 Hello, and welcome to today's CUBE presentation of AWS Startup Showcase. I'm John Furrier, your host, highlighting the hottest companies in DevOps, data analytics and cloud management. Lisa Martin and Dave Vellante are here to kick it off. We've got a great program for you again. This is our new community event model where we're doing every quarter. We have a new episode. This is quarter three this year or episode three, season one of the hottest cloud startups and we're going to feature them. We're going to do a keynote package and then 15 companies will present their story, go check them out and then have a closing keynote with a practitioner and we've got some great lineups. Lisa, Dave, great to see you. Thanks for joining me. Hey guys. Great to be here. So Dave, I got to ask you, you're back in events. Lisa and I were at the Fortinet event where they had the Golf PGA Championship of the CUBE. Now we've got the hybrid model. This is the new normal we're in. We got these great companies. We're showcasing them. What's your take? Well, you're right. I mean, I think there's a combination of things. We're seeing some live shows. We saw what we did at Mobile World Congress. We did the show with AWS Storage Day where it was, we were at the spheres. There was no, there was a live audience but they weren't there physically, it was just virtual. And yeah, so, and I just got pained about reinvent. Hey Dave, you got to make your flights. So I'm making my flights. Yeah, we're going to be at the Amazon Web Services Public Sector Summit next week. Lisa, a lot of cloud convergence going on here. We got many companies being featured here that we spoke with, the CEOs and their top people, cloud management, DevOps, data analysis, security. Really cutting edge companies. Yes, cutting edge companies who were all focused on acceleration. We've talked about the acceleration of digital transformation the last 18 months and we've seen a tremendous amount of acceleration in innovation with what these startups are doing. We've talked to, like you said, their C-suite. We've also talked to their customers about how they are innovating so quickly with this hybrid environment, this remote work. And we've talked a lot about security in the last week or so. You mentioned that we were at 40 net, the cybersecurity skills gap. What some of these companies are doing with automation, for example, to help shorten that gap, which is a big opportunity for the job market. Yeah, great stuff Dave. So the format of this event, you're going to have a fireside chat with a practitioner. We'd like to end these programs with a great experience practitioner cutting edge in data fabric at the beginning. Lisa and I are going to be kicking off with, of course, Jeff Bard to give us the update on what's going on at AWS. And then a special presentation from Emily Freeman, who's the author of DevOps for Dummies. She's introducing new content, the revolution in DevOps, DevOps 2.0. And of course, Jerry Chen from Greylock, CUBE alumni is going to come on and talk about his new thesis, castles in the cloud, creating motes at cloud scale. We've got a great lineup of people. And so the front end is going to be great. Dave, give us a little preview of what people are going to expect at the end in the fireside chat. Well, at the highest level, John, I've always said we're entering the third great wave of cloud. First wave was experimentation. The second big wave was migration. The third wave is integration, deep business integration. And what you're going to hear from HelloFresh today is how they, like many companies that started early last decade, they started with an on-prem Hadoop system. And then of course, we all know what happened is S3 essentially took the knees out from the on-prem Hadoop market, lowered costs, brought things into the cloud. And what HelloFresh is doing is they're transforming from that legacy Hadoop system into, and it's running on AWS, but into a data mesh. You know, it's a passionate topic of mine. HelloFresh was scaling. They realized that they couldn't keep up. So they had to rethink their entire data architecture and they built it around data mesh. Clements Chi and Kristoff Sowande are going to explain how they actually did that on a journey toward decentralized data mesh. Great, and your posts have been awesome on data mesh. We get a lot of traction. Certainly your breaking analysis for the folks watching. Check out Dave Vellante's breaking analysis every week, highlighting the cutting edge trends in tech. Dave, we're going to see you later. Lisa and I are going to be here in the morning talking about with Emily. We've got Jeff Barr teed up. Dave, thanks for coming on. We're looking forward to the fireside chat. Lisa, we'll see you when Emily comes back on, but we're going to go to Jeff Barr right now for Dave and I are going to interview Jeff. Hey, Jeff. There he is. Hey, how are you? How are you doing? How's it going? Very well. So I got to ask you, the reinvent is on. Everyone wants to know that's happening, right? We're good with reinvent. Reinvent is happening. I've got my hotel and actually listening to Dave, I just remembered I still need to actually book my flights. I've got my to-do list on my desk and I do need to get my flights. Really looking forward to it. I can't wait to see all the announcements and blog posts. We're going to see you from Jerry Chen later. I'd love to, after on our next event, get your reaction to this. Castle and Castle's on the cloud where competitive advantages can be built in the cloud, we're seeing examples of that. But first I got to ask you, give us an update on what's going on in the APN ecosystem. There's been an incredible celebration these past couple of weeks. So a lot of different things happening and the interesting thing to me is that as part of my job, I often think that I'm effectively living in the future because I get to see all this really cool stuff that we're building just a little bit before our customers get to. And so I'm always thinking, okay, here I am now and what's the world going to be like in a couple of weeks to a month or two when these launches I'm working on actually get out the door. And that's always really, really fun, just kind of getting that little edge into where we're going. But this year was a little interesting because we had two really significant birthdays. We had the 15 year anniversary of both EC2 and S3 and we're so focused on innovating and moving forward that it's actually pretty rare for us at AWS to look back and say, wow, we've actually done all these amazing things in the last 15 years. You know what's kind of cool, Jeff, if I may is, you know, of course in the early days, everybody said, well, place for startup is AWS. And now the great thing about the startup showcases we're seeing these startups that are very near or some of them have even reached escape velocity. So they're not tiny little companies anymore. They're in there transforming their respective industries. They really are. And I think that as these startups grow, they really start to lean into the power of the cloud. As they start to think, okay, we've got our basic infrastructure in place. We're serving data, we're serving up a few customers. Everything's actually working pretty well for us. We've got our fundamental model proven out. Now we can invest in publicity and marketing, in scaling, but they don't have to think about what's happening behind the scenes. If they've got their auto scaling or if they're serverless, the infrastructure simply grows to meet their demand. And it's just a lot less things that they have to worry about. They can focus on the fun part of their business, which is actually listening to customers and building up an awesome business. Jeff, as you guys are putting together all the big pre reinvent, I know there's a lot of stuff that goes on prior as well. And they say, well, the good stuff are reinvent. But you start to see some themes emerge this year. One of them is modernization of applications. The speed of application development in the cloud with the cloud scale, DevOps personas, whatever personas you want to talk about, but basically speed. It's the speed of the app developers where other departments have been slowing things down. I won't say name names, but security group and IT. I mean, I shouldn't have said that, but not only kidding. But no, but seriously, people want it in minutes and seconds now, not days or weeks, whether it's policy. What are some of the trends that you are seeing around this year as we get into some of the new stuff coming out? So Dave, customers really do want speed. And we've actually encapsulated this for a long time in Amazon in what we call the bias for action leadership principle where we just need to jump in and move forward and make things happen. A lot of customers look at that and they say, yes, this is great. We need to have the same bias for action. Some do, some are still trying to figure out exactly how to put it into play. And they absolutely for sure need to pay attention to the security, they need to respect the past and make sure that whatever they're doing is in line with IT, but they do want to move forward. And the interesting thing that I see time and time again is it's not simply about let's adopt a new technology. It's how do we keep our workforce engaged? How do we make sure that they've got the right training? How do we bring our IT team along for this hopefully new and fun and exciting journey where they get to learn some interesting new technologies. They've got all this very much accumulated business knowledge that they still want to put to use. Maybe they're a little bit apprehensive about something brand new and they hear about the cloud, but they're by and large, they really want to move forward. They just need a little bit of help to make it happen. Real quick. One of the things that you're going to hear today when talking about speed, traditionally going fast, oftentimes you meant you have to sacrifice some things on quality. What are you going to hear from some of the startups today is how they're addressing that to automation and modern DevOps technologies and sort of rethinking that whole application development approach. That's something I'm really excited to see organizations beginning to adopt so they don't have to make that trade off anymore. Yeah, I would never want to see someone sacrifice quality but I do think that iterating very quickly and using the best of DevOps principles to be able to iterate incredibly quickly and get that first launch out there and then listen with both ears just as much as you can. Everything you hear iterate really quickly to meet those needs in hours and in days, not months, quarters or years. Great stuff, Jeff. And a lot of the companies we're featuring here in the startup showcase represent that new kind of thinking, systems thinking, as well as the cloud scale. And again, it's finally here, the revolution of DevOps is going to the next generation and we're excited to have Emily Freeman who's going to come on and give a little preview for her new talk on this revolution. So Jeff, thank you for coming on. Appreciate you sharing the update here on theCUBE. Happy to be here. I'm actually really looking forward to hearing from Emily. Yeah, it's great. Great, looking forward to the talk. Brand new premiere. Okay, Lisa Martin, Emily Freeman is here. She's ready to come in and we're going to preview her lightning talk. Emily, thanks for coming on. We really appreciate you coming on. Really, this is about a talk around DevOps next gen. And I think, Lisa, this is one of those things we've been discussing with all the companies. It's a new kind of thinking. It's a revolution. It's a systems mindset. You're starting to see the connections. There she is, Emily. Thanks for coming on. Appreciate it. Thank you for having me. So your teaser video was amazing. You know, that little secret radical idea, something completely different. You got a talk coming up. What's the premise behind this revolution? You know, tying together architecture, development, automation, deployment, operating all together. Yes. Well, we have traditionally always used the SDLC, which is the software delivery lifecycle. And it is a straight linear process that has actually been around since the sixties, which is wild to me and really originated in manufacturing. And as much as I love, you know, the Toyota production system and how much it has shown up in DevOps as a sort of inspiration on how to run things better, we are not making cars. We are making software. And I think we have to use different approaches and create a sort of model that better reflects our modern software development process. Well, it's a bold idea. I'm looking forward to the talk. And as motivation, I went into my basement and dusted off all my books from college in the eighties. And the CES meant it was waterfall. It was software development, lifecycle. They trained us to think this way. And it came from the mainframe, people. It was like it's old school, like really, really old. And it really hasn't been updated. Where's the motivation? I actually cloud is kind of converging everything together, we see that. But you kind of hit on this persona thing. Where did that come from, this persona? Because, you know, people want to put people in buckets. I'm a release engineer. I mean, where's that motivation coming from? Yes, you're absolutely right that it came from the mainframes. I think, you know, waterfall was necessary when you're using a punch card or a mag tape to load things onto a mainframe. But we don't exist in that world anymore, thank goodness. And yes, so we use personas all the time in tech. You know, even to register, well, not actually to register for this event, but a lot of events, a lot of events, you have to click that dropdown, right? Are you a developer? Are you a manager? Whatever. And the thing is personas are immutable in my opinion. I was a developer, I will always identify as a developer despite playing a lot of different roles and doing a lot of different jobs. And this can vary throughout the day, right? You might have someone who has a title of software architect who ends up, you know, helping someone pair program or develop or test or deploy. And so we wear a lot of hats day to day. And I think our discussions around roles would be a better, certainly a better approach than personas. You know, Lisa and I have been discussing with many of these companies around the roles and we're hearing from them directly and they're finding out that people have, they're mixing and matching on teams. So you're an SRE on one team and you're doing something on another team where the workflows and the workloads define the team formation. So this is a cultural discussion. It absolutely is, yes. I think it is a cultural discussion and it really comes to the heart of DevOps, right? It's people process and then tools. DevOps has always been about culture and making sure that developers have all the tools they need to be productive and honestly happy. What good is all of this if developing software isn't a joyful experience? Well, I got to ask you while I got you here, obviously with serverless and functions you're starting to see this kind of this next gen. And we're going to hear from Jerry Chen, who's a Greylock VC who's going to talk about castles in the clouds where he's discussing the motes that could be created with a competitive advantage in cloud scale. And I think he points to the snowflakes of the world. You're starting to see this new thing happening. This is DevOps 2.0. This is the revolution. Is this kind of where you see the same vision of your talk? Yes, so DevOps created 2008, 2009, totally different ecosystem in the world we were living in. We didn't have things like serverless and containers. We didn't have this sort of default distributed nature certainly not the cloud. And so I'm very excited for Jerry's talk. I'm curious to hear more about these motes. I think it's fascinating. But yeah, you're seeing different companies you use different tools and processes to accelerate their delivery. And that is the competitive advantage. How can we figure out, how do you utilize these tools in the most efficient way possible? Well, Emily, thank you for coming on and giving a little preview. Let's now go to your lightning keynote talk. Fresh content premiere of this revolution in DevOps Emily Freeman's talk. We'll go there now. Hi, I'm Emily Freeman. I'm the author of DevOps for Dummies and the curator of 97 things every cloud engineer should know. I am thrilled to be here with you all today. I'm really excited to share with you a kind of wild idea, a complete re-imagining of the SDLC. And I wanna be clear, I need your feedback. I want to know what you think of this. You can always find me on Twitter at editing Emily. Most of my work centers around DevOps. And I really can't overstate what an impact the concept of DevOps has had on this industry. In many ways, it built on the foundation of agile to become a default, a standard we all reach for in our everyday work. When DevOps surfaced as an idea in 2008, the tech industry was in a vastly different space. AWS was an infancy offering only a handful of services. Azure and GCP didn't exist yet. The majority of companies maintained their own infrastructure. Developers wrote code and relied on sysadmins to deploy new code at scheduled intervals. Sometimes months apart. Container technology hadn't been invented. Applications adhered to a monolithic architecture. Databases were almost exclusively relational and serverless wasn't even a concept. Everything from the application to the engineers was centralized. Our current ecosystem couldn't be more different. Software is still hard. Don't get me wrong, but we continued to find novel solutions to consistently difficult, persistent problems. Now, some of these end up being a sort of rebranding of old ideas, but others are a unique and clever take to abstracting complexity or automating toil, or perhaps most important, rethinking, challenging the very premises we have accepted as canon for years, if not decades. In the years since DevOps attempted to answer the critical conflict between developers and operations engineers, DevOps has become a catch-all term and there have been a number of derivative works. DevOps has come to mean 5,000 different things to 5,000 different people. For some, it can be distilled to continuous integration and continuous delivery, or CI CD. For others, it's simply deploying code more frequently, perhaps adding a smattering of tests. For others, still it's organizational. They've added a platform team, perhaps even a questionably named DevOps team, or have created an engineering structure that focuses on a separation of concerns, leaving feature teams to manage the development, deployment, security, and maintenance of their siloed services. Whatever the interpretation, what's important is that there isn't a universally accepted standard of what DevOps is or what it looks like in execution. It's a philosophy more than anything else, a framework. People can utilize to configure and customize their specific circumstances to modern development practices. The characteristic of DevOps that I think we can all agree on though, is that it attempted to capture the challenges of the entire software development process. It's that broad umbrella, that holistic view that I think we need to breathe life into again. The challenge we face is that DevOps is an increasingly outmoded solution to a previous problem. Developers now face cultural and technical challenges far greater than how to more quickly deploy a monolithic application. Cloud Native is the future, the next collection of default development decisions, and one the DevOps story can't absorb in its current form. I believe the era of DevOps is waning. And in this moment, as the sun sets on DevOps, we have a unique opportunity to rethink, rebuild, replatform even. Now I don't have a crystal ball that would be very handy. I'm not completely certain what the next decade of tech looks like. And I can't write this story alone. I need you. But I have some ideas that can get the conversation started. I believe to build on what was, we have to throw away assumptions that we've taken for granted all this time. In order to move forward, we must first step back. The software or systems development lifecycle, what we call the SDLC, has been in use since the 1960s. And it's remained more or less the same since before color television and the touch-tone phone. Over the last 60 or so odd years, we've made tweaks, slight adjustments, massaged it. The stages or steps are always a little different with agile and then DevOps. We sort of looped it into a circle and then an infinity loop. We've added pretty colors. But the SDLC is more or less the same. And it has become an assumption. We don't even think about it anymore. Universally adopted constructs like the SDLC have an unspoken permanence. They feel as if they have always been and always will be. I think the impact of that is even more potent if you were born after a construct was popularized. Nearly everything around us is a construct, a model, an artifact of a human idea. The chair you're sitting in, the desk you work at, the mug from which you drink coffee, or sometimes wine, buildings, toilets, plumbing, roads, cars, art, computers, everything. The SDLC is a remnant, an artifact of a previous era. And I think we should throw it away. Or perhaps more accurately, replace it. Replace it with something that better reflects the actual nature of our work. A linear, single-threaded model designed for the manufacture of material goods cannot possibly capture the distributed complexity of modern socio-technical systems. It just can't. And these two ideas aren't mutually exclusive. That the SDLC was industry-changing, valuable, and extraordinarily impactful. And that it's time for something new. I believe we are strong enough to hold these two ideas at the same time showing respect for the past while envisioning the future. Now, I don't know about you. I've never had a software project go smoothly in one go. No matter how small. Even if I'm the only person working on it and committing directly to master. Software development is chaos. It's a study in entropy, and it is not getting any more simple. The model with which we think and talk about software development must capture the multi-threaded, non-sequential nature of our work. It should embody the roles engineers take on and the considerations they make along the way. It should build on the foundations of Agile and DevOps and represent the iterative nature of continuous innovation. Now, when I was thinking about this, I was inspired by ideas like extreme programming and the spiral model. I wanted something that would have layers, threads even, a way of visually representing multiple processes happening in parallel. And what I settled on is the revolution model. I believe the visualization of revolution is capable of capturing the pivotal moments of any software scenario. And I'm going to dive into all the discrete elements, but I wanna give you a moment to have a first impression, to absorb my idea. I call it revolution because, well, for one, it revolves. Its circular shape reflects the continuous and iterative nature of our work, but also because it is revolutionary. I am challenging a 60-year-old model that is embedded into our daily language. I don't expect Gartner to build a magic quadrant around this tomorrow, but that would be super cool and you should call me. My mission with this is to challenge the status quo, to create a model that I think more accurately reflects the complexity of modern cloud-native software development. The revolution model is constructed of five concentric circles, describing the critical roles of software development, architecting, development, automating, deploying, and operating. Intersecting each loop are six spokes that describe the production considerations every engineer has to consider throughout any engineering work. And that's testability, security, reliability, observability, flexibility, and scalability. The considerations listed are not all-encompassing. There are, of course, things not explicitly included. I figured if I put 20 spokes, some of us, including myself, might feel a little overwhelmed. So let's dive into each element in this model. We have long-used personas as the default way to divide audiences and tailor messages to group people. Every company in the world right now is repeating the mantra of developers, developers, developers. But personas have always bugged me a bit because this approach typically either oversimplifies someone's career or needlessly complicates it. A few people fit cleanly and completely into persona-based buckets, like developers and operations anymore. The lines have gotten fuzzy. On the other hand, I don't think we need to specifically tailor messages as to call out the difference between a DevOps engineer and a released engineer or a security administrator versus a security engineer. But perhaps most critically, I believe personas are immutable. A persona is wholly dependent on how someone identifies themselves. It's intrinsic, not extrinsic. Their titles may change, their jobs may differ, but they're probably still selecting the same persona on that ubiquitous dropdown we all have to choose from when registering for an event. Probably this one too. I was a developer and I will always identify as a developer despite doing a ton of work in areas like DevOps and AIOps and DevRel. In my heart, I'm a developer. I think about problems from that perspective first. It influences my thinking and my approach. Roles are very different. Roles are temporary, inconsistent, constantly fluctuating. If I were an actress, the parts I would play would be lengthy and varied, but the persona I would identify as would remain an actress, an artist, a thespian. Your work isn't confined to a single set of skills. It may have been a decade ago, but it is not today. In any given week or sprint, you may play the role of an architect thinking about how to design a feature or service. A developer, building out code or fixing a bug, an automation engineer, looking at how to improve manual processes we often refer to as TOIL, a release engineer, deploying code to different environments or releasing it to customers, or an operations engineer, ensuring an application functions in consistent, expected ways. And no matter what role we play, we have to consider a number of issues. The first is testability. All software systems require testing to assure architects that designs work, developers that code works, operators that infrastructure is running as expected, and engineers of all disciplines that code changes won't bring down the whole system. Testing in its many forms is what enables systems to be durable and have longevity. It's what reassures engineers that changes won't impact current functionality. A system without tests is a disaster waiting to happen, which is why testability is first among equals at this particular round table. Security is everyone's responsibility, but if you understand how to design and execute secure systems, I struggle with this. Security incidents, for the most part, are high-impact, low-probability events. The really big disasters, the ones that end up on the news and get us all free credit reporting for a year, they don't happen super frequently. And then goodness, because you know that there are endless small vulnerabilities lurking in our systems. Security is something we all know we should dedicate time to, but often don't make time for. And let's be honest, it's hard and complicated and a little scary. DevSecOps, the first derivative of DevOps asked engineers to move security left. This approach meant security was a consideration early in the process, not something that would block a release at the last moment. This is also the consideration under which I'm putting compliance and governance. While not perfectly aligned, I figure all the things you have to call lawyers for should just live together. I'm kidding, but in all seriousness, these three concepts are really about risk management. Identity, data, authorization, it doesn't really matter what specific issue you're speaking about. The question is who has access to what, when and how? And that is everyone's responsibility at every stage. Site reliability engineering or SRE is a discipline and job and approach for good reason. It is absolutely critical that applications and services work as expected most of the time. That said, availability is often mistakenly treated as a synonym for reliability. Instead, it's a single aspect of the concept. If a system is available, but customer data is inaccurate or out of sync, the system is not reliable. Reliability has five key components. Availability, latency, throughput, fidelity and durability. Reliability is the end result, but resiliency for me is the journey. The action engineers can take to improve reliability. Observability is the ability to have insight into an application or system. It's the combination of telemetry and monitoring and alerting available to engineers and leadership. There's an aspect of observability that overlaps with reliability. But the purpose of observability isn't just to maintain a reliable system, though that is of course important. It is the capacity for engineers working on a system to have visibility into the inner workings of that system. The concept of observability actually originates in linear dynamic systems. It's defined as how well internal states of a system can be understood based on information about its external outputs. It is critical when companies move systems to the cloud or utilize managed services that they don't lose visibility and confidence in their systems. The shared responsibility model of cloud storage, compute and managed services require that engineering teams be able to quickly be alerted to identify and remediate issues as they arise. Flexible systems are capable of adapting to meet the ever-changing needs of the customer in the market segment. Flexible code bases absorb new code smoothly, embody a clean separation of concerns, are partitioned into small components or classes, and architected to enable the now as well as the next. In flexible systems, change dependencies are reduced or eliminated. Database schemas accommodate change well, components communicate via a standardized and well-documented API. The only thing constant in our industry is change. And every role we play, creating flexibility and solutions that can be flexible, that will grow as the applications grow, is absolutely critical. Finally, scalability. Scalability refers to more than a system's ability to scale for additional load. It implies growth. Scalability in the revolution model carries the continuous innovation of a team and the byproducts of that growth within a system. For me, scalability is the most human of the considerations. It requires each of us in our various roles to consider everyone around us. Our customers who use the system or rely on its services, our colleagues, current and future with whom we collaborate, and even our future selves. Software development isn't a straight line, nor is it a perfect loop. It is an ever-changing, complex dance. There are twirls and pivots and difficult spins, forward and backward engineers move in parallel, creating truly magnificent pieces of art. We need a modern model for this modern era, and I believe this is just the revolution to get us started. Thank you so much for having me. Hey, we're back here live in the keynote studio. I'm John Furrier, your host here with Lisa Martin. Dave Vellante is getting ready for the fireside chat, ending keynote with the practitioner. Hello, Fresh with our data mesh. Lisa, Emily is amazing. The funky artwork there, she's amazing with the talk. I was mesmerized, it was impressive. The revolution of DevOps and the creative element was a really nice surprise there, but I love what she's doing. She's challenging the status quo. We've learned nothing in the last year and a half. We need to challenge the status quo. A model from the 1960s that is no longer linear. What she's doing is revolutionary. And we hear this in all the time, all the key interviews we do is that you're seeing the leaders, the SVPs of engineering or these departments, where there's new people coming in that are engineering or developers, they're playing multiple roles. It's almost a multidisciplinary aspect where it's like going in to in and out, but you're on the fryer later and then you're doing the grill, you're doing the cashier. People are changing roles. They're in architect, they're test release, all in one. No longer departmental, slow, siloed groups. She brought up a great point about personas that we no longer fit into these buckets, that the changing roles are really the driver of how we should be looking at this. I think I'm really impressed. Really bold idea, no brainer as far as I'm concerned. I think one of the things, and the comments were off the charts, that a lot of young people come from Discord servers. We had a good traction over there, but they're all like learning. Then you have the experienced people saying, this definitely has happened and happening. The dominoes are falling and they're falling in the direction of modernization. That's the key, Trant. Speed. Absolutely with speed, but the way that Emily is presenting it is not in a branch, it's bold, but it's in a way that makes great sense. The way that she creatively and visually lined out what she was talking about is amenable to the folks that have been doing this since the 60s and the new folks now to really look at this from a different lens. Yeah, and I think that she's a great setup on that lightning top of the 15 companies we got because you think about Sysdig, Harness I.O., White Source, Lumigo, Hacker One, Send.io, Okara Thought Spot, Rockset, Privacera, OpsRAMP and Ops, Montecloud, Opsani, all are doing modern stuff and we talked to them. And they're all on this new wave, this monster wave coming. What's your observation when you talk to these companies? They are, it was great. I got to talk with 8 of the 15 and the amount of acceleration of innovation that they've done in the last 18 months is phenomenal. Obviously with the power and the fuel and the brand reputation of AWS, but really what they're all facilitating is a cultural shift. When we think of DevOps and the security folks, there's a lot of work going on with AI to an automation to really kind of enable the DevOps folks to be in control of the process, not have to be security experts, but ensuring that the security is baked in, shifting left. Yeah, and we saw that the chatroom was really active on the security side. And one of the things I noticed was not just shift left, but the other groups, the security groups and the theme of cultural, I won't say war, but collision, cultural shift that's happening between the groups is interesting because you have this new DevOps persona that's been around as Emily pointed out for a while, but now it's going to the next level. There's new revolutions about a mindset, a systems mindset, it's a thinking. And you start to see the new young companies coming out, being funded by the Grey Lux of the world, who are now like not going to be given the, oh, we lost the top three clouds won everything. There's new business models and new technical architectures in the cloud. And that's going to be Jerry Chen's talk coming up next is going to be castles in the cloud. Because Jerry Chen always talks about moats, competitive advantage and how moats are key to success to guard the castle. And then we always joke, there's no more moats because the cloud has killed all the moats. But now the moats are in the cloud. The castles are in the cloud, not on the ground. So very interesting thought provoking, but he's got data. And if you look at the successful companies like the snowflakes of the world, he's starting to see these new formations of this new layer of innovation where companies are growing rapidly. 98 unicorns now in the cloud, unbelievable. Wow, that's a lot. One of the things you mentioned there's competitive advantage and these startups are all fueled by that. They know that there are other companies in the rearview mirror right behind them. If they're not able to work as quickly and as flexibly as a competitor, they have to have that speed, that time to market, that time to value. It was absolutely critical. And that's one of the things, I think thematically that I saw along the eighth startups that I talked to is that time to value is absolutely table stakes. Well, I'm looking forward to talking to Jerry Chan because we've talked on theCUBE before about this whole idea of what happens when winter takes most, meaning the top three, four cloud players. What happens? And we were talking about that and saying, if you have a model where an ecosystem can develop, what does that look like? And back in 2013, 2014, 2015, no one really had an answer. Jerry was the only VC. He really nailed it with this castles in the cloud. He nailed the idea that this is going to happen. So I think we'll look back at the tape or the videos from theCUBE, we'll find those cuts, but we were talking about this then. We were pontificating and riffing on the fact that there's going to be new winners and they're going to look different. As Andy Jassy always says on theCUBE, you have to be misunderstood if you're really going to make something happen. Most of the most successful companies are misunderstood. Not anymore, the cloud scales there. And that's what's exciting about all of this. It is exciting that the scale is there. The appetite is there. The appetite to challenge the status quo, which is right now in this economic and dynamic market that we're living in is there's nothing better. Yeah, one of the things that's come up and that's just real quick before we bring Jerry in is automation has been in security. Security's been in every conversation. But automation is now so hot in the sense of it's real and it's becoming part of all the design decisions. How can we automate? Can we automate faster? What are the keys to automation? Is it having the right data? What data is available? So I think the idea of automation and AI are driving all the change. And that's to me is what these new companies represent this modern error where AI is built into the outcome and the apps and all that infrastructure. So it's super exciting. Let's check in. We got Jerry Chen lined up. Lisa, great to share with you. We're going to come back after Jerry and then kick off the day. Let's bring in Jerry Chen from Greylock. Is he here? Let's bring him in. There he is. Hey, John, good to see you. Hey, congratulations on an amazing talk and thesis on the castles on the cloud. Thanks for coming on. Thanks for reading. It's always weird when you put a piece of work out on the ether, not sure what the response is but it seemed to resonate with a bunch of developers, founders and investors and folks like yourself. So the smart people seem to gravitate to us. So thank you very much. Well, one of the benefits of doing the cube for 11 years, Jerry, is we have videotape of many, many people talking about what the future will hold. You kind of were on this early. It wasn't called castles on the cloud, but you were all, I was, we had many conversations and we were kind of connecting the dots in real time. But you've been on this for a while and it's great to see the work. I really think you nailed this. I think you're absolutely on point here. So let's get into it. What is castles on the cloud? New research has come out from Greylock that you spearheaded, it's a collaborative effort but you've got data behind it. Give a quick overview of what is castles on the cloud, the new modes of competitive advantage for companies. Yeah, it's a group project that our team put together but basically, John, the question is, how do you win in the cloud? Right, remember the conversations we had eight years ago at Amazon re-event was, holy cow, like, can you compete with them? Like, is it winner take all, winner take most? And if it is winner take most, where are the white spaces for some startups to emerge? And clearly the past eight years in the cloud, this journey, we've seen big companies, Databricks, Snowflakes, Elastic, Mongo, DataRobot. And so, the spot of the question is, why are the castles in the cloud, the big three cloud providers, Amazon, Google, and Azure winning, what advantages do they have? And then given their modes of scale, network effects, how can you as a startup win? And so, look, there are 500 plus services between all three cloud vendors, but there are like 500 plus startups competing against the cloud vendors. And there's like almost a hundred unicorns of private companies competing successfully against the cloud vendors, including public companies. So like, Elastic, Mongo, Snowflake, Databricks, not public yet, HashiCorp, not public yet. These are some examples of the names I think are winning and, you know, watch this space because you see more of these guys storm the castle if you will. Yeah, and you know, one of the things that's a funny metaphor because it has many different implications. One is we talk about security, the perimeter, the gates, the modes being on land, but now you're in the cloud, you have also different security paradigm. You have a different new kinds of services that are coming on board faster than ever before, not just from the cloud players, but from companies contributing into the ecosystem. So you have a combination of the big three, making the market, the main markets. You got, I think you call it 31 markets that we know of, that probably may be more. And then you have this notion of a sub market, which means that there's like, we used to call it white space back in the day. Remember how many whites, where's the white space? I mean, and if you're in the cloud, there's like a zillion white spaces. So talk about this sub market dynamic between markets and that are being enabled by the cloud players and how these sub markets play into it. Sure, so first, the first problem was, what we did, we downloaded all the services from the big three clouds, right? And, you know, what Azure calls a database or a database service like a document DB and Amazon is like CosmoDB and Azure. So first thing first is we had to like, look at all three cloud providers and, you know, re-caggerize all the services, almost 500 apples to apples to apples, number one. Number two is you looked at all these markets or sub markets and said, okay, how can we cluster these services into things that, you know, you and I can grok, right? Because what Amazon and Azure and Google think about it is very different. And the beauty of the cloud is this kind of fat long tail of services for developers. So instead of like Oracle as a single database for all your needs, they're like 20 or 30 different databases from time series, analytic databases. We're talking to Rockset later today, right? Document databases like Mongo, search database like Elastic. And so what happens is there's not one giant market like databases, there's a database market and 30, 40 sub markets that serve the needs of developers. So the great news is cloud has reduced the cost and creates something new for developers. Also the good news is for a startup you can find plenty of white speeds with solving a pain point very specific to a different type of problem. Yeah, and you can sequence up the power law too. I love the power law metaphor. You know, it used to be a very thin neck, no torso and then a long tail. But now as you're pointing out this expansion of the fat tail of services, but also there's big tabs and markets available at the top of the power law where you see companies like Snowflake essentially take on the data warehousing market by basically sitting on Amazon and refactoring with new services and then getting a flywheel, completely changing the economic, unit economics, completely changing the consumption model, completely changing the value proposition. Literally overnight. So you think Snowflake has created like a storm, create a whole of that mode or that castle wall against Redshift, then companies like Rockset doing real-time analytics is rushing right behind Snowflake saying, hey, Snowflake's great for data warehouse, but it's not fast enough for real-time analytics. Let me give you something new. So to your power law argument, even the big logistics, Snowflake have created kind of a wake behind them that created even more white space for guys at Rockset. So that's exciting for guys like me and you. And then also as we were talking about our last episode two or quarter two of our showcase from a VC came on, it's like the old shelf where you didn't know if a company was successful until they had to return the inventory. Now with cloud, if you're not successful, you know it right away. It's like, it's no debate. Like, I mean, you're either winning or not. There's like, that's so instrumented. So a company can have a good, better mousetrap and win and fill the white space and then move up. It goes both ways. The cloud vendor, the big three, Amazon, Google and Azure for sure, they instrument their own class. They know, John, which ecosystem partners doing well and which ecosystem is doing poorly and they hear from the customers exactly what they want. So it goes both ways. They can weaponize that info just as well as use a starter to weaponize that info. And that's the big argument of dude that Snowflake still pays the Amazon bills. They're still there. So again, repeat creation comes back. That's a big conversation that's come up. What's your quick take on that? Because if you're going to have a castle in the cloud, then you're going to bring it back to land. I mean, what's that dynamic? Where do you see that competing? Because on one hand it's innovation. The other one's maybe cost efficiency. Is that a growth indicator? Slow down. What's your view on the movement from and to the cloud? I think there's probably three forces you're finding here. One is the cost advantage and the scale advantage of cloud. So that I think has been going for the past eight years. There's a repatriation movement for a certain subset of customers that I think for cost purposes makes sense. I think that's a tiny handful that believe they can actually run things better than a cloud. The third thing we're seeing around repatriation is not necessarily against cloud, but you're going to see more decentralized clouds and things pushed to the edge, right? So you look at companies like Cloudflare, Fastly or a company that we're investing in, Kato Networks. All they do is focus on secure access at the edge. And so I think that's not necessarily repatriation to my own data center, but it's kind of a disaggregation of cloud from one giant monolithic cloud in like AWS East or like a Google region in Europe to multiple smaller clouds for governance purposes, security purposes or latency purposes. So I'm looking at my notes here. I have to look down on the screen here for this, to read this, because it's a cut and paste from your thesis on the cloud, Fastly on the cloud. The of the $38 billion invested this quarter, AI and ML number one, analytics number two, security number three, actually security is number one, but you can see the bubbles here. So all those are data problems. So I need to ask you, I see data is hot. Data as intellectual property. How do you look at that? Because we've been reporting on this and we just started a CUBE conversation around workflows as intellectual property. If you have scale and your mode is in the cloud, you could argue that data and the workflows around those data streams is intellectual property. It's a protocol. I believe both are. And they just kind of, they go hand in hand, like peanut butter and jelly, right? So data for sure is IP. So if people talk about data and the oil, the new research, that's largely true because it powers a bunch, but the workflow to your point, John is sticky because every company is a unique snowflake, right? Like the process used to run the CUBE and your business different how we run our business. So if you can build a workflow that leverages the data, that's super sticky. So in terms of switching costs, if my workflow is very bespoke to your business, then I think that's a competitive advantage. Well, certainly your workflow is a lot different than the CUBE. You guys have been doing a lot of billions of dollars in capital, we're talking to all the people out here. Jerry, great to have you on. Final thought on your thesis. Where does it go from here? What's been the reaction? I know you put it out there, great. Love the research. I think you're on point on this one. Where does it go from here? We have two follow-up pieces in the near term. One around a deep diver on open source. So look out for that pretty soon and how that's been a powerful strategy. A second is this kind of just aggregation of the cloud via blockchain and decentralized apps, via edge applications. So that's in the near term, two more pieces of deep diver doing. And then the goal here is to update this on a quarterly annual basis. So we're getting submissions from founders that wanted to say, hey, you missed us or you screwed up here. We got the big cloud vendor saying, hey, Jerry, we just lost this new thing. So our goal here is to update this every single year and then probably do a look back saying, okay, where were we wrong? Where were we right? And then let's say the cast on the cloud is 2022. We'll see the difference. Where are the more unicorns? Where are the more services? Where are the IPOs happening? So look for some short-term work from us on analytics, like around open source and cloud. And then next year we hope to roll this forward saying, hey, year after year, what's happening? What's changing? Great stuff. And congratulations. I just saw the news. You guys put another half a billion dollars into early, early stage, which is your roots. And you're still doing a lot of great investments and got a lot of unicorns. Congratulations, that great luck on the team. Thanks for coming on. And congratulations. You nailed this one. I think we're going to look back and say that this is a pretty seminal piece of work here. Thanks for sharing. Thanks, John. Thanks for having me as always. Okay, this is theCUBE here at 80 by Startup Showcase. We're about to get going in on all the hot companies closing out the keynote. Lisa, obviously Jerry Chen, CUBE alumni. He was right from day one. We've been riffing on this, but he nails it here. I think Greylock is lucky to have him as the general partner. He's done great deals. But I think he's hitting the next wave big. And this is huge. I was listening to you guys talk and thinking if you had a crystal ball back in 2013, 2014, some of the things Jerry's saying now, his narrative now, did he have a crystal ball? He did. I mean, he could be a CUBE host and I could be a venture capitalist. We were both right on these. So we could have been doing that together. No, in all seriousness, no, he was right. I mean, we talked off camera about who's the next Amazon? Who's going to challenge Amazon? And Andy Jassy was quoted many times in the CUBE by saying he was surprised that it took so long for people to figure out what they were doing. Okay, Jerry was at VMware. He had visibility into the cloud. He saw Amazon right away like we did. Like this is a winning formula. And so he was really upfront on this one. Well, the investments that they're making in these unicorns is exciting. They have this lens that they're able to see the opportunities there almost before anybody else can and finding more white space where we didn't even know there was any. Yeah. And what's interesting with two about the report I'm going to dig into it. I want to get to them while he's on camera because it was a great report, but he says it's like 500 services. I think Amazon has 5,000. So how you define services is an interesting thing. And a lot of Amazon services that they have, Azure doesn't have, and vice versa, they do call that out. So I find the report interesting. It's going to be a feature game in the future between clouds, the big three. They're going to say, we do this. You're starting to see the formation. Google is much more developer oriented. Amazon is much more stronger in the governance area with data. Obviously, as he pointed out, they have such experience. Microsoft, not so much. They're developer cloud and more office, not so much on the governance side. So that's an indicator in my opinion of kind of where they rank. So clearly number one is still Amazon web services. Azure, long second place, way behind. Google, right behind Azure. So we'll see how the horses come in. Right. And it's also kind of speaks to the hybrid world in which we're living, the hybrid multi-cloud world in which many companies are living as companies to not just survive in the last year and a half, but to thrive and really have to become data companies and leverage that data as a competitive advantage to be able to unlock the value of it. And a lot of these startups that we talked to in the showcase are talking about how they're helping organizations unlock that data value. As Jerry said, data's the new oil. It's the new gold. Not unless you can unlock that value faster than your competition. Yeah. Well, I'm super excited. We've got a great day ahead of us with all the hot startups. And then at the end, Dave Vellante is going to interview hello, fresh practitioners. We're going to close it out every episode and now we're going to do with a closing practitioner. We try to get JPMorgan Chase. Data mesh is the hottest area right now in the enterprise. Data is new competitive advantage. We know that data workflows are now an intellectual property. You're starting to see data really factor into these applications now as a key aspect of the competitive advantage and the value creation. So companies that are smart are investing heavily in that and the ones that are kind of slow on the uptake are lagging the market and just trying to figure it out. So you're starting to see that transition and you're starting to see people fall away now from the fact that they're not going to make it, right? You're starting to look at any app and saying how much AI is really in there? Real AI, what's their data strategy? And you can almost squint through that and go, okay, that's going to be a losing application. Well, the winners are making it a board level conversation. Yeah. And security isn't built in. Lisa, great to have you on this morning. Kicking it off. Thanks, John. Okay. We're going to go into the next set of the program at 10 o'clock. We're going to move into the breakouts. Check out the companies. There's three tracks in there. We have an awesome track on DevOps, pure DevOps. We've got the data and analytics and we've got the cloud management and just to run down real quick, check out the Sysdig, Harness I.O. Sysdig is doing great securing DevOps, Harness I.O. modern software delivery platform, white source. They're preventing and remediating the rest of the internet for them, for the companies. That's a really interesting, and Lumigo is effortless. It is Lambda monitoring. Functions, server lists is super hot. And of course, Hacker One is always great and doing a lot of great missions and bounties. You see those success continue. Ascend I.O., they're in Palo Alto. Chasing the game on data engineering and data pipelining. Okay, data-driven, another new platform, horizontally scalable, and of course ThoughtSpot, AI-driven, kind of a search paradigm. And of course, Rockset, Jerry Chen's companies here and Prasera, all doing great in the analytics. And then the cloud management. Cost side, AT operations, day two offers ops ramps and ops, Monty Cloud are all there and Opsani all going to present. So check them out. This is theCUBE's AWS startup showcase, episode three.