 From our studios, in the heart of Silicon Valley, Palo Alto, California, this is a CUBE Conversation. Well everyone, welcome to this CUBE Conversation. I'm John Furrier, host of theCUBE here in our CUBE Studios in Palo Alto, California, heart of Silicon Valley, where all the startups are happening, all the venture capitalists are here. We have with us, Sunil Daliwal, who's the general partner of Amplify Partners and co-founder with Mike Dauber. You guys have a very successful firm. I've known you since the beginning. When you started this firm, you guys are very successful on your third fund. Congratulations. It's great to see you. Thanks for coming in. It's always fun to be back here. It's first time we're doing it in person, local as opposed to not at a conference. Yeah, we've got our studio here. We're kicking off two days a week, soon to be five days a week. Folks watching, studio will be open for a lot more startup coverage. So great to have you in. And congrats on 10 years for you guys. 10 years of theCUBE, 10th year at VMworld. We're doing a big special, so we're excited. We hope for another great 10 years. It's been a lot of fun. A lot of interesting things happened in those 10 years. And again, you've been on the track, too, during that time. Yeah. And by the way, congratulations, Fastly win public. Thank you very much. And you also invested early investor in Datadog, which you probably can't comment on, but they look like they're going to go public. It's a great business. And it's moving in the right direction. And I think they got a lot of happy users. So there's more good stuff in the future for them. So you guys came out early, made some big bets. They're paying off. Two of them, certainly one did. Another one coming around the bike more. Take a, give us an update on Amplify partners. Current fund, third fund, give us the numbers. How much, what are you guys investing in? What's some of the thesis? What's the vision? Yeah, the vision is really simple. So Amplify has been around from the beginning to work with technical founders. And really, if you wanted to stop there, you could. You know, we're the people that engineers, academics, practitioners, operators, that they go to get their first capital. When they are thinking about starting a company or have an itch that they just feel need to scratch, we tend to be first call for those folks. A lot of times before they even know that they're going to start something. And so we've been doing that investing at Seed and Series A with those people in these really technical enterprise markets now for seven years. Third fund, the most recent funds, a $200 million fund. And that has us doing everything from crazy pie in the sky, first check into somebody with wild vision to now bigger Series A lead rounds, which we're doing a lot more of too. So on the business model, just to get it clear. First of all, congratulations, it's really good venturing, by the way. That's the way venture capital should be. First money in, you know, people not, we're doing the big rounds, so that's a, congratulations, it's successful. But now that you have $200 million plus, are you doing follow-on rounds? Are you getting in on the pro radas? Are you guys following on? Because some of these big hits are pretty big. Yeah, we've been doing that from the beginning. And I think we've always wanted to be people who will start early and go long. We've invested in every round that Fastly did. We've invested in every round that Datadog did. So yeah, we're long-term supporters and we can go along with the companies. But, you know, our differentiation isn't showing up and being the guys who are going to lead your Series G round at a $3 billion valuation, you know, which might as well be your IPO. You know, we're really there to help people figure out how to recruit a kick-ass team and figure out how to find product market fit and get that engine working. And also help be a friend of it on the same side of the table as the entrepreneur, rather than being there potentially on the side. So the question is, I know you guys do step away and don't go on board. Sometimes you do, sometimes you don't. Was there a formula there? Do you go on the boards as further in the round? Are you happy to relieve? It's a mix, you know? We talked about a couple of these companies. Fastly, I've been on the board since day zero and Datadog, I was never on the board. And, you know, what we do tend to be, though, is pretty active. So people come work with us when they go, I've got this vision. I know where I want to go. But when I think about the hard things I've got to do over the first two to three years of a company's life, you know, who do I want by my side? And not the person who wants to be my boss or tell me what to do or tell me why they need to own a third of my company or control four seats on my board. But who kind of wants to sit shoulder to shoulder with me and probably has a long list of companies that look just like mine that tell me that they're going to be a decent partner. We've had a lot of fun together. You and Mike and the team have applied a great party. You've got great networking. You've got to do that. Great party should hopefully be written on my tombstone. Well, you got to have the networking and that's always a good catalyst. Lubrican, if they say, is to get people going. But you guys were hanging out with us in the big data space, the Hadoop world. We saw Cloudera got two activist board members. That's not looking good there. It's unfortunate. Big friend of Amar Awadala. But what ended up happening was cloud, right? Cloud kind of changed the game a little bit. Didn't change big data as an industry. You're seeing AI machine learning booming. So, you know, big data Hadoop changed, certainly cloud as our speculation. But looking back over those 10 years, you saw the rise of the cloud really become more of a force than some people thought. And most people thought DevOps really became the cultural shift. If I had to point to anything over the 10 years, it's DevOps, which is implies data. Talk about your reaction to that because certainly it's been an enabler but also changed the game a bit. It has, it's exploded. There's a couple of things in there. So I think there's been a lot of innovation that's come out of the cloud platforms. There's a lot of innovation the cloud platforms have sucked up. We look at that a lot as guys who back startups. One of the things we always say is, hey, is this a primitive? Is this an infrastructure primitive? Because if it is, it's probably going to be best delivered by a big platform. Unless you're able to deliver a very compelling and differentiated solution or service around it. And that's different. You know, it's different than having a solely a API accessible primitive that, you know, you would swap out with the next thing if it was, you know, two cents cheaper or 2% faster. So when I think about what's been happening in the cloud, the, this kind of cloud 2.0 phenomenon starts coming up which is a lot of people got excited very early on. It was about storage and compute and the real basic building blocks. But now you see people building really compelling experiences for developers, for database engineers, for application development owners, all the way up and down the stack that yeah, they're cloud companies but they look a heck of a lot like more like solutions. And, you know, we've mentioned a couple of companies in our portfolio that are going great but there's a ton of companies that we admire. You know, I look at what the folks that at Hashi Corp have done and what they continue to do. You know, what a great business in security and in giving people automation and configuration that hasn't been there before. I mean, that's a phenomenal business. I mean, monitoring, you mentioned, there's a monitoring 2.0 going on. You said, paid your duty, you got a dynamic trace, these companies. Both public this year. Public and you got more coming around the corner. You got analytics is turning. That's calling it. I mean, monitoring has been around for a long time. Observability now. It's observability is the monitoring 2.0 and that's taking advantage of this DevOps growth. Yeah, this is really a big deal. Yeah, well, it's, if you're really getting into what a lot of this comes down to is velocity, right? A lot of people are trying to deliver software faster, deliver it more reliably, take away the bottlenecks that are between the vision that a product person has, the fingers on a keyboard and the delightful experience that a user gets. And that has a lot of gates. And I think one of the things that DevOps has really enabled is how do you shrink that time? And when you're trying to shrink that time and you're trying to say, hey, if someone can code it, we can push it. Well, that's a great way to do things, except if you don't know what you've pushed and things are failing. So as velocity increases, the need to have an understanding of what's going on is going right alongside of it. Sonia, I want to get your thoughts on enterprise scale, because Cloud 2.0 really is about enterprise. You guys have invested in pure cloud native startups, you've invested in networking, you've invested in open source. You guys have a strong view on DevOps and Cloud 2.0. But the enterprise is now experiencing that. And you guys also have done a lot of enterprise deals. What's the intersection of the enterprise as it comes in with Cloud 2.0? You're seeing intelligent edge being discussed, hybrid, multi-cloud. These are kind of the structural big kind of battlegrounds with the changes. How do you guys look at that? How do you invest in that? How do you look for startups in that area? Yeah, well, I think we invest in it by starting from the perspective of the customer. What's the problem? And the problem is a lot of times, as people know, there's security, there's compliance. And in a lot of cases, there's legacy infrastructure, but it's not a greenfield environment is nowhere more applicable than in the enterprise. And so when you think about customers that are going to need to accommodate the investments the last five and 10 years, as well as this beautiful new vision of what the future is, you're basically talking about every enterprise CIO's problem. So we think a lot about companies that can solve those real clear enterprise pain points. Security, we're one of them. We've had a bunch of successful cloud security companies that have been acquired already. We've got great stuff in compliance and data management, an awesome company like Integris that's up in Seattle. And in really making sure that projects and software works well with legacy and more traditional enterprise environments, companies like Replicated down in LA. Those folks have really figured out what it means to deliver modern on-premise software. And modern on-premise really is in your VPC, in your own environment, in your own cloud. But that's on-prem now. That is what on-prem really looks like. No one's racking and stacking servers in a closet. It's cloud operations on-premises. But if you're going to do that and you're going to integrate all those legacy investments you've made in audit and access control, et cetera, and you want to put that together with modern cloud applications, your SaaS vendors, et cetera, you can't really do that in the native cloud unless you can really make it work for the enterprise. What are some of the market basket sectors that you see where there's a, market sectors that have a market basket of companies forming around it. You mentioned observability, obviously that's one. We're seeing a clear map of landscape develop there. Okay, is there other areas you're seeing a landscape around this cloud 2.0 that are either new or reconfigurations of other markets? Machine learning, what are the buckets? What are the markets out there that people are clustering around? What are some of the big high level? Well, I think one of the things you're going to see talking about new markets and people, there's a bunch of people who will tell you what's already happening in the industry today, but if you want to talk about what's coming that isn't really on people's radar screen, I think there is a lot that's happening in machine learning and data science infrastructure. And if you're a cloud vendor in the public cloud today, you are really ramping up quickly to understand what the suite of offerings are that you're going to offer to both ML developers as well as traditional non-machine learning natives to help them incorporate what is really a powerful set of tools into their applications. And that could be model optimization. It could be helping manage costs and scalability. It could be working on explainability. It could be working on optimizing performance or the introduction of different acceleration techniques. All of that stack is really new. People gobbled up TensorFlow from Google and that was a great example of what you could do if you turned on ML specific tooling for developers. But I think there's a lot more coming there and we're just starting to see the beginning of the organization. It's interesting you bring this up because I've been thinking about this and I haven't been talking about it publicly other than the cloud 2.0 is kind of a generic area, but you're kind of pointing out the benefits of what cloud does. I mean the idea of not having to provision something or invest a lot of cash to just get something up and running fast. I mean whether it's machine learning tooling, that's the big problem was stacking everything up and getting it all built. And it goes back to velocity we were talking about earlier, right? So velocity is the key to success. It could be any category, it could be video, it could be anything. So we've also seen another, the other side of it is another form of velocity is we're going to see more of that's happening in things that look like low code or no code. So lowering the barriers for someone doesn't have to be a true native or an expert in domain but can get all the benefits of working with let's say ML tooling, right? How do you make this stuff more accessible so you don't need a PhD from Berkeley or Stanford to go figure it out, right? That's a huge market that's just happening. We've got a phenomenal company in New York called Runway ML that has huge adoption of their platform and their magic is, hey, here's how we're going to bring ML to the creative class. If you're creative and you want to take advantage of ML techniques and the videos you're working on or the content that you're creating, maybe there's something you can do here at theCUBE. These guys are figuring out how to do that and saying, look, we know you're not a machine learning native. Here are some simple primitives you can use. Well, this brings, you know, it does joke about video, but I was serious, we have a video cloud, people have seen it out there demoing, seeing highlights going around but you bring up a good point. If we wanted to incorporate, say, machine learning into that, I can just connect to a service. I mean, Slack, I think, is the poster child for how they grew a service that's very traditional, a message board, put a great UI around it, but the API integrations were critical for that. They've created a great way to do that. So this is the whole services game. This is the velocity and adding functionality through services. Yeah, and this idea that the workflow is what matters I think has not traditionally been a thing that we've talked a lot about in enterprise infrastructure. It was, here's your tool, it's better than the previous tool three years ago throughout the new one by this one. And now people are saying, well, I don't want to be wed to the tool. What I really want to understand is a process and a workflow, how should I do this right? And if I do that right, then you're not going to be opinionated as to whether I'm using, you know, Jira for managing issues or something else, or if it's just monitoring the other. So I got to get the VC perspective on this because what you just essentially pointed out is what we've been talking about as the new IP. The workflow is the IP that translates to an application which then can be codified and scaled up with infrastructure, cloud and other things. That becomes the IP. How do you guys identify that? Is that, first of all, do you agree with that? And then too, how do you invest into that? Because it's not your traditional view of things if that's the case. Do you agree with it? And if you do, how do you invest in it? I've modified slightly. It's the marriage of understanding that workflow with the ability to actually innovate and do something different, that's the magic. And so I'll give you a popular problem that we see amongst a lot of startups that come see us. I am the best, and I'll pick on machine learning for a second, I've got the best natural language processing team in this market. We are going to go out and solve the medical coding and transcription and billing problem. Hey, sounds awesome, you got some great tech. What do you know about medical transcription and billing? We got to go hire that person. Do you know how doctors work? Do you know how insurance companies work? That's kind of Byzantine to how payers and providers are all going to work together. We'll get back to you. That company's not going to be that successful. The marriage of that workflow knowledge. Good idea, no expertise in the work edge or the workflow. Well, traditionally you'd get excited about the expertise in tech. And what you realize in a lot of these areas, if you care about workflow, you care about solutions, it's about the marriage of the two. So when you look across our portfolio in applied AI and machine learning, we've actually got shockingly nine companies now that are at the intersection of machine intelligence and healthcare, both pre-clinical and clinical. And people are like, wow, that's really surprising for an infrastructure firm or an enterprise-focused firm like Amplify, and we're going, no. There's groundbreaking ML technology, but we're also finding that people know there's really high-value verticals and you put domain experts in there who really understand the solutions, give them powerful tools and we're seeing customers just adopt like this. And unlike the whole full-stack kind of integration, if you're going to have domain experts in the edge or that workflow, you got to have the data. You got to have the data. So data machine learning, I can see the connection there. Very smart, very clever. So I want to get your thoughts on two areas around this cloud 2.0, I think that come up a lot. Certainly machine learning, you mentioned is one of them but these other ones come up all the time as 2.0 problems and opportunities. Cloud 1.0, storage, compute and storage, no problem, easy, code away. Cloud 2.0, networking and security. So as the cloud, as everyone went to the cloud and cloud 1.0, they're now the clouds coming out of the cloud on premise. So you got edge of the network. So intelligent edge, security, if you're going to have low code and no code, it better be secure on the cover. So this has become two important points. Your reaction to networking and security as an investor in this cloud 2.0 vision. Yeah, there's different pieces of it. So networking, the closer you go to the edge and you say the word edge and edge is, a good bit of it is networking and it's also executing with limited resources because we could debate what the edge means for probably three hours when I was going to go there but what it certainly means is you don't have a big data center that's Amazon scale to run your stuff so you got to be more efficient and optimized in some dimension. So people that are really at the intersection of figuring out how to move things around efficiently, deliver with speed and reduce latency, giving platforms to developers at the edge, which, you know, if you've, you know, one of the big reasons for Fastly going public was to bring their edge development story out to the larger market. Absolutely agree with that. As it relates to broader security, we're seeing security started stop being a cyclical trend and started becoming a secular one pretty much at the moment the cloud exploded and those things are not, you know, not just a coincidence. As people got more comfortable with giving up control of the stuff that they'd had their arms around for years. The perimeter. Right at the same time that they said we're going to throw everything online and connect everything up and get our developers whatever they want and bring in all our partners to our, the amount of access to systems grew dramatically right at the same time people handed over a lot of these traditional workflows and processes and pieces of infrastructure. So yeah, I think a lot of people right now are really re-platforming to understand what it means to be, to build securely, to deploy securely, to run securely. And that's not always a firewall rack and stack boxes and scan packets type of a game. Yeah, yeah, security's certainly embedded in everything. It's not just part of the applications everywhere. That's native. Yeah. Final question for you. What are you guys investing in now? What's the hot air? As you mentioned machine learning. Give a quick plug for your key investment is what's the pitch to the entrepreneur? Yeah, so again, our pitch to the entrepreneur really hasn't changed from day zero and I don't see it changing anytime in the future which is if you're a world-beating technologist, you want someone who understand what it's like to work with other world-beating technologists and take them from startup to IPO and that's the thing that we know how to do both in previous careers as well as in the history at Amplify, that's the pitch. The things that we're really excited right now is what does it look like when the best academic experts in the world who understand new areas of machine learning who are really able to push the forefront of what we're seeing in reinforcement learning and machine vision and natural language processing are able to think beyond the narrow confines of what the tech can do and really partner up with domain experts. So there is a lot of domain-specific applied AI and ML that we're really excited about these days. We talked about healthcare but that is just the tip of the iceberg. We're excited about financial services. We're excited about traditional enterprise workflows. I'd say that that's one big bucket. We're as excited about the developers we've ever been. You and I were talking before we came on camera for this CUBE conversation around our early days in the industry. We were riffing on the OSI, Open Systems Interconnect stack. If you look at what that did, certainly it didn't always get standardized. It kind of standardized up to the TCP IP layer. But still, that changed the game in the computing industry now more than ever. This trend that we're on the next 10 years is really going to be about stacks involving and just complete horizontal scalability elastic resources, new ways to develop applications. I mean, a completely different ball game for the next 10 years. Your view of the next 10 years as this thousand flowers start to bloom with stacks changing and new application methods, how do you see it all? OSI was a great example of this trend that we go through every few months, so many years. Somebody creates something new, it's genius. It's maybe a little bit harder than it needs to be and at some point you want it to go mass market and you introduce an abstraction. And the abstractions continue to work as ways to bring more people in and allow them not to be top to bottom experts. We've done it in the technology industry since the 60s, thank you, thank you semiconductor world all the way on up. But now I think the new abstractions actually look a heck of a lot like the cloud platforms. They're abstractions. People want to say things like, I am going to deploy using Kubernetes. I want to container package my application. Now let me think from that level. Don't have me think about particular machines. Don't have me think about particular servers. That's one great example. Development's the same thing. You know, when you talk about low code and no code as ideas, it's just getting people away from the complexity of getting down on the weeds. So if you said, what's the next 10 years look like? I think it's going to be this continual pull of making things easier and more accessible for business users, abstracting, abstracting, abstracting. And then right up into the point where the abstractions get too generalized and then innovation will come in behind it. As I always say in the venture business, cool and relevant works and making things simple, easy to use and reducing the steps it takes to do something is always a winning formula. That's pretty good. Don't start any fun to compete with. Sunil, no, of course not. theCUBE funds coming in the next 10 years. Celebrating our 10 years, great to see you and it's been great to be on this journey with you guys at Amplify. Congratulations. Hey, congrats on all your success, John. It's always a pleasure. I appreciate it. Take care. Okay, I'm here with Sunil Daliwal inside theCUBE Studios. I'm John Furrier. Thanks for watching.