronger to the enterprise and up the stack of the C Suite, the corporate boards. >> Jerry: Correct. To John's question, where is the buying power? Are you seeing a shift towards up the stack or are the developers now becoming stronger influencers in that case? >> It's never either or. I think its where you start and where you grow to. So I think Amazon did so well and Google's doing now is, you start with the developers because they're going to build the apps, you're going to make the decisions on what technology they use. But, you and I both know that's where you start but it's not how you finish. To get Sticky, you need security, operations, IT. So eventually the CIO or the CFO is going to write that seven figure, 10 figure, eight figure, nine figure deal to Amazon or to Google or to Agger because they're going to standardize on this cloud, this technology. If your business is running on Amazon, you're depending on Amazon. You know the CEO is going to make the decision, not just the developers. So, I think you start with the developer because they're going to make the right choices and you have to offer them the right set of tools and technologies, the right weapons. But ultimately, you build a house but someones going to pay for it and that's going to be the C Suite. >> Jerry, you've been involved in one of the best deals, seminal deals in the history of this new generation, Docker Containers. Container madness now turns into Cooper Nettie's madness. So you start to see at the top of the stack ... >> Jerry: Yeah. >> The application, the orchestration really tease that multi-cloud. So that's, although a lot of meat on the bone in my mind, but still certainly customers want choice. So what's your investment thesis these days as you see if it's a renaissance of developers, which we believe. And this ecosystem is going to grow, by the way, not just Amazon, you've got Microsoft, you've got Google, you've got Alibaba in China. So now, new gateways outside of North America. How do you invest in that and market? What's the strategy for Greylock? How are you guys looking at the market? Are there things that are new? Can you share some color around what goes on in the board meetings with all the investors? >> I would say there's probably two themes I'm thinking about right now to ride this wave around cloud. Both around the infrastructure layer and the app layer on top of it. So, I would say, whenever you see a new platform shift around mainframe client server, client sever cloud mobile, cloud mobile where we're at now. The first shift is always, take what I'm doing now and move it to cloud, right. And so I think that a lot of the tools you see now, database migration, how to transpose my data from one cloud to the next cloud. But what you see the second wave is, this cloud needed developers, right. These guys coming out of college, good men and women, that never racked a server. They're building cloud native databases, cloud native applications. And what you can do now, is you'll see another generation of applications being built, they'll look nothing like the generations behind, right. So the way you think about data, AI and apps will look very different. So there is a new sub-straight around data and applications in the cloud that we're looking at. >> An certainly, I know we've gotta go, we're going to have to bring you back, but, decentralization ... >> Jerry: Sure. >> You guys, Greylock, invested in CoinBase ... >> Jerry: Yes. >> You did very well, BitCoin is at 10,000. Crypto is hot. Token economics, potentially you looking good? >> I think you're going to have >> John: Look at the board. >> Yeah, I think that all things a hype cycle. You have a trial of disillusionment where the garner guys say, before you have any expectations. We will hit a crypto winter. But then it'll come back in some realization. There's a bunch of great technologies, great companies out there in the crypto space. CoinBase being one of them, we're lucky enough to be investors in. A bunch of other ICO's that are legitimate. But a bunch of stuff that's just noise. >> There's a lot of junk. You can see the ICO's are down now. So it looks like it's a little bit cold, the leaves are coming off the tree. >> I'd say in three or four years, I think BitCoin and some of these other assets will do well. Some of these other token services will do well. And a bunch won't exist. But they paved the way for, I think, a new paradigm. >> Well the new paradigm certainly will be CUBE Coin's (laughter) so look out for those, for all the CUBE alumni. >> Where do I sign up? >> No, you already get them. You're fifth on the all-time list. >> Now sixth. >> Jerry Chen is a CUBE alumni here inside the CUBE. Venture capitalist with Greylock. Tier one, big time investors in Silicon Valley. Great friend of the CUBE. Thanks for coming on sharing your commentary. I'm John Furrier with Lisa Martin, we'll be back with more coverage at re:Invent 2017 after this break. (digital music)

>> Announcer: From Austin, Texas, it's theCUBE covering DockerCon 2017. Brought to you by Docker and support from its ecosystem partners. (techno music) >> Welcome back. Hi, I'm Stu Miniman, joined with Jim Kobielus. You're watching theCUBE's SiliconANGLE Media's production of DockerCon 2017. We're the worldwide leader in live enterprise tech coverage. And we can't finish any DockerCon without having Jerry Chen on. So, Jerry, partner with Greylock, always a pleasure to interview you. We've had you on the Amazon shows a lot, Docker, other ecosystem shows, so, great to see ya. >> Stu, Jim. Hey, thanks for having me, as always. It's great to be here. >> Alright, so first of all, I mean, you invested back in the dotCloud days. Could you imagine, when you were meeting with Solomon and those guys and everything that we'd be here with 5,500 people as to where they'd go? What's your take on the growth? >> Every year just blows my mind, both in open-source community developers, ecosystem partners, and more recently, past year and a half, the enterprise customers that take Docker seriously, or replatformed applications on Docker, amazes me. I think I did an investment in 2013, and there were a few hundred thousand downloads of Docker, now there's billions and billions of containers being pulled. When I talk to CIOs that I deal with frequently, they're like, "Docker containers, what is this thing, pants?" And then, (laughter) three and a half, four years later, I can't have a conversation without a Fortune 500 CIO without talking about their Docker container strategy. >> By the way, I hear if you do send back a belt or something that's broken to the Docker people, they'll fix it for you, and maybe send some whale stickers. >> It's like the old school Nordstroms where they take any return. They're this urban store, with the four tires return to Nordstrom, return some pants, you'll be fine. >> You know, we work on container strategy, but we're also your repair shop for you know, men's apparel. So, it's always interesting to look at-- >> Jim: Integration fabric. >> Brilliant. You know, the maturation of technology, of ecosystem, of monetization. I feel like you talked about the growth of the containers. We've seen the ecosystem. It's gone through some fits and spurts and changes over the last couple of years. I think we're really well-received this week. And then there's the money maturation and how they mature that. What do you see? How does open-source fit into your investment strategy, and any commentary on Docker and beyond? >> I was thinking about this on the flight over here today. Open source today is very different than open source five years ago, 10 years ago, as 15. So what what Red Hat did 20 years ago, is very different than what Xen tried to do 10 years ago. When I was at VMware, very different from what Docker is doing today. And it's different in a couple ways. I think the way you monetize is different. Because you have cloud, and cloud changes things. The ecosystem's very different, because all of a sudden the developers, contributors, are not just kind of your misfits and rebels working on the weekends. They are Fortune 100, Fortune 500 companies. Their jobs are now dedicated to this. And then the business models of the developers' ecosystem, how you work with them is very different. So before, you had maybe one or two models to make money in open source. Or one or two ways to develop a community. We did that at Red Hat, which Greylock was lucky enough to be investors in years ago. I was at VMware around Cloud Foundry, we built that. We had a model mine, we had a spring source as well, and what you've seen Docker in the past three or four years, is they're really pioneering a way to bring open source and community ecosystem into the next 10-20 years. So I think it's one to watch. I think Solomon's probably as good as anybody understanding what developers need. >> So a little broader, what's your thoughts on developers today? You actually made the comment coming over, there's two big developer shows this week. You've got F8 and you've got DockerCon, two very different communities. >> Right, it's kind of funny. There's always this sense of, do you consider yourself a developer? So if I write a line of JavaScript, am I a developer? My two cents is yes. If I'm a developer, from JavaScript to Swift to Docker to cURL hacking, it's all great. But if you look at those two conferences, you have F8 going on right now, and the announcements there around augmented reality and messaging, and it's trying to be a platform, but they're doing many of the same things. You have a distribution platform be it Messenger or Facebook, and they're open sourcing technologies around the camera, the lens, the filters, to have developers a) go through the channel, b) add apps or widgets. It's really beyond my ability to comprehend these filters, but Docker today announced a couple great projects: Moby and Linux Kit, much the same way as trying to give tools to the ecosystem developers to build what they want. I think what you've learned is, if you give developers the building blocks, the "Legos" as they call it today, they're going to build some awesome structures. >> Jim was, we talked about coming in here as the role of how data science fits into the developers, and developer is such a broad term, as to what we have here. >> One of the core themes I have is that the data scientist is the nucleus of next generation developer because much of the IP that's being built in the applications now, is statistical models and machine learning and so forth, driving recommendation, but much of that development is being containerized using new tool kits and so forth. But it needs to be more containerized so you can deploy statistical predictive models, machine learning, deep porting to routing the string ecosystem into a hybrid cloud to perform various functions. >> Right now there's, in most companies, there's a data engineer, there's a data scientist, and the two typically work hand in hand. >> Jim: One manages Hadoop, the other one does the modeling. >> Does the modeling, so one speaks in R and Python and works in Jupyter Notebook, the other person runs on Hadoop or database or Redis. The two need to work together and so what you're seeing now and obviously we're investors of Cloudera, that's another great open source company, what you see now is either a) a set of tools and technologies to either blend the two together in some cases, either enable engineers to be more data scientists, or enable data scientists to be more engineers, but also see a bunch of technology tools that say, no, two different roles, I'm going to create tools purpose-built for the data scientists, create tools purpose-built for the power of a data engineer. And I think there's space for both to the extent that you have applications running from news feed or ads to predicting how my self-driving car should make a left turn, you're going to need tools that are used by both types of populations. >> I think Cloudera now has a collaboration environment in the data science department. IBM has something very similar with what they're doing, so it's a team that has specialties such as coders, such as data modelers and data engineers. Point well taken. Cloudera's made a major entrance into that space of collaborative development, of these rich stacks of IP, essentially, that include deterministic program code, but also probabilistic models in a deepening stack. >> I think you've seen Cloudera definitely follow that path from Hadoop and low-level file system HDFS, to these high-level tools for data scientists that's becoming a platform for machine learning for these next generation applications. I think you see Docker in the infrastructure analogy doing low-level tools like Project Moby and Linux Kit, to high-level services around Docker Datacenter. So you can either have the basic tools for your low-level developer, or for the system admin or administrator who wants to operate or run the cloud, you have tools for him or her, too. >> It's interesting, you look at some of these projects and some of the maturation and pivots you see. We talked about dotCloud went over to Docker. You see a bunch of open stock companies that are now Kubernetes companies. I see companies that were big data, they're now, "Oh, I'm an AI or ML company." It's always like, it's usually not the tool, it's the wave. What is the driver? Is data the driver of our next wave there? Is it the application? Is it some combination of the two? Those are the two that I usually look at. Follow the data, follow the application. >> I would say it's data driving. It's really data application, it's data, and the applications make use of the data. Algorithms, I think, is a component. They're important, but they're a component. So what you see now is, to be on the right side of history, data is outstripping compute and storage, so the amount of videos and center data that we're generating from our phones, our cars, our homes, that is outstripping most of the other charts in compute, networking, whatever. That's definitely kind of a rising tide or a wave, as Stu was saying. Now how do we extract data, or value from this data? And historically, because you didn't have infrastructure, that cloud, or compute capacity to make use of this data, it was kind of stranded, so what you've seen in generation technologies like Hadoop or big data or cloud technologies like Docker did, is distribute your applications across a cloud. That's actually enabling you to now build applications to get value out of this data. And that value can be something like forecasting your sales this quarter. It can be about figuring which shade of brown belt you should wear with your pants, going back to our clothing analogy. Or it could be like, let me build a model around how this car or this drone should drive or fly itself. So you combine the vast amount of data, nearly infinite resource of compute, with these machine-learning or AI techniques. Machine learning is one AI technique, but all these other techniques, you can build another generation application, this new intelligent application to power everything from your home, your car, your watch, or your enterprise app, as wonderful as that is. >> Much of the sea change is less and less coding or programming is actually being done or needs to be done because more of the application logic is being distilled directly from the data in the form of machine learning. There's automated machine learning tools that are coming. Google has been a major investor as is Facebook in automated machine learning. >> I would say application logic from the inside, right. So in my mind, application logic, an application is reflecting business process. Hire to fire, order to cash. You still need a program that does logic. Data in itself, or AI in itself without that context, without that business process, is meaningless, right. Just having a model around Jim or Stu, it doesn't matter unless you're trying to buy something. Google pioneered machine learning in a workflow perfectly. You're searching for something, they knew who you were based upon history, you're searching the right ad and say, "Oh, you really want to buy a car, you want to buy a house." So in the workflow, or in the application logic of a search, they used ML to serve you timely information. Now if you're an enterprise, you're looking at help desk tickets, be it ITSM like ServiceNow, or support tickets like Zendesk supporting B to C support tickets. That's a workflow, there's application logic. They take information on a user or a grumpy customer, and they do things like automatically respond to a help ticket, reset your password, provision a server. So I think when you have AI or have applications using this data in the context of a business process, that's magic. And I think we're seeing some core technologies like TensorFlow out there that are super compelling. But we're seeing a generation of developers and founders take that technology, apply it to a problem, it could be HR or CRM, ITSM, or true vertical. Construction, finance, health care. >> Jim: Streaming media analytics is a core area where that's coming in. >> Media analytics because there's a ton of data. Understand what you watch and what you want to see, and so you apply things to a vertical, like health care, or apply the technology to a problem space like media analytics, and you have a wonderful application and hopefully a great company. >> Jerry, we've talked a lot at the cloud shows about how do the startups maintain relevant and get involved when there's all of these platforms. We talked about what Google does, Amazon of course is eating the entire world in everything. Microsoft is making lot of moves here. How do companies, what do you look for? Has your investment strategy changed at all in the last couple of years? >> It is daunting. I think about this a lot in terms of business models and defensibility, and the question goes, what are the sustainable moats you can build around your business as a startup anymore? 'Cause you feel like economies of scale and ecosystems, network effects, those were historically big defensive moats for a Windows operating system. Now those apply to Facebook's platform, Apple's platform, or AWS. They have scale and they have network effects for the ecosystem, so now your startup is saying, okay, how can I either a) overcome those moats, or b) how can I develop my own IP or my own moats around myself that I can actually sustain and thrive in this generation. I think you got to play a different game. As a startup, you're not going to try to out-scale Google or Microsoft; leave that to Amazon and those three or four players. But you can get scale in a domain, so either a problem space like autonomous vehicles, security is a great one, or vertical construction or health care. You redefine the market that you can dominate, can you build your own moat around that IP. >> It's interesting. did you hear Adrian Cockcroft who went from Battery Ventures over to AWS. He's like, "Well, rather than go startup that business, "come build that next thing at Amazon "and we'll do it there." Is that a viable way for people with the entrepreneurial spirit to go be part of that two-pizza team doing something cool inside a large platform? >> I think Adrian probably has motivation and more developers on Amazon now, but I would say most of our companies, not all, but a lot of them started at Amazon. Some start in ads, some start in Google, some start with their own data centers. I think what they believe is they'll get started in one of these clouds but I don't believe, so we talked about this first, it's not a one-cloud-rules-all world. I think there'll be three or four, if not more, clouds in every different geography from Europe to Asia to Russia to the US, will have different clouds, different players. So I think it's fine to get started in Amazon and be a two-pizza team with the other two-pizza team, but over time I see these applications being cross-cloud, and that's where something like Docker comes into play. Docker wants to be cross-cloud, better than any other technology out there. >> On some level, actually, the moat could be, or increasingly is, the training data that drives the refinement of your AI, like Tesla is a perfect example. The self-driving capabilities that they built into the vehicle, they have now a few years' worth of rich test data, training data I should say, that is a core moat in terms of continuing refinement of those algorithms. So that gives you sort of an example of some startup might come along with some very specialized application that takes the consumer world by storm and then they build up some deep well of training data in some very specialized area that becomes their core asset that their next competitor down the pipe doesn't have. >> It has to be a set of data that's unique or proprietary. You're not going to basically out-train your model on cat photos from Google, right? So it has to be a combination of either proprietary data or a combination of data sources that you can stick together. So it's not just one data source, I believe you have to combine multiple data sources together. >> So Jerry, sitting over Jim's shoulder is VMware's booth. I haven't talked about VMware at all this week. You worked at VMware, I've worked with VMware since pretty early days. What advice would you give VMware in the containerized cloud future? How should they be doing more to be part of more conversations? >> I think it's amazing that they have a presence here in the size and scale. The past couple years they're really done a lot to embrace containers and Docker, so I think that's first and foremost. They've done a couple great moves lately. Embracing Amazon last year, with VMware on Amazon, was a big move. Embracing containers with some of their cloud and data technologies I think was an aggressive move too. So I think they're moving in the right direction. I think what they need to understand is, are they going to revolutionize themselves and push these new technologies aggressively, or are they going to keep hanging onto some of their old businesses? For any company of their size and scale, they have multiple motivations, but I think they're making the right steps. So five years ago, or four years ago, I don't think they would have taken this DockerCon seriously. I don't think they were exhibitors at the first DockerCon. But in the past 24 months they've done some amazing moves, so I would say it makes me smile to see them take these great steps forward. >> Jerry, I want to give you the last word. Any cool companies we should be looking at, or things that are exciting to you without giving away trade secrets? >> I can't broadcast the companies I want because everyone else is going to chase those investments. I don't know, I think I'm going to enjoy spending time, actually less with the companies here but a lot with the developers and customers, because I think by the time they have a booth here, everybody knows the company's investment is probably too far along maybe for me to invest, maybe not. But talking to developers to hear what are their friction points? I think when you hear enough friction either in this ecosystem or another ecosystem or at AWS or VWware, then there's something there, you just got to scratch. >> I was talking to some of the people working the booths and they just said the quality of the attendees here, you learn something with every single person you talk to, and there's only a few shows that say that. Amazon reinvented one, the quality of the attendees always real good, this one and a few others. >> I think people who come here by definition are learners, both the companies and the individuals, and you want to surround yourself with learners, people who are open and honest and always learning. >> Jerry, I think that's a perfect note to end it on. We are always learners here and helping to help our audience in trying to understand these technologies, so Jerry Chen, always a pleasure. And we'll be back with the wrap-up here of day one DockerCon 2017. You're watching theCUBE. (techno music)

okay welcome back day two of the cube here and Las Vegas for live this is looking angles exclusive coverage of Amazon Web Services reinvent I'm John furrier with Dave vellante co-host of the cube Dave we got our first segment here we're pleased to have Jerry chin new venture capitalist cloud guru was at VMware it's been in the enterprise for a while guys welcome welcome to the cube Jay to kick off here at amazon reinvent Jerry welcome back decided Amy thanks for having guys cube alumni how was Hong Kong you just back from I'm stack I think Hong Kong was great my my body and time clocks someplace our Pacific though so I don't know them jet lag but thank God in Vegas I never need to leave the building so I don't need to know what time is on my mom actually in so it's good to be here so Amazon's pushing the cloud hard obviously they are the cloud huge market share on infrastructure as a service check the boxes there they got like thirty six percent by are not I think it's much higher than that actually her but jesse was saying today well I mean by vechs the next 14 it's got to be higher than thirty six percent I think it's closer to seven but ok that's infrastructure service but the actions platform as a service and SAS yeah if you can I got to get your take on guys we're following OpenStack you were just in Hong Kong you got amazon public cloud you get OpenStack coming up you know as that horse those a two-horse race right now clouds Dax out there but really it's OpenStack is like the enterprise hope it's the great hope for the enterprise with Amazon kind of rolling rolling out massive services what's your take on the two and and and is it a two-horse race and what's what's what's the what's the difference between the two you know I don't think it's a it's a two horse race yet but Amazon is quickly becoming the marker soph monopoly of the public cloud at the rate they're going and and it there have the size and scale that pretty soon to be really hard to compete and I think only google and maybe Marcus off and the public cloud space can really compete but if you take a step back and look at you know to your question OpenStack versus amazon I was in Hong Kong last week the OpenStack design summit and openstax philosophies one be all things to all people right it's open source multiple projects Amazon's philosophy is they want to be one cloud all people so you saw their announcements today around enterprise use cases desktop use cases startup use cases me to use cases there won't be one cloud to all people so it is not the race isn't over yet but very different philosophies right now between the two different cams was there much to talk about incorporating amazon api's into the whole OpenStack framework you know six months ago you heard a lot about that we had a crowd chatter on that run what was the the buzz there you know I I'll be honest into to the point that you guys brought up early around the Amazon ap is almost are becoming a lingua franca for infrastructure of a service but quite frankly debating whatnot they're the right api's or not isn't I think where the actions and the actions add to the point you made around pass and other developer services so the actual API so you do the api's right should be pretty easy for developers to adopt you just create really great developer service around it database services storage services security services those are what developers really care about so I feel like we have you know sometimes called cloud plus there are infrastructure service plus and you got sass minus you know it's like what you have with Salesforce do you feel like we really need that pass layer does that just sort of bifurcate into one of those two there's there's a there's a school of thought that says the world goes into two worlds a long telus a sax so there's an app for everything in which case you have SAS or SATA minus and then you know infrastructure private cloud for a budget likes the apps there's no middle ground for pass you know I'm more towards the middle ground because in a world where we have multiple SAS providers in multiple clouds I believe you're going to have multiple SAS multiple clouds you're going to need to integrate and stitch together a mash-up of applications right you have work day for HCM Salesforce for crm applications your own custom website running on amazon there are three different kinds now servers now how are you connect the data are going to move data around there's going to be at least some kind of past layer integration layer or cloud layer that needs to help stitch together this multi-cloud world so you like the pivotal play a pill I think the concept Indian concept right I think Paul is is a pulse of visionary and bus my friends to work there their announcement yes sir was was I think a step in the right direction that they're planning a flag saying that there has to be something beyond amazon there has to be a relevant private cloud initiative be it VMware or OpenStack of someplace else and let's create some services around it and the angle are taking around data and data services i think is proud of the right the right bed because all these new applications will need these data services to be relevant we were talking about pivotal yesterday one of the things that we were critical on and but also hopeful as you pointed out it's early right so true pivotal a mulligan or a pass if you will is this early and it's really a new company if you think about a 1,600 employees but new but it's window dressing announcement it really wasn't really i mean so the same logos i mean come on that they're trying to overhype and that's that was that's what people are talking about saying hey guys just be honest and say we're working as fast as i can because amazon is not going to break the enterprise right away I mean they also have a longer road going hard at the enterprise so they are going after IBM we must saw in the keynote that called out IBM specifically around some of the advertising there on the show yeah so Amazon is clearly trying to knock on the door or the enterprise so the question we are asking and talking about is how much time is it till they proliferate the enterprise I mean they're in there now toe in the water little beachhead still not enterprise-ready in the ends of the SLA s and the demands or does it matter so what's your take how much time is really on the radar for Amazon when will the clock be expiring for the IBM's HP pivotal's in terms of retooling so I think the evolution around enterprise public cloud like Amazon would take three potential paths so path one around amazon amazon invests enough engineering and product talent to make their cloud enterprise friendly privacy security reliability and they're they're hiring a bunch of folks a bunch of folks my old place vmware try to do that that's path one path to is you see a category of startups out there trying to meet amazon more cloud and enterprise friendly security privacy reliability right so that's path to and as a Greylock a venture capitalist we're investing a bunch of companies trying to you make that happen or past three is developers out there I'm engineer around the weaknesses amazon so the new Amazon is an enterprise friendly they know and about Amazon's got a bunch of weakness around security and privacy and he's just right there application around those weaknesses so I think those are the three evolutionary path paths I think it's a race to see who wins right one two or three yeah there's no doubt that Amazon is forcing the hand of the big guys he's seeing that clearly we have a question on our crowd check go to crowd chatting at / reinvent we've got a live live crowd-sourced thought leader chat there all those to Twitter and LinkedIn pendulum will you sign in but the question Jerry to you is how our cloud providers catering to provide low latency access to developing markets like India Indonesia Philippines etc you know given that the Hurricanes just destroyed all the infrastructure considering there's huge potential explosive internet growth so given that those new emerging markets are essentially refreshing their infrastructure what is the the cloud providers take on the end you do you work in that area what you're giving the opinion on what's going on in those areas sure I mean I think that the world is looking at two or three different clouds you say there's a u.s. dominated cloud maybe a China dominate cloud and rest of the world right generally a lot of analyst kind of segment the world in three major pockets when you think about developing markets or other geographies like Asia South Asia or South America huge markets lot of developers all applications it's the reason why I think there's only a handful of providers that can have the scoop in the reeds to reach globally I think Equinix Rackspace on Google Marcus off or all global footprint players everyone else I think you're going to look at a Federation of multiple players so every region has a local telco cloud provider it could be like an entity or rakuten in Japan it could be a sink tell in Singapore South East Asia so I think you're going to see a global brand around like Amazon or or VMware and VMware trying to franchise our own cloud or Microsoft and then I would see partnerships working between the different geographies and maybe OpenStack is that partnership maybe amazon API is the way different class communicate its remains to be seen what that interface between the different gos look like in the future what do you see as IBM's role I mean first of all do they have the global scale are you sort of purposefully leaving them out or just forget about them and just don't feel like they can compete on that global scale what do you see is their role in OpenStack so um bunch of questions there IBM didn't mean to leave them out there are definitely relevant especially for the large enterprises so I think you're seeing enterprise adoption come from large startups or small starts growing up in the cloud as well as large enterprises that are looking to modernize your applications and I think IBM has a great role to play from kind of that top-down approach I think IBM between a combination of a soft layers which is their their acquired cloud provider combined with their global services and their consulting business will be really relevant to large enterprises my mind so talk about the Amazon enterprise marchi obviously they're talking about cloud trails which is kind of like a monitoring service compliance oriented and I'll see vbi so you you've been close to the vdi movement so that's those are I started VDI hearted the beady eye movement so you know being there what is your take on that because that's very enterprising and that's rude good for business I'm what sir what's their chances there well I think so first on the vdi market we started that at VMware at 05 06 we coined the term VDI and I think it's a great service for large enterprises than need secure mass desktops I think I would love to see in a VDI service from VMware in Amazon five six seven years ago because now video i think is part of a larger solution it's it's it's significant but not enough right he's now enterprise to care about their madness desktops like VDI but my ipad devices iOS devices Android devices they really want kind of a holistically managed desktop or workspace environment so if i were amazon i would expand beyond windows and two other you know operating systems to manage like android and iOS but that's other serious about you know managing enterprise workspaces do they have do they have advantage and you're in your opinion despite the fact that they're so late to market do they have an advantage in that and I mean in essence they are starting around mobile developers aren't they whereas when you started that was especially a consideration Wright and Citrix sort of found its way there right but I think between um amazon I think Google's in a great position because they own so much of the Android stack right if they want to create an enterprise friendly manage um Android environment for Chromebooks Android devices they can start creating a bunch of great developer services like magic google drive but secured on on kind of a google cloud or something like that that could be pretty compelling I don't know if they're going there i think dropbox has a great opportunity kind of be that back and platform obviously Greylock investment but dropbox has a huge opportunity to be that kind of manage secure servers across mobile devices and desktop devices it's all a sudden the one overarching fact you have between Windows iOS and Android is your data and drop boxes on all three platforms chair we got to get rolling and we got in our next guest but I want to ask you actually talk about what you're investing in at greylock rate locked here 1dc you guys have done amazing deals I mean just recently in the past decade Greylock has emerged from just a tier 1 BC to a mega success good investments and if you're on the enterprise team they're actually the consumer side kick ass what's going on for you guys what are you investing in what are you looking at and if price is not an easy game to invest in obviously it's hard but what are you guys doing what are you investing what are you looking for I'm thinking about looking at across the categories most relevant for this audience is I'm really interested looking at startups that can either a make amazon a more enterprise funding cloud or be startups that will pose alternative or challenge to amazon in the enterprise cloud space and you do that either by you know focus on enterprise requirements or focus on enterprise services like data storage security that matter enterprises focus on doing that really really well better than vmware better than Microsoft there in the Amazon I think in the build a really big enterprise cloud business around those technology services you're essentially betting on that transformation from the way the world is the cloud is post of the world known as buying servers they're all trying to find a lab partner that's the direction and and are you bullish on this integrated stack offering obviously DevOps has been a big success you see Facebook you see Google you see Amazon building their own gear they were kind of saying we're not playing an open compute but sure that aside DevOps is a software model absolutely and so the integrated stack which are common on integrated stack and how that's going to involve for both the mainstream of DevOps absolutely so you see this DevOps culture permeating first development of applications now how you manage your infrastructure so you look at what's happened with open compute and open source switches which I think open compute project announced a couple days ago you're seeing that kind of DevOps culture and how they manage and update their applications / minate storage compute and now networking that's going to be kind of a common adoption curve throughout the cloud so the way DevOps technologies are getting adopted from languages to frameworks of databases is the same way we're seeing storage compute and networking technologies get adopted in this next cloud wave what's your take on the iphone for the enterprise amazon cloud kind of metaphor and OpenStack being more the Android we were talking earlier right just get your thoughts there an OpenStack also has a lot of legs right now but it's very open iPhone model or Amazon is kind of closed or some say lock in alright but it still apps are not closed right so the metaphor the metaphor was you know iphone is to Amazon as Android is to OpenStack and I think at a high level that kind of makes sense but not really because there's no Google behind OpenStack like there's a google behind Android so I think Rackspace is was an early leader and still as a leader in the OpenStack space but there's also red hat there's a bunch of the players there so as a result there's no single entity kind of driving OpenStack like Google's driving Android so that analogy can breaks down and then as far as Apple analogy to Amazon I I think Amazon is a lot more open than the iOS ecosystem is because just the fact that there's no governing board to prove her apps to launch on amazon right I can go stand up on an ec2 instance lost my application use it I don't need wait for this there's not a 20-page approval process so knowingly directionally that's more correct than not but it's analogy breaks down when you really get into it and OpenStack your prospects roman sec what's your what's your outlook on OpenStack real quick I think OpenStack so holistically i think is great a more bullets than sort of sub projects that i am overall I think they keep launching new projects some are better than others the core processing around compute and storage and this um API management I'm bullish on I'm supposed to be bullish on what they're doing around containers like docker and core OS and kind of adopting this next generation of cloud platforms well we got to go we got some fans out there want to hear what your take on VDI so go tweet to at jerry chen j ER are wide CH en we got a break here we'd love to have you on a little longer we got our next guest coming on it's the cube live in Las Vegas day two of Amazon's reinvent changing the cloud game and the enterprise and we get all the detailed coverage here on the key we'll be right back after this short break the cute

>>Good afternoon everyone, and welcome back to Cuan where my cohost John Farer and I are broadcasting live, along with Lisa Martin from Cuan Detroit, Michigan. We are joined this afternoon by two very interesting gentlemen who also happen to be legends on the cube. John, how long have you known the next few? They've, >>They've made their mark on the cube with Jerry Chen from Greylock was one of our most attended cube guests. He's a VC partner at Greylock and an investor and this company that just launched their new cloud observability platform should be a great segment. >>Well, I'm excited. I are. Are you excited? Should I string this out just a little bit longer? No, I won't. I won't do that to you. Please welcome Martin and Jeff from Chronosphere Martin. Jeff, thank you so much for being >>Here. Thank you for having us. Thank you. >>I noticed right away that you have raised a mammoth series C. Yeah. 200 million if I'm not mistaken. >>That is correct. >>Where's the company at? >>Yeah, so we raised that series C a year ago. In fact, we were just talking about it a year ago at Cub Con. Since then, at the time we're about 80 employees or so. Since then, we've tripled the headcount, so we're over 200 people. Casual, triple casual, triple of the headcount. Yeah. Luckily it was the support of business, which is also tripled in the last year. So we're very lucky from that perspective as well. And a couple of other things we're pretty proud of last year. We've had a hundred percent customer retention, which is always a great thing to have as a SaaS platform there. >>Real metric if you've had a hundred percent. I'm >>Kidding. It's a good metric to, to put out there if you had a hundred percent. I would say for sure. It's an A for sure and exactly welcome to meet >>Anyone else who's had a hundred percent >>Customer attention here at coupon this week and 90% of our customers are using more of the service and, and you know, therefore paying more for the service as well. So those are great science for us and I think it shows that we're clearly doing something right on the product side. I would say. And >>Last and last time you're on the cube. We're talking about about the right data. Not so much a lot of data, if I remember correctly. Yeah, a hundred percent. And that was a unique approach. Yeah, it's a data world on relative observability. And you guys just launched a new release of your platform, cloud native platform. What's new in the platform? Can you share an update on what you guys release? >>Yeah, well we did and, and you, you bring up a great point. You know, like it's not just in observably but overall data is exploding. Alright, so three things there. It's like, hey, can your platform even handle the explosion of data? Can it control it over time and make sure that as your business grows, the data doesn't continue explode at the same time. And then for the end users, can they make sense of all this data? Cuz what's the point of having it if the end users can't make sense of it? So actually our product announcement this time is a pretty big refresh of, of a lot of features in our, in our platform. And it actually tackles all three of these particular components. And I'll let Jeff, our head of product, Doug, >>You, you run product, you get the keys to the kingdom, I do product roadmap. People saying, Hey this, take this out. You're under a lot of pressure. What makes the platform platform a great observability product? >>So the keystone of what we do that's different is helping you control the data, right? As we're talking about there's an infinite amount of data. These systems are getting more and more and more complicated. A lot of what we do is help you understand the utility of the telemetry so that you can optimize for keeping and storing and paying for the data that's actually helpful as opposed to the stuff that isn't. >>What's the benefit now with observability, with all the noise out in the marketplace, there's been a shift over the past couple years. Cloud native at scale, you're seeing a lot more automation, almost a set to support the growth for more application development. We had a Docker CEO on earlier today, he said there are more applications being deployed in the past year than in the history of open source. So more and more apps are being deployed, more data's being generated. What's the key to observability right now that's gonna separate the winners from the losers? >>Yeah, I think, you know, not only are there more applications being deployed, but there are smaller and small applications being deployed mostly on containers these days more than if they, hence this conference gets larger and larger every year. Right? So, you know, I think the key is a can your system handle this data explosion is, is the first thing. Not only can it handle the data explosion, but you know, APM solutions have been around for a very long time and those were really introspecting into an application. Whereas these days what's more important is, well how is your application interfacing with every other application in your distributed architecture there, right? So the use case is slightly different there. And then to what Jeff was saying is like once the data is there, not only making use of what is actually useful to you, but then having the end user make sense of it. >>Because we, we, we always think about the technology changes. We forget that the end users are different now we used to have IT operations team operating everything and the developers would write the application, just throw it over the wall. These days the developers have to actually operate this thing in production. So the end users of these systems are very different as well. And you can imagine these are folks, your average developer as maybe not operated things for many years in production before. So they need to, that they need to pick up a new skill set, they need to use new tooling in order to, to do that. So yeah, it's, it's, >>And you got the developer persona, you got a developer that's building products for builders and developers that are building products to be consumed. So they're not, they're not really infrastructure builders, they're just app developers. >>Exactly. Exactly. That's right. And that's what a lot of the new functionality that we're introducing here at the show is all about is helping developers who build software by day and are on call by night, actually get in context. There's so much data chances of when that, when one of those pages goes off and your number comes up, that the problem happens to be in the part of the system that you know a lot about are pretty low, chances are you're gonna get bothered about something else. So we've built a feature, we call it collections that's about putting you in the right context and connecting you into the piece of the system where the problem is to orient you and to get you started. So instead of waiting through, through hundreds of millions of things, you're waiting through the stuff that's in the immediate neighborhood of where the >>Problem is. Yeah. To your point about data, you can't let it go unchecked. That's right. You gotta gotta understand that. And we were talking about containers again with, again with docker, you know, nuance point, but oh, scan your container. But not everyone's scanning the containers security nightmare, right? I mean, >>Well I think one of the things that I, I loved in reading the notes in preparation for you coming up is you've actually created cloud native observability with the goal of eliminating engineering burnout. And what you're talking about there is actually the cognitive burden of when things happen. Yeah, for sure. We we're, you know, we're not just designing for when everything goes right, You need to be prepared for when everything goes wrong and that poor lonely individual in the middle of the night has, it's >>A tough job. >>Has to navigate that >>And, and observability is just one thing you gotta mean like security is another thing. So, so many more things have been piled on top of the developer in addition to actually creating the application. Right? It is. There is a lot. And you know, observably is one of those key things you need to do your job. So as much as, as much as we can make that easier, that's a better bit. Like there are so many things being piled on right now. >>That's the holy grail right there. Because they don't want to be doing exactly >>The work. Exactly. They're not observability experts. >>Exactly. And automating that in. So where do you guys weigh in on the automation wave? Everything's automation. Yeah. Is that kind of a hand waving or what's going on? What's the reality? What's actually happening? >>Yeah, I think automation I think is key. You hear a lot of ai ml ops there. I, I don't know if I really believe in that or having a machine self heal itself or anything like that. But I think automation is key because there are a lot of repeatable tasks in a lot of what you're doing. So once you detect that something goes wrong, generally if you've seen it before, you know what the fix is. So I think automation plays a key on the sense that once it's detected again the second time, the third time, okay, I know what I did the previous time, let, let's make sure we can do that again. So automation I think is key. I think it helps a lot with the burnout. I dunno if I'd go as far as the >>Same burnout's a big deal. >>Well there's an example again in the, in the stuff we're releasing this week, a new feature we call query accelerator. That's a form of automation. Problem is you got all this data, mountain of data, put you in the right context so you're at least in the right neighborhood, but now you need to query it. You gotta get the data to actually inform the specific problem you're trying to solve. And the burden on the developer in that situation is really high. You have to know what you're looking for and you have to know how to efficiently ask for it. So you're not waiting for a long time and >>We >>Built a feature, you tell us what you want, we will figure out how to get it for you efficiently. That's the kind of automation that we're focused on. That's actually a good service. How can we, it >>Sounds >>Blissful. How can we accelerate and optimize what you were gonna do anyway, rather than trying to read your mind or predict the future. >>Yes, >>Savannah, some community forward. Yeah, I, I'm, so I'm curious, you, you clearly lead with a lot of empathy, both of you and, and putting your, well you probably have experience with this as well, but putting your mind or putting yourself in the mind to the developer are, what's that like for you from a product development standpoint? Are you doing a lot of community engagement? Are you talking to developers to try and anticipate what they're gonna be needing next in terms of, of your offering? Or how has that work >>For you? Oh, for sure. So, so I run product, I have a lot of product managers who work for me. Somebody that I used to work with, she was accusing me, but what she called, she called me an anthropologist of a product manager. I >>Get these kind of you, the very good design school vibes from you both of you, which >>Is, and the reason why she said the way you do this, you go and you live with them in order to figure out what a day in their life is really like, what the job is really like, what's easy, what's hard. And that's what we try to aim at and try to optimize for. So that's very much the way that we do all of >>Our work. And that's really also highlights the fact that we're in a market that requires acute realtime data from the customer. Cause it's, and it's all new data. Well >>Yeah, it's all changing. The tools change every day. I mean if we're not watching how, and >>So to your point, you need it in real time as well. The whole point of moving to cloud native is you have a reliable product or service there. And like if you need to wait a few minutes to even know that something's wrong, like you've already lost at that point, you've already lost a ton of customers, potentially. You've already lost a ton of business. You know, to your point about the, the community earlier, one other thing we're trying to do is also give back to the community a little bit. So actually two days ago we just announced the open source of a tool that we've been using in our product for a very long time. But of course our product is, is a paid product, right? But actually open source a part of that tool thus that the broader community can benefit as well. And that tool which, which tool is that? It's, it's called Prom lens. And it's actually the Prometheus project is the open sourced metrics project that everybody uses. So this is a query builder that helps developers understand how to create queries in a much more efficient way. We've had in our product for a long time, but we're like, let's give that back to the community so that the broader community of developers out there can have a much easier time creating these queries as well. What's >>Been the feedback? >>We only now it's two days ago so I'm not, I'm not exactly sure. I imagine >>It's great. They're probably playing with it right now. >>Exactly. Exactly. Exactly. For sure. I imagine. Great. >>Yeah, you guys mentioned burnout before and we heard this a lot now you mentioned in terms of data we've been hearing and reporting about Insta security world, which is also data specific observability ties right into security. Yep. How does a company figure out, first of all, burnout's a big problem. It's more and more data coming. It's like, it's like doesn't stop and the breaches are coming too. How does a company know when they need that their observability strategy is broken? Is there sig signs of you know, burnout? Is there signs of breaches? I mean, what are some of the tell signs that if I'm a CSO I go, you know what, maybe I should check out promisee. When do, when do you guys match in and go we're a perfect fit to solve that problem? >>Yeah, I, I would say, you know, because we're focused on the observability side, less so on the security side, some of those signals are like how many incidents do you have? How many outages do you have? What's the occurrence of these things and how long does it take to recover from from from these particular incidents? How >>Upsetting are we finding customers? >>Upsetting are >>Customer. Exactly. >>And and one trend was seeing >>Not churn happening. Exactly. >>And one trend we're seeing in the industry is that 68% of companies are saying that they're having more incidents over time. Right. And if you have more incidents, you can imagine more engineers are being paid, are being woken up and they're being put under more stress. And one thing you said that very interesting is, you know, I think generally in the observability world, you ideally actually don't want to figure out the problem when it goes wrong. Ideally what you want to do these days is figure out how do I remediate this and get the business back to a running state as quickly as I can. And then when the business isn't burning, let me go and figure out what the underlying root cause is. So the strategy there is changed as well from the APM days where like I don't want to figure out the problem in real time. I wanna make sure my business and my service is running as it should be. And then separately from that, once it is then I wanna go >>Under understand that assume it's gonna happen, be ready to close that isolate >>The >>Fire. Exactly. Exactly. And, and you know, you can imagine, you know the whole movement towards C I C D, like generally when you don't touch a system, nothing goes wrong. You deploy change, first thing you do is not figure out why you change break thing. Get that back like underplay that change roll that change back, get your business back to a estate and then take the time where you're not under pressure, you're not gonna be burnt out to figure out what was it about my change that that broke everything. So, yeah. Got >>It. >>Well it's not surprising that you've added some new exciting customers to the roster. We have. We have. You want to tell the audience who they might >>Be? Yes. It's been a few big names in the last year we're pretty excited about. One is Snapchat, I think everybody knows, knows that application And one is Robin Hood. So you know, you can imagine very large, I'll say tech forward companies that have completed their migrations to, to cloud native or a wallet on their way to Cloudnative and, and we like helping those customers for sure. We also like helping a lot of startups out there cause they start off in the cloud native world. Like if you're gonna build a business today, you're gonna use Kubernetes from day one. Right? But we're actually interestingly seeing more and more of is traditional enterprises who are just early, pretty early on in their cloudnative migration then now starting to adopt cloud native at scale and now they're running to the same problems. As well >>Said, the Gartner data last year was something like 85% of companies had not made that transformation. Right. So, and that, I mean that's looking at larger scale companies, obviously >>A hundred, you're >>Right on the pulse. They >>Have finished it, but a lot of them are starting it now. So we're seeing pilot >>Projects, testing and cadence. And I imagine it's a bit of a different pace when you're working with some of those transforming companies versus those startups that are, are just getting rolling. I >>Love and you know, you have a lot of legacy use case you have to, like, if you're a startup, you can imagine there's no baggage, there's no legacy. You're just starting brand new, right? If you're a large enterprise, you have to really think about, okay, well how do I get my active business moved over? But yeah. >>Yeah. And how do you guys see the whole cloud native scale moving with the hyper scales? Like aws? You've got a lot of multi-cloud conversation. We call it super cloud in our narrative, but there's now this new, we're gonna get some of common services being identified. We're seeing a, we're seeing a lot more people recognize and with Kubernetes that hey, you know what, you could get some common services maybe across clouds with SOS doing storage. We got Min iOS doing some storage. Yeah. Cloud flare, I mean starting to see a lot more non-hyper scale systems. >>Yeah, I mean I, and I think that's the pattern there and I think it, it's, especially for enterprise at the top end, right? You see a, a lot of companies are trying to de-risk by saying, Hey, I, I don't want to bet maybe on one cloud provider, I sort of need to hedge my bets a little bit. And Kubernetes is a great tool to go do that. You can imagine some of these other tools you mentioned is a great way to do that. Observability is another great way to do that. Or the cloud providers have their observability or monitoring tooling, but it's really optimized just for that cloud provider, just for those services there. So if you're really trying to run either your custom applications or a multi-cloud approach, you really can't use one cloud providers solution to go solve that problem. Do you >>Guys see yourselves with that unifying >>Layer? We, we, we are a little bit as that lay because it's agnostic to each of the cloud providers. And the other thing is we actually like to understand where our customers run and then try to run their observability stack on a different cloud provider. Cuz we use the cloud ourselves. We're not running our own data centers of course, but it's an interesting thing where everybody has a common dependency on the cloud provider. So when us e one ofs hate to call them out, but when us E one ofs goes down, imagine half the internet goes down, right? And that's the time that you actually need observability. Right? Seriously. And every other tooling there. So we try to find out where do you run and then we try to actually run you elsewhere. But yeah, >>I like that. And nobody wants to see the ugly bits anyway. Exactly. And we all know who when we're all using someone when everything >>Exactly. Exactly, exactly. >>People off the internet. So it's very, I, I really love that. Martin, Jeff, thank you so much for being here with us. Thank you. What's next? What, how do people find out, how do they get one of the jobs since three Xing your >>Employee growth? We're hiring a lot. I think the best thing is to go check out our website chronosphere.io. You'll find out a lot about our, our, our careers, our job openings, the culture we're trying to build here. Find out a lot about the product as well. If you do have an observability problem, like that's the best place to go to find out about that as well. Right. >>Fantastic. Well if you want to join a quarter billion, a quarter of a billion dollar rocket ship over here and certainly a unicorn, get in touch with Martin and Jeff. John, thank you so much for joining me for this very special edition and thank all of you for tuning in to the Cube live here from Motor City. My name's Savannah Peterson and we'll see you in a little bit. >>Robert Herbeck. People obviously know you from Shark Tanks, but the Herbeck group has been really laser focused on cyber security. So I actually helped to bring my.

(bright upbeat music) >> Welcome back, everyone, to the "Supercloud 22." I'm John Furrier, host of "The Cube." This is the Cloud-erati panel, the distinguished experts who have been there from day one, watching the cloud grow, from building clouds, and all open source stuff as well. Just great stuff. Good friends of "The Cube," and great to introduce back on "The Cube," Adrian Cockcroft, formerly with Netflix, formerly AWS, retired, now commentating here in "The Cube," as well as other events. Great to see you back out there, Adrian. Lori MacVittie, Cloud Evangelist with F5, also wrote a great blog post on supercloud, as well as Dave Vellante as well, setting up the supercloud conversation, which we're going to get into, and Chris Hoff, who's the CTO and CSO of LastPass who's been building clouds, and we know him from "The Cube" before with security and cloud commentary. Welcome, all, back to "The Cube" and supercloud. >> Thanks, John. >> Hi. >> All right, Lori, we'll start with you to get things going. I want to try to sit back, as you guys are awesome experts, and involved from building, and in the trenches, on the front lines, and Adrian's coming out of retirement, but Lori, you wrote the post setting the table on supercloud. Let's start with you. What is supercloud? What is it evolving into? What is the north star, from your perspective? >> Well, I don't think there's a north star yet. I think that's one of the reasons I wrote it, because I had a clear picture of this in my mind, but over the past, I don't know, three, four years, I keep seeing, in research, my own and others', complexity, multi-cloud. "We can't manage it. They're all different. "We have trouble. What's going on? "We can't do anything right." And so digging into it, you start looking into, "Well, what do you mean by complexity?" Well, security. Migration, visibility, performance. The same old problems we've always had. And so, supercloud is a concept that is supposed to overlay all of the clouds and normalize it. That's really what we're talking about, is yet another abstraction layer that would provide some consistency that would allow you to do the same security and monitor things correctly. Cornell University actually put out a definition way back in 2016. And they said, "It's an architecture that enables migration "across different zones or providers," and I think that's important, "and provides interfaces to everything, "makes it consistent, and normalizes the network," basically brings it all together, but it also extends to private clouds. Sometimes we forget about that piece of it, and I think that's important in this, so that all your clouds look the same. So supercloud, big layer on top, makes everything wonderful. It's unicorns again. >> It's interesting. We had multiple perspectives. (mumbles) was like Snowflake, who built on top of AWS. Jerry Chan, who we heard from earlier today, Greylock Penn's "Castles in the Cloud" saying, "Hey, you can have a moat, "you can build an advantage and have differentiation," so startups are starting to build on clouds, that's the native cloud view, and then, of course, they get success and they go to all the other clouds 'cause they got customers in the ecosystem, but it seems that all the cloud players, Chris, you commented before we came on today, is that they're all fighting for the customer's workloads on their infrastructure. "Come bring your stuff over to here, "and we'll make it run better." And all your developers are going to be good. Is there a problem? I mean, or is this something else happening here? Is there a real problem? >> Well, I think the north star's over there, by the way, Lori. (laughing) >> Oh, there it is. >> Right there. The supercloud north star. So indeed I think there are opportunities. Whether you call them problems or not, John, I think is to be determined. Most companies have, especially if they're a large enterprise, whether or not they've got an investment in private cloud or not, have spent time really trying to optimize their engineering and workload placement on a single cloud. And that, regardless of your choice, as we take the big three, whether it's Amazon, Google, or Microsoft, each of them have their pros and cons for various types of workloads. And so you'll see a lot of folks optimizing for a particular cloud, and it takes a huge effort up and down the stack to just get a single cloud right. That doesn't take into consideration integrations with software as a service, instantiated, oftentimes, on top of infrastructure of the service that you need to supplement where the obstruction layer ends in infrastructure of the service. You've seen most IS players starting to now move up-chain, as we predicted years ago, to platform as a service, but platforms of various types. So I definitely see it as an opportunity. Previous employers have had multiple clouds, but they were very specifically optimized for the types of workloads, for example, in, let's say, AWS versus GCP, based on the need for different types and optimized compute platforms that each of those providers ran. We never, in that particular case, thought about necessarily running the same workloads across both clouds, because they had different pricing models, different security models, et cetera. And so the challenge is really coming down to the fact that, what is the cost benefit analysis of thinking about multi-cloud when you can potentially engineer the resiliency or redundancy, all the in-season "ilities" that you might need to factor into your deployments on a single cloud, if they are investing at the pace in which they are? So I think it's an opportunity, and it's one that continues to evolve, but this just reminds me, your comments remind me, of when we were talking about OpenStack versus AWS. "Oh, if there were only APIs that existed "that everybody could use," and you saw how that went. So I think that the challenge there is, what is the impetus for a singular cloud provider, any of the big three, deciding that they're going to abstract to a single abstraction layer and not be able to differentiate from the competitors? >> Yeah, and that differentiation's going to be big. I mean, assume that the clouds aren't going to stay still like AWS and just not stop innovating. We see the devs are doing great, Adrian, open source is bigger and better than ever, but now that's been commercialized into enterprise. It's an ops problem. So to Chris's point, the cost benefit analysis is interesting, because do companies have to spin up multiple operations teams, each with specialized training and tooling for the clouds that they're using, and does that open up a can of worms, or is that a good thing? I mean, can you design for this? I mean, is there an architecture or taxonomy that makes it work, or is it just the cart before the horse, the solution before the problem? >> Yeah, well, I think that if you look at any large vendor... Sorry, large customer, they've got a bit of everything already. If you're big enough, you've bought something from everybody at some point. So then you're trying to rationalize that, and trying to make it make sense. And I think there's two ways of looking at multi-cloud or supercloud, and one is that the... And practically, people go best of breed. They say, "Okay, I'm going to get my email "from Google or Microsoft. "I'm going to run my applications on AWS. "Maybe I'm going to do some AI machine learning on Google, "'cause those are the strengths of the platforms." So people tend to go where the strength is. So that's multi-cloud, 'cause you're using multiple clouds, and you still have to move data and make sure they're all working together. But then what Lori's talking about is trying to make them all look the same and trying to get all the security architectures to be the same and put this magical layer, this unicorn magical layer that, "Let's make them all look the same." And this is something that the CIOs have wanted for years, and they keep trying to buy it, and you can sell it, but the trouble is it's really hard to deliver. And I think, when I go back to some old friends of ours at Enstratius who had... And back in the early days of cloud, said, "Well, we'll just do an API that abstracts "all the cloud APIs into one layer." Enstratius ended up being sold to Dell a few years ago, and the problem they had was that... They didn't have any problem selling it. The problem they had was, a year later, when it came up for renewal, the developers all done end runs around it were ignoring it, and the CIOs weren't seeing usage. So you can sell it, but can you actually implement it and make it work well enough that it actually becomes part of your core architecture without, from an operations point of view, without having the developers going directly to their favorite APIs around them? And I'm not sure that you can really lock an organization down enough to get them onto a layer like that. So that's the way I see it. >> You just defined- >> You just defined shadow shadow IT. (laughing) That's pretty- (crosstalk) >> Shadow shadow IT, yeah. >> Yeah, shadow shadow it. >> Yeah. >> Yeah. >> I mean, this brings up the question, I mean, is there really a problem? I mean, I guess we'll just jump to it. What is supercloud? If you can have the magic outcome, what is it? Enstratius rendered in with automation? The security issues? Kubernetes is hot. What is the supercloud dream? I guess that's the question. >> I think it's got easier than it was five, 10 years ago. Kubernetes gives you a bunch of APIs that are common across lots of different areas, things like Snowflake or MongoDB Atlas. There are SaaS-based services, which are across multiple clouds from vendors that you've picked. So it's easier to build things which are more portable, but I still don't think it's easy to build this magic API that makes them all look the same. And I think that you're going to have leaky abstractions and security being... Getting the security right's going to be really much more complex than people think. >> What about specialty superclouds, Chris? What's your view on that? >> Yeah, I think what Adrian is alluding to, those leaky abstractions, are interesting, especially from the security perspective, 'cause I think what you see is if you were to happen to be able to thin slice across a set of specific types of workloads, there is a high probability given today that, at least on two of the three major clouds, you could get SaaS providers that sit on those same infrastructure of the service clouds for you, string them together, and have a service that technically is abstracted enough from the things you care about to work on one, two, or three, maybe not all of them, but most SaaS providers in the security space, or identity space, data space, for example, coexist on at least Microsoft and AWS, if not all three, with Google. And so you could technically abstract a service to the point that you let that level of abstract... Like Lori said, no computer science problem could not be... So, no computer science problem can't be solved with more layers of abstraction or misdirection... Or redirection. And in that particular case, if you happen to pick the right vendors that run on all three clouds, you could possibly get close. But then what that really talks about is then, if you built your seven-layer dip model, then you really have specialty superclouds spanning across infrastructure of the service clouds. One for your identity apps, one for data and data layers, to normalize that, one for security, but at what cost? Because you're going to be charged not for that service as a whole, but based on compute resources, based on how these vendors charge across each cloud. So again, that cost-benefit ratio might start being something that is rather imposing from a budgetary perspective. >> Lori, weigh in on this, because the enterprise people love to solve complexity with more complexity. Here, we need to go the other way. It's a commodity. So there has to be a better way. >> I think I'm hearing two fundamental assumptions. One, that a supercloud would force the existing big three to implement some sort of equal API. Don't agree with that. There's no business case for that. There's no reason that could compel them to do that. Otherwise, we would've convinced them to do that, what? 10, 15 years ago when we said we need to be interoperable. So it's not going to happen there. They don't have a good reason to do that. There's no business justification for that. The other presumption, I think, is that we would... That it's more about the services, the differentiated services, that are offered by all of these particular providers, as opposed to treating the core IaaS as the commodity it is. It's compute, it's some storage, it's some networking. Look at that piece. Now, pull those together by... And it's not OpenStack. That's not the answer, it wasn't the answer, it's not the answer now, but something that can actually pull those together and abstract it at a different layer. So cloud providers don't have to change, 'cause they're not going to change, but if someone else were to build that architecture to say, "all right, I'm going to treat all of this compute "so you can run your workloads," as Chris pointed out, "in the best place possible. "And we'll help you do that "by being able to provide those cost benefit analysis, "'What's the best performance, what are you doing,' "And then provide that as a layer." So I think that's really where supercloud is going, 'cause I think that's what a lot of the market actually wants in terms of where they want to run their workloads, because we're seeing that they want to run workloads at the edge, "a lot closer to me," which is yet another factor that we have to consider, and how are you going to be moving individual workloads around? That's the holy grail. Let's move individual workloads to where they're the best performance, the security, cost optimized, and then one layer up. >> Yeah, I think so- >> John Considine, who ultimately ran CloudSwitch, that sold to Verizon, as well as Tom Gillis, who built Bracket, are both rolling in their graves, 'cause what you just described was exactly that. (Lori laughing) Well, they're not even dead yet, so I can't say they're rolling in their graves. Sorry, Tom. Sorry, John. >> Well, how do hyperscalers keep their advantage with all this? I mean, to that point. >> Native services and managed services on top of it. Look how many flavors of managed Kubernetes you have. So you have a choice. Roll your own, or go with a managed service, and then differentiate based on the ability to take away and simplify some of that complexity. Doesn't mean it's more secure necessarily, but I do think we're seeing opportunities where those guys are fighting tooth and nail to keep you on a singular cloud, even though, to Lori's point, I agree, I don't think it's about standardized APIs, 'cause I think that's never going to happen. I do think, though, that SaaS-y supercloud model that we were talking about, layering SaaS that happens to span all the three infrastructure of the service are probably more in line with what Lori was talking about. But I do think that portability of workload is given to you today within lots of ways. But again, how much do you manage, and how much performance do you give up by running additional abstraction layers? And how much security do you give up by having to roll your own and manage that? Because the whole point was, in many cases... Cloud is using other people's computers, so in many cases, I want to manage as little of it as I possibly can. >> I like this whole SaaS angle, because if you had the old days, you're on Amazon Web Services, hey, if you build a SaaS application that runs on Amazon, you're all great, you're born in the cloud, just like that generations of startups. Great. Now when you have this super pass layer, as Dave Vellante was riffing on his analysis, and Lori, you were getting into this pass layer that's kind of like SaaS-y, what's the SaaS equation look like? Because that, to me, sounds like a supercloud version of saying, "I have a workload that runs on all the clouds equally." I just don't think that's ever going to happen. I agree with you, Chris, on that one. But I do see that you can have an abstraction that says, "Hey, I don't really want to get in the weeds. "I don't want to spend a lot of ops time on this. "I just want it to run effectively, and magic happens," or, as you said, some layer there. How does that work? How do you see this super pass layer, if anything, enabling a different SaaS game? >> I think you hit on it there. The last like 10 or so years, we've been all focused on developers and developer productivity, and it's all about the developer experience, and it's got to be good for them, 'cause they're the kings. And I think the next 10 years are going to be very focused on operations, because once you start scaling out, it's not about developers. They can deliver fast or slow, it doesn't matter, but if you can't scale it out, then you've got a real problem. So I think that's an important part of it, is really, what is the ops experience, and what is the best way to get those costs down? And this would serve that purpose if it was done right, which, we can argue about whether that's possible or not, but I don't have to implement it, so I can say it's possible. >> Well, are we going to be getting into infrastructure as code moves into "everything is code," security, data, (laughs) applications is code? I mean, "blank" is code, fill in the blank. (Lori laughing) >> Yeah, we're seeing more of that with things like CDK and Pulumi, where you are actually coding up using a real language rather than the death by YAML or whatever. How much YAML can you take? But actually having a real language so you're not trying to do things in parsing languages. So I think that's an interesting trend. You're getting some interesting templates, and I like what... I mean, the counterexample is that if you just go deep on one vendor, then maybe you can go faster and it is simpler. And one of my favorite vendor... Favorite customers right now that I've been talking to is Liberty Mutual. Went very deep and serverless first on AWS. They're just doing everything there, and they're using CDK Patterns to do it, and they're going extremely fast. There's a book coming out called "The Value Flywheel" by Dave Anderson, it's coming out in a few months, to just detail what they're doing, but that's the counterargument. If you could pick one vendor, you can go faster, you can get that vendor to do more for you, and maybe get a bigger discount so you're not splitting your discounts across vendors. So that's one aspect of it. But I think, fundamentally, you're going to find the CIOs and the ops people generally don't like sitting on one vendor. And if that single vendor is a horizontal platform that's trying to make all the clouds look the same, now you're locked into whatever that platform was. You've still got a platform there. There's still something. So I think that's always going to be something that the CIOs want, but the developers are always going to just pick whatever the best tool for building the thing is. And a analogy here is that the developers are dating and getting married, and then the operations people are running the family and getting divorced. And all the bad parts of that cycle are in the divorce end of it. You're trying to get out of a vendor, there's lawyers, it's just a big mess. >> Who's the lawyer in this example? (crosstalk) >> Well... (laughing) >> Great example. (crosstalk) >> That's why ops people don't like lock-in, because they're the ones trying to unlock. They aren't the ones doing the lock-in. They're the ones unlocking, when developers, if you separate the two, are the ones who are going, picking, having the fun part of it, going, trying a new thing. So they're chasing a shiny object, and then the ops people are trying to untangle themselves from the remains of that shiny object a few years later. So- >> Aren't we- >> One way of fixing that is to push it all together and make it more DevOps-y. >> Yeah, that's right. >> But that's trying to put all the responsibilities in one place, like more continuous improvement, but... >> Chris, what's your reaction to that? Because you're- >> No, that's exactly what I was going to bring up, yeah, John. And 'cause we keep saying "devs," "dev," and "ops" and I've heard somewhere you can glue those two things together. Heck, you could even include "sec" in the middle of it, and "DevSecOps." So what's interesting about what Adrian's saying though, too, is I think this has a lot to do with how you structure your engineering teams and how you think about development versus operations and security. So I'm building out a team now that very much makes use of, thanks to my brilliant VP of Engineering, a "Team Topologies" approach, which is a very streamlined and product oriented way of thinking about, for example, in engineering, if you think about team structures, you might have people that build the front end, build the middle tier, and the back end, and then you have a product that needs to make use of all three components in some form. So just from getting stuff done, their ability then has to tie to three different groups, versus building a team that's streamlined that ends up having front end, middleware, and backend folks that understand and share standards but are able to uncork the velocity that's required to do that. So if you think about that, and not just from an engineering development perspective, but then you couple in operations as a foundational layer that services them with embedded capabilities, we're putting engineers and operations teams embedded in those streamlined teams so that they can run at the velocity that they need to, they can do continuous integration, they can do continuous deployment. And then we added CS, which is continuously secure, continuous security. So instead of having giant, centralized teams, we're thinking there's a core team, for example, a foundational team, that services platform, makes sure all the trains are running on time, that we're doing what we need to do foundationally to make the environments fully dev and operator and security people functional. But then ultimately, we don't have these big, monolithic teams that get into turf wars. So, to Adrian's point about, the operators don't like to be paned in, well, they actually have a say, ultimately, in how they architect, deploy, manage, plan, build, and operate those systems. But at the same point in time, we're all looking at that problem across those teams and go... Like if one streamline team says, "I really want to go run on Azure, "because I like their services better," the reality is the foundational team has a larger vote versus opinion on whether or not, functionally, we can satisfy all of the requirements of the other team. Now, they may make a fantastic business case and we play rock, paper, scissors, and we do that. Right now, that hasn't really happened. We look at the balance of AWS, we are picking SaaS-y, supercloud vendors that will, by the way, happen to run on three platforms, if we so choose to expand there. So we have a similar interface, similar capability, similar processes, but we've made the choice at LastPass to go all in on AWS currently, with respect to how we deliver our products, for all the reasons we just talked about. But I do think that operations model and how you build your teams is extremely important. >> Yeah, and to that point- >> And has the- (crosstalk) >> The vendors themselves need optionality to the customer, what you're saying. So, "I'm going to go fast, "but I need to have that optionality." I guess the question I have for you guys is, what is today's trade-off? So if the decision point today is... First of all, I love the go-fast model on one cloud. I think that's my favorite when I look at all this, and then with the option, knowing that I'm going to have the option to go to multiple clouds. But everybody wants lock-in on the vendor side. Is that scale, is that data advantage? I mean, so the lock-in's a good question, and then also the trade-offs. What do people have to do today to go on a supercloud journey to have an ideal architecture and taxonomy, and what's the right trade-offs today? >> I think that the- Sorry, just put a comment and then let Lori get a word in, but there's a lot of... A lot of the market here is you're building a product, and that product is a SaaS product, and it needs to run somewhere. And the customers that you're going to... To get the full market, you need to go across multiple suppliers, most people doing AWS and Azure, and then with Google occasionally for some people. But that, I think, has become the pattern that most of the large SaaS platforms that you'd want to build out of, 'cause that's the fast way of getting something that's going to be stable at scale, it's got functionality, you'd have to go invest in building it and running it. Those platforms are just multi-cloud platforms, they're running across them. So Snowflake, for example, has to figure out how to make their stuff work on more than one cloud. I mean, they started on one, but they're going across clouds. And I think that that is just the way it's going to be, because you're not going to get a broad enough view into the market, because there isn't a single... AWS doesn't have 100% of the market. It's maybe a bit more than them, but Azure has got a pretty solid set of markets where it is strong, and it's market by market. So in some areas, different people in some places in the world, and different vertical markets, you'll find different preferences. And if you want to be across all of them with your data product, or whatever your SaaS product is, you're just going to have to figure this out. So in some sense, the supercloud story plays best with those SaaS providers like the Snowflakes of this world, I think. >> Lori? >> Yeah, I think the SaaS product... Identity, whatever, you're going to have specialized. SaaS, superclouds. We already see that emerging. Identity is becoming like this big SaaS play that crosses all clouds. It's not just for one. So you get an evolution going on where, yes, I mean, every vendor who provides some kind of specific functionality is going to have to build out and be multi-cloud, as it were. It's got to work equally across them. And the challenge, then, for them is to make it simple for both operators and, if required, dev. And maybe that's the other lesson moving forward. You can build something that is heaven for ops, but if the developers won't use it, well, then you're not going to get it adopted. But if you make it heaven for the developers, the ops team may not be able to keep it secure, keep everything. So maybe we have to start focusing on both, make it friendly for both, at least. Maybe it won't be the perfect experience, but gee, at least make it usable for both sides of the equation so that everyone can actually work in concert, like Chris was saying. A more comprehensive, cohesive approach to delivery and deployment. >> All right, well, wrapping up here, I want to just get one final comment from you guys, if you don't mind. What does supercloud look like in five years? What's the Nirvana, what's the steady state of supercloud in five to 10 years? Or say 10 years, make it easier. (crosstalk) Five to 10 years. Chris, we'll start with you. >> Wow. >> Supercloud, what's it look like? >> Geez. A magic pane, a single pane of glass. (laughs) >> Yeah, I think- >> Single glass of pain. >> Yeah, a single glass of pain. Thank you. You stole my line. Well, not mine, but that's the one I was going to use. Yeah, I think what is really fascinating is ultimately, to answer that question, I would reflect on market consolidation and market dynamics that happens even in the SaaS space. So we will see SaaS companies combining in focal areas to be able to leverage the positions, let's say, in the identity space that somebody has built to provide a set of compelling services that help abstract that identity problem or that security problem or that instrumentation and observability problem. So take your favorite vendors today. I think what we'll end up seeing is more consolidation in SaaS offerings that run on top of infrastructure of the service offerings to where a supercloud might look like something I described before. You have the combination of your favorite interoperable identity, observability, security, orchestration platforms run across them. They're sold as a stack, whether it be co-branded by an enterprise vendor that sells all of that and manages it for you or not. But I do think that... You talked about, I think you said, "Is this an innovator's dilemma?" No, I think it's an integrator's dilemma, as it has always ultimately been. As soon as you get from Genesis to Bespoke Build to product to then commoditization, the cycle starts anew. And I think we've gotten past commoditization, and we're looking at niche areas. So I see just the evolution, not necessarily a revolution, of what we're dealing with today as we see more consolidation in the marketplace. >> Lori, what's your take? Five years, 10 years, what does supercloud look like? >> Part of me wants to take the pie in the sky unicorn approach. "No, it will be beautiful. "One button, and things will happen," but I've seen this cycle many times before, and that's not going to happen. And I think Chris has got it pretty close to what I see already evolving. Those different kinds of super services, basically. And that's really what we're talking about. We call them SaaS, but they're... X is a service. Everything is a service, and it's really a supercloud that can run anywhere, but it presents a different interface, because, well, it's easier. And I think that's where we're going to go, and that's just going to get more refined. And yes, a lot of consolidation, especially on the observability side, but that's also starting to consume the security side, which is really interesting to watch. So that could be a little different supercloud coming on there that's really focused on specific types of security, at least, that we'll layer across, and then we'll just hook them all together. It's an API first world, and it seems like that's going to be our standard for the next while of how we integrate everything. So superclouds or APIs. >> Awesome. Adrian... Adrian, take us home. >> Yeah, sure. >> What's your- I think, and just picking up on Lori's point that these are web services, meaning that you can just call them from anywhere, they don't have to run everything in one place, they can stitch it together, and that's really meant... It's somewhat composable. So in practice, people are going to be composable. Can they compose their applications on multiple platforms? But I think the interesting thing here is what the vendors do, and what I'm seeing is vendors running software on other vendors. So you have Google building platforms that, then, they will support on AWS and Azure and vice versa. You've got AWS's distro of Kubernetes, which they now give you as a distro so you can run it on another platform. So I think that trend's going to continue, and it's going to be, possibly, you pick, say, an AWS or a Google software stack, but you don't run it all on AWS, you run it in multiple places. Yeah, and then the other thing is the third tier, second, third tier vendors, like, I mean, what's IBM doing? I think in five years time, IBM is going to be a SaaS vendor running on the other clouds. I mean, they're already halfway there. To be a bit more controversial, I guess it's always fun to... Like I don't work for a corporate entity now. No one tells me what I can say. >> Bring it on. >> How long can Google keep losing a billion dollars a quarter? They've either got to figure out how to make money out of this thing, or they'll end up basically being a software stack on another cloud platform as their, likely, actual way they can make money on it. Because you've got to... And maybe Oracle, is that a viable cloud platform that... You've got to get to some level of viability. And I think the second, third tier of vendors in five, 10 years are going to be running on the primary platform. And I think, just the other final thing that's really driving this right now. If you try and place an order right now for a piece of equipment for your data center, key pieces of equipment are a year out. It's like trying to buy a new fridge from like Sub-Zero or something like that. And it's like, it's a year. You got to wait for these things. Any high quality piece of equipment. So you go to deploy in your data center, and it's like, "I can't get stuff in my data center. "Like, the key pieces I need, I can't deploy a whole system. "We didn't get bits and pieces of it." So people are going to be cobbling together, or they're going, "No, this is going to cloud, because the cloud vendors "have a much stronger supply chain to just be able "to give you the system you need. "They've got the capacity." So I think we're going to see some pandemic and supply chain induced forced cloud migrations, just because you can't build stuff anymore outside the- >> We got to accelerate supercloud, 'cause they have the supply. They are the chain. >> That's super smart. That's the benefit of going last. So I'm going to scoop in real quick. I can't believe we can call this "Web3 Supercloud," because none of us said "Web3." Don't forget DAO. (crosstalk) (indistinct) You have blockchain, blockchain superclouds. I mean, there's some very interesting distributed computing stuff there, but we'll have to do- >> (crosstalk) We're going to call that the "Cubeverse." The "Cubeverse" is coming. >> Oh, the "Cubeverse." All right. >> We will be... >> That's very meta. >> In the metaverse, Cubeverse soon. >> "Stupor cloud," perhaps. But anyway, great points, Adrian and Lori. Loved it. >> Chris, great to see you. Adrian, Lori, thanks for coming on. We've known each other for a long time. You guys are part of the cloud-erati, the group that has been in there from day one, and watched it evolve, and you get the scar tissue to prove it, and the experience. So thank you so much for sharing your commentary. We'll roll this up and make it open to everybody as additional content. We'll call this the "outtakes," the longer version. But really appreciate your time, thank you. >> Thank you. >> Thanks so much. >> Okay, we'll be back with more "Supercloud 22" right after this. (bright upbeat music)

>> From theCUBE studios in Palo Alto in Boston bringing you data driven insights from theCUBE and ETR. This is breaking analysis with Dave Vellante. >> The term Supercloud is somewhat new, but the concepts behind it have been bubbling for years, early last decade when NIST put forth a definition of cloud computing it said services had to be accessible over a public network essentially cutting the on-prem crowd out of the cloud conversation. Now a guy named Chuck Hollis, who was a field CTO at EMC at the time and a prolific blogger objected to that criterion and laid out his vision for what he termed a private cloud. Now, in that post, he showed a workload running both on premises and in a public cloud sharing the underlying resources in an automated and seamless manner. What later became known more broadly as hybrid cloud that vision as we now know, really never materialized, and we were left with multi-cloud sets of largely incompatible and disconnected cloud services running in separate silos. The point is what Hollis laid out, IE the ability to abstract underlying infrastructure complexity and run workloads across multiple heterogeneous estates with an identical experience is what super cloud is all about. Hello and welcome to this week's Wikibon cube insights powered by ETR and this breaking analysis. We share what we hope to learn from super cloud 22 next week, next Tuesday at 9:00 AM Pacific. The community is gathering for Supercloud 22 an inclusive pilot symposium hosted by theCUBE and made possible by VMware and other founding partners. It's a one day single track event with more than 25 speakers digging into the architectural, the technical, structural and business aspects of Supercloud. This is a hybrid event with a live program in the morning running out of our Palo Alto studio and pre-recorded content in the afternoon featuring industry leaders, technologists, analysts and investors up and down the technology stack. Now, as I said up front the seeds of super cloud were sewn early last decade. After the very first reinvent we published our Amazon gorilla post, that scene in the upper right corner here. And we talked about how to differentiate from Amazon and form ecosystems around industries and data and how the cloud would change IT permanently. And then up in the upper left we put up a post on the old Wikibon Wiki. Yeah, it used to be a Wiki. Check out my hair by the way way no gray, that's how long ago this was. And we talked about in that post how to compete in the Amazon economy. And we showed a graph of how IT economics were changing. And cloud services had marginal economics that looked more like software than hardware at scale. And this would reset, we said opportunities for both technology sellers and buyers for the next 20 years. And this came into sharper focus in the ensuing years culminating in a milestone post by Greylock's Jerry Chen called Castles in the Cloud. It was an inspiration and catalyst for us using the term Supercloud in John Furrier's post prior to reinvent 2021. So we started to flesh out this idea of Supercloud where companies of all types build services on top of hyperscale infrastructure and across multiple clouds, going beyond multicloud 1.0, if you will, which was really a symptom, as we said, many times of multi-vendor at least that's what we argued. And despite its fuzzy definition, it resonated with people because they knew something was brewing, Keith Townsend the CTO advisor, even though he frankly, wasn't a big fan of the buzzy nature of the term Supercloud posted this awesome Blackboard on Twitter take a listen to how he framed it. Please play the clip. >> Is VMware the right company to make the super cloud work, term that Wikibon came up with to describe the taking of discreet services. So it says RDS from AWS, cloud compute engines from GCP and authentication from Azure to build SaaS applications or enterprise applications that connect back to your data center, is VMware's cross cloud vision 'cause it is just a vision today, the right approach. Or should you be looking towards companies like HashiCorp to provide this overall capability that we all agree, or maybe you don't that we need in an enterprise comment below your thoughts. >> So I really like that Keith has deep practitioner knowledge and lays out a couple of options. I especially like the examples he uses of cloud services. He recognizes the need for cross cloud services and he notes this capability is aspirational today. Remember this was eight or nine months ago and he brings HashiCorp into the conversation as they're one of the speakers at Supercloud 22 and he asks the community, what they think, the thing is we're trying to really test out this concept and people like Keith are instrumental as collaborators. Now I'm sure you're not surprised to hear that mot everyone is on board with the Supercloud meme, in particular Charles Fitzgerald has been a wonderful collaborator just by his hilarious criticisms of the concept. After a couple of super cloud posts, Charles put up his second rendition of "Supercloudifragilisticexpialidoucious". I mean, it's just beautiful, but to boot, he put up this picture of Baghdad Bob asking us to just stop, Bob's real name is Mohamed Said al-Sahaf. He was the minister of propaganda for Sadam Husein during the 2003 invasion of Iraq. And he made these outrageous claims of, you know US troops running in fear and putting down their arms and so forth. So anyway, Charles laid out several frankly very helpful critiques of Supercloud which has led us to really advance the definition and catalyze the community's thinking on the topic. Now, one of his issues and there are many is we said a prerequisite of super cloud was a super PaaS layer. Gartner's Lydia Leong chimed in saying there were many examples of successful PaaS vendors built on top of a hyperscaler some having the option to run in more than one cloud provider. But the key point we're trying to explore is the degree to which that PaaS layer is purpose built for a specific super cloud function. And not only runs in more than one cloud provider, Lydia but runs across multiple clouds simultaneously creating an identical developer experience irrespective of a state. Now, maybe that's what Lydia meant. It's hard to say from just a tweet and she's a sharp lady, so, and knows more about that market, that PaaS market, than I do. But to the former point at Supercloud 22, we have several examples. We're going to test. One is Oracle and Microsoft's recent announcement to run database services on OCI and Azure, making them appear as one rather than use an off the shelf platform. Oracle claims to have developed a capability for developers specifically built to ensure high performance low latency, and a common experience for developers across clouds. Another example we're going to test is Snowflake. I'll be interviewing Benoit Dageville co-founder of Snowflake to understand the degree to which Snowflake's recent announcement of an application development platform is perfect built, purpose built for the Snowflake data cloud. Is it just a plain old pass, big whoop as Lydia claims or is it something new and innovative, by the way we invited Charles Fitz to participate in Supercloud 22 and he decline saying in addition to a few other somewhat insulting things there's definitely interesting new stuff brewing that isn't traditional cloud or SaaS but branding at all super cloud doesn't help either. Well, indeed, we agree with part of that and we'll see if it helps advanced thinking and helps customers really plan for the future. And that's why Supercloud 22 has going to feature some of the best analysts in the business in The Great Supercloud Debate. In addition to Keith Townsend and Maribel Lopez of Lopez research and Sanjeev Mohan from former Gartner analyst and principal at SanjMo participated in this session. Now we don't want to mislead you. We don't want to imply that these analysts are hopping on the super cloud bandwagon but they're more than willing to go through the thought experiment and mental exercise. And, we had a great conversation that you don't want to miss. Maribel Lopez had what I thought was a really excellent way to think about this. She used TCP/IP as an historical example, listen to what she said. >> And Sanjeev Mohan has some excellent thoughts on the feasibility of an open versus de facto standard getting us to the vision of Supercloud, what's possible and what's likely now, again, I don't want to imply that these analysts are out banging the Supercloud drum. They're not necessarily doing that, but they do I think it's fair to say believe that something new is bubbling and whether it's called Supercloud or multicloud 2.0 or cross cloud services or whatever name you choose it's not multicloud of the 2010s and we chose Supercloud. So our goal here is to advance the discussion on what's next in cloud and Supercloud is meant to be a term to describe that future of cloud and specifically the cloud opportunities that can be built on top of hyperscale, compute, storage, networking machine learning, and other services at scale. And that is why we posted this piece on Answering the top 10 questions about Supercloud. Many of which were floated by Charles Fitzgerald and others in the community. Why does the industry need another term what's really new and different? And what is hype? What specific problems does Supercloud solve? What are the salient characteristics of Supercloud? What's different beyond multicloud? What is a super pass? Is it necessary to have a Supercloud? How will applications evolve on superclouds? What workloads will run? All these questions will be addressed in detail as a way to advance the discussion and help practitioners and business people understand what's real today. And what's possible with cloud in the near future. And one other question we'll address is who will build super clouds? And what new entrance we can expect. This is an ETR graphic that we showed in a previous episode of breaking analysis, and it lays out some of the companies we think are building super clouds or in a position to do so, by the way the Y axis shows net score or spending velocity and the X axis depicts presence in the ETR survey of more than 1200 respondents. But the key callouts to this slide in addition to some of the smaller firms that aren't yet showing up in the ETR data like Chaossearch and Starburst and Aviatrix and Clumio but the really interesting additions are industry players Walmart with Azure, Capital one and Goldman Sachs with AWS, Oracle, with Cerner. These we think are early examples, bubbling up of industry clouds that will eventually become super clouds. So we'll explore these and other trends to get the community's input on how this will all play out. These are the things we hope you'll take away from Supercloud 22. And we have an amazing lineup of experts to answer your question. Technologists like Kit Colbert, Adrian Cockcroft, Mariana Tessel, Chris Hoff, Will DeForest, Ali Ghodsi, Benoit Dageville, Muddu Sudhakar and many other tech athletes, investors like Jerry Chen and In Sik Rhee the analyst we featured earlier, Paula Hansen talking about go to market in a multi-cloud world Gee Rittenhouse talking about cloud security, David McJannet, Bhaskar Gorti of Platform9 and many, many more. And of course you, so please go to theCUBE.net and register for Supercloud 22, really lightweight reg. We're not doing this for lead gen. We're doing it for collaboration. If you sign in you can get the chat and ask questions in real time. So don't miss this inaugural event Supercloud 22 on August 9th at 9:00 AM Pacific. We'll see you there. Okay. That's it for today. Thanks for watching. Thank you to Alex Myerson who's on production and manages the podcast. Kristen Martin and Cheryl Knight. They help get the word out on social media and in our newsletters. And Rob Hof is our editor in chief over at SiliconANGLE. Does some really wonderful editing. Thank you to all. Remember these episodes are all available as podcasts wherever you listen, just search breaking analysis podcast. I publish each week on wikibon.com and Siliconangle.com. And you can email me at David.Vellantesiliconangle.com or DM me at Dvellante, comment on my LinkedIn post. Please do check out ETR.AI for the best survey data in the enterprise tech business. This is Dave Vellante for theCUBE insights powered by ETR. Thanks for watching. And we'll see you next week in Palo Alto at Supercloud 22 or next time on breaking analysis. (calm music)

(upbeat music) >> On August 9th at 9:00 am Pacific, we'll be broadcasting live from theCUBE Studios in Palo Alto, California. Supercloud22, an open industry event made possible by VMware. Supercloud22 will lay out the future of multi-cloud services in the 2020s. John Furrier and I will be hosting a star lineup, including Kit Colbert, VMware CTO, Benoit Dageville, co-founder of Snowflake, Marianna Tessel, CTO of Intuit, Ali Ghodsi, CEO of Databricks, Adrian Cockcroft, former CTO of Netflix, Jerry Chen of Greylock, Chris Hoff aka Beaker, Maribel Lopez, Keith Townsend, Sanjiv Mohan, and dozens of thought leaders. A full day track with 17 sessions. You won't want to miss Supercloud22. Go to thecube.net to mark your calendar and learn more about this free hybrid event. We'll see you there. (upbeat music)

(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)

(upbeat music) >> Welcome back. Day two of theCUBE's coverage of re:MARS in Las Vegas. Amazon re:MARS, it's part of the Re Series they call it at Amazon. re:Invent is their big show, re:Inforce is a security show, re:MARS is the new emerging machine learning automation, robotics, and space. The confluence of machine learning powering a new industrial age and inflection point. I'm John Furrier, host of theCUBE. We're here to break it down for another wall to wall coverage. We've got a great guest here, CUBE alumni from our AWS startup showcase, Krishna Gade, founder and CEO of fiddler.ai. Welcome back to theCUBE. Good to see you. >> Great to see you, John. >> In person. We did the remote one before. >> Absolutely, great to be here, and I always love to be part of these interviews and love to talk more about what we're doing. >> Well, you guys have a lot of good street cred, a lot of good word of mouth around the quality of your product, the work you're doing. I know a lot of folks that I admire and trust in the AI machine learning area say great things about you. A lot going on, you guys are growing companies. So you're kind of like a startup on a rocket ship, getting ready to go, pun intended here at the space event. What's going on with you guys? You're here. Machine learning is the centerpiece of it. Swami gave the keynote here at day two and it really is an inflection point. Machine learning is now ready, it's scaling, and some of the examples that they were showing with the workloads and the data sets that they're tapping into, you know, you've got CodeWhisperer, which they announced, you've got trust and bias now being addressed, we're hitting a level, a new level in ML, ML operations, ML modeling, ML workloads for developers. >> Yep, yep, absolutely. You know, I think machine learning now has become an operational software, right? Like you know a lot of companies are investing millions and billions of dollars and creating teams to operationalize machine learning based products. And that's the exciting part. I think the thing that that is very exciting for us is like we are helping those teams to observe how those machine learning applications are working so that they can build trust into it. Because I believe as Swami was alluding to this today, without actually building trust into AI, it's really hard to actually have your business users use it in their business workflows. And that's where we are excited about bringing their trust and visibility factor into machine learning. >> You know, a lot of us all know what you guys are doing here in the ecosystem of AWS. And now extending here, take a minute to explain what Fiddler is doing for the folks that are in the space, that are in discovery mode, trying to understand who's got what, because like Swami said on stage, it's a full-time job to keep up on all the machine learning activities and tool sets and platforms. Take a minute to explain what Fiddler's doing, then we can get into some, some good questions. >> Absolutely. As the enterprise is taking on operationalization of machine learning models, one of the key problems that they run into is lack of visibility into how those models perform. You know, for example, let's say if I'm a bank, I'm trying to introduce credit risk scoring models using machine learning. You know, how do I know when my model is rejecting someone's loan? You know, when my model is accepting someone's loan? And why is it doing it? And I think this is basically what makes machine learning a complex thing to implement and operationalize. Without this visibility, you cannot build trust and actually use it in your business. With Fiddler, what we provide is we actually open up this black box and we help our customers to really understand how those models work. You know, for example, how is my model doing? Is it accurately working or not? You know, why is it actually rejecting someone's loan application? We provide these both fine grain as well as coarse grain insights. So our customers can actually deploy machine learning in a safe and trustworthy manner. >> Who is your customer? Who you're targeting? What persona is it, the data engineer, is it data science, is it the CSO, is it all the above? >> Yeah, our customer is the data scientist and the machine learning engineer, right? And we usually talk to teams that have a few models running in production, that's basically our sweet spot, where they're trying to look for a single pane of glass to see like what models are running in their production, how they're performing, how they're affecting their business metrics. So we typically engage with like head of data science or head of machine learning that has a few machine learning engineers and data scientists. >> Okay, so those people that are watching, you're into this, you can go check it out. It's good to learn. I want to get your thoughts on some trends that I see emerging, and I want to get your reaction to those. Number one, we're seeing the cloud scale now and integration a big part of things. So the time to value was brought up on stage today, Swami kind of mentioned time to value, showed some benchmark where they got four hours, some other teams were doing eight weeks. Where are we on the progression of value, time to value, and on the scale side. Can you scope that for me? >> I mean, it depends, right? You know, depending upon the company. So for example, when we work with banks, for them to time to operationalize a model can take months actually, because of all the regulatory procedures that they have to go through. You know, they have to get the models reviewed by model validators, model risk management teams, and then they audit those models, they have to then ship those models and constantly monitor them. So it's a very long process for them. And even for non-regulated sectors, if you do not have the right tools and processes in place, operationalizing machine learning models can take a long time. You know, with tools like Fiddler, what we are enabling is we are basically compressing that life cycle. We are helping them automate like model monitoring and explainability so that they can actually ship models more faster. Like you get like velocity in terms of shipping models. For example, one of the growing fintech companies that started with us last year started with six models in production, now they're running about 36 models in production. So it's within a year, they were able to like grow like 10x. So that is basically what we are trying to do. >> At other things, we at re:MARS, so first of all, you got a great product and a lot of markets that grow onto, but here you got space. I mean, anyone who's coming out of college or university PhD program, and if they're into aero, they're going to be here, right? This is where they are. Now you have a new core companies with machine learning, not just the engineering that you see in the space or aerospace area, you have a new engineering. Now I go back to the old days where my parents, there was Fortran, you used Fortran was Lingua Franca to manage the equipment. Little throwback to the old school. But now machine learning is companion, first class citizen, to the hardware. And in fact, and some will say more important. >> Yep, I mean, machine learning model is the new software artifact. It is going into production in a big way. And I think it has two different things that compare to traditional software. Number one, unlike traditional software, it's a black box. You cannot read up a machine learning model score and see why it's making those predictions. Number two, it's a stochastic entity. What that means is it's predictive power can wane over time. So it needs to be constantly monitored and then constantly refreshed so that it's actually working in tech. So those are the two main things you need to take care. And if you can do that, then machine learning can give you a huge amount of ROI. >> There is some practitioner kind of like craft to it. >> Correct. >> As you said, you got to know when to refresh, what data sets to bring in, which to stay away from, certainly when you get to the bias, but I'll get to that in a second. My next question is really along the lines of software. So if you believe that open source will dominate the software business, which I do, I mean, most people won't argue. I think you would agree with that, right? Open source is driving everything. If everything's open source, where's the differentiation coming from? So if I'm a startup entrepreneur or I'm a project manager working on the next Artemis mission, I got to open source. Okay, there's definitely security issues here. I don't want to talk about shift left right now, but like, okay, open source is everything. Where's the differentiation, where do I have the proprietary edge? >> It's a great question, right? So I used to work in tech companies before Fiddler. You know, when I used to work at Facebook, we would build everything in house. We would not even use a lot of open source software. So there are companies like that that build everything in house. And then I also worked at companies like Twitter and Pinterest, which are actually used a lot of open source, right? So now, like the thing is, it depends on the maturity of the organization. So if you're a Facebook or a Google, you can build a lot of things in house. Then if you're like a modern tech company, you would probably leverage open source, but there are lots of other companies in the world that still don't have the talent pool to actually build, take things from open source and productionize it. And that's where the opportunity for startups comes in so that we can commercialize these things, create a great enterprise experience, so actually operationalize things for them so that they don't have to do it in house for them. And that's the advantage working with startups. >> I don't want to get all operating systems with you on theory here on the stage here, but I will have to ask you the next question, which I totally agree with you, by the way, that's the way to go. There's not a lot of people out there that are peaked. And that's just statistical and it'll get better. Data engineering is really narrow. That is like the SRE of data. That's a new role emerging. Okay, all the things are happening. So if open source is there, integration is a huge deal. And you start to see the rise of a lot of MSPs, managed service providers. I run Kubernetes clusters, I do this, that, and the other thing. So what's your reaction to the growth of the integration side of the business and this role of new services coming from third parties? >> Yeah, absolutely. I think one of the big challenges for a chief data officer or someone like a CTO is how do they devise this infrastructure architecture and with components, either homegrown components or open source components or some vendor components, and how do they integrate? You know, when I used to run data engineering at Pinterest, we had to devise a data architecture combining all of these things and create something that actually flows very nicely, right? >> If you didn't do it right, it would break. >> Absolutely. And this is why it's important for us, like at Fiddler, to really make sure that Fiddler can integrate to all varies of ML platforms. Today, a lot of our customers use machine learning, build machine learning models on SageMaker. So Fiddler nicely integrate with SageMaker so that data, they get a seamless experience to monitor their models. >> Yeah, I mean, this might not be the right words for it, but I think data engineering as a service is really what I see you guys doing, as well other things, you're providing all that. >> And ML engineering as a service. >> ML engineering as a- Well it's hard. I mean, it's like the hard stuff. >> Yeah, yeah. >> Hear, hear. But that has to enable. So you as a business entrepreneur, you have to create a multiple of value proposition to your customers. What's your vision on that? What is that value? It has to be a multiple, at least 5 to 10. >> I mean, the value is simple, right? You know, if you have to operationize machine learning, you need visibility into how these things work. You know, if you're CTO or like chief data officer is asking how is my model working and how is it affecting my business? You need to be able to show them a dashboard, how it's working, right? And so like a data scientist today struggles to do this. They have to manually generate a report, manually do this analysis. What Fiddler is doing them is basically reducing their work so that they can automate these things and they can still focus on the core aspect of model building and data preparation and this boring aspect of monitoring the model and creating reports around the models is automated for them. >> Yeah, you guys got a great business. I think it's a lot of great future there and it's only going to get bigger. Again, the TAM's going to expand as the growth rising tide comes in. I want to ask you on while we're on that topic of rising tides, Dave Malik and I, since re:Invent last year have been kind of kicked down around this term that we made up called supercloud. And supercloud was a word that came out of these clouds that were not Amazon hyperscalers. So Snowflake, Buildman Sachs, Capital One, you name it, they're building massive proprietary value on top of the CapEx of Amazon. Jerry Chen at Greylock calls it castles in the cloud. You can create these moats. >> Yeah, right. >> So this is a phenomenon, right? And you land on one, and then you go to the others. So the strategies, everyone goes to Amazon first, and then hits Azure and GCP. That then creates this kind of multicloud so, okay, so super cloud's kind of happening, it's a thing. Charles Fitzgerald will disagree, he's a platformer, he says he's against the term. I get why, but he's off base a little. We can't wait to debate him on that. So superclouds are happening, but now what do I do about multicloud, because now I understand multicloud, I have this on that cloud, integrating across clouds is a very difficult thing. >> Krishna: Right, right, right. >> If I'm Snowflake or whatever, hey, I'll go to Azure, more TAM expansion, more market. But are people actually working together? Are we there yet? Where it's like, okay, I'm going to re-operationalize this code base over here. >> I mean, the reality of it, enterprise wants optionality, right? I think they don't want to be locked in into one particular cloud vendor on one particular software. And therefore you actually have in a situation where you have a multicloud scenario where they want to have some workloads in Amazon, some workloads in Azure. And this is an opportunity for startups like us because we are cloud agnostic. We can monitor models wherever you have. So this is where a lot of our customers, they have some of their models are running in their data centers and some of their models running in Amazon. And so we can provide a universal single pan of glass, right? So we can basically connect all of those data and actually showcase. I think this is an opportunity for startups to combine the data streams come from various different clouds and give them a single pain of experience. That way, the sort of the where is your data, where are my models running, which cloud are there, is all abstracted out from the customer. Because at the end of the day, enterprises will want optionality. And we are in this multicloud. >> Yeah, I mean, this reminds me of the interoperability days back when I was growing into the business. Everything was interoperability and OSI and the standards came out, but what's your opinion on openness, okay? There's a kneejerk reaction right now in the market to go silo on your data for governance or whatever reasons, but yet machine learning gurus and experts will say, "Hey, you want to horizon horizontal scalability and have the best machine learning models, you've got to have access to data and fast in real time or near real time." And the antithesis is siloing. >> Krishna: Right, right, right. >> So what's the solution? Customers control the data plane and have a control plane that's... What do customers do? It's a big challenge. >> Yeah, absolutely. I think there are multiple different architectures of ML, right, you know? We've seen like where vendors like us used to deploy completely on-prem, right? And they still do it, we still do it in some customers. And then you had this managed cloud experience where you just abstract out the entire operations from the customer. And then now you have this hybrid experience where you split the control plane and data plane. So you preserve the privacy of the customer from the data perspective, but you still control the infrastructure, right? I don't think there's a right answer. It depends on the product that you're trying to solve. You know, Databricks is able to solve this control plane, data plane split really well. I've seen some other tools that have not done this really well. So I think it all depends upon- >> What about Snowflake? I think they a- >> Sorry, correct. They have a managed cloud service, right? So predominantly that's their business. So I think it all depends on what is your go to market? You know, which customers you're talking to? You know, what's your product architecture look like? You know, from Fiddler's perspective today, we actually have chosen, we either go completely on-prem or we basically provide a managed cloud service and that's actually simpler for us instead of splitting- >> John: So it's customer choice. >> Exactly. >> That's your position. >> Exactly. >> Whoever you want to use Fiddler, go on-prem, no problem, or cloud. >> Correct, or cloud, yeah. >> You'll deploy and you'll work across whatever observability space you want to. >> That's right, that's right. >> Okay, yeah. So that's the big challenge, all right. What's the big observation from your standpoint? You've been on the hyperscaler side, your journey, Facebook, Pinterest, so back then you built everything, because no one else had software for you, but now everybody wants to be a hyperscaler, but there's a huge CapEx advantage. What should someone do? If you're a big enterprise, obviously I could be a big insurance, I could be financial services, oil and gas, whatever vertical, I want a supercloud, what do I do? >> I think like the biggest advantage enterprise today have is they have a plethora of tools. You know, when I used to work on machine learning way back in Microsoft on Bing Search, we had to build everything. You know, from like training platforms, deployment platforms, experimentation platforms. You know, how do we monitor those models? You know, everything has to be homegrown, right? A lot of open source also did not exist at the time. Today, the enterprise has this advantage, they're sitting on this gold mine of tools. You know, obviously there's probably a little bit of tool fatigue as well. You know, which tools to select? >> There's plenty of tools available. >> Exactly, right? And then there's like services available for you. So now you need to make like smarter choices to cobble together this, to create like a workflow for your engineers. And you can really get started quite fast, and actually get on par with some of these modern tech companies. And that is the advantage that a lot of enterprises see. >> If you were going to be the CTO or CEO of a big transformation, knowing what you know, 'cause you just brought up the killer point about why it's such a great time right now, you got platform as a service and the tooling essentially reset everything. So if you're going to throw everything out and start fresh, you're basically brewing the system architecture. It's a complete reset. That's doable. How fast do you think you could do that for say a large enterprise? >> See, I think if you set aside the organization processes and whatever kind of comes in the friction, from a technology perspective, it's pretty fast, right? You can devise a data architecture today with like tools like Kafka, Snowflake and Redshift, and you can actually devise a data architecture very clearly right from day one and actually implement it at scale. And then once you have accumulated enough data and you can extract more value from it, you can go and implement your MLOps workflow as well on top of it. And I think this is where tools like Fiddler can help as well. So I would start with looking at data, do we have centralization of data? Do we have like governance around data? Do we have analytics around data? And then kind of get into machine learning operations. >> Krishna, always great to have you on theCUBE. You're great masterclass guest. Obviously great success in your company. Been there, done that, and doing it again. I got to ask you, since you just brought that up about the whole reset, what is the superhero persona right now? Because it used to be the full stack developer, you know? And then it's like, then I call them, it didn't go over very well in theCUBE, the half stack developer, because nobody wants to be a half stack anything, a half sounds bad, worse than full. But cloud is essentially half a stack. I mean, you got infrastructure, you got tools. Now you're talking about a persona that's going to reset, look at tools, make selections, build an architecture, build an operating environment, distributed computing operating. Who is that person? What's that persona look like? >> I mean, I think the superhero persona today is ML engineering. I'm usually surprised how much is put on an ML engineer to do actually these days. You know, when I entered the industry as a software engineer, I had three or four things in my job to do, I write code, I test it, I deploy it, I'm done. Like today as an ML engineer, I need to worry about my data. How do I collect it? I need to clean the data, I need to train my models, I need to experiment with what it is, and to deploy them, I need to make sure that they're working once they're deployed. >> Now you got to do all the DevOps behind it. >> And all the DevOps behind it. And so I'm like working halftime as a data scientist, halftime as a software engineer, halftime as like a DevOps cloud. >> Cloud architect. >> It's like a heroic job. And I think this is why this is why obviously these jobs are like now really hard jobs and people want to be more and more machine learning >> And they get paid. >> engineering. >> Commensurate with the- >> And they're paid commensurately as well. And this is where I think an opportunity for tools like Fiddler exists as well because we can help those ML engineers do their jobs better. >> Thanks for coming on theCUBE. Great to see you. We're here at re:MARS. And great to see you again. And congratulations on being on the AWS startup showcase that we're in year two, episode four, coming up. We'll have to have you back on. Krishna, great to see you. Thanks for coming on. Okay, This is theCUBE's coverage here at re:MARS. I'm John Furrier, bringing all the signal from all the noise here. Not a lot of noise at this event, it's very small, very intimate, a little bit different, but all on point with space, machine learning, robotics, the future of industrial. We'll back with more coverage after the short break. >> Man: Thank you John. (upbeat music)