>>Oh, welcome back to the cubes coverage of coop con cloud native con 2021. I'm John is the Cuba, David Nicholson, our cloud host analyst, and it's exciting to be back in person in event. So we're back. It's been two years with the cube con and Linux foundation. So scrape, it was a hybrid event and we have a great guest here, Cuban London, Nick Dirk, and CT field CTO of harness and harness.io. The URL love the.io. Good to see you. >>Thank you guys for having me on. I genuinely appreciate >>It. Thanks for coming on. You were a part of our AWS startup showcase, which you guys were featured as a fast growing mature company, uh, as cloud scales, you guys have been doing extremely well. So congratulations. But now we're in reality now, right? So, okay. Cloud native has kind of like, okay, we don't have to sell it anymore. People buying into it. Um, and now operationalizing it with cloud operations, which means you're running stuff, applications and infrastructure is code and it costs money. Yeah. Martine Casada at Andreessen Horowitz. Oh, repatriated from the cloud. So there's a lot of, there's some cost conversations starting to happen. This is what you guys are in the middle of. >>Yeah, absolutely. What's interesting is when you think about it today, we want to shift left. When you want to empower all the engineers, we want to empower people. We're not giving them the data they need, right. They get a call from the CFO 30 days later, as opposed to actually being able to look at what change I did and how it actually affected. And this is what we're bringing in. Allowing people to have is now really empowering. So throughout the whole software delivery life cycle from CGI continuous integration, continuous delivery feature flagging, and even bringing cost modeling and in cloud cost management. And even then being able to shut down, shut down the services that you're not using, how much of that is waste. We talk about it. Every single cloud conference it's how much is waste. And so being able to actually turn those on, use those accordingly and then take advantage of even the cheapest instances when you should. That's really what >>It's so funny. People almost trip over dollars to pick up pennies in the cloud business because they're so focused on innovation that they think, okay, we've got to just innovate at all costs, but at some point you can make it productive for the developers in process in the pipeline to actually manage that. >>That's exactly it. I mean, if you think about it to me in order to breach state continuous delivery, we have to automate everything. Right. But that doesn't mean stop at just delivering, you know, to production. That means to customer, which means we've got to make them happy, but then ultimately all of those resources in dev and QA and staging and UAT, we've sticker those as well. And if we're not being mindful of it, the costs are astronomical, right. And we've seen it time and time again with every company you see, you've seen every article about how they've blown through all their budgets. So bring it to the people that can affect change. That's really the difference, making it visible, looking at it. In-depth not just at the cloud level and all the spend there, but also even at the, uh, thinking about it, the Kubernetes level down to the containers, the pods and understanding where are the resources even inside of the clusters and bringing that as an aggregate, not just for visibility and, and giving recommendations, but now more importantly, because part of a pipeline start taking action. That's where it's interesting. It's not just about being able to see it and understand it and hope, right? Hope is not a strategy acting upon it is what makes it valuable. And that's part of the automate everything. >>Yeah. We'll let that at the Dawn of the age of DevOps, uh, there was a huge incentive for a developer just to get their job done, to seize control of infrastructure, the idea of infrastructure as code, you know, and it's, it's, you know, w when it was being born, it's a fantastic, I've always wondered though, you know, be careful what you wish for. Do you really want all of that responsibility? So we've got responsibility from a compliance and security perspective and of course cost. So, so where do we, where do we go from here, I guess is the question. Yeah. So >>When we look at building this all together, I think when we think about software delivery, everybody wants to go fast. We start with velocity, right? Everybody says, that's where I want to go. And to your point with governance compliance, the next roadblock to hit is weight. In order to go fast, I have to do it appropriately. I've got governing bodies that tell me how this has to work. And that becomes a challenge. >>It slows it down too. It doesn't, I mean, basically people are getting pissed off, right? This is, this general sentiment is, is that developers are moving fast with their code. And then they have to stop. Compliance has to give the green light sometimes days, correct? Uh, it used to be weeks now. It's days, it's still unacceptable. So there's like this always been that tension to the security groups or say it, or finance was like slow down and they actually want to go faster. So that has to be policy-based something. Yep. This is the future. What is your take on that? >>Take on, this is pretty simple. When everybody talks about people, process and technology, it's kind of bogus, right? It's all about confidence. If you're confident that your developers can deploy appropriately and they're not going to do something wrong, you'll let them to play all the time. Well, that requires process. But if you have tooling that literally guarantees your governance, make sure that at no point in time, can any of your developers actually do something wrong. Now you have, >>That's the key. That's the key. That's the key because you're giving them a policy-based guardrails to execute in their programs >>And that's it. So now you can free up all those pieces. So all those bottlenecks, all those waiting all those time, and this is how all of our customers, they move from, you know, change advisory boards that approve deployments. >>Can you give us some, give us some, give us some, uh, customer anecdotal examples of this inaction and kind of the love letters you get, or, or the customer you take us through a use case of how it all. >>So this is one of my favorites. So NCR national cash register. If you slide a credit card at like a Chick-fil-A or a Safeway, right? Um, traditional technology. But what was interesting is they went from doing PCI audit, which would take seven days to go to a PCI audit right now with harness, because, >>And by the way, when you and the seventh, six day, the things that you did on day one change. >>Exactly, exactly. And so now, because of using harness and everything's audited, and all the changes are, are controlled to make sure that developers again, can only do what they're allowed. They only get to broadcast two per production. If they've met all their security requirements, all their compliance, permits, all their quality checks. Now, because of that, they literally gave a re read only view of harness to their auditor. And in three hours it was over. And it's because now we're that evidence file from code commit through to production. Yeah. It's there for point of sale compliant. >>So what is the benefits to them? What's the result saves them time, saves the money. What's the good, the free up more times. I'll see the chops it down. That's the key. >>Yeah. It's actually something we didn't build in like our ROI calculators, which was, we talked to their engineers and we gave them their nights and their weekends back, which I thought was amazing. But Thursday night, when we're doing that deploy, they don't have to be up. Harness is actually managing and understanding, using machine learning to understand what normal looks like. So they don't have to, they don't have to sit and look at the knock or sit in the war room and eat the free pizza. Yeah. Right. And then when those things break, same concept rates aren't as good. So >>I got to ask you, I got you here. You know, as the software development delivery lifecycle is radically being overhauled right now, which people generally agree that that's the case, the old models are, are different. How do you see your vision around AI and automation playing into this? Because you could say, okay, we're going to have different kinds of coding styles. This batch has got an AI block here. It's very Lego block. Like yep. Okay. Services and higher level services in the cloud. What's your reaction to how this impacts automation and >>Sure. So throughout our entire platform, we've designed our AI to take care of the worst parts of anyone's job as Guinea dev ops person. If they love babysitting deployments, they don't harness handles that for them, ask your engineers that they love sitting there waiting for their tests to run. Every time they build, they go get coffee, right. Because we're waiting for all of our tests to run. Y yeah. Right. The reality >>Is sometimes they have to wait days and >>That's it. But like, if I change the gas cap on, uh, on your car, would you expect me to check every light switch and every electronic piece? No. Well, why do we do that with code? And so our AI, our ML is designed to remove all the things that people hate. It's not to remove people's jobs. It's actually to make their jobs much better. >>How do you guys feed the data? What's the training algorithm for that? How does that work? Yeah, >>Actually, it's interesting. A lot of people think it's going to take a ton of time to figure this out. The good news is we start seeing this on the second deployment. On the second bill, we have to have a baseline of what good looks like, and that's where it starts. And it goes from there. And by the way, this isn't a lot of people say AI, and this AML, I teach a class on this because ML is not standard deviation. It's not some checks. So we use a massive amount of machine learning, but we have neural networks to think about things like engineers do. Like if we looked at a log and I saw the same log with two different user IDs, you and I would know, well, it's the same thing. It's just different users, but machine learning models. Don't so we've got to build neural networks to actually think like humans. So that, >>So that's the whole expectation maximization kind of concept of people talk about, >>Well, and that's it because at the end of the day, we're like I said, I'm not trying to take people's jobs. I want to meet. >>Yeah. You want to do the crap work out of the way. And I had to do other redundant, heavy lifting that they have to do every single time we use the cloud way. We've >>Built mechanical muscle in, in the early 19 hundreds. Right. And it made everyone's jobs easier, allowed them to do more with their time. That's exactly what we're doing here. >>I mean, we've seen the big old guys in the industry trying to evolve. You got the hot startups coming out. So you got, you know, adapt or die as classic thing. We've been saying for many years, David on the cube, you know that. So it's like, this is a moment of truth. We're going to see who comes out the other side. How do you, Nick, what would you be your, your kind of guess of when that other side is, when are we gonna know the winners and the losers truly in the sense of where we are now? >>So I think what I've found is that in this space specifically, there's a constant shift and this is something with software. And the problem is, is that we see them come in ebbs and flows, right. And very few times are there businesses that actually carry the model? And what you find is that when they focus on one specific problem, it solves it. Now, if I was working on VMs a few years ago, great, but now we're, we're here at coop con, right? And that's because it's eaten, uh, that side of the world. And so I think it's the companies that can actually grow the test of time and continue to expand to where the problems are. Right. And that's one of the things that I traditionally think about harness and we've done it. We cover our customers where they were, I think the old mainframes, if you had to, where they were, where they are at their traditional, their VM. >>I mean, if you think about it, Nick, it's one of those things where it's like, that's such a common sense way to look at it evolves with a problem. So I ride the right with tech ways. But if you think about the high order bit, here is just applications. We ended the day. Companies have applications that they want to write modern. The applications of their business is going to be codified so that you just work backwards from there. Then you say, okay, what is the infrastructure as code working for me? That's an ethos of dev ops. And that's where we're at. So that's why I think that the cloud need is kind of one already, but we still have the edge devices, more complexity. This is a huge next level conversation at one point is that we just put a hard and top on the complexity. When is that coming? Because the developers are clear. They want to go fast. They want to go shift left and have all that data, get the right analytics, the telemetry and the AI. But it's too complicated still. That is a big problem. >>It's too complicated. You ask for a full-stack developer to also know infrastructure, to also know edge computing. Like it's impossible, right? And this is where tooling helps, right? Because if you can actually parameterize that and make it to the engineers and have to care, they can do what they're best at. Hey, I'm great at turning code in artifact, let them do that and have tooling take care of the rest. This is where our goal is. Again, allow people >>We'll do what they love. And this is kind of the new roles that are changing. What SRE has done. Everyone talks about the SRE and some states just as he had dev ops guy, but it's not just that there's also, uh, different roles emerging. It's, it's an architectural game. At this point, we would say, >>I'd say a hundred percent. And this is where the decisions that you make on are architecturally. If you don't know how to then roll them out, this is what we've seen. Time and time again, you go to these large companies, I've got these great architectures on planning four years later, we haven't reached it because to that point process, >>The process killed them four >>Different new tools throughout the process. Well, yeah. >>So when do we hit peak Kubernetes peak >>Kubernetes? I think we have a bit to go in and I'm excited about the networking space and really what we're doing there and, and bringing that holistic portion of the network, like when Istio was originally released, I thought that was one of the most amazing things, uh, to truly come to it. And I think there's a vast space in networking. Um, and, and so I think in the next few years, we're going to see this, you know, turn into that a hundred percent utilized across the board. This will be that where everyone's workloads continue to exist. Um, somewhat like VMs we're in >>And, and, and no, no fear of developers as code in the very near future. You're talking about automating the mundane. Correct. Uh, there have been stories recently about the three-day workweek, you know, as a, as a fan of, um, utopian science fiction, myself, as opposed to dystopian. Absolutely. I think that, you know, technology does have the opportunity to lift all boats and, uh, and it's, it's not nothing to be afraid of. You know, the fact that I put my dishes in the dishwasher and they run by themselves for three hours. It's a good thing. It's a great thing. >>I don't need to deal with that. Yeah, I agree. No, I think that's, and that's what I said in the beginning. Right. That's really where we can start empowering people. So allow them to do what they're good at and do what they're best at. And if you look at why do people quit? We don't have to go so hard to find. Yeah. Why? Because they're secondary to babysit and implement and they're told everywhere they go, they're not going to have to >>That's the line. And that's all right. We got a break, but it's great insight to have you on the Q one final question for you. Um, I got to ask about the whole data as code something that I've been riffing on for a bunch of years now. And as infrastructures could we get that, but data is now the resource everyone needs, and everyone's trying to, okay, I have the control plane for this and that, but ultimately data cannot be siloed. This is a critical architectural element. How does that get resolved in the land of the competitive advantage and lock in and whatnot? What's your take on that? >>So data's an interesting one because it has, it has gravity and this is the problem. And as we move, as I think you guys know, as you move to the edge as remove, move it places there's insights to be taken at the edge there's insights to be taken as it moves through. And I think what you'll see honestly, going forward is you'll see compute done differently to your point. It needs to be aggregated. It needs to be able to be used together, but I think you'll see people computing it on its way through it. So now even in transport, you'll start seeing insights gained in real time before you can have the larger insights. And I see that happening more and more. Um, and I think ultimately we just want to empower that >>Nick, great to have you on CTO of field CTO of harness and harness.io is a URL. Check it out. Thanks for the insight. Thank you so much. Great comments. Appreciate it. Natural cube analysts right here, Nick, of course, we've got our, our analysts right here, David Nicholson. You're good on your own. I'm John for a, you know, we have the host. Thanks for watching. Stay with two more days of coverage. We'll be back after this short break.

(upbeat music) >> Okay, we're back here at theCUBE on this floor in CLOUD CITY, the center of all the action at Mobile World Congress. I'm John Brown your host. Michael current CTO of Virta San is here with me remote because this is a virtual event as well, this is a hybrid event. The first industry hybrid event, Greg would be back in real life on the floor, Michael, you coming in remotely. Thanks for joining us here in the cube in cloud city. >> Thanks for having me and said the beer. >> We were just talking on camera about. He went to Michigan and football, all that good time while we were waiting from Adam to pseudo great stuff, but let's get into what you guys are doing. You've got a great cloud news, we're going to get to, but take a minute to explain what you guys do first. >> So Virtasant helps organizations of any size thrive in the cloud. So we have a unique combination of proprietary technologies, such as our cloud optimization platform that we'll talk about in a minute and a global team of experts that helps companies make the most of the cloud from getting to the cloud and building the cloud to optimizing the cloud all the way to managing the cloud at scale. >> Well, you got a lot of experience dealing with the enterprise, a lot of customer growth over the years, great leader. The cloud dynamic here is the big story at mobile world congress, this year, the change over, I won't say change over per se, but certainly the shift or growth of cloud on top of telco, you guys have some news here at mobile world congress. Let's share the news, what's the big scoop? >> So we have an automated cloud optimization platform that helps companies automatically understand your usage patterns and do spend fully, automatically. And we focus first on AWS is the biggest cloud provider, but starting this week, we wanted announces we're actually going live with our GCP product, which means people who are on the GCP cloud platform can now leverage our platform to constantly understand usage patterns and spend and automatically take action to reduce spend. So we typically see customers save over 50% when they use our platform. So now GCP customers can take advantage of the same capabilities that our AWS customers take advantage of every day. >> Talk about the relationships as you get deeper. And this seems to be the pattern I want to just unpack it. You don't mind a little bit the relationship with Google and this announcement and Amazon you're tightly coupled with them, is it more integration? Talk about what makes these deals different and special for your customers? What's what's, what's about them. What's the big deal? >> Well, I think for us, obviously we think that, you know, the public cloud's the future, right? And obviously cloud city and all the different companies there agree with us, and we think that much like, you know, you don't, you don't generate your own electricity. We don't think you're going to generate you're to you're going to build your own technology infrastructure. For the most part, we think that pretty much all compute will be in the public cloud. And obviously AWS is the market leader in the largest cloud provider in the, but you know, GCP, especially with telecom has some compelling offerings. And we think that, you know, organizations are going to want choice. Many will go multicloud, meaning they'll have 1, 2, 3 of the big providers and move workloads across those. But even those who choose one cloud provider, you know, each cloud provider has their strengths and different companies will choose different providers. And they're all, you know, they've all got strong capabilities and their uniqueness. So we want to make sure that whether, you know, an organization goes across all cloud providers or they choose one that we can support them no matter what the workloads look like, and so for us, you know, developing deep relationships with each of the public cloud providers, but also, you know, expanding our full set of capabilities to support all of them is critically important because we do think that there's going to be, you know, a handful of large public cloud providers and obviously AWS and GCP are among them. >> Yeah, I mean, I talk to people all the time and even, you know, we're an Amazon customer, pretty robust cloud in the bills out of control is what's, what's this charge for it. There's more services to tap into, you know, it's like first one's on me, you know? And then next thing you know, you're, you're consuming a hell of a lot of new services, but there's value there and there's breaths a minute for the cloud, we all love that. But just as a random aside here, I want to get your thoughts real quick, if you don't mind, this idea of a cloud economist has become part of a new role in an organization, certainly SRS is DevOps. Then you starting to get into people who actually can squint through the data and understand the consumption and be more on the economics side, because people are changing how they report their earnings. They're changing how they report their KPIs based upon the usage and costs, and... What, is this real? what's your thoughts on that? I know that's a little random, but I want to get your, get your thoughts on that. >> Well, yeah, it's interesting that that's been a development. What I will say is, you know, the economics of cloud are complicated and they're still changing and still emerging, so I think that's probably more of a reaction to how dynamic the environment is then kind of a long-term trend. I mean, admittedly for us we hope that, you know, a lot of that analysis and the data that's required and will be provided by our platform. So you can think about it as, you know, a digital or AI powered cloud economist. So I don't, I don't know, hopefully our customers can use the platform and get everything they need and they won't need to go out and hire a cloud economist. That sounds expensive. >> Well, I think one of the things that sounds like great opportunities to make that go away, where you don't have to waste a resource to go through the cost side. I want to get your thoughts on this. This comes up all the time, certainly on Twitter, I'm always riffing on it. It comes up on a lot of my interviews and private chats with people about their, their cloud architecture, spend can get out of control pretty quickly. And data is a big part of it. Moving data is always going to be... Especially Amazon and Google, moving data in and out of the cloud is great. Now with the edge, I just talked to Bill Vass at a Amazon web service. He's the VP of engineering. You can literally bring the cloud to the edge and all the clouds are going to be doing this, these edge hubs. So that's going to process data at the edge, but it's also going to open up more services, right? So, you know, it's complicated enough as it is, spend is getting out of control. And it's only seems to be getting out of control even more. How do you talk to customers? I'd want to not be afraid they want to jump in, but they also want to have a hedge. Yeah, what's your, what's your take on your story? >> I think there's a lot of debate right now as to whether or not, you know, moving to the cloud from a cost perspective is cost-effective or more costly. And there's a pretty healthy debate going on at the moment. I think that the reality is, you know, yes, the cloud makes it easier for you to take on new services and bring on new things, and that of course drives spend, but it also unlocks incredible possibilities. What we try to do is help organizations take advantage of those possibilities and kind of the capabilities of the cloud while managing spend, and it's a complex problem, but it's a solvable problem. So for us, we think that, you know the job of the cloud providers is to, you know, continue to innovate and continue to bring more and more capability to bear so that organizations can transform through technology, the job of the teams using that technologies is to really leverage those capabilities, to build and to innovate and to serve their customers. And what we want to do is enable them to do that in a cost-effective manner, and we believe, and we have data to prove that if you do public cloud, right, it's cheaper because you know, those, those organizations, you know, much like, you know, at the turn of the industrial revolution, factories used to have their own power plants because you couldn't effectively reliably and kind of cost-effectively generate power at scale. Obviously no one does that now. And I think with the cloud providers, that's the same thing. I mean, they're investing in proprietary hardware, tons of software, tons of automation. They're highly secure. You know, at the end of the day, they're going to always be able to provide a given capability at a lower cost point. Like, of course they need to make profit. So there's a bit of margin in there, but, you know, at the end of the day, we think that both the flexibility and capability of it combined with their ability to operate at scale gives you a better value proposition, especially if you do it right. And that's what we want to focus on is, you know, the answer is there. You just need the right data and the right intelligence to find it. >> Totally, I totally agree with you. In fact, I had a big debate with Martine Casada at Andreessen Horowitz about cloud repatriation, and he was calling his paradigm. Do you focus on the cost or the revenue? And obviously they have Dropbox, which is a big example of that, and I even interviewed the Zynga guys and they actually went back to Amazon, although they didn't report that, but I'm a big believer that if you can't get the new revenue, then you're in cosmos then, and there are the issues, but again, I don't want to go there right now. I'll talk about that another time, but I want to get your, I want to get the playbook, so first of all, I love what you do, I think it's an opportunity to take that heavy lifting away from customers around understanding cost optimization. A lot of people don't know how to do it. So take us through a playbook. What are some best practices that you guys have seen to help people figure this out? What do you say to somebody, help me, Michael, I'm in a world of hurt, what do I do? What's the playbook? Can you give some examples of day in the life? >> Sure, so I think, I think the first thing is know what you're spending money on which sounds obvious, but you know, there's cloud environments are complicated, especially at scale. There's hundreds of thousands of skews and lots of different usage patterns. And I think the first thing is understand what you're spending money on. Number two is understand what you're getting for that spend. So, you know, what value are you driving with that spend? And then number three is put the information in the hands of the people who can do something about it. And I think that is, is one of the things that we really focus on is, you know, we built our product from an engineering focus first. It was engineers solving the problem of understanding how to keep cloud costs in control. And so our whole principle is give the people, working with the technology, the data to make good decisions and give them the power to act on it. And so, you know, a lot of companies say, "Oh, we're spending more over here. Or maybe we should look at that." But, but what we believe is actually be specific, where are you spending money? Where exactly are you spending too much? And what should you do about that? And give that information to the people who can take action, which are the engineers. And then lastly make it important in the organization because there's a ton of competing priorities. And what we've found is that, you know, where there's leadership support there's results. And so I think if you do those four things, you know, results will follow. Now, obviously, you know, you need to understand specific utilization patterns and know what to do with different kinds of resources and all of that stuff is complicated, but there are certainly solutions out there. Ours included who helped you with that. So if you get the other four things, right, plus you have some help, you can keep it under control and actually not just keep it under control, but operate in an environment that's much cheaper than hosting all this technology yourself and much more flexible. >> That's a great point, I mean, the fact that you mentioned earlier, the engineering piece that is so true people I've talked to, you mean our experiences and it's pretty common. The DevOps team tends to get involved in things like making sure you're buying reserve instances or all kinds of ways to optimize patterns, and that's also an issue, right? I mean, first of all, it makes sense that they're doing it, but also engineering time is being spent on essentially accounting at that point. Demonstrates the shift, I'm not saying it's good or bad. I'm just saying that got to be realistic. It's a time sink for the engineering when they're not engineering accounting, or should they, this is a legit question, it's not so much they should or shouldn't, I mean, if you say to someone, "Hey, you're paid to build and write software and you're spending your time solving accounting problems." That's obviously a mismatch. But when you talk about SREs and DevOps, Michael, it's kind of what might not be a bad thing, right? I mean, so how do people react to that? Are they kind of scratching their head on the same way? Or are you guys the solution to that? >> Well, I think that at first they are, but for us, at least it's, you know, we don't want them trying to understand the intricacies of a savings plan or understanding kind of the different options for compute instances. What we want them to do is we give them all the information. So our approach is give them all the information. They need to quickly make a decision, let them make a decision, like push a button and then let the change happen automatically. So if you think about it, you know, the amount of time they spend is, is a minute. That's the goal because then we can use their expertise. So it's not a finance person or an accountant doing research and making decisions that may or may not make technical sense and then looping in a bunch of people and they all talk, and then all that, that kind of whole process it's now here is a data-driven observation and recommendation. You have context to say yes or no, if you push the button and then you say, yes, then, you know, the change happens. If you say, no, the system learns. >> It's building right into the pipeline and they're shifting left to security, it's the same concept. It's really a great thing. I really think you're onto something big.,I love this story. It's kind of one of those things where reality's there. Michael, we've got 30 seconds left. I want to get your thoughts to share what put a plug in for the company, what you guys are doing, what are you looking at higher? You got a 30 second plug, go plug the company, what do you got? >> Well, you know, we think that, you know, for any organization, big or small, trying to make the most of the public cloud and be cloud first, you know, we, we bring a unique set of expertise, automation, and technology capabilities to bear, to help them thrive in the cloud and make the most of it. So, you know, obviously we would love to work with any company that, that wants to be cloud first and fully embrace the public cloud. I think we've got all the tools to help them thrive. >> Yeah, and I think, I think the confluence of business logic technology engineering working together is a home run. It's only going to get more stronger, so congratulations. Thanks for coming on theCUBE. >> Thank you. >> Adam, back to you in the studio for more action, theCUBE is out, we'll see you later.

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