(light airy music) >> Hello, everyone, welcome to theCUBE's presentation of the AWS Startup Showcase, AI and machine learning. "Top Startups Building Generative AI on AWS." This is season three, episode one of the ongoing series covering the exciting startups from the AWS ecosystem, talking about AI machine learning. We have three great guests Bratin Saha, VP, Vice President of Machine Learning and AI Services at Amazon Web Services. Tom Mason, the CTO of Stability AI, and Aidan Gomez, CEO and co-founder of Cohere. Two practitioners doing startups and AWS. Gentlemen, thank you for opening up this session, this episode. Thanks for coming on. >> Thank you. >> Thank you. >> Thank you. >> So the topic is hype versus reality. So I think we're all on the reality is great, hype is great, but the reality's here. I want to get into it. Generative AI's got all the momentum, it's going mainstream, it's kind of come out of the behind the ropes, it's now mainstream. We saw the success of ChatGPT, opens up everyone's eyes, but there's so much more going on. Let's jump in and get your early perspectives on what should people be talking about right now? What are you guys working on? We'll start with AWS. What's the big focus right now for you guys as you come into this market that's highly active, highly hyped up, but people see value right out of the gate? >> You know, we have been working on generative AI for some time. In fact, last year we released Code Whisperer, which is about using generative AI for software development and a number of customers are using it and getting real value out of it. So generative AI is now something that's mainstream that can be used by enterprise users. And we have also been partnering with a number of other companies. So, you know, stability.ai, we've been partnering with them a lot. We want to be partnering with other companies as well. In seeing how we do three things, you know, first is providing the most efficient infrastructure for generative AI. And that is where, you know, things like Trainium, things like Inferentia, things like SageMaker come in. And then next is the set of models and then the third is the kind of applications like Code Whisperer and so on. So, you know, it's early days yet, but clearly there's a lot of amazing capabilities that will come out and something that, you know, our customers are starting to pay a lot of attention to. >> Tom, talk about your company and what your focus is and why the Amazon Web Services relationship's important for you? >> So yeah, we're primarily committed to making incredible open source foundation models and obviously stable effusions been our kind of first big model there, which we trained all on AWS. We've been working with them over the last year and a half to develop, obviously a big cluster, and bring all that compute to training these models at scale, which has been a really successful partnership. And we're excited to take it further this year as we develop commercial strategy of the business and build out, you know, the ability for enterprise customers to come and get all the value from these models that we think they can get. So we're really excited about the future. We got hugely exciting pipeline for this year with new modalities and video models and wonderful things and trying to solve images for once and for all and get the kind of general value and value proposition correct for customers. So it's a really exciting time and very honored to be part of it. >> It's great to see some of your customers doing so well out there. Congratulations to your team. Appreciate that. Aidan, let's get into what you guys do. What does Cohere do? What are you excited about right now? >> Yeah, so Cohere builds large language models, which are the backbone of applications like ChatGPT and GPT-3. We're extremely focused on solving the issues with adoption for enterprise. So it's great that you can make a super flashy demo for consumers, but it takes a lot to actually get it into billion user products and large global enterprises. So about six months ago, we released our command models, which are some of the best that exist for large language models. And in December, we released our multilingual text understanding models and that's on over a hundred different languages and it's trained on, you know, authentic data directly from native speakers. And so we're super excited to continue pushing this into enterprise and solving those barriers for adoption, making this transformation a reality. >> Just real quick, while I got you there on the new products coming out. Where are we in the progress? People see some of the new stuff out there right now. There's so much more headroom. Can you just scope out in your mind what that looks like? Like from a headroom standpoint? Okay, we see ChatGPT. "Oh yeah, it writes my papers for me, does some homework for me." I mean okay, yawn, maybe people say that, (Aidan chuckles) people excited or people are blown away. I mean, it's helped theCUBE out, it helps me, you know, feed up a little bit from my write-ups but it's not always perfect. >> Yeah, at the moment it's like a writing assistant, right? And it's still super early in the technologies trajectory. I think it's fascinating and it's interesting but its impact is still really limited. I think in the next year, like within the next eight months, we're going to see some major changes. You've already seen the very first hints of that with stuff like Bing Chat, where you augment these dialogue models with an external knowledge base. So now the models can be kept up to date to the millisecond, right? Because they can search the web and they can see events that happened a millisecond ago. But that's still limited in the sense that when you ask the question, what can these models actually do? Well they can just write text back at you. That's the extent of what they can do. And so the real project, the real effort, that I think we're all working towards is actually taking action. So what happens when you give these models the ability to use tools, to use APIs? What can they do when they can actually affect change out in the real world, beyond just streaming text back at the user? I think that's the really exciting piece. >> Okay, so I wanted to tee that up early in the segment 'cause I want to get into the customer applications. We're seeing early adopters come in, using the technology because they have a lot of data, they have a lot of large language model opportunities and then there's a big fast follower wave coming behind it. I call that the people who are going to jump in the pool early and get into it. They might not be advanced. Can you guys share what customer applications are being used with large language and vision models today and how they're using it to transform on the early adopter side, and how is that a tell sign of what's to come? >> You know, one of the things we have been seeing both with the text models that Aidan talked about as well as the vision models that stability.ai does, Tom, is customers are really using it to change the way you interact with information. You know, one example of a customer that we have, is someone who's kind of using that to query customer conversations and ask questions like, you know, "What was the customer issue? How did we solve it?" And trying to get those kinds of insights that was previously much harder to do. And then of course software is a big area. You know, generating software, making that, you know, just deploying it in production. Those have been really big areas that we have seen customers start to do. You know, looking at documentation, like instead of you know, searching for stuff and so on, you know, you just have an interactive way, in which you can just look at the documentation for a product. You know, all of this goes to where we need to take the technology. One of which is, you know, the models have to be there but they have to work reliably in a production setting at scale, with privacy, with security, and you know, making sure all of this is happening, is going to be really key. That is what, you know, we at AWS are looking to do, which is work with partners like stability and others and in the open source and really take all of these and make them available at scale to customers, where they work reliably. >> Tom, Aidan, what's your thoughts on this? Where are customers landing on this first use cases or set of low-hanging fruit use cases or applications? >> Yeah, so I think like the first group of adopters that really found product market fit were the copywriting companies. So one great example of that is HyperWrite. Another one is Jasper. And so for Cohere, that's the tip of the iceberg, like there's a very long tail of usage from a bunch of different applications. HyperWrite is one of our customers, they help beat writer's block by drafting blog posts, emails, and marketing copy. We also have a global audio streaming platform, which is using us the power of search engine that can comb through podcast transcripts, in a bunch of different languages. Then a global apparel brand, which is using us to transform how they interact with their customers through a virtual assistant, two dozen global news outlets who are using us for news summarization. So really like, these large language models, they can be deployed all over the place into every single industry sector, language is everywhere. It's hard to think of any company on Earth that doesn't use language. So it's, very, very- >> We're doing it right now. We got the language coming in. >> Exactly. >> We'll transcribe this puppy. All right. Tom, on your side, what do you see the- >> Yeah, we're seeing some amazing applications of it and you know, I guess that's partly been, because of the growth in the open source community and some of these applications have come from there that are then triggering this secondary wave of innovation, which is coming a lot from, you know, controllability and explainability of the model. But we've got companies like, you know, Jasper, which Aidan mentioned, who are using stable diffusion for image generation in block creation, content creation. We've got Lensa, you know, which exploded, and is built on top of stable diffusion for fine tuning so people can bring themselves and their pets and you know, everything into the models. So we've now got fine tuned stable diffusion at scale, which is democratized, you know, that process, which is really fun to see your Lensa, you know, exploded. You know, I think it was the largest growing app in the App Store at one point. And lots of other examples like NightCafe and Lexica and Playground. So seeing lots of cool applications. >> So much applications, we'll probably be a customer for all you guys. We'll definitely talk after. But the challenges are there for people adopting, they want to get into what you guys see as the challenges that turn into opportunities. How do you see the customers adopting generative AI applications? For example, we have massive amounts of transcripts, timed up to all the videos. I don't even know what to do. Do I just, do I code my API there. So, everyone has this problem, every vertical has these use cases. What are the challenges for people getting into this and adopting these applications? Is it figuring out what to do first? Or is it a technical setup? Do they stand up stuff, they just go to Amazon? What do you guys see as the challenges? >> I think, you know, the first thing is coming up with where you think you're going to reimagine your customer experience by using generative AI. You know, we talked about Ada, and Tom talked about a number of these ones and you know, you pick up one or two of these, to get that robust. And then once you have them, you know, we have models and we'll have more models on AWS, these large language models that Aidan was talking about. Then you go in and start using these models and testing them out and seeing whether they fit in use case or not. In many situations, like you said, John, our customers want to say, "You know, I know you've trained these models on a lot of publicly available data, but I want to be able to customize it for my use cases. Because, you know, there's some knowledge that I have created and I want to be able to use that." And then in many cases, and I think Aidan mentioned this. You know, you need these models to be up to date. Like you can't have it staying. And in those cases, you augmented with a knowledge base, you know you have to make sure that these models are not hallucinating. And so you need to be able to do the right kind of responsible AI checks. So, you know, you start with a particular use case, and there are a lot of them. Then, you know, you can come to AWS, and then look at one of the many models we have and you know, we are going to have more models for other modalities as well. And then, you know, play around with the models. We have a playground kind of thing where you can test these models on some data and then you can probably, you will probably want to bring your own data, customize it to your own needs, do some of the testing to make sure that the model is giving the right output and then just deploy it. And you know, we have a lot of tools. >> Yeah. >> To make this easy for our customers. >> How should people think about large language models? Because do they think about it as something that they tap into with their IP or their data? Or is it a large language model that they apply into their system? Is the interface that way? What's the interaction look like? >> In many situations, you can use these models out of the box. But in typical, in most of the other situations, you will want to customize it with your own data or with your own expectations. So the typical use case would be, you know, these are models are exposed through APIs. So the typical use case would be, you know you're using these APIs a little bit for testing and getting familiar and then there will be an API that will allow you to train this model further on your data. So you use that AI, you know, make sure you augmented the knowledge base. So then you use those APIs to customize the model and then just deploy it in an application. You know, like Tom was mentioning, a number of companies that are using these models. So once you have it, then you know, you again, use an endpoint API and use it in an application. >> All right, I love the example. I want to ask Tom and Aidan, because like most my experience with Amazon Web Service in 2007, I would stand up in EC2, put my code on there, play around, if it didn't work out, I'd shut it down. Is that a similar dynamic we're going to see with the machine learning where developers just kind of log in and stand up infrastructure and play around and then have a cloud-like experience? >> So I can go first. So I mean, we obviously, with AWS working really closely with the SageMaker team, do fantastic platform there for ML training and inference. And you know, going back to your point earlier, you know, where the data is, is hugely important for companies. Many companies bringing their models to their data in AWS on-premise for them is hugely important. Having the models to be, you know, open sources, makes them explainable and transparent to the adopters of those models. So, you know, we are really excited to work with the SageMaker team over the coming year to bring companies to that platform and make the most of our models. >> Aidan, what's your take on developers? Do they just need to have a team in place, if we want to interface with you guys? Let's say, can they start learning? What do they got to do to set up? >> Yeah, so I think for Cohere, our product makes it much, much easier to people, for people to get started and start building, it solves a lot of the productionization problems. But of course with SageMaker, like Tom was saying, I think that lowers a barrier even further because it solves problems like data privacy. So I want to underline what Bratin was saying earlier around when you're fine tuning or when you're using these models, you don't want your data being incorporated into someone else's model. You don't want it being used for training elsewhere. And so the ability to solve for enterprises, that data privacy and that security guarantee has been hugely important for Cohere, and that's very easy to do through SageMaker. >> Yeah. >> But the barriers for using this technology are coming down super quickly. And so for developers, it's just becoming completely intuitive. I love this, there's this quote from Andrej Karpathy. He was saying like, "It really wasn't on my 2022 list of things to happen that English would become, you know, the most popular programming language." And so the barrier is coming down- >> Yeah. >> Super quickly and it's exciting to see. >> It's going to be awesome for all the companies here, and then we'll do more, we're probably going to see explosion of startups, already seeing that, the maps, ecosystem maps, the landscape maps are happening. So this is happening and I'm convinced it's not yesterday's chat bot, it's not yesterday's AI Ops. It's a whole another ballgame. So I have to ask you guys for the final question before we kick off the company's showcasing here. How do you guys gauge success of generative AI applications? Is there a lens to look through and say, okay, how do I see success? It could be just getting a win or is it a bigger picture? Bratin we'll start with you. How do you gauge success for generative AI? >> You know, ultimately it's about bringing business value to our customers. And making sure that those customers are able to reimagine their experiences by using generative AI. Now the way to get their ease, of course to deploy those models in a safe, effective manner, and ensuring that all of the robustness and the security guarantees and the privacy guarantees are all there. And we want to make sure that this transitions from something that's great demos to actual at scale products, which means making them work reliably all of the time not just some of the time. >> Tom, what's your gauge for success? >> Look, I think this, we're seeing a completely new form of ways to interact with data, to make data intelligent, and directly to bring in new revenue streams into business. So if businesses can use our models to leverage that and generate completely new revenue streams and ultimately bring incredible new value to their customers, then that's fantastic. And we hope we can power that revolution. >> Aidan, what's your take? >> Yeah, reiterating Bratin and Tom's point, I think that value in the enterprise and value in market is like a huge, you know, it's the goal that we're striving towards. I also think that, you know, the value to consumers and actual users and the transformation of the surface area of technology to create experiences like ChatGPT that are magical and it's the first time in human history we've been able to talk to something compelling that's not a human. I think that in itself is just extraordinary and so exciting to see. >> It really brings up a whole another category of markets. B2B, B2C, it's B2D, business to developer. Because I think this is kind of the big trend the consumers have to win. The developers coding the apps, it's a whole another sea change. Reminds me everyone use the "Moneyball" movie as example during the big data wave. Then you know, the value of data. There's a scene in "Moneyball" at the end, where Billy Beane's getting the offer from the Red Sox, then the owner says to the Red Sox, "If every team's not rebuilding their teams based upon your model, there'll be dinosaurs." I think that's the same with AI here. Every company will have to need to think about their business model and how they operate with AI. So it'll be a great run. >> Completely Agree >> It'll be a great run. >> Yeah. >> Aidan, Tom, thank you so much for sharing about your experiences at your companies and congratulations on your success and it's just the beginning. And Bratin, thanks for coming on representing AWS. And thank you, appreciate for what you do. Thank you. >> Thank you, John. Thank you, Aidan. >> Thank you John. >> Thanks so much. >> Okay, let's kick off season three, episode one. I'm John Furrier, your host. Thanks for watching. (light airy music)

(bright music) >> Hello, everyone. Welcome to theCUBE special presentation of International Women's Day. I'm John Furrier, host of theCUBE. This is a global special open program we're doing every year. We're going to continue it every quarter. We're going to do more and more content, getting the voices out there and celebrating the diversity. And I'm excited to have an amazing guest here, LaDavia Drane, who's the head of Global Inclusion Diversity & Equity at AWS. LaDavia, we tried to get you in on AWS re:Invent, and you were super busy. So much going on. The industry has seen the light. They're seeing everything going on, and the numbers are up, but still not there, and getting better. This is your passion, our passion, a shared passion. Tell us about your situation, your career, how you got into it. What's your story? >> Yeah. Well, John, first of all, thank you so much for having me. I'm glad that we finally got this opportunity to speak. How did I get into this work? Wow, you know, I'm doing the work that I love to do, number one. It's always been my passion to be a voice for the voiceless, to create a seat at the table for folks that may not be welcome to certain tables. And so, it's been something that's been kind of the theme of my entire professional career. I started off as a lawyer, went to Capitol Hill, was able to do some work with members of Congress, both women members of Congress, but also, minority members of Congress in the US Congress. And then, that just morphed into what I think has become a career for me in inclusion, diversity, and equity. I decided to join Amazon because I could tell that it's a company that was ready to take it to the next level in this space. And sure enough, that's been my experience here. So now, I'm in it, I'm in it with two feet, doing great work. And yeah, yeah, it's almost a full circle moment for me. >> It's really an interesting background. You have a background in public policy. You mentioned Capitol Hill. That's awesome. DC kind of moves slow, but it's a complicated machinery there. Obviously, as you know, navigating that, Amazon grew significantly. We've been at every re:Invent with theCUBE since 2013, like just one year. I watched Amazon grow, and they've become very fast and also complicated, like, I won't say like Capitol, 'cause that's very slow, but Amazon's complicated. AWS is in the realm of powering a generation of public policy. We had the JEDI contract controversy, all kinds of new emerging challenges. This pivot to tech was great timing because one, (laughs) Amazon needed it because they were growing so fast in a male dominated world, but also, their business is having real impact on the public. >> That's right, that's right. And when you say the public, I'll just call it out. I think that there's a full spectrum of diversity and we work backwards from our customers, and our customers are diverse. And so, I really do believe, I agree that I came to the right place at the right time. And yeah, we move fast and we're also moving fast in this space of making sure that both internally and externally, we're doing the things that we need to do in order to reach a diverse population. >> You know, I've noticed how Amazon's changed from the culture, male dominated culture. Let's face it, it was. And now, I've seen over the past five years, specifically go back five, is kind of in my mental model, just the growth of female leaders, it's been impressive. And there was some controversy. They were criticized publicly for this. And we said a few things as well in those, like around 2014. How is Amazon ensuring and continuing to get the female employees feel represented and empowered? What's going on there? What programs do you have? Because it's not just doing it, it's continuing it, right? And 'cause there is a lot more to do. I mean, the half (laughs) the products are digital now for everybody. It's not just one population. (laughs) Everyone uses digital products. What is Amazon doing now to keep it going? >> Well, I'll tell you, John, it's important for me to note that while we've made great progress, there's still more that can be done. I am very happy to be able to report that we have big women leaders. We have leaders running huge parts of our business, which includes storage, customer experience, industries and business development. And yes, we have all types of programs. And I should say that, instead of calling it programs, I'm going to call it strategic initiatives, right? We are very thoughtful about how we engage our women. And not only how we hire, attract women, but how we retain our women. We do that through engagement, groups like our affinity groups. So Women at Amazon is an affinity group. Women in finance, women in engineering. Just recently, I helped our Black employee network women's group launch, BEN Women. And so you have these communities of women who come together, support and mentor one another. We have what we call Amazon Circles. And so these are safe spaces where women can come together and can have conversations, where we are able to connect mentors and sponsors. And we're seeing that it's making all the difference in the world for our women. And we see that through what we call Connections. We have an inclusion sentiment tracker. So we're able to ask questions every single day and we get a response from our employees and we can see how are our women feeling, how are they feeling included at work? Are they feeling as though they can be who they are authentically at Amazon? And so, again, there's more work that needs to be done. But I will say that as I look at the data, as I'm talking to engaging women, I really do believe that we're on the right path. >> LaDavia, talk about the urgent needs of the women that you're hearing from the Circles. That's a great program. The affinity circles, the groups are great. Now, you have the groups, what are you hearing? What are the needs of the women? >> So, John, I'll just go a little bit into what's becoming a conversation around equity. So, initially I think we talked a lot about equality, right? We wanted everyone to have fair access to the same things. But now, women are looking for equity. We're talking about not just leveling the playing field, which is equality, but don't give me the same as you give everyone else. Instead, recognize that I may have different circumstances, I may have different needs. And give me what I need, right? Give me what I need, not just the same as everyone else. And so, I love seeing women evolve in this way, and being very specific about what they need more than, or what's different than what a man may have in the same situation because their circumstances are not always the same and we should treat them as such. >> Yeah, I think that's a great equity point. I interviewed a woman here, ex-Amazonian, she's now a GSI, Global System Integrator. She's a single mom. And she said remote work brought her equity because people on her team realized that she was a single mom. And it wasn't the, how do you balance life, it was her reality. And what happened was, she had more empathy with the team because of the new work environment. So, I think this is an important point to call out, that equity, because that really makes things smoother in terms of the interactions, not the assumptions, you have to be, you know, always the same as a man. So, how does that go? What's the current... How would you characterize the progress in that area right now? >> I believe that employers are just getting better at this. It's just like you said, with the hybrid being the norm now, you have an employer who is looking at people differently based on what they need. And it's not a problem, it's not an issue that a single mother says, "Well, I need to be able to leave by 5:00 PM." I think that employers now, and Amazon is right there along with other employers, are starting just to evolve that muscle of meeting the needs. People don't have to feel different. You don't have to feel as though there's some kind of of special circumstance for me. Instead, it's something that we, as employers, we're asking for. And we want to meet those needs that are different in some situations. >> I know you guys do a lot of support of women outside of AWS, and I had a story I recorded for the program. This woman, she talked about how she was a nerd from day one. She's a tomboy. They called her a tomboy, but she always loved robotics. And she ended up getting dual engineering degrees. And she talked about how she didn't run away and there was many signals to her not to go. And she powered through, at that time, and during her generation, that was tough. And she was successful. How are you guys taking the education to STEM, to women, at young ages? Because we don't want to turn people away from tech if they have the natural affinity towards it. And not everyone is going to be, as, you know, (laughs) strong, if you will. And she was a bulldog, she was great. She's just like, "I'm going for it. I love it so much." But not everyone's like that. So, this is an educational thing. How do you expose technology, STEM for instance, and making it more accessible, no stigma, all that stuff? I mean, I think we've come a long way, but still. >> What I love about women is we don't just focus on ourselves. We do a very good job of thinking about the generation that's coming after us. And so, I think you will see that very clearly with our women Amazonians. I'll talk about three different examples of ways that Amazonian women in particular, and there are men that are helping out, but I'll talk about the women in particular that are leading in this area. On my team, in the Inclusion, Diversity & Equity team, we have a program that we run in Ghana where we meet basic STEM needs for a afterschool program. So we've taken this small program, and we've turned their summer camp into this immersion, where girls and boys, we do focus on the girls, can come and be completely immersed in STEM. And when we provide the technology that they need, so that they'll be able to have access to this whole new world of STEM. Another program which is run out of our AWS In Communities team, called AWS Girls' Tech Day. All across the world where we have data centers, we're running these Girls' Tech Day. They're basically designed to educate, empower and inspire girls to pursue a career in tech. Really, really exciting. I was at the Girls' Tech Day here recently in Columbus, Ohio, and I got to tell you, it was the highlight of my year. And then I'll talk a little bit about one more, it's called AWS GetIT, and it's been around for a while. So this is a program, again, it's a global program, it's actually across 13 countries. And it allows girls to explore cloud technology, in particular, and to use it to solve real world problems. Those are just three examples. There are many more. There are actually women Amazonians that create these opportunities off the side of their desk in they're local communities. We, in Inclusion, Diversity & Equity, we fund programs so that women can do this work, this STEM work in their own local communities. But those are just three examples of some of the things that our Amazonians are doing to bring girls along, to make sure that the next generation is set up and that the next generation knows that STEM is accessible for girls. >> I'm a huge believer. I think that's amazing. That's great inspiration. We need more of that. It's awesome. And why wouldn't we spread it around? I want to get to the equity piece, that's the theme for this year's IWD. But before that, getting that segment, I want to ask you about your title, and the choice of words and the sequence. Okay, Global Inclusion, Diversity, Equity. Not diversity only. Inclusion is first. We've had this debate on theCUBE many years now, a few years back, it started with, "Inclusion is before diversity," "No, diversity before inclusion, equity." And so there's always been a debate (laughs) around the choice of words and their order. What's your opinion? What's your reaction to that? Is it by design? And does inclusion come before diversity, or am I just reading it to it? >> Inclusion doesn't necessarily come before diversity. (John laughs) It doesn't necessarily come before equity. Equity isn't last, but we do lead with inclusion in AWS. And that is very important to us, right? And thank you for giving me the opportunity to talk a little bit about it. We lead with inclusion because we want to make sure that every single one of our builders know that they have a place in this work. And so it's important that we don't only focus on hiring, right? Diversity, even though there are many, many different levels and spectrums to diversity. Inclusion, if you start there, I believe that it's what it takes to make sure that you have a workplace where everyone knows you're included here, you belong here, we want you to stay here. And so, it helps as we go after diversity. And we want all types of people to be a part of our workforce, but we want you to stay. And inclusion is the thing. It's the thing that I believe makes sure that people stay because they feel included. So we lead with inclusion. Doesn't mean that we put diversity or equity second or third, but we are proud to lead with inclusion. >> Great description. That was fabulous. Totally agree. Double click, thumbs up. Now let's get into the theme. Embracing equity, 'cause this is a term, it's in quotes. What does that mean to you? You mentioned it earlier, I love it. What does embrace equity mean? >> Yeah. You know, I do believe that when people think about equity, especially non-women think about equity, it's kind of scary. It's, "Am I going to give away what I have right now to make space for someone else?" But that's not what equity means. And so I think that it's first important that we just educate ourselves about what equity really is. It doesn't mean that someone's going to take your spot, right? It doesn't mean that the pie, let's use that analogy, gets smaller. The pie gets bigger, right? >> John: Mm-hmm. >> And everyone is able to have their piece of the pie. And so, I do believe that I love that IWD, International Women's Day is leading with embracing equity because we're going to the heart of the matter when we go to equity, we're going to the place where most people feel most challenged, and challenging people to think about equity and what it means and how they can contribute to equity and thus, embrace equity. >> Yeah, I love it. And the advice that you have for tech professionals out there on this, how do you advise other groups? 'Cause you guys are doing a lot of great work. Other organizations are catching up. What would be your advice to folks who are working on this equity challenge to reach gender equity and other equitable strategic initiatives? And everyone's working on this. Sustainability and equity are two big projects we're seeing in every single company right now. >> Yeah, yeah. I will say that I believe that AWS has proven that equity and going after equity does work. Embracing equity does work. One example I would point to is our AWS Impact Accelerator program. I mean, we provide 30 million for early stage startups led by women, Black founders, Latino founders, LGBTQ+ founders, to help them scale their business. That's equity. That's giving them what they need. >> John: Yeah. >> What they need is they need access to capital. And so, what I'd say to companies who are looking at going into the space of equity, I would say embrace it. Embrace it. Look at examples of what companies like AWS is doing around it and embrace it because I do believe that the tech industry will be better when we're comfortable with embracing equity and creating strategic initiatives so that we could expand equity and make it something that's just, it's just normal. It's the normal course of business. It's what we do. It's what we expect of ourselves and our employees. >> LaDavia, you're amazing. Thank you for spending the time. My final couple questions really more around you. Capitol Hill, DC, Amazon Global Head of Inclusion, Diversity & Equity, as you look at making change, being a change agent, being a leader, is really kind of similar, right? You've got DC, it's hard to make change there, but if you do it, it works, right? (laughs) If you don't, you're on the side of the road. So, as you're in your job now, what are you most excited about? What's on your agenda? What's your focus? >> Yeah, so I'm most excited about the potential of what we can get done, not just for builders that are currently in our seats, but for builders in the future. I tend to focus on that little girl. I don't know her, I don't know where she lives. I don't know how old she is now, but she's somewhere in the world, and I want her to grow up and for there to be no question that she has access to AWS, that she can be an employee at AWS. And so, that's where I tend to center, I center on the future. I try to build now, for what's to come, to make sure that this place is accessible for that little girl. >> You know, I've always been saying for a long time, the software is eating the world, now you got digital transformation, business transformation. And that's not a male only, or certain category, it's everybody. And so, software that's being built, and the systems that are being built, have to have first principles. Andy Jassy is very strong on this. He's been publicly saying, when trying to get pinned down about certain books in the bookstore that might offend another group. And he's like, "Look, we have first principles. First principles is a big part of leading." What's your reaction to that? How would you talk to another professional and say, "Hey," you know this, "How do I make the right call? Am I doing the wrong thing here? And I might say the wrong thing here." And is it first principles based? What's the guardrails? How do you keep that in check? How would you advise someone as they go forward and lean in to drive some of the change that we're talking about today? >> Yeah, I think as leaders, we have to trust ourselves. And Andy actually, is a great example. When I came in as head of ID&E for AWS, he was our CEO here at AWS. And I saw how he authentically spoke from his heart about these issues. And it just aligned with who he is personally, his own personal principles. And I do believe that leaders should be free to do just that. Not to be scripted, but to lead with their principles. And so, I think Andy's actually a great example. I believe that I am the professional in this space at this company that I am today because of the example that Andy set. >> Yeah, you guys do a great job, LaDavia. What's next for you? >> What's next. >> World tour, you traveling around? What's on your plate these days? Share a little bit about what you're currently working on. >> Yeah, so you know, at Amazon, we're always diving deep. We're always diving deep, we're looking for root cause, working very hard to look around corners, and trying to build now for what's to come in the future. And so I'll continue to do that. Of course, we're always planning and working towards re:Invent, so hopefully, John, I'll see you at re:Invent this December. But we have some great things happening throughout the year, and we'll continue to... I think it's really important, as opposed to looking to do new things, to just continue to flex the same muscles and to show that we can be very, very focused and intentional about doing the same things over and over each year to just become better and better at this work in this space, and to show our employees that we're committed for the long haul. So of course, there'll be new things on the horizon, but what I can say, especially to Amazonians, is we're going to continue to stay focused, and continue to get at this issue, and doing this issue of inclusion, diversity and equity, and continue to do the things that work and make sure that our culture evolves at the same time. >> LaDavia, thank you so much. I'll give you the final word. Just share some of the big projects you guys are working on so people can know about them, your strategic initiatives. Take a minute to plug some of the major projects and things that are going on that people either know about or should know about, or need to know about. Take a minute to share some of the big things you guys got going on, or most of the things. >> So, one big thing that I would like to focus on, focus my time on, is what we call our Innovation Fund. This is actually how we scale our work and we meet the community's needs by providing micro grants to our employees so our employees can go out into the world and sponsor all types of different activities, create activities in their local communities, or throughout the regions. And so, that's probably one thing that I would like to focus on just because number one, it's our employees, it's how we scale this work, and it's how we meet our community's needs in a very global way. And so, thank you John, for the opportunity to talk a bit about what we're up to here at Amazon Web Services. But it's just important to me, that I end with our employees because for me, that's what's most important. And they're doing some awesome work through our Innovation Fund. >> Inclusion makes the workplace great. Empowerment, with that kind of program, is amazing. LaDavia Drane, thank you so much. Head of Global Inclusion and Diversity & Equity at AWS. This is International Women's Day. I'm John Furrier with theCUBE. Thanks for watching and stay with us for more great interviews and people and what they're working on. Thanks for watching. (bright music)

(light music) >> Narrator: theCUBE's live coverage is made possible by funding from Dell Technologies. Creating technologies that drive human progress. (upbeat music) >> Welcome back to Spain everyone. Lisa Martin here with theCUBE Dave Vellante, my co-host for the next four days. We're live in Barcelona, covering MWC23. This is only day one, but I'll tell you the theme of this conference this year is velocity. And I don't know about you Dave, but this day is flying by already. This is ecosystem day. We're going to have a great discussion on the ecosystem next. >> Well we're seeing the disaggregation of the hardened telco stack, and that necessitates an ecosystem open- we're going to talk about Open RAN, we've been talking about even leading up to the show. It's a critical technology enabler and it's compulsory to have an ecosystem to support that. >> Absolutely compulsory. We've got two guests here joining us, Gautam Bhagra, Vice President partnerships at Dell, and Scott Walker, Vice President of global Telco ecosystem at Wind River. Guys, welcome to the program. >> Nice to be here. >> Thanks For having us. >> Thanks for having us. >> So you've got some news, this is day one of the conference, there's some news, Gautam, and let's start with you, unpack it. >> Yeah, well there's a lot of news, as you know, on Dell World. One of the things we are very excited to announce today is the launch of the Open Telecom Ecosystems Community. I think Dave, as you mentioned, getting into an Open RAN world is a challenge. And we know some of the challenges that our customers face. To help solve for those challenges, Dell wants to work with like-minded partners and customers to build innovative solutions, and join go-to-market. So we are launching that today. Wind River is one of our flagship partners for that, and I'm excited to be here to talk about that as well. >> Can you guys talk a little bit about the partnership, maybe a little bit about Wind River so the audience gets that context? >> Sure, absolutely, and the theme of the show, Velocity, is what this partnership is all about. We create velocity for operators if they want to adopt Open RAN, right? We simplify it. Wind River as a company has been around for 40 years. We were part of Intel at one point, and now we're independent, owned by a company called Aptiv. And with that we get another round of investment to help continue our acceleration into this market. So, the Dell partnership is about, like I said, velocity, accelerating the adoption. When we talk to operators, they have told us there are many roadblocks that they face, right? Like systems integration, operating at scale. 'Cause when you buy a traditional radio access network solution from a single supplier, it's very easy. It's works, it's been tested. When you break these components apart and disaggregate 'em, as we talked about David, it creates integration points and support issues, right? And what Dell and Wind River have done together is created a cloud infrastructure solution that could host a variety of RAN workloads, and essentially create a two layer cake. What we're, overall, what we're trying to do is create a traditional RAN experience, with the innovation agility and flexibility of Open RAN. And that's really what this partnership does. >> So these work, this workload innovation is interesting to me because you've got now developers, you know, the, you know, what's the telco developer look like, you know, is to be defined, right? I mean it's like this white sheet of paper that can create all this innovation. And to do that, you've got to have, as I said earlier, an ecosystem. But you've got now, I'm interested in your Open RAN agenda and how you see that sort of maturity model taking place. 'Cause today, you got disruptors that are going to lean right in say "Hey, yeah, that's great." The traditional carriers, they have to have a, you know, they have to migrate, they have to have a hybrid world. We know that takes time. So what's that look like in the marketplace today? >> Yeah, so I mean, I can start, right? So from a Dell's perspective, what we see in the market is yes, there is a drive towards, everyone understands the benefits of being open, right? There's the agility piece, the innovation piece. That's a no-brainer. The question is how do we get there? And I think that's where partnerships become critical to get there, right? So we've been working with partners like Wind River to build solutions that make it easier for customers to start adopting some of the foundational elements of an open network. The, one of the purposes in the agenda of building this community is to bring like-minded developers, like you said like we want those guys to come and work with the customers to create new solutions, and come up with something creative, which no one's even thought about, that accelerates your option even quicker, right? So that's exactly what we want to do as well. And that's one of the reasons why we launched the community. >> Yeah, and what we find with a lot of carriers, they are used to buying, like I said, traditional RAN solutions which are provided from a single provider like Erickson or Nokia and others, right? And we break this apart, and you cloudify that network infrastructure, there's usually a skills gap we see at the operator level, right? And so from a developer standpoint, they struggle with having the expertise in order to execute on that. Wind River helps them, working with companies like Dell, simplify that bottom portion of the stack, the infrastructure stack. So, and we lifecycle manage it, we test- we're continually testing it, and integrating it, so that the operator doesn't have to do that. In addition to that, wind River also has a history and legacy of working with different RAN vendors, both disruptors like Mavenir and Parallel Wireless, as well as traditional RAN providers like Samsung, Erickson, and others soon to be announced. So what we're doing on the northbound side is making it easy by integrating that, and on the southbound side with Dell, so that again, instead of four or five solutions that you need to put together, it's simply two. >> And you think about today how we- how you consume telco services are like there's these fixed blocks of services that you can buy, that has to change. It's more like the, the app stores. It's got to be an open marketplace, and that's where the innovation's going to come in, you know, from the developers, you know, top down maybe. I don't know, how do you see that maturity model evolving? People want to know how long it's going to take. So many questions, when will Open RAN be as reliable. Does it even have to be? You know, so many interesting dynamics going on. >> Yeah, and I think that's something we at Dell are also trying to find out, right? So we have been doing a lot of good work here to help our customers move in that direction. The work with Dish is an example of that. But I think we do understand the challenges as well in terms of getting, adopting the technologies, and adopting the innovation that's being driven by Open. So one of the agendas that we have as a company this year is to work with the community to drive this a lot further, right? We want to have customers adopt the technology more broadly with the tier one, tier two telcos globally. And our sales organizations are going to be working together with Wind Rivers to figure out who's the right set of customers to have these conversations with, so we can drop, drive, start driving this agenda a lot quicker than what we've seen historically. >> And where are you having those customer conversations? Is that at the operator level, is it higher, is it both? >> Well, all operators are deploying 5G in preparation for 6G, right? And we're all looking for those killer use cases which will drive top line revenue and not just make it a TCO discussion. And that starts at a very basic level today by doing things like integrating with Juniper, for their cloud router. So instead of at the far edge cell site, having a separate device that's doing the routing function, right? We take that and we cloudify that application, run it on the same server that's hosting the RAN applications, so you eliminate a device and reduce TCO. Now with Aptiv, which is primarily known as an automotive company, we're having lots of conversations, including with Dell and Intel and others about vehicle to vehicle communication, vehicle to anything communication. And although that's a little bit futuristic, there are shorter term use cases that, like, vehicle to vehicle accident avoidance, which are going to be much nearer term than autonomous driving, for example, which will help drive traffic and new revenue streams for operators. >> So, oh, that's, wow. So many other things (Scott laughs) that's just opened up there too. But I want to come back to, sort of, the Open RAN adoption. And I think you're right, there's a lot of questions that that still have to be determined. But my question is this, based on your knowledge so far does it have to be as hardened and reliable, obviously has to be low latency as existing networks, or can flexibility, like the cloud when it first came out, wasn't better than enterprise IT, it was just more flexible and faster, and you could rent it. And, is there a similar dynamic here where it doesn't have to replicate the hardened stack, it can bring in new benefits that drive adoption, what are your thoughts on that? >> Well there's a couple of things on that, because Wind River, as you know, where our legacy and history is in embedded devices like F-15 fighter jets, right? Or the Mars Rover or the James Web telescope, all run Wind River software. So, we know about can't fail ultra reliable systems, and operators are not letting us off the hook whatsoever. It has to be as hardened and locked down, as secure as a traditional RAN environment. Otherwise they will (indistinct). >> That's table stakes. >> That's table stakes that gets us there. And when River, with our legacy and history, and having operator experience running live commercial networks with a disaggregated stack in the tens of thousands of nodes, understand what this is like because they're running live commercial traffic with live customers. So we can't fail, right? And with that, they want their cake and eat it too, right? Which is, I want ultra reliable, I want what I have today, but I want the agility and flexibility to onboard third party apps. Like for example, this JCNR, this Juniper Cloud-Native Router. You cannot do something as simple as that on a traditional RAN Appliance. In an open ecosystem you can take that workload and onboard it because it is an open ecosystem, and that's really one of the true benefits. >> So they want the mainframe, but they want (Scott laughs) the flexibility of the developer cloud, right? >> That's right. >> They want their, have their cake eat it too and not gain weight. (group laughs) >> Yeah I mean David, I come from the public cloud world. >> We all don't want to do that. >> I used to work with a public cloud company, and nine years ago, public cloud was in the same stage, where you would go to a bank, and they would be like, we don't trust the cloud. It's not secure, it's not safe. It was the digital natives that adopted it, and that that drove the industry forward, right? And that's where the enterprises that realized that they're losing business because of all these innovative new companies that came out. That's what I saw over the last nine years in the cloud space. I think in the telco space also, something similar might happen, right? So a lot of this, I mean a lot of the new age telcos are understanding the value, are looking to innovate are adopting the open technologies, but there's still some inertia and hesitancy, for the reasons as Scott mentioned, to go there so quickly. So we just have to work through and balance between both sides. >> Yeah, well with that said, if there's still some inertia, but there's a theme of velocity, how do you help organizations balance that so they trust evolving? >> Yeah, and I think this is where our solution, like infrastructure block, is a foundational pillar to make that happen, right? So if we can take away the concerns that the organizations have in terms of security, reliability from the fundamental elements that build their infrastructure, by working with partners like Wind River, but Dell takes the ownership end-to-end to make sure that service works and we have those telco grade SLAs, then the telcos can start focusing on what's next. The applications and the customer services on the top. >> Customer service customer experience. >> You know, that's an interesting point Gautam brings up, too, because support is an issue too. We all talk about when you break these things apart, it creates integration points that you need to manage, right? But there's also, so the support aspect of it. So imagine if you will, you had one vendor, you have an outage, you call that one vendor, one necktie to choke, right, for accountability for the network. Now you have four or five vendors that you have to work. You get a lot of finger pointing. So at least at the infrastructure layer, right? Dell takes first call support for both the hardware infrastructure and the Wind River cloud infrastructure for both. And we are training and spinning them up to support, but we're always behind them of course as well. >> Can you give us a favorite customer example of- that really articulates the value of the partnership and the technologies that it's delivering to customers? >> Well, Infra Block- >> (indistinct) >> Is quite new, and we do have our first customer which is LG U plus, which was announced yesterday. Out of Korea, small customer, but a very important one. Okay, and I think they saw the value of the integrated system. They don't have the (indistinct) expertise and they're leveraging Dell and Wind River in order to make that happen. But I always also say historically before this new offering was Vodafone, right? Vodafone is a leader in Europe in terms of Open RAN, been very- Yago and Paco have been very vocal about what they're doing in Open RAN, and Dell and Wind River have been there with them every step of the way. And that's what I would say, kind of, led up to where we are today. We learned from engagements like Vodafone and I think KDDI as well. And it got us where we are today and understanding what the operators need and what the impediments are. And this directly addresses that. >> Those are two very different examples. You were talking about TCO before. I mean, so the earlier example is, that's an example to me of a disruptor. They'll take some chances, you know, maybe not as focused on TCO, of course they're concerned about it. Vodafone I would think very concerned about TCO. But I'm inferring from your comments that you're trying to get the industry, you're trying to check the TCO box, get there. And then move on to higher levels of value monetization. The TCO is going to come down to how many humans it takes to run the network, is it not, is that- >> Well a lot of, okay- >> Or is it devices- >> So the big one now, particularly with Vodafone, is energy cost, right? >> Of course, greening the network. >> Two-thirds of the energy consumption in RAN is the the Radio Access Network. Okay, the OPEX, right? So any reductions, even if they're 5% or 10%, can save tens or hundreds of millions of dollars. So we do things creatively with Dell to understand if there's a lot of traffic at the cell site and if it's not, we will change the C state or P state of the server, which basically spins it down, so it's not consuming power. But that's just at the infrastructure layer. Where this gets really powerful is working with the RAN vendors like Samsung and Ericson and others, and taking data from the traffic information there, applying algorithms to that in AI to shut it down and spin it back up as needed. 'Cause the idea is you don't want that thing powered up if there's no traffic on it. >> Well there's a sustainability, ESG, benefit to that, right? >> Yes. >> And, and it's very compute intensive. >> A hundred percent. >> Which is great for Dell. But at the same time, if you're not able to manage that power consumption, the whole thing fails. I mean it's, because there's going to be so much data, and such a intense requirement. So this is a huge issue. Okay, so Scott, you're saying that in the TCO equation, a big chunk is energy consumption? >> On the OPEX piece. Now there's also the CapEx, right? And Open RAN solutions are now, what we've heard from our customers today, are they're roughly at parity. 'Cause you can do things like repurpose servers after the useful life for a lower demand application which helps the TCO, right? Then you have situations like Juniper, where you can take, now software that runs on the same device, eliminating at a whole other device at the cell site. So we're not just taking a server and software point of view, we're taking a whole cell site point of view as it relates to both CapEx and OPEX. >> And then once that infrastructure it really gets adopted, that's when the innovation occurs. The ecosystem comes in. Developers now start to think of new applications that we haven't thought of yet. >> Gautam: Exactly. >> And that's where, that's going to force the traditional carriers to respond. They're responding, but they're doing so very carefully right now, it's understandable why. >> Yeah, and I think you're already seeing some news in the, I mean Nokia's announcement yesterday with the rebranding, et cetera. That's all positive momentum in my opinion, right? >> What'd you think of the logo? >> I love the logo. >> I liked it too. (group laughs) >> It was beautiful. >> I thought it was good. You had the connectivity down below, You need pipes, right? >> Exactly. >> But you had this sort of cool letters, and then the the pink horizon or pinkish, it was like (Scott laughs) endless opportunity. It was good, I thought it was well thought out. >> Exactly. >> Well, you pick up on an interesting point there, and what we're seeing, like advanced carriers like Dish, who has one of the true Open RAN networks, publishing APIs for programmers to build in their 5G network as part of the application. But we're also seeing the network equipment providers also enable carriers do that, 'cause carriers historically have not been advanced in that way. So there is a real recognition that in order for these networks to monetize new use cases, they need to be programmable, and they need to publish standard APIs, so you can access the 5G network capabilities through software. >> Yeah, and the problem from the carriers, there's not enough APIs that the carriers have produced yet. So that's where the ecosystem comes in, is going to >> A hundred percent >> I think there's eight APIs that are published out of the traditional carriers, which is, I mean there's got to be 8,000 for a marketplace. So that's where the open ecosystem really has the advantage. >> That's right. >> That's right. >> That's right. >> Yeah. >> So it all makes sense on paper, now you just, you got a lot of work to do. >> We got to deliver. Yeah, we launched it today. We got to get some like-minded partners and customers to come together. You'll start seeing results coming out of this hopefully soon, and we'll talk more about it over time. >> Dave: Great Awesome, thanks for sharing with us. >> Excellent. Guys, thank you for sharing, stopping by, sharing what's going on with Dell and Wind River, and why the opportunity's in it for customers and the technological evolution. We appreciate it, you'll have to come back, give us an update. >> Our pleasure, thanks for having us. (Group talks over each other) >> All right, thanks guys >> Appreciate it. >> For our guests and for Dave Vellante, I'm Lisa Martin. You're watching theCUBE, Live from MWC23 in Barcelona. theCUBE is the leader in live tech coverage. (upbeat music)

(upbeat music) >> Hello everyone. Welcome to Silicon Angle news breaking story here. Amazon Web Services, expanding their relationship with Hugging Face, breaking news here on Silicon Angle. I'm John Furrier, Silicon Angle reporter, founder and also co-host of theCUBE. And I have with me Swami from Amazon Web Services, vice president of database analytics machine learning with AWS. Swami, great to have you on for this breaking news segment on AWS's big news. Thanks for coming on, taking the time. >> Hey John, pleasure to be here. >> We've had many conversations on theCUBE over the years. We've watched Amazon really move fast into the large data modeling. You SageMaker became a very smashing success. Obviously you've been on this for a while, now with Chat GPT, open AI, a lot of buzz going mainstream, takes it from behind the curtain, inside the ropes, if you will, in the industry to a mainstream. And so this is a big moment I think in the industry. I want to get your perspective because your news with Hugging Face, I think is a is another tell sign that we're about to tip over into a new accelerated growth around making AI now application aware application centric, more programmable, more API access. What's the big news about with AWS Hugging Face, you know, what's going on with this announcement? >> Yeah, first of all, they're very excited to announce our expanded collaboration with Hugging Face because with this partnership, our goal, as you all know, I mean Hugging Face I consider them like the GitHub for machine learning. And with this partnership, Hugging Face and AWS will be able to democratize AI for a broad range of developers, not just specific deep AI startups. And now with this we can accelerate the training, fine tuning, and deployment of these large language models and vision models from Hugging Face in the cloud. So, and the broader context, when you step back and see what customer problem we are trying to solve with this announcement, essentially if you see these foundational models are used to now create like a huge number of applications, suggest like tech summarization, question answering, or search image generation, creative, other things. And these are all stuff we are seeing in the likes of these Chat GPT style applications. But there is a broad range of enterprise use cases that we don't even talk about. And it's because these kind of transformative generative AI capabilities and models are not available to, I mean, millions of developers. And because either training these elements from scratch can be very expensive or time consuming and need deep expertise, or more importantly, they don't need these generic models. They need them to be fine tuned for the specific use cases. And one of the biggest complaints we hear is that these models, when they try to use it for real production use cases, they are incredibly expensive to train and incredibly expensive to run inference on, to use it at a production scale, so And unlike search, web search style applications where the margins can be really huge, here in production use cases and enterprises, you want efficiency at scale. That's where a Hugging Face and AWS share our mission. And by integrating with Trainium and Inferentia, we're able to handle the cost efficient training and inference at scale. I'll deep dive on it and by training teaming up on the SageMaker front now the time it takes to build these models and fine tune them as also coming down. So that's what makes this partnership very unique as well. So I'm very excited. >> I want to get into the, to the time savings and the cost savings as well on the on the training and inference. It's a huge issue. But before we get into that, just how long have you guys been working with Hugging Face? I know this is a previous relationship. This is an expansion of that relationship. Can you comment on the what's different about what's happened before and then now? >> Yeah, so Hugging Face, we have had an great relationship in the past few years as well where they have actually made their models available to run on AWS in a fashion, even inspect their Bloom project was something many of our customers even used. Bloom Project for context is their open source project, which builds a GPT three style model. And now with this expanded collaboration, now Hugging Face selected AWS for that next generation of this generative AI model, building on their highly successful Bloom project as well. And the nice thing is now by direct integration with Trainium and Inferentia, where you get cost savings in a really significant way. Now for instance, tier 1 can provide up to 50% cost to train savings, and Inferentia can deliver up to 60% better costs and Forex more higher throughput. Now these models, especially as they train that next generation generated AI model, it is going to be not only more accessible to all the developers who use it in open. So it'll be a lot cheaper as well. And that's what makes this moment really exciting because yeah, we can't democratize AI unless we make it broadly accessible and cost efficient, and easy to program and use as well. >> Okay, thanks Swami. We really appreciate. Swami's a Cube alumni, but also vice President, database analyst machine learning web services breaking down the Hugging Face announcement. Obviously the relationship he called it the GitHub of machine learning. This is the beginning of what we will see, a continuing competitive battle with Microsoft. Microsoft launching OpenAI. Amazon's been doing it for years. They got Alexa, they know what they're doing. It's going to be very interesting to see how this all plays out. You're watching Silicon Angle News, breaking here. I'm John Furrier, host of the Cube. Thanks for watching. (ethereal music)

(bright upbeat music) >> Hello, everyone. Welcome to SiliconANGLE News breaking story here. Amazon Web Services expanding their relationship with Hugging Face, breaking news here on SiliconANGLE. I'm John Furrier, SiliconANGLE reporter, founder, and also co-host of theCUBE. And I have with me, Swami, from Amazon Web Services, vice president of database, analytics, machine learning with AWS. Swami, great to have you on for this breaking news segment on AWS's big news. Thanks for coming on and taking the time. >> Hey, John, pleasure to be here. >> You know- >> Looking forward to it. >> We've had many conversations on theCUBE over the years, we've watched Amazon really move fast into the large data modeling, SageMaker became a very smashing success, obviously you've been on this for a while. Now with ChatGPT OpenAI, a lot of buzz going mainstream, takes it from behind the curtain inside the ropes, if you will, in the industry to a mainstream. And so this is a big moment, I think, in the industry, I want to get your perspective, because your news with Hugging Face, I think is another tell sign that we're about to tip over into a new accelerated growth around making AI now application aware, application centric, more programmable, more API access. What's the big news about, with AWS Hugging Face, you know, what's going on with this announcement? >> Yeah. First of all, they're very excited to announce our expanded collaboration with Hugging Face, because with this partnership, our goal, as you all know, I mean, Hugging Face, I consider them like the GitHub for machine learning. And with this partnership, Hugging Face and AWS, we'll be able to democratize AI for a broad range of developers, not just specific deep AI startups. And now with this, we can accelerate the training, fine tuning and deployment of these large language models, and vision models from Hugging Face in the cloud. And the broader context, when you step back and see what customer problem we are trying to solve with this announcement, essentially if you see these foundational models, are used to now create like a huge number of applications, suggest like tech summarization, question answering, or search image generation, creative, other things. And these are all stuff we are seeing in the likes of these ChatGPT style applications. But there is a broad range of enterprise use cases that we don't even talk about. And it's because these kind of transformative, generative AI capabilities and models are not available to, I mean, millions of developers. And because either training these elements from scratch can be very expensive or time consuming and need deep expertise, or more importantly, they don't need these generic models, they need them to be fine tuned for the specific use cases. And one of the biggest complaints we hear is that these models, when they try to use it for real production use cases, they are incredibly expensive to train and incredibly expensive to run inference on, to use it at a production scale. So, and unlike web search style applications, where the margins can be really huge, here in production use cases and enterprises, you want efficiency at scale. That's where Hugging Face and AWS share our mission. And by integrating with Trainium and Inferentia, we're able to handle the cost efficient training and inference at scale, I'll deep dive on it. And by teaming up on the SageMaker front, now the time it takes to build these models and fine tune them is also coming down. So that's what makes this partnership very unique as well. So I'm very excited. >> I want to get into the time savings and the cost savings as well on the training and inference, it's a huge issue, but before we get into that, just how long have you guys been working with Hugging Face? I know there's a previous relationship, this is an expansion of that relationship, can you comment on what's different about what's happened before and then now? >> Yeah. So, Hugging Face, we have had a great relationship in the past few years as well, where they have actually made their models available to run on AWS, you know, fashion. Even in fact, their Bloom Project was something many of our customers even used. Bloom Project, for context, is their open source project which builds a GPT-3 style model. And now with this expanded collaboration, now Hugging Face selected AWS for that next generation office generative AI model, building on their highly successful Bloom Project as well. And the nice thing is, now, by direct integration with Trainium and Inferentia, where you get cost savings in a really significant way, now, for instance, Trn1 can provide up to 50% cost to train savings, and Inferentia can deliver up to 60% better costs, and four x more higher throughput than (indistinct). Now, these models, especially as they train that next generation generative AI models, it is going to be, not only more accessible to all the developers, who use it in open, so it'll be a lot cheaper as well. And that's what makes this moment really exciting, because we can't democratize AI unless we make it broadly accessible and cost efficient and easy to program and use as well. >> Yeah. >> So very exciting. >> I'll get into the SageMaker and CodeWhisperer angle in a second, but you hit on some good points there. One, accessibility, which is, I call the democratization, which is getting this in the hands of developers, and/or AI to develop, we'll get into that in a second. So, access to coding and Git reasoning is a whole nother wave. But the three things I know you've been working on, I want to put in the buckets here and comment, one, I know you've, over the years, been working on saving time to train, that's a big point, you mentioned some of those stats, also cost, 'cause now cost is an equation on, you know, bundling whether you're uncoupling with hardware and software, that's a big issue. Where do I find the GPUs? Where's the horsepower cost? And then also sustainability. You've mentioned that in the past, is there a sustainability angle here? Can you talk about those three things, time, cost, and sustainability? >> Certainly. So if you look at it from the AWS perspective, we have been supporting customers doing machine learning for the past years. Just for broader context, Amazon has been doing ML the past two decades right from the early days of ML powered recommendation to actually also supporting all kinds of generative AI applications. If you look at even generative AI application within Amazon, Amazon search, when you go search for a product and so forth, we have a team called MFi within Amazon search that helps bring these large language models into creating highly accurate search results. And these are created with models, really large models with tens of billions of parameters, scales to thousands of training jobs every month and trained on large model of hardware. And this is an example of a really good large language foundation model application running at production scale, and also, of course, Alexa, which uses a large generator model as well. And they actually even had a research paper that showed that they are more, and do better in accuracy than other systems like GPT-3 and whatnot. So, and we also touched on things like CodeWhisperer, which uses generative AI to improve developer productivity, but in a responsible manner, because 40% of some of the studies show 40% of this generated code had serious security flaws in it. This is where we didn't just do generative AI, we combined with automated reasoning capabilities, which is a very, very useful technique to identify these issues and couple them so that it produces highly secure code as well. Now, all these learnings taught us few things, and which is what you put in these three buckets. And yeah, like more than 100,000 customers using ML and AI services, including leading startups in the generative AI space, like stability AI, AI21 Labs, or Hugging Face, or even Alexa, for that matter. They care about, I put them in three dimension, one is around cost, which we touched on with Trainium and Inferentia, where we actually, the Trainium, you provide to 50% better cost savings, but the other aspect is, Trainium is a lot more power efficient as well compared to traditional one. And Inferentia is also better in terms of throughput, when it comes to what it is capable of. Like it is able to deliver up to three x higher compute performance and four x higher throughput, compared to it's previous generation, and it is extremely cost efficient and power efficient as well. >> Well. >> Now, the second element that really is important is in a day, developers deeply value the time it takes to build these models, and they don't want to build models from scratch. And this is where SageMaker, which is, even going to Kaggle uses, this is what it is, number one, enterprise ML platform. What it did to traditional machine learning, where tens of thousands of customers use StageMaker today, including the ones I mentioned, is that what used to take like months to build these models have dropped down to now a matter of days, if not less. Now, a generative AI, the cost of building these models, if you look at the landscape, the model parameter size had jumped by more than thousand X in the past three years, thousand x. And that means the training is like a really big distributed systems problem. How do you actually scale these model training? How do you actually ensure that you utilize these efficiently? Because these machines are very expensive, let alone they consume a lot of power. So, this is where SageMaker capability to build, automatically train, tune, and deploy models really concern this, especially with this distributor training infrastructure, and those are some of the reasons why some of the leading generative AI startups are actually leveraging it, because they do not want a giant infrastructure team, which is constantly tuning and fine tuning, and keeping these clusters alive. >> It sounds like a lot like what startups are doing with the cloud early days, no data center, you move to the cloud. So, this is the trend we're seeing, right? You guys are making it easier for developers with Hugging Face, I get that. I love that GitHub for machine learning, large language models are complex and expensive to build, but not anymore, you got Trainium and Inferentia, developers can get faster time to value, but then you got the transformers data sets, token libraries, all that optimized for generator. This is a perfect storm for startups. Jon Turow, a former AWS person, who used to work, I think for you, is now a VC at Madrona Venture, he and I were talking about the generator AI landscape, it's exploding with startups. Every alpha entrepreneur out there is seeing this as the next frontier, that's the 20 mile stairs, next 10 years is going to be huge. What is the big thing that's happened? 'Cause some people were saying, the founder of Yquem said, "Oh, the start ups won't be real, because they don't all have AI experience." John Markoff, former New York Times writer told me that, AI, there's so much work done, this is going to explode, accelerate really fast, because it's almost like it's been waiting for this moment. What's your reaction? >> I actually think there is going to be an explosion of startups, not because they need to be AI startups, but now finally AI is really accessible or going to be accessible, so that they can create remarkable applications, either for enterprises or for disrupting actually how customer service is being done or how creative tools are being built. And I mean, this is going to change in many ways. When we think about generative AI, we always like to think of how it generates like school homework or arts or music or whatnot, but when you look at it on the practical side, generative AI is being actually used across various industries. I'll give an example of like Autodesk. Autodesk is a customer who runs an AWS and SageMaker. They already have an offering that enables generated design, where designers can generate many structural designs for products, whereby you give a specific set of constraints and they actually can generate a structure accordingly. And we see similar kind of trend across various industries, where it can be around creative media editing or various others. I have the strong sense that literally, in the next few years, just like now, conventional machine learning is embedded in every application, every mobile app that we see, it is pervasive, and we don't even think twice about it, same way, like almost all apps are built on cloud. Generative AI is going to be part of every startup, and they are going to create remarkable experiences without needing actually, these deep generative AI scientists. But you won't get that until you actually make these models accessible. And I also don't think one model is going to rule the world, then you want these developers to have access to broad range of models. Just like, go back to the early days of deep learning. Everybody thought it is going to be one framework that will rule the world, and it has been changing, from Caffe to TensorFlow to PyTorch to various other things. And I have a suspicion, we had to enable developers where they are, so. >> You know, Dave Vellante and I have been riffing on this concept called super cloud, and a lot of people have co-opted to be multicloud, but we really were getting at this whole next layer on top of say, AWS. You guys are the most comprehensive cloud, you guys are a super cloud, and even Adam and I are talking about ISVs evolving to ecosystem partners. I mean, your top customers have ecosystems building on top of it. This feels like a whole nother AWS. How are you guys leveraging the history of AWS, which by the way, had the same trajectory, startups came in, they didn't want to provision a data center, the heavy lifting, all the things that have made Amazon successful culturally. And day one thinking is, provide the heavy lifting, undifferentiated heavy lifting, and make it faster for developers to program code. AI's got the same thing. How are you guys taking this to the next level, because now, this is an opportunity for the competition to change the game and take it over? This is, I'm sure, a conversation, you guys have a lot of things going on in AWS that makes you unique. What's the internal and external positioning around how you take it to the next level? >> I mean, so I agree with you that generative AI has a very, very strong potential in terms of what it can enable in terms of next generation application. But this is where Amazon's experience and expertise in putting these foundation models to work internally really has helped us quite a bit. If you look at it, like amazon.com search is like a very, very important application in terms of what is the customer impact on number of customers who use that application openly, and the amount of dollar impact it does for an organization. And we have been doing it silently for a while now. And the same thing is true for like Alexa too, which actually not only uses it for natural language understanding other city, even national leverages is set for creating stories and various other examples. And now, our approach to it from AWS is we actually look at it as in terms of the same three tiers like we did in machine learning, because when you look at generative AI, we genuinely see three sets of customers. One is, like really deep technical expert practitioner startups. These are the startups that are creating the next generation models like the likes of stability AIs or Hugging Face with Bloom or AI21. And they generally want to build their own models, and they want the best price performance of their infrastructure for training and inference. That's where our investments in silicon and hardware and networking innovations, where Trainium and Inferentia really plays a big role. And we can nearly do that, and that is one. The second middle tier is where I do think developers don't want to spend time building their own models, let alone, they actually want the model to be useful to that data. They don't need their models to create like high school homeworks or various other things. What they generally want is, hey, I had this data from my enterprises that I want to fine tune and make it really work only for this, and make it work remarkable, can be for tech summarization, to generate a report, or it can be for better Q&A, and so forth. This is where we are. Our investments in the middle tier with SageMaker, and our partnership with Hugging Face and AI21 and co here are all going to very meaningful. And you'll see us investing, I mean, you already talked about CodeWhisperer, which is an open preview, but we are also partnering with a whole lot of top ISVs, and you'll see more on this front to enable the next wave of generated AI apps too, because this is an area where we do think lot of innovation is yet to be done. It's like day one for us in this space, and we want to enable that huge ecosystem to flourish. >> You know, one of the things Dave Vellante and I were talking about in our first podcast we just did on Friday, we're going to do weekly, is we highlighted the AI ChatGPT example as a horizontal use case, because everyone loves it, people are using it in all their different verticals, and horizontal scalable cloud plays perfectly into it. So I have to ask you, as you look at what AWS is going to bring to the table, a lot's changed over the past 13 years with AWS, a lot more services are available, how should someone rebuild or re-platform and refactor their application of business with AI, with AWS? What are some of the tools that you see and recommend? Is it Serverless, is it SageMaker, CodeWhisperer? What do you think's going to shine brightly within the AWS stack, if you will, or service list, that's going to be part of this? As you mentioned, CodeWhisperer and SageMaker, what else should people be looking at as they start tinkering and getting all these benefits, and scale up their ups? >> You know, if we were a startup, first, I would really work backwards from the customer problem I try to solve, and pick and choose, bar, I don't need to deal with the undifferentiated heavy lifting, so. And that's where the answer is going to change. If you look at it then, the answer is not going to be like a one size fits all, so you need a very strong, I mean, granted on the compute front, if you can actually completely accurate it, so unless, I will always recommend it, instead of running compute for running your ups, because it takes care of all the undifferentiated heavy lifting, but on the data, and that's where we provide a whole variety of databases, right from like relational data, or non-relational, or dynamo, and so forth. And of course, we also have a deep analytical stack, where data directly flows from our relational databases into data lakes and data virus. And you can get value along with partnership with various analytical providers. The area where I do think fundamentally things are changing on what people can do is like, with CodeWhisperer, I was literally trying to actually program a code on sending a message through Twilio, and I was going to pull up to read a documentation, and in my ID, I was actually saying like, let's try sending a message to Twilio, or let's actually update a Route 53 error code. All I had to do was type in just a comment, and it actually started generating the sub-routine. And it is going to be a huge time saver, if I were a developer. And the goal is for us not to actually do it just for AWS developers, and not to just generate the code, but make sure the code is actually highly secure and follows the best practices. So, it's not always about machine learning, it's augmenting with automated reasoning as well. And generative AI is going to be changing, and not just in how people write code, but also how it actually gets built and used as well. You'll see a lot more stuff coming on this front. >> Swami, thank you for your time. I know you're super busy. Thank you for sharing on the news and giving commentary. Again, I think this is a AWS moment and industry moment, heavy lifting, accelerated value, agility. AIOps is going to be probably redefined here. Thanks for sharing your commentary. And we'll see you next time, I'm looking forward to doing more follow up on this. It's going to be a big wave. Thanks. >> Okay. Thanks again, John, always a pleasure. >> Okay. This is SiliconANGLE's breaking news commentary. I'm John Furrier with SiliconANGLE News, as well as host of theCUBE. Swami, who's a leader in AWS, has been on theCUBE multiple times. We've been tracking the growth of how Amazon's journey has just been exploding past five years, in particular, past three. You heard the numbers, great performance, great reviews. This is a watershed moment, I think, for the industry, and it's going to be a lot of fun for the next 10 years. Thanks for watching. (bright music)

>> From the Cube Studios in Palo Alto in Boston, bringing you data-driven insights from The Cube and ETR. This is "Breaking Analysis" with Dave Vellante. >> The world's leading telcos are trying to shed the stigma of being monopolies lacking innovation. Telcos have been great at operational efficiency and connectivity and living off of transmission, and the costs and expenses or revenue associated with that transmission. But in a world beyond telephone poles and basic wireless and mobile services, how will telcos modernize and become more agile and monetize new opportunities brought about by 5G and private wireless and a spate of new innovations and infrastructure, cloud data and apps? Hello, and welcome to this week's Wikibon CUBE Insights powered by ETR. In this breaking analysis and ahead of Mobile World Congress or now, MWC23, we explore the evolution of the telco business and how the industry is in many ways, mimicking transformations that took place decades ago in enterprise IT. We'll model some of the traditional enterprise vendors using ETR data and investigate how they're faring in the telecommunications sector, and we'll pose some of the key issues facing the industry this decade. First, let's take a look at what the GSMA has in store for MWC23. GSMA is the host of what used to be called Mobile World Congress. They've set the theme for this year's event as "Velocity" and they've rebranded MWC to reflect the fact that mobile technology is only one part of the story. MWC has become one of the world's premier events highlighting innovations not only in Telco, mobile and 5G, but the collision between cloud, infrastructure, apps, private networks, smart industries, machine intelligence, and AI, and more. MWC comprises an enormous ecosystem of service providers, technology companies, and firms from virtually every industry including sports and entertainment. And as well, GSMA, along with its venue partner at the Fira Barcelona, have placed a major emphasis on sustainability and public and private partnerships. Virtually every industry will be represented at the event because every industry is impacted by the trends and opportunities in this space. GSMA has said it expects 80,000 attendees at MWC this year, not quite back to 2019 levels, but trending in that direction. Of course, attendance from Chinese participants has historically been very high at the show, and obviously the continued travel issues from that region are affecting the overall attendance, but still very strong. And despite these concerns, Huawei, the giant Chinese technology company. has the largest physical presence of any exhibitor at the show. And finally, GSMA estimates that more than $300 million in economic benefit will result from the event which takes place at the end of February and early March. And The Cube will be back at MWC this year with a major presence thanks to our anchor sponsor, Dell Technologies and other supporters of our content program, including Enterprise Web, ArcaOS, VMware, Snowflake, Cisco, AWS, and others. And one of the areas we're interested in exploring is the evolution of the telco stack. It's a topic that's often talked about and one that we've observed taking place in the 1990s when the vertically integrated IBM mainframe monopoly gave way to a disintegrated and horizontal industry structure. And in many ways, the same thing is happening today in telecommunications, which is shown on the left-hand side of this diagram. Historically, telcos have relied on a hardened, integrated, and incredibly reliable, and secure set of hardware and software services that have been fully vetted and tested, and certified, and relied upon for decades. And at the top of that stack on the left are the crown jewels of the telco stack, the operational support systems and the business support systems. For the OSS, we're talking about things like network management, network operations, service delivery, quality of service, fulfillment assurance, and things like that. For the BSS systems, these refer to customer-facing elements of the stack, like revenue, order management, what products they sell, billing, and customer service. And what we're seeing is telcos have been really good at operational efficiency and making money off of transport and connectivity, but they've lacked the innovation in services and applications. They own the pipes and that works well, but others, be the over-the-top content companies, or private network providers and increasingly, cloud providers have been able to bypass the telcos, reach around them, if you will, and drive innovation. And so, the right-most diagram speaks to the need to disaggregate pieces of the stack. And while the similarities to the 1990s in enterprise IT are greater than the differences, there are things that are different. For example, the granularity of hardware infrastructure will not likely be as high where competition occurred back in the 90s at every layer of the value chain with very little infrastructure integration. That of course changed in the 2010s with converged infrastructure and hyper-converged and also software defined. So, that's one difference. And the advent of cloud, containers, microservices, and AI, none of that was really a major factor in the disintegration of legacy IT. And that probably means that disruptors can move even faster than did the likes of Intel and Microsoft, Oracle, Cisco, and the Seagates of the 1990s. As well, while many of the products and services will come from traditional enterprise IT names like Dell, HPE, Cisco, Red Hat, VMware, AWS, Microsoft, Google, et cetera, many of the names are going to be different and come from traditional network equipment providers. These are names like Ericsson and Huawei, and Nokia, and other names, like Wind River, and Rakuten, and Dish Networks. And there are enormous opportunities in data to help telecom companies and their competitors go beyond telemetry data into more advanced analytics and data monetization. There's also going to be an entirely new set of apps based on the workloads and use cases ranging from hospitals, sports arenas, race tracks, shipping ports, you name it. Virtually every vertical will participate in this transformation as the industry evolves its focus toward innovation, agility, and open ecosystems. Now remember, this is not a binary state. There are going to be greenfield companies disrupting the apple cart, but the incumbent telcos are going to have to continue to ensure newer systems work with their legacy infrastructure, in their OSS and BSS existing systems. And as we know, this is not going to be an overnight task. Integration is a difficult thing, transformations, migrations. So that's what makes this all so interesting because others can come in with Greenfield and potentially disrupt. There'll be interesting partnerships and ecosystems will form and coalitions will also form. Now, we mentioned that several traditional enterprise companies are or will be playing in this space. Now, ETR doesn't have a ton of data on specific telecom equipment and software providers, but it does have some interesting data that we cut for this breaking analysis. What we're showing here in this graphic is some of the names that we've followed over the years and how they're faring. Specifically, we did the cut within the telco sector. So the Y-axis here shows net score or spending velocity. And the horizontal axis, that shows the presence or pervasiveness in the data set. And that table insert in the upper left, that informs as to how the dots are plotted. You know, the two columns there, net score and the ends. And that red-dotted line, that horizontal line at 40%, that is an indicator of a highly elevated level. Anything above that, we consider quite outstanding. And what we'll do now is we'll comment on some of the cohorts and share with you how they're doing in telecommunications, and that sector, that vertical relative to their position overall in the data set. Let's start with the public cloud players. They're prominent in every industry. Telcos, telecommunications is no exception and it's quite an interesting cohort here. On the one hand, they can help telecommunication firms modernize and become more agile by eliminating the heavy lifting and you know, all the cloud, you know, value prop, data center costs, and the cloud benefits. At the same time, public cloud players are bringing their services to the edge, building out their own global networks and are a disruptive force to traditional telcos. All right, let's talk about Azure first. Their net score is basically identical to telco relative to its overall average. AWS's net score is higher in telco by just a few percentage points. Google Cloud platform is eight percentage points higher in telco with a 53% net score. So all three hyperscalers have an equal or stronger presence in telco than their average overall. Okay, let's look at the traditional enterprise hardware and software infrastructure cohort. Dell, Cisco, HPE, Red Hat, VMware, and Oracle. We've highlighted in this chart just as sort of indicators or proxies. Dell's net score's 10 percentage points higher in telco than its overall average. Interesting. Cisco's is a bit higher. HPE's is actually lower by about nine percentage points in the ETR survey, and VMware's is lower by about four percentage points. Now, Red Hat is really interesting. OpenStack, as we've previously reported is popular with telcos who want to build out their own private cloud. And the data shows that Red Hat OpenStack's net score is 15 percentage points higher in the telco sector than its overall average. OpenShift, on the other hand, has a net score that's four percentage points lower in telco than its overall average. So this to us talks to the pace of adoption of microservices and containers. You know, it's going to happen, but it's going to happen more slowly. Finally, Oracle's spending momentum is somewhat lower in the sector than its average, despite the firm having a decent telco business. IBM and Accenture, heavy services companies are both lower in this sector than their average. And real quickly, snowflake's net score is much lower by about 12 percentage points relative to its very high average net score of 62%. But we look for them to be a player in this space as telcos need to modernize their analytics stack and share data in a governed manner. Databricks' net score is also much lower than its average by about 13 points. And same, I would expect them to be a player as open architectures and cloud gains steam in telco. All right, let's close out now on what we're going to be talking about at MWC23 and some of the key issues that we'll be unpacking. We've talked about stack disaggregation in this breaking analysis, but the key here will be the pace at which it will reach the operational efficiency and reliability of closed stacks. Telcos, you know, in a large part, they're engineering heavy firms and much of their work takes place, kind of in the basement, in the dark. It's not really a big public hype machine, and they tend to move slowly and cautiously. While they understand the importance of agility, they're going to be careful because, you know, it's in their DNA. And so at the same time, if they don't move fast enough, they're going to get hurt and disrupted by competitors. So that's going to be a topic of conversation, and we'll be looking for proof points. And the other comment I'll make is around integration. Telcos because of their conservatism will benefit from better testing and those firms that can innovate on the testing front and have labs and certifications and innovate at that level, with an ecosystem are going to be in a better position. Because open sometimes means wild west. So the more players like Dell, HPE, Cisco, Red Hat, et cetera, that do that and align with their ecosystems and provide those resources, the faster adoption is going to go. So we'll be looking for, you know, who's actually doing that, Open RAN or Radio Access Networks. That fits in this discussion because O-RAN is an emerging network architecture. It essentially enables the use of open technologies from an ecosystem and over time, look at O-RAN is going to be open, but the questions, you know, a lot of questions remain as to when it will be able to deliver the operational efficiency of traditional RAN. Got some interesting dynamics going on. Rakuten is a company that's working hard on this problem, really focusing on operational efficiency. Then you got Dish Networks. They're also embracing O-RAN. They're coming at it more from service innovation. So that's something that we'll be monitoring and unpacking. We're going to look at cloud as a disruptor. On the one hand, cloud can help drive agility, as we said earlier and optionality, and innovation for incumbent telcos. But the flip side is going to also do the same for startups trying to disrupt and cloud attracts startups. While some of the telcos are actually embracing the cloud, many are being cautious. So that's going to be an interesting topic of discussion. And there's private wireless networks and 5G, and hyperlocal private networks, they're being deployed, you know, at the edge. This idea of open edge is also a really hot topic and this trend is going to accelerate. You know, the importance here is that the use cases are going to be widely varied. The needs of a hospital are going to be different than those of a sports venue are different from a remote drilling location, and energy or a concert venue. Things like real-time AI inference and data flows are going to bring new services and monetization opportunities. And many firms are going to be bypassing traditional telecommunications networks to build these out. Satellites as well, we're going to see, you know, in this decade, you're going to have, you're going to look down at Google Earth and you're going to see real-time. You know, today you see snapshots and so, lots of innovations going in that space. So how is this going to disrupt industries and traditional industry structures? Now, as always, we'll be looking at data angles, right? 'Cause it's in The Cube's DNA to follow the data and what opportunities and risks data brings. The Cube is going to be on location at MWC23 at the end of the month. We got a great set. We're in the walkway between halls four and five, right in Congress Square, it's booths CS60. So we'll have a full, they're called Stan CS60. We have a full schedule. I'm going to be there with Lisa Martin, Dave Nicholson and the entire Cube crew, so don't forget to stop by. All right, that's a wrap. I want to thank Alex Myerson, who's on production and manages the podcast, Ken Schiffman as well. Kristin Martin and Cheryl Knight help get the word out on social media and in our newsletters. And Rob Hof is our editor-in-chief over at Silicon Angle, does some great stuff for us. Thank you all. Remember, all these episodes are available as podcasts. Wherever you listen, just search "Breaking Analysis" podcasts I publish each week on wikibon.com and silicon angle.com. And all the video content is available on demand at thecube.net. You can email me directly at david.vellante@silicon angle.com. You can DM me at dvellante or comment on my LinkedIn post. Please do check out etr.ai for the best survey data in the enterprise tech business. This is Dave Vellante for The Cube Insights powered by ETR. Thanks for watching and we'll see you at Mobile World Congress, and/or at next time on "Breaking Analysis." (bright music) (bright music fades)

(upbeat music) >> Hello, and welcome to Supercloud2. I'm John Furrier, host of theCUBE here. We're exploring all the new Supercloud trends around multiple clouds, hyper scale gaps in their systems, new innovations, new applications, new companies, new products, new brands emerging from this big inflection point. Got a great guest who's going to unpack it with me today, Ramesh Prabagaran, who's the co-founder and CEO of Prosimo, CUBE alumni. Ramesh, legend in the industry, you've been around. You've seen many cycles. Welcome to Supercloud2. >> Thank you. You're being too kind. >> Well, you know, you guys have been a technical, great technical founding team, multiple ventures, multiple times around the track as they say, but now we're seeing something completely different. This is our second event, kind of we're doing to start the the ball rolling around unpacking this idea of Supercloud which evolved from a riff with me and Dave to now a working group paper, multiple definitions. People are saying they're Supercloud. CloudFlare says this is their version. Someone says there over there. Fitzi over there in the blog is always, you know, challenging us on our definitions, but it's, the consensus is though something's happening. >> Ramesh: Absolutely. >> And what's your take on this kind of big inflection point? >> Absolutely, so if you just look at kind of this in layers right, so you have hyper scalers that are innovating really quickly on underlying capabilities, and then you have enterprises adopting these technologies, right, there is a layer in the middle that I would say is largely missing, right? And one that addresses the gaps introduced by these new capabilities, by the hyper scalers. At the same time, one that actually spans, let's say multiple regions, multiple clouds and so forth. So that to me is kind of the Supercloud layer of sorts. One that helps enterprises adopt the underlying hyper scaler capabilities a lot faster, and at the same time brings a certain level of consistency and homogeneity also. >> What do you think the big driver of Supercloud is? Is it the industry growing up or is it the demand for new kinds of capabilities or both? Or just evolution? What's your take? >> I would say largely it depends on kind of who the entity is that you're talking about, right? And so I would say both. So if you look at one cohort here, it's adoption, right? If I have a externally facing digital presence, for example, then I'm going to scale that up and get to as many subscribers and users no matter what, right? And at that time it's a different set of problems. If you're looking at kind of traditional enterprise inward that are bringing apps into the cloud and so forth, it's a different set of care abouts, right? So both are, I would say, equally important problems to solve for. >> Well, one reality that we're definitely tracking, and it's not really a debate anymore, is hybrid. >> Ramesh: Yep >> Hybrid happened. It happened faster than most people thought. But, you know, we were talking about this in 2015 when it first got kicked around, but now you see hybrid in the cloud, on premises and the edge. This kind of forms that distributed computing paradigm that we've always been predicting. And so if that continues to play out the way it is, you're now going to have a completely distributed, connected internet and sets of systems, intra and external within companies. So again, the world is connected 100%. Everything's changing, right? >> And that introduces. >> It wasn't your grandfather's networking anymore or storage. The game is still the same, but the play, the components are acting differently. What's your take on this? >> Absolutely. No, absolutely. That's a very key important point, and it's one that we always ask our customers right at the front end, right? Because your starting assumptions matter. If you have workloads of workloads in the cloud and data center is something that you want to connect into, then you'll make decisions kind of keeping cloud in the center and then kind of bolt on technologies for what that means to extend it to the data center. If your center of gravity is in the data center, and then cloud is let's say 10% right now, but you see that growing, then what choices do you have? Right, do you want to bring your data center technologies into the cloud because you want that consistency in operations? Or do you want to start off fresh, right? So this is a really key, important question, and one that many of our customers are actually are grappling with, right? They have this notion that going cloud native is the right approach, but at the same time that means I have a bifurcation in kind of how do I operate my data center versus my cloud, right? Two different operating models, and slowly it'll shift over to one. But you're going to have to deal with dual reality for a while. >> I was talking to an old friend of mine, CIO, very experienced CIO. Big time company, large deployment, a lot of IT. I said, so what's the big trend everyone's telling me about IT's going. He goes no, not really. IT's not going away for me. It's going everywhere in the company. >> Ramesh: Exactly. >> So I need to scale my IT-like capabilities everywhere and then make it invisible. >> Ramesh: Correct. >> Which is essentially code words for saying it's going to be completely cloud native everywhere. This is what is happening. Do you agree? >> Absolutely right, and so if you look at what do enterprises care about it? The reason to go to the cloud is to get speed of operations, and it's apps, apps, apps, right? Do you ever have a conversation on networking and infrastructure first? No, that kind of gets brought into the conversation because you want to deal with users, applications and services, right? And so the end goal is essentially how do users communicate with apps and get the right experience, security and whatnot, and how do apps talk to each other and make sure that you get all of the connectivity and security requirements? Underneath the covers, what does this mean for infrastructure, networking, security and whatnot? It's actually going to be someone else's job, right? And you shouldn't have to think too much about it. So this whole notion of kind of making that transparent is real actually, right? But at the same time, us and all the guys that we talk to on the customer side, that's their job, right? Like we have to work towards making that transparent. Some are going to be in the form of capability, some are going to be driven by data, but that's really where the two worlds are going to come together. >> Lots of debates going on. We just heard from Bob Muglia here on Supercloud2. He said Supercloud's a platform that provides programmatically consistent services hosted on heterogeneous cloud providers. So the question that's being debated is is Supercloud a platform or an architecture in your view? >> Okay, that's a tough one actually. I'm going to side on the side on kind of the platform side right, and the reason for that is architectural choices are things that you make ahead of time. And you, once you're in, there really isn't a fork in the road, right? Platforms continue to evolve. You can iterate, innovate and so on and so forth. And so I'm thinking Supercloud is more of a platform because you do have a choice. Hey, am I going AWS, Azure, GCP. You make that choice. What is my center of gravity? You make that choice. That's kind of an architectural decision, right? Once you make that, then how do I make things work consistently across like two or three clouds? That's a platform choice. >> So who's responsible for the architecture as the platform, the vendor serving the platform or is the platform vendor agnostic? >> You know, this is where you have to kind of peel the onion in layers, right? If you talk about applications, you can't go to a developer team or an app team and say I want you to operate on Google or AWS. They're like I'll pick the cloud that I want, right? Now who are we talking to? The infrastructure guys and the networking guys, right? They want to make sure that it's not bifurcated. It's like, hey, I want to make sure whatever I build for AWS I can equally use that on Azure. I can equally use that on GCP. So if you're talking to more of the application centric teams who really want infrastructure to be transparent, they'll say, okay, I want to make this choice of whether this is AWS, Azure, GCP, and stick to that. And if you come kind of down the layers of the stack into infrastructure, they are thinking a little more holistically, a little more Supercloud, a little more multicloud, and that. >> That's a good point. So that brings up the deployment question. >> Ramesh: Exactly! >> I want to ask you the next question, okay, what is the preferred deployment in your opinion for a Supercloud narrative? Is it single instance, spread it around everywhere? What's the, do you have a single global instance or do you have everything synchronized? >> So I would say first layer of that Supercloud really kind of fix the holes that have been introduced as a result of kind of adopting the hyper scaler technologies, right? So each, the hyper scalers have been really good at innovating and providing really massive scale elastic capabilities, right? But once you start to build capabilities on top of that to help serve the application, there's a few holes start to show up. So first job of Supercloud really is to plug those holes, right? Second is can I get to an operating model, so that I can replicate this not just in a single region, but across multiple regions, same cloud, and then across multiple clouds, right? And so both of those need to be solved for in order to be (cross talking). >> So is that multiple instantiations of the stack or? >> Yeah, so this again depends on kind of the capability, right? So if you take a more solution view, and so I can speak for kind of networking security combined right? There you always take a solution view. You don't ever look at, you know, what does this mean for a single instance in a single region. You take a macro view, and then you then break it down into what does this mean for region, what does it mean for instance, what does this mean for AZs? And so on and so forth. So you kind of have to go top to bottom. >> Okay, welcome you down into the trap now. Okay, synchronizing the data, latency, these are all questions. So what does the network Supercloud look like to you? Because networking is big here. >> Ramesh: Yes, absolutely. >> This is what you guys do. >> Exactly, yeah. So the different set of problems as you go up the stack, right? So if you have hundreds of workloads in a single region, the set of problems you're dealing with there are kind of app native connectivity, how do I go from kind of east/west, all of those fun things, right? Which are usually bound in terms of latency. You don't have those challenges as much, but can you build your entire enterprise application architecture in one region? No, you're going to have to create multiple instances, right? So my data lake is invariably going to be in one place. My business logic is going to be spread across a few places. What does that bring in? I need to go across regions. Am I going to put those two regions right next to each other? No, I'm not going to, right? I'm going to have places in Europe. I'm going to have APAC, and I'm going to have a North American presence, and I need to bring all these things together. So this is where, back to your point, latency really matters, right? Because I need to be able to find out not just best path but also how do I reduce the millisecond, microseconds that my application cares about, which brings in a layer of optimization and then so on and so on and so forth. So this is what we call kind of to borrow the Prosimo language full stack networking, right? Because I'm not just dealing with how do I go from one region to another because that's laws of physics. I can only control so much. But there are a few elements up the application stack in software that you can tweak to actually bring these things closer and closer. >> And on that point, you're seeing security being talked a lot more at the network layer. So how do you secure the Supercloud at the network layer? What's that look like? >> Yeah, we've been grappling with essentially is security kind of foundational, and then is the network on top. And then we had an alternative viewpoint which is kind of network and then security on top. And the answer is actually it's neither, right? It's almost like a meshed up sandwich of sorts. So you need to have networking security work really well together, right? Case in point, I mean we were talking to a customer yesterday. He said, hey, I have my data lake in one region that needs to talk to an analytics service in a completely different region of a different cloud. These two things just need to be able to talk to each other, which means I need to bring elements of networking. I need to bring elements of security, secure access, app segmentation, all of those things. Very simple, I have an analytics service that needs to contact a data lake. That's what he starts with, but then before you know it, it actually brings up a whole stack underneath, so that's. >> VMware calls that cloud chaos. >> Ramesh: Yes, exactly. >> And then that's the halfway point between cloud smart. Cloud first, cloud chaos, cloud smart, and the next thing, you can skip that whole step. But again, again, it's pick your strategy right? Again, this comes back down to your earlier point. I want to ask you from a customer standpoint, you got the hyper scalers doing very, very well. >> Ramesh: Yep, absolutely. >> And I love what their Amazon's doing. I think Microsoft again though they had a little bit of downgrade are catching up fast, and they have their installed base. So you got the land of the installed bases. >> Correct. >> First and greater, better cloud. Install base getting better, almost as good, almost as good is a gift, but close. Now you have them specializing. Silicon, special silicon. So there's gaps for other services. >> Ramesh: Correct. >> And Amazon Web Services, Adam Selipsky's a open book saying, hey, we want our ecosystem to pick up these gaps and build on them. Go ahead, go to town. >> So this is where I think choices are tough, right? Because if you had one choice, you would work with it, and you would work around it, right? Now I have five different choices. Now what do I do? Our viewpoint is there are a bunch of things that say AWS does really, really well. Use that as a foundational layer, right? Like don't reinvent the wheel on those things. Transit gateways, global accelerators and whatnot, they exist for a reason. Billions of dollars have gone into building those things. Use that foundational layer, right? But what you want to build on top of that is actually driven by the application. The requirements of a lambda application that's serverless, it's very different than a packaged application that's responding for transactions, right? Like it's just completely very, very different. And so bring in the right set of capabilities required for those set of applications, and then you go based on that. This is also where I think whether something is a regional construct versus an overall global construct really, really matters, right? Because if you start with the assumption that everything is going to be built regionally, then it's someone else's job to make sure that all of these things are connected. But if you start with kind of the global purview, then the rest of them start to (cross talking). >> What are some of the things that the enterprises might want that are gaps that are going to be filled by the, by startups like you guys and the ecosystem because we're seeing the ecosystem form into two big camps. >> Ramesh: Yep. >> ISVs, which is an old school definition of independent software vendor, aka someone who writes software. >> Ramesh: Exactly. >> SaaS app. >> Ramesh: Correct. >> And then ecosystem software players that were once ISVs now have people building on top of them. >> Ramesh: Correct. >> They're building on top of the cloud. So you have that new hyper scale effect going on. >> Ramesh: Exactly. >> You got ISVs, which is software developers, software vendors. >> Ramesh: Correct. >> And ecosystems. >> Yep. >> What's that impact of that? Cause it's a new dynamic. >> Exactly, so if you take kind of enterprises, want to make sure that that their apps and the data center migrate to the cloud, new apps are developed the right way in the cloud, right? So that's kind of table stakes. So now what choices do they have? They listen to AWS and say, okay, I have all these cloud native services. I want to be able to instantiate all that. Now comes the interesting choice that they have to make. Do I go hire a whole bunch of people and do it myself or do I go there on the platform route, right? Because I made an architectural choice. Now I have to decide whether I want to do this myself or the platform choice. DIY works great for some, but you don't know what you're getting into, and it's people involved, right? People, process, all those fun things involved, right? So we show up there and say, you don't know what you don't know, right? Like because that's the nature of it. Why don't you invest in a platform like what what we provide, and then you actually build on top of it. We will, it's our job to make sure that we keep up with the innovation happening underneath the covers. And at the same time, this is not a closed ended system. You can actually build on top of our platform, right? And so that actually gives you a good mix. Now the care abouts are interesting. Some apps care about experience. Some apps care about latency. Some apps are extremely charty and extremely data intensive, but nobody wants to pay for it, right? And so it's a interesting Jenga that you have to play between experience versus security versus cost, right? And that makes kind of head of infrastructure and cloud platform teams' life really, really, really interesting. >> And this is why I love your background, and Stu Miniman, when he was with theCUBE, and now he's at Red Hat, we used to riff about the network and how network folks are now, those concepts are now up the top of the stack because the cloud is one big network effect. >> Ramesh: Exactly, correct. >> It's a computer. >> Yep, absolutely. No, and case in point, right, like say we're in let's say in San Jose here or or Palo Alto here, and let's say my application is sitting in London, right? The cloud gives you different express lanes. I can go down to my closest pop location provided by AWS and then I can go ride that all the way up to up to London. It's going to give me better performance, low latency, but I'm going to have to incur some costs associated with it. Or I can go all the wild internet all the way from Palo Alta up to kind of the ingress point into London and then go access, but I'm spending time on the wild internet, which means all kinds of fun things happen, right? But I'm not paying much, but my experience is not going to be so great. So, and there are various degrees of shade in them, of gray in the middle, right? So how do you pick what? It all kind of is driven by the applications. >> Well, we certainly want you back for Supercloud3, our next version of this virtual/live event here in our Palo Alto studios. Really appreciate you coming on. >> Absolutely. >> While you're here, give a quick plug for the company. Next minute, we can take a minute to talk about the success of the company. >> Ramesh: Absolutely. >> I know you got a fresh financing this past year. Plenty of money in the bank, going to ride this new wave, Supercloud wave. Give us a quick plug. >> Absolutely, yeah. So three years going on to four this calendar year. So it's an interesting time for the company. We have proven that our technology, product and our initial customers are quite happy with it. Now comes essentially more of those and scale and so forth. That's kind of the interesting phase that we are in. Also heartened to see quite a few of kind of really large and dominant players in the market, partners, channels and so forth, invest in us to take this to the next set of customers. I would say there's been a dramatic shift in the conversation with our customers. The first couple of years or so of the company, we are about three years old right now, was really about us educating them. This is what you need. This is what you need. Now actually it's a lot of just pull, right? We've seen a good indication, as much as a hate RFIs, a good indication is the number of RFIs that show up at our door saying we want you to participate in this because we want to understand more, right? And so as a, I think we are at an interesting point of the, of that shift. >> RFIs always like do all this work and hope for the best. Pray for a deal. You know, you guys on the right side of history. If a customer asks with respect to Supercloud, multicloud, is that your focus? Is that the direction you guys are going into? >> Yeah, so I would say we are kind of both, right? Supercloud and multicloud because we, our customers are hybrid, multiple clouds, all of the above, right? Our main pitch and kind of value back to the customers is go embrace cloud native because that's the right approach, right? It doesn't make sense to go reinvent the wheel on that one, but then make a really good choice about whether you want to do this yourself or invest in a platform to make your life easy. Because we have seen this story play out with many many enterprises, right? They pick the right technologies. They do a simple POC overnight, and they say, yeah, I can make this work for two apps, right? And then they say, yes, I can make this work for 100. You go down a certain path. You hit a wall. You hit a wall, and it's a hard wall. It's like, no, there isn't a thing that you can go around it. >> A lot of dead bodies laying around. >> Ramesh: Exactly. >> Dead wall. >> And then they have to unravel around that, and then they come talk to us, and they say, okay, now what? Like help me, help me through this journey. So I would say to the extent that you can do this diligence ahead of time, do that, and then, and then pick the right platform. >> You've got to have the talent. And you got to be geared up. You got to know what you're getting into. >> Ramesh: Exactly. >> You got to have the staff to do this. >> And cloud talent and skillset in particular, I mean there's lots available but it's in pockets right? And if you look at kind of web three companies, they've gone and kind of amassed all those guys, right? So enterprises are not left with the cream of the crop. >> John: They might be coming back. >> Exactly, exactly, so. >> With this downturn. Ramesh, great to see you and thanks for contributing to Supercloud2, and again, love your team. Very technical team, and you're in the right side of history in this one. Congratulations. >> Ramesh: No, and thank you, thank you very much. >> Okay, this is Supercloud2. I'm John Furrier with Dave Vellante. We'll be back right after this short break. (upbeat music)

(upbeat music) >> Okay, welcome back everyone at Supercloud 2 event, live here in Palo Alto, theCUBE Studios live stage performance, virtually syndicating it all over the world. I'm John Furrier with Dave Vellante here as Cube alumni, and special influencer guest, Howie Xu, VP of Machine Learning and Zscaler, also part-time as a CUBE analyst 'cause he is that good. Comes on all the time. You're basically a CUBE analyst as well. Thanks for coming on. >> Thanks for inviting me. >> John: Technically, you're not really a CUBE analyst, but you're kind of like a CUBE analyst. >> Happy New Year to everyone. >> Dave: Great to see you. >> Great to see you, Dave and John. >> John: We've been talking about ChatGPT online. You wrote a great post about it being more like Amazon, not like Google. >> Howie: More than just Google Search. >> More than Google Search. Oh, it's going to compete with Google Search, which it kind of does a little bit, but more its infrastructure. So a clever point, good segue into this conversation, because this is kind of the beginning of these kinds of next gen things we're going to see. Things where it's like an obvious next gen, it's getting real. Kind of like seeing the browser for the first time, Mosaic browser. Whoa, this internet thing's real. I think this is that moment and Supercloud like enablement is coming. So this has been a big part of the Supercloud kind of theme. >> Yeah, you talk about Supercloud, you talk about, you know, AI, ChatGPT. I really think the ChatGPT is really another Netscape moment, the browser moment. Because if you think about internet technology, right? It was brewing for 20 years before early 90s. Not until you had a, you know, browser, people realize, "Wow, this is how wonderful this technology could do." Right? You know, all the wonderful things. Then you have Yahoo and Amazon. I think we have brewing, you know, the AI technology for, you know, quite some time. Even then, you know, neural networks, deep learning. But not until ChatGPT came along, people realize, "Wow, you know, the user interface, user experience could be that great," right? So I really think, you know, if you look at the last 30 years, there is a browser moment, there is iPhone moment. I think ChatGPT moment is as big as those. >> Dave: What do you see as the intersection of things like ChatGPT and the Supercloud? Of course, the media's going to focus, journalists are going to focus on all the negatives and the privacy. Okay. You know we're going to get by that, right? Always do. Where do you see the Supercloud and sort of the distributed data fitting in with ChatGPT? Does it use that as a data source? What's the link? >> Howie: I think there are number of use cases. One of the use cases, we talked about why we even have Supercloud because of the complexity, because of the, you know, heterogeneous nature of different clouds. In order for me as a developer, in order for me to create applications, I have so many things to worry about, right? It's a complexity. But with ChatGPT, with the AI, I don't have to worry about it, right? Those kind of details will be taken care of by, you know, the underlying layer. So we have been talking about on this show, you know, over the last, what, year or so about the Supercloud, hey, defining that, you know, API layer spanning across, you know, multiple clouds. I think that will be happening. However, for a lot of the things, that will be more hidden, right? A lot of that will be automated by the bots. You know, we were just talking about it right before the show. One of the profound statement I heard from Adrian Cockcroft about 10 years ago was, "Hey Howie, you know, at Netflix, right? You know, IT is just one API call away." That's a profound statement I heard about a decade ago. I think next decade, right? You know, the IT is just one English language away, right? So when it's one English language away, it's no longer as important, API this, API that. You still need API just like hardware, right? You still need all of those things. That's going to be more hidden. The high level thing will be more, you know, English language or the language, right? Any language for that matter. >> Dave: And so through language, you'll tap services that live across the Supercloud, is what you're saying? >> Howie: You just tell what you want, what you desire, right? You know, the bots will help you to figure out where the complexity is, right? You know, like you said, a lot of criticism about, "Hey, ChatGPT doesn't do this, doesn't do that." But if you think about how to break things down, right? For instance, right, you know, ChatGPT doesn't have Microsoft stock price today, obviously, right? However, you can ask ChatGPT to write a program for you, retrieve the Microsoft stock price, (laughs) and then just run it, right? >> Dave: Yeah. >> So the thing to think about- >> John: It's only going to get better. It's only going to get better. >> The thing people kind of unfairly criticize ChatGPT is it doesn't do this. But can you not break down humans' task into smaller things and get complex things to be done by the ChatGPT? I think we are there already, you know- >> John: That to me is the real game changer. That's the assembly of atomic elements at the top of the stack, whether the interface is voice or some programmatic gesture based thing, you know, wave your hand or- >> Howie: One of the analogy I used in my blog was, you know, each person, each professional now is a quarterback. And we suddenly have, you know, a lot more linebacks or you know, any backs to work for you, right? For free even, right? You know, and then that's sort of, you should think about it. You are the quarterback of your day-to-day job, right? Your job is not to do everything manually yourself. >> Dave: You call the play- >> Yes. >> Dave: And they execute. Do your job. >> Yes, exactly. >> Yeah, all the players are there. All the elves are in the North Pole making the toys, Dave, as we say. But this is the thing, I want to get your point. This change is going to require a new kind of infrastructure software relationship, a new kind of operating runtime, a new kind of assembler, a new kind of loader link things. This very operating systems kind of concepts. >> Data intensive, right? How to process the data, how to, you know, process so gigantic data in parallel, right? That's actually a tough job, right? So if you think about ChatGPT, why OpenAI is ahead of the game, right? You know, Google may not want to acknowledge it, right? It's not necessarily they do, you know, not have enough data scientist, but the software engineering pieces, you know, behind it, right? To train the model, to actually do all those things in parallel, to do all those things in a cost effective way. So I think, you know, a lot of those still- >> Let me ask you a question. Let me ask you a question because we've had this conversation privately, but I want to do it while we're on stage here. Where are all the alpha geeks and developers and creators and entrepreneurs going to gravitate to? You know, in every wave, you see it in crypto, all the alphas went into crypto. Now I think with ChatGPT, you're going to start to see, like, "Wow, it's that moment." A lot of people are going to, you know, scrum and do startups. CTOs will invent stuff. There's a lot of invention, a lot of computer science and customer requirements to figure out. That's new. Where are the alpha entrepreneurs going to go to? What do you think they're going to gravitate to? If you could point to the next layer to enable this super environment, super app environment, Supercloud. 'Cause there's a lot to do to enable what you just said. >> Howie: Right. You know, if you think about using internet as the analogy, right? You know, in the early 90s, internet came along, browser came along. You had two kind of companies, right? One is Amazon, the other one is walmart.com. And then there were company, like maybe GE or whatnot, right? Really didn't take advantage of internet that much. I think, you know, for entrepreneurs, suddenly created the Yahoo, Amazon of the ChatGPT native era. That's what we should be all excited about. But for most of the Fortune 500 companies, your job is to surviving sort of the big revolution. So you at least need to do your walmart.com sooner than later, right? (laughs) So not be like GE, right? You know, hand waving, hey, I do a lot of the internet, but you know, when you look back last 20, 30 years, what did they do much with leveraging the- >> So you think they're going to jump in, they're going to build service companies or SaaS tech companies or Supercloud companies? >> Howie: Okay, so there are two type of opportunities from that perspective. One is, you know, the OpenAI ish kind of the companies, I think the OpenAI, the game is still open, right? You know, it's really Close AI today. (laughs) >> John: There's room for competition, you mean? >> There's room for competition, right. You know, you can still spend you know, 50, $100 million to build something interesting. You know, there are company like Cohere and so on and so on. There are a bunch of companies, I think there is that. And then there are companies who's going to leverage those sort of the new AI primitives. I think, you know, we have been talking about AI forever, but finally, finally, it's no longer just good, but also super useful. I think, you know, the time is now. >> John: And if you have the cloud behind you, what do you make the Amazon do differently? 'Cause Amazon Web Services is only going to grow with this. It's not going to get smaller. There's more horsepower to handle, there's more needs. >> Howie: Well, Microsoft already showed what's the future, right? You know, you know, yes, there is a kind of the container, you know, the serverless that will continue to grow. But the future is really not about- >> John: Microsoft's shown the future? >> Well, showing that, you know, working with OpenAI, right? >> Oh okay. >> They already said that, you know, we are going to have ChatGPT service. >> $10 billion, I think they're putting it. >> $10 billion putting, and also open up the Open API services, right? You know, I actually made a prediction that Microsoft future hinges on OpenAI. I think, you know- >> John: They believe that $10 billion bet. >> Dave: Yeah. $10 billion bet. So I want to ask you a question. It's somewhat academic, but it's relevant. For a number of years, it looked like having first mover advantage wasn't an advantage. PCs, spreadsheets, the browser, right? Social media, Friendster, right? Mobile. Apple wasn't first to mobile. But that's somewhat changed. The cloud, AWS was first. You could debate whether or not, but AWS okay, they have first mover advantage. Crypto, Bitcoin, first mover advantage. Do you think OpenAI will have first mover advantage? >> It certainly has its advantage today. I think it's year two. I mean, I think the game is still out there, right? You know, we're still in the first inning, early inning of the game. So I don't think that the game is over for the rest of the players, whether the big players or the OpenAI kind of the, sort of competitors. So one of the VCs actually asked me the other day, right? "Hey, how much money do I need to spend, invest, to get, you know, another shot to the OpenAI sort of the level?" You know, I did a- (laughs) >> Line up. >> That's classic VC. "How much does it cost me to replicate?" >> I'm pretty sure he asked the question to a bunch of guys, right? >> Good luck with that. (laughs) >> So we kind of did some napkin- >> What'd you come up with? (laughs) >> $100 million is the order of magnitude that I came up with, right? You know, not a billion, not 10 million, right? So 100 million. >> John: Hundreds of millions. >> Yeah, yeah, yeah. 100 million order of magnitude is what I came up with. You know, we can get into details, you know, in other sort of the time, but- >> Dave: That's actually not that much if you think about it. >> Howie: Exactly. So when he heard me articulating why is that, you know, he's thinking, right? You know, he actually, you know, asked me, "Hey, you know, there's this company. Do you happen to know this company? Can I reach out?" You know, those things. So I truly believe it's not a billion or 10 billion issue, it's more like 100. >> John: And also, your other point about referencing the internet revolution as a good comparable. The other thing there is online user population was a big driver of the growth of that. So what's the equivalent here for online user population for AI? Is it more apps, more users? I mean, we're still early on, it's first inning. >> Yeah. We're kind of the, you know- >> What's the key metric for success of this sector? Do you have a read on that? >> I think the, you know, the number of users is a good metrics, but I think it's going to be a lot of people are going to use AI services without even knowing they're using it, right? You know, I think a lot of the applications are being already built on top of OpenAI, and then they are kind of, you know, help people to do marketing, legal documents, you know, so they're already inherently OpenAI kind of the users already. So I think yeah. >> Well, Howie, we've got to wrap, but I really appreciate you coming on. I want to give you a last minute to wrap up here. In your experience, and you've seen many waves of innovation. You've even had your hands in a lot of the big waves past three inflection points. And obviously, machine learning you're doing now, you're deep end. Why is this Supercloud movement, this wave of Supercloud and the discussion of this next inflection point, why is it so important? For the folks watching, why should they be paying attention to this particular moment in time? Could you share your super clip on Supercloud? >> Howie: Right. So this is simple from my point of view. So why do you even have cloud to begin with, right? IT is too complex, too complex to operate or too expensive. So there's a newer model. There is a better model, right? Let someone else operate it, there is elasticity out of it, right? That's great. Until you have multiple vendors, right? Many vendors even, you know, we're talking about kind of how to make multiple vendors look like the same, but frankly speaking, even one vendor has, you know, thousand services. Now it's kind of getting, what Kid was talking about what, cloud chaos, right? It's the evolution. You know, the history repeats itself, right? You know, you have, you know, next great things and then too many great things, and then people need to sort of abstract this out. So it's almost that you must do this. But I think how to abstract this out is something that at this time, AI is going to help a lot, right? You know, like I mentioned, right? A lot of the abstraction, you don't have to think about API anymore. I bet 10 years from now, you know, IT is one language away, not API away. So think about that world, right? So Supercloud in, in my opinion, sure, you kind of abstract things out. You have, you know, consistent layers. But who's going to do that? Is that like we all agreed upon the model, agreed upon those APIs? Not necessary. There are certain, you know, truth in that, but there are other truths, let bots take care of, right? Whether you know, I want some X happens, whether it's going to be done by Azure, by AWS, by GCP, bots will figure out at a given time with certain contacts with your security requirement, posture requirement. I'll think that out. >> John: That's awesome. And you know, Dave, you and I have been talking about this. We think scale is the new ratification. If you have first mover advantage, I'll see the benefit, but scale is a huge thing. OpenAI, AWS. >> Howie: Yeah. Every day, we are using OpenAI. Today, we are labeling data for them. So you know, that's a little bit of the- (laughs) >> John: Yeah. >> First mover advantage that other people don't have, right? So it's kind of scary. So I'm very sure that Google is a little bit- (laughs) >> When we do our super AI event, you're definitely going to be keynoting. (laughs) >> Howie: I think, you know, we're talking about Supercloud, you know, before long, we are going to talk about super intelligent cloud. (laughs) >> I'm super excited, Howie, about this. Thanks for coming on. Great to see you, Howie Xu. Always a great analyst for us contributing to the community. VP of Machine Learning and Zscaler, industry legend and friend of theCUBE. Thanks for coming on and sharing really, really great advice and insight into what this next wave means. This Supercloud is the next wave. "If you're not on it, you're driftwood," says Pat Gelsinger. So you're going to see a lot more discussion. We'll be back more here live in Palo Alto after this short break. >> Thank you. (upbeat music)

(sparkly music) >> Welcome to the Cube Special Program series "Women of the Cloud", brought to you by AWS. I'm your host, Lisa Martin. I'm very pleased to welcome Veronica McCarthy to the program, Senior Sales Manager ISB for Amazon Web Services. Veronica, great to have you on the program. Thanks for joining me today. >> Thanks for having me. >> Tell me a little bit about your current role. A little bit about yourself. >> Absolutely. Yeah, so I've been at Amazon just about four years now. I am really passionate about technology. I've been in the tech industry for about 20 plus years. Right now I'm a sales leader, so I lead a team of folks that help software companies build technology in the cloud or move technology to the cloud and help them scale and innovate in the cloud. >> Awesome, I love that. Talk a little bit about for, for those looking to grow their careers in tech, what are some of the tactical recommendations that you have that you think are really, really pertinent for others that are looking to climb that ladder? >> Yeah, it's so important to have that passion for technology 'cause that's what we do every day. It excites me to jump out of bed and learn what's new, what's coming, what we're building together and how early we are in cloud computing and in technology as a whole. So really get curious and even, you know feel free to get, get hands on. I remember early as a kid just building computers with my dad in his room. So get hands on. Today there's so many things available on the internet for free tiers. You can just play with software to get building websites, games, whatever interests you. And oh by the way, watch the Cube 'cause you're going to learn a lot and you're going to get immersed in technology, which is so important when you're learning to grow a career here because it comes across when you're interviewing, when you're talking with others, when you're networking, that you're really interested in the topic and you're really here to, to grow and and help build tech to be what it can be in the future. >> These are all great recommendations for really building that authenticity. I love your advice of really from an immersion perspective. You're right, there's so many opportunities for people of all ages to start playing around with tech and, and, but that your point of opening up your mind and being curious and embracing the different learning paths is also that curiosity. I always think creativity as well are just really important recommendations for others that are looking to grow their career in tech. >> I want to understand some of, based on some of, of those tactical recommendations. Talk to us about a success story that you've had where you've solved problems for customers relating to cloud computing based on some of your recommendations. >> Totally, just picking up on the curiosity theme that we were talking about, one of the things that I did when I was earlier in my career and I was looking after a customer, is I got curious about their business. How did they interact with their customers? And I worked backwards from that experience 'cause they were selling to consumers and I said what if they could do all these other things that could open up the consumer's eyes? So I came up with a zany idea of what if they did a partnership with Amazon and we flew their goods directly to the end consumer by a drone, you know, just crazy stuff. And I wrote something called a PRFAQ which at Amazon we use very often. It's a press release, frequently asked questions. This PRFAQ was, what could you do in the future with tech? What could, you know things what could we unlock with tech in your business? The C-suite of this company said, "You know what, that's really interesting. We're not going to do that crazy drone thing. But we like the thinking, we like the learning we like thinking about the future. How does cloud help us unlock that future?" So the long story short, they had a monolith OnPrem getting their, getting their technology from a OnPrem monolith to microservices in the cloud unlocks and opens up APIs for them to partner with other organizations to grow their customer base and in turn grow their revenue. This company in particular, pandemic hit, market change. They had to pivot or else they were going to go out of business. And because we had moved their technology from an OnPrem monolith to the cloud they were able to make that pivot and they survived the pandemic and are thriving. So it's a real life example of a success story of just getting curious, understanding the customer's business, coming back from that and then aligning for the future and getting a customer to, to get curious with you and build for the future, which worked out. And who could have predicted the pandemic, but it worked >> Right. But getting the the customer to be curious with you kind of leads me into talking about, you know, and, and the customer wanting to embrace and, and embrace cloud computing is really a transformative business model. Also takes cultural impact. Sounds like what you've been able to achieve with this particular success story. The customer had the appetite from a cultural transformation perspective but that's a hard thing to accomplish. Talk a little bit about that maybe from that customer's perspective and how they really were able to transform into a culture that embraces cloud computing. >> Absolutely. You're spot on . With all of these transformations, it's people process technology. Technology's the easy part, right? The cloud's there, we can, the architecture's there, we can build software. It's the people and the process that's hard. So as part of that transformation and part of that engagement, they actually hired me. So I left Amazon and I went and became the VP of technology for this company and I led 650 engineers globally through this transformation from an OnPrem model with microservices in the cloud. So they put faith in me because they knew this was the outcome we needed to get to but they needed the people in the process to change. So bringing the, the engineers on that journey of I know you've been building this way for a really long time and in this place, we're going to bring you into the future and we're all going to do it together. So it's a learning journey because we're all going to learn how to build microservices in the cloud and we're going to do it together and then it opens up their future as well as they continue to grow as engineers. So it's not easy to do, but it takes time. But we were able to do it in that case. >> But you bring up a great point, it's a learning journey. Yeah. And for organizations to have that appetite and that understanding and appreciation, that is as critical as the technology. You talk about, you know, people across technology. The technology is easy, it's really changing the frames of mind at the speed at which they need to change for organizations to be competitive so they can leverage cloud to really help unlock the competitive advantage as as that success story customer that you mentioned. >> Absolutely. Absolutely. And building on that innovation, right which innovation is just a, a flywheel of learning. So absolutely. >> It is. Let's shift gears a little bit, but speaking of people and processes, you know, what are some of the challenges that you see from a diversity perspective whether it's thought diversity in tech today? >> Yeah, great question. Tech is an opportunity for a level playing ground because tech is a platform with which you can build things. The important piece of building tech though is we need to make sure that many diversities are represented in the room. So when we're making tech decisions of how we're going to build, what our consumers are going to, how they're going to interact with our technology. Not everyone is one individual person. It's not a monolith out there, you know consuming our technology. So let's make sure we have that diversity in the decision making and building the tech as well as in the user use case and, and working backwards from our end users of our technology. I think one of the most, one of the easiest ways to start to approach, approach that diversity of thought and getting that diversity within your teams is looking at a gender diversity ratio. And, and we've seen historically, whilst we've seen gains in gender diversity and technology over the last few years, it's still not where it needs to be. There's a stat that I read recently in a McKinsey study that only one in four C-suite leaders are women today. And of all of all the entry level jobs from entry level to manager of all, like let's say you take a hundred men only 87 of those are women that are concurrently being promoted. Only 82 are women of color. So it's an opportunity for us to really level the playing field and think about how do we intentionally put people in the room when tech decisions are being made that can make change and build tech for who we, we know is out there to consume and, and are be a part of our tech community. >> Intention you mentioned. That is so critical for organizations really need to be looking at diversity, DEI from a, from an an intentional perspective. It can't just be ad hoc here and there. They really have to have a strategy behind it. And when I see companies, and there are a few that I've worked with that really caught my eye that have done a phenomenal job of that thought diversity, gender diversity, cultural diversity within their leadership even the people that they put on stage to talk to their events, they stand out incredibly well. We also know that there's, you probably have numbers on this, that organizations with women in the C-suite are far more profitable than organizations that don't have that. So the data, we want to talk nerdy tech, the data is there. It's demonstrating what the potentials are the capabilities, the, the opportunities. Yet we're still so far behind and we have so much road to cover. We know the direction we need to go in, we just got to be able to get the teams behind that to get there. >> Absolutely. And data's key. I read a study recently that said if you don't have at least 30% diversity in the room when you're making decisions, you are statistically not going to make the right decision, which is incredible. So the powers and the data. We know better decisions are made. Companies do better when there's diversity in the room of all types. >> Absolutely. And can you imagine the sky's the limit, if organizations are actually able to just start making headway on that percentage number and shifting it towards that diversity. What incredible opportunities and technologies and services and solutions that can be developed and delivered to meet the demanding consumers needs. So much potential there. It's, it's a, it's kind of like a crystal ball. If only we had one, we could actually see what we could actually be. >> Yeah, you're absolutely right. And I think thinking about some of the older reasons why maybe women didn't stay in the workforce longer or maybe didn't take a a career in tech, a lot of those were minimized during the pandemic. So we think about the work from home concept, right? Like that's so normal now it's, we're no longer grinding you know, I have to leave early for daycare pickup or whatever the challenges or the perceived challenges there were to women progressing in their careers. A lot of that can be managed now. So there was some good things that have come out of that pandemic time that, you know, it's much more acceptable to be home remote working. I think the balance isn't making sure that we continue our in-person innovation where we can. I find with customers today, bringing executive teams together in a room to have them brainstorm and innovate is still priceless, right? Like we still have to spend that time, we're humans, but as a woman in technology, I love the flexibility that we are now taking and adopting as a norm. And even, you know, some of my male peers that have kids at home, they love being around the kids at home and and it's a, it's a real positive impact I think that we've had amongst a lot of negative impacts by the pandemic as well. >> It is, they're definitely silver linings. That's one of them. I was talking with somebody in, in Italy this morning we were filming and you said, "I don't think my daughters are going to run in here." And I thought, you know what, even if they do that's part of totally the remote workforce, that's part of the hybrid workforce that we're all embracing. But you bring up a great point about the in-person innovation. You know, events are starting to come back, so exciting. There's just certain things about event from an innovation perspective you just can't replicate by video. So getting those executives in a room together. Talk about what you guys are doing there and, and some of the things that you think of over the next few years that will really help drive evolution and innovation of tech. >> Absolutely, yeah. I have a lot of clients that often will say, "Oh well we're we're a remote first company." So it's okay that we do our innovation session online. But then I remind them of when was the last happy hour you had online? Like do you remember the early days of the pandemic? And we all sat on, you know pick your web conferencing platform and we, you know drank wine and but there was only one person that you could hear in that. So when they're, everybody's going around and all the boxes are on the screen, it was difficult to have multiple conversations. If you walk into a happy hour in, in real life people all over the room are having multiple conversations and a lot of different things are happening in the room at the same time. It's the same thing with innovation. If we bring an executive team into the room, guess what? There's going to be a couple sidebar conversations going on as the big room progresses. And that's really healthy and that's a great way to get people that may not be the one, the star of the happy hour that wants to speak the whole time to also get their inputs and their feedback into the innovation process. So that's just an example of why it's so important. One of the things we do here at Amazon is we have so called a digital innovation workshop which is exactly as it sounds, right? Just get in a room with some whiteboards, with some thought leaders and really let's innovate for the future and it's a blank sheet of paper kind of start and out of it we come up with a business plan, a PRFAQ, like a press release I mentioned in my story earlier. That's the seeds of that. So it's really powerful and I'm so excited we're continuing to do those face to face 'cause it's so important. >> It's so important, you know, to have diversity present in the room when decisions are being made, whether it's decisions about technology or not. That thought diversity is, and as the data show that you mentioned, demonstrates how much more successful and profitable organizations can be. I'm going to ask you kind of switching gears again. Last question. If we look kind of down the road from an evolution perspective of of you're in cloud, of your role evolving. What are some of the things that you see down down the pike? >> Yeah, so great question. I am in a field sales organization today, so when the pandemic first hit, I thought, oh boy, that's the end of our career. I think we're not going to be going out and calling on customers face to face anymore. But it's actually been the opposite. I've seen more engagement from our customers. They, they really do want to spend time with us innovating. When we come into those conversations we come in with a curious mindset. So I think from a field sales perspective, it's it's not, you know, going away. And I think it's going to continue to build and it's a great career for women in particular to get into. Super flexible, the privilege of travel which is a nice vacation from home life sometimes. And the, the benefit of working from home as well. So a good balance there. So I think from a, my role specifically it's going to continue to evolve and continue to be a growth area. >> From previous roles I've had where I've worked in technology and, and software development, I think are we're still such at early stages in cloud computing and cloud technology that there is so much technology that we're continuing to build from an engineering standpoint. And I think back to my, you know, 20 year old self if I was in those shoes today and I would absolutely be doing a career in engineering. I think it's such an exciting space and as a person of, of of a, as a female I want to be at the forefront of the engineering team. So I encourage anyone if they're, you know of a diverse background, like you are the people that I want in engineering in the future because that's how you're going to build the future is build the tech, which is really cool. >> So absolutely. It's, it's very cool. I do have one more question for you. What's of your lens, what's next in cloud? What are some of the things that you think are coming down the horizon? >> Yeah, so great question. So I, I actually have a son who's special needs and I think about some of the accommodations that we have to make for him today. And I think about the tech that's coming in terms of personal tech on helping him communicate or helping him read or helping him write. And I'm excited for his future where I think a diagnosis like his, if I'd gotten it many years ago, I would be very fearful about his future. But I know that tech is going to support people like him. So I'm excited for what it's going to do for humanity. I'm excited for what it's going to help us unlock for people that may have been hindered in previous lives. My, my mom grew up with a disability and she had to keep her career relatively low level because she couldn't overcome that disability without tech. And now that she has tech, you know it would've changed the game for her. So I'm excited for my son and his future. That's what inspires me and, and I'm excited about. >> I love that. Well, with a mom like you, he's sure to succeed and fly flying colors. Veronica, it's been such a pleasure having you on the Cube. >> Thank you. >> Exciting special series of women in the cloud. We so appreciate your insights and your time. You'll have to come back. >> Thank you so much. I appreciate it. >> All right, Veronica McCarthy. I'm Lisa Martin. You're watching The Cube's special program series Women of the Cloud, brought to you by AWS. Thanks for watching. (sparkly music)

>> Hey everyone. Welcome back to theCUBE's coverage day two of CloudNative Security CON 23. Lisa Martin here in studio in Palo Alto with John Furrier. John, we've had some great conversations. I've had a global event. This was a global event. We had Germany on yesterday. We had the Boston Studio. We had folks on the ground in Seattle. Lot of great conversations, a lot of great momentum at this event. What is your number one takeaway with this inaugural event? >> Well, first of all, our coverage with our CUBE alumni experts coming in remotely this remote event for us, I think this event as an inaugural event stood out because one, it was done very carefully and methodically from the CNCF. I think they didn't want to overplay their hand relative to breaking out from CUBE CON So Kubernetes success and CloudNative development has been such a success and that event and ecosystem is booming, right? So that's the big story is they have the breakout event and the question was, was it a good call? Was it successful? Was it going to, would the dog hunt as they say, in this case, I think the big takeaway is that it was successful by all measures. One, people enthusiastic and confident that this has the ability to stand on its own and still contribute without taking away from the benefits and growth of Kubernetes CUBE CON and CloudNative console. So that was the key. Hallway conversations, the sessions all curated and developed properly to be different and focused for that reason. So I think the big takeaway is that the CNCF did a good job on how they rolled this out. Again, it was very intimate event small reminds me of first CUBE CON in Seattle, kind of let's test it out. Let's see how it goes. Again, clearly it was people successful and they understood why they're doing it. And as we commented out in our earlier segments this is not something new. Amazon Web Services has re:Invent and re:Inforce So a lot of parallels there. I see there. So I think good call. CNCF did the right thing. I think this has legs. And then as Dave pointed out, Dave Vellante, on our last keynote analysis was the business model of the hackers is better than the business model of the industry. They're making more money, it costs less so, you know, they're playing offense and the industry playing defense. That has to change. And as Dave pointed out we have to make the cost of hacking and breaches and cybersecurity higher so that the business model crashes. And I think that's the strategic imperative. So I think the combination of the realities of the market globally and open source has to go faster. It's good to kind of decouple and be highly cohesive in the focus. So to me that's the big takeaway. And then the other one is, is that there's a lot more security problems still unresolved. The emphasis on developers productivity is at risk here, if not solved. You saw supply chain software, again, front and center and then down in the weeds outside of Kubernetes, things like BIND and DNS were brought up. You're seeing the Linux kernel. Really important things got to be paid attention to. So I think very good call, very good focus. >> I would love if for us to be able to, as the months go on talk to some of the practitioners that actually got to attend. There were 72 sessions, that's a lot of content for a small event. Obviously to your point, very well curated. We did hear from some folks yesterday who were just excited to get the community back together in person. To your point, having this dedicated focus on CloudNativesecurity is incredibly important. You talked about, you know, the offense defense, the fact that right now the industry needs to be able to pivot from being on defense to being on offense. This is a challenging thing because it is so lucrative for hackers. But this seems to be from what we've heard in the last couple days, the right community with the right focus to be able to make that pivot. >> Yeah, and I think if you look at the success of Kubernetes, 'cause again we were there at theCUBE first one CUBE CON, the end user stories really drove end user participation. Drove the birth of Kubernetes. Left some of these CloudNative early adopters early pioneers that were using cloud hyperscale really set the table for CloudNative CON. I think you're seeing that here with this CloudNative SecurityCON where I think we're see a lot more end user stories because of the security, the hairs on fire as we heard from Madrona Ventures, you know, as they as an investor you have a lot of use cases out there where customers are leaning in with getting the rolling up their sleeves, working with open source. This has to be the driver. So I'm expecting to see the next level of SecurityCON to be end user focused. Much more than vendor focused. Where CUBECON was very end user focused and then attracted all the vendors in that grew the industry. I expect the similar pattern here where end user action will be very high at the beginning and that will essentially be the rising tide for the vendors to be then participating. So I expect almost a similar trajectory to CUBECON. >> That's a good path that it needs to all be about all the end users. One of the things I'm curious if what you heard was what are some of the key factors that are going to move CloudNative Security forward? What did you hear the last two days? >> I heard that there's a lot of security problems and no one wants to kind of brag about this but there's a lot of under the hood stuff that needs to get taken care of. So if automation scales, and we heard that from one of the startups we've just interviewed. If automation and scale continues to happen and with the business model of the hackers still booming, security has to be refactored quickly and there's going to be an opportunity structurally to use the cloud for that. So I think it's a good opportunity now to get dedicated focus on fixing things like the DNS stuff old school under the hood, plumbing, networking protocols. You're going to start to see this super cloud-like environment emerge where data's involved, everything's happening and so security has to be re imagined. And I think there's a do over opportunity for the security industry with CloudNative driving that. And I think this is the big thing that I see as an opportunity to, from a story standpoint from a coverage standpoint is that it's a do-over for security. >> One of the things that we heard yesterday is that there's a lot of it, it's a pretty high percentage of organizations that either don't have a SOCK or have a very primitive SOCK. Which kind of surprised me that at this day and age the risks are there. We talked about that today's focus and the keynote was a lot about the software supply chain and what's going on there. What did you hear in terms of the appetite for organizations through the voice of the practitioner to say, you know what guys, we got to get going because there's going to be the hackers are they're here. >> I didn't hear much about that in the coverage 'cause we weren't in the hallways. But from reading the tea leaves and talking to the folks on the ground, I think there's an implied like there's an unlimited money from customers. So it's a very robust from the data infrastructure stack building we cover with the angel investor Kane you're seeing data infrastructure's going to be part of the solution here 'cause data and security go hand in hand. So everyone's got basically checkbook wide open everyone wants to have the answer. And we commented that the co-founder of Palo Alto you had on our coverage yesterday was saying that you know, there's no real platform, there's a lot of tools out there. People will buy anything. So there's still a huge appetite and spend in security but the answer's not going to more tool sprawling. It's going to more platform auto, something that enables automation, fix some of the underlying mechanisms involved and fix it fast. So to me I think it's going to be a robust monetary opportunity because of the demand on the business side. So I don't see that changing at all and I think it's going to accelerate. >> It's a great point in terms of the demand for the business side because as we know as we said yesterday, the next Log4j is out there. It's not a matter of if this happens again it's when, it's the extent, it's how frequent we know that. So organizations all the way up to the board have to be concerned about brand reputation. Nobody wants to be the next big headline in terms of breaches and customer data being given to hackers and hackers making all this money on that. That has to go all the way up to the board and there needs to be alignment between the board and the executives at the organization in terms of how they're going to deal with security, and now. This is not a conversation that can wait. Yeah, I mean I think the five C's we talked about yesterday the culture of companies, the cloud is an enabler, you've got clusters of servers and capabilities, Kubernetes clusters, you've got code and you've got all kinds of, you know, things going on there. Each one has elements that are at risk for hacking, right? So that to me is something that's super important. I think that's why the focus on security's different and important, but it's not going to fork the main event. So that's why I think the spin out was, spinout, or the new event is a good call by the CNCF. >> One of the things today that struck me they're talking a lot about software supply chain and that's been in the headlines for quite a while now. And a stat that was shared this morning during the keynote just blew my brains that there was a 742% increase in the software supply chain attacks occurring over the last three years. It's during Covid times, that is a massive increase. The threat landscape is just growing so amorphously but organizations need to help dial that down because their success and the health of the individuals and the end users is at risk. Well, Covid is an environment where everyone's kind of working at home. So there was some disruption to infrastructure. Also, when you have change like that, there's opportunities for hackers, they'll arbitrage that big time. But I think general the landscape is changing. There's no perimeter anymore. It's CloudNative, this is where it is and people who are moving from old IT to CloudNative, they're at risk. That's why there's tons of ransomware. That's why there's tons of risk. There's just hygiene, from hygiene to architecture and like Nick said from Palo Alto, the co-founder, there's not a lot of architecture in security. So yeah, people have bulked up their security teams but you're going to start to see much more holistic thinking around redoing security. I think that's the opportunity to propel CloudNative, and I think you'll see a lot more coming out of this. >> Did you hear any specific information on some of the CloudNative projects going on that really excite you in terms of these are the right people going after the right challenges to solve in the right direction? >> Well I saw the sessions and what jumped out to me at the sessions was it's a lot of extensions of what we heard at CUBECON and I think what they want to do is take out the big items and break 'em out in security. Kubescape was one we just covered. They want to get more sandbox type stuff into the security side that's very security focused but also plays well with CUBECON. So we'll hear more about how this plays out when we're in Amsterdam coming up in April for CUBECON to hear how that ecosystem, because I think it'll be kind of a relief to kind of decouple security 'cause that gives more focus to the stakeholders in CUBECON. There's a lot of issues going on there and you know service meshes and whatnot. So it's a lot of good stuff happening. >> A lot of good stuff happening. One of the things that'll be great about CUBECON is that we always get the voice of the customer. We get vendors coming on with the voice of the customer talking about and you know in that case how they're using Kubernetes to drive the business forward. But it'll be great to be able to pull in some of the security conversations that spin out of CloudNative Security CON to understand how those end users are embracing the technology. You brought up I think Nir Zuk from Palo Alto Networks, one of the themes there when Dave and I did their Ignite event in December was, of 22, was really consolidation. There are so many tools out there that organizations have to wrap their heads around and they need to be able to have the right enablement content which this event probably delivered to figure out how do we consolidate security tools effectively, efficiently in a way that helps dial down our risk profile because the risks just seem to keep growing. >> Yeah, and I love the technical nature of all that and I think this is going to be the continued focus. Chris Aniszczyk who's the CTO listed like E and BPF we covered with Liz Rice is one of the most three important points of the conference and it's just, it's very nerdy and that's what's needed. I mean it's technical. And again, there's no real standards bodies anymore. The old days developers I think are super important to be the arbiters here. And again, what I love about the CNCF is that they're developer focused and we heard developer first even in security. So you know, this is a sea change and I think, you know, developers' choice will be the standards bodies. >> Lisa: Yeah, yeah. >> They decide the future. >> Yeah. >> And I think having the sandboxing and bringing this out will hopefully accelerate more developer choice and self-service. >> You've been talking about kind of putting the developers in the driver's seat as really being the key decision makers for a while. Did you hear information over the last couple of days that validates that? >> Yeah, absolutely. It's clearly the fact that they did this was one. The other one is, is that engineering teams and dev teams and script teams, they're blending together. It's not just separate silos and the ones that are changing their team dynamics, again, back to the culture are winning. And I think this has to happen. Security has to be embedded everywhere in making it frictionless and to provide kind of the guardrail so developers don't slow down. And I think where security has become a drag or an anchor or a blocker has been just configuration of how the organization's handling it. So I think when people recognize that the developers are in charge and they're should be driving the application development you got to make sure that's secure. And so that's always going to be friction and I think whoever does it, whoever unlocks that for the developer to go faster will win. >> Right. Oh, that's what I'm sure magic to a developer's ear is the ability to go faster and be able to focus on co-development in a secure fashion. What are some of the things that you're excited about for CUBECON. Here we are in February, 2023 and CUBECON is just around the corner in April. What are some of the things that you're excited about based on the groundswell momentum that this first inaugural CloudNative Security CON is generating from a community, a culture perspective? >> I think this year's going to be very interesting 'cause we have an economic challenge globally. There's all kinds of geopolitical things happening. I think there's going to be very entrepreneurial activity this year more than ever. I think you're going to see a lot more innovative projects ideas hitting the table. I think it's going to be a lot more entrepreneurial just because the cycle we're in. And also I think the acceleration of mainstream deployments of out of the CNCF's main event CUBECON will happen. You'll see a lot more successes, scale, more clarity on where the security holes are or aren't. Where the benefits are. I think containers and microservices are continuing to surge. I think the Cloud scale hyperscale as Amazon, Azure, Google will be more aggressive. I think AI will be a big theme this year. I think you can see how data is going to infect some of the innovation thinking. I'm really excited about the data infrastructure because it powers a lot of things in the Cloud. So I think the Amazon Web Services, Azure next level gen clouds will impact what happens in the CloudNative foundation. >> Did you have any conversations yesterday or today with respect to AI and security? Was that a focus of anybody's? Talk to me about that. >> Well, I didn't hear any sessions on AI but we saw some demos on stage. But they're teasing out that this is an augmentation to their mission, right? So I think a lot of people are looking at AI as, again, like I always said there's the naysayers who think it's kind of a gimmick or nothing to see here, and then some are just going to blown away. I think the people who are alpha geeks and the industry connect the dots and understand that AI is going to be an accelerant to a lot of heavy lifting that was either manual, you know, hard to do things that was boring or muck as they say. I think that's going to be where you'll see the AI stories where it's going to accelerate either ways to make security better or make developers more confident and productive. >> Or both. >> Yeah. So definitely AI will be part of it. Yeah, definitely. One of the things too that I'm wondering if, you know, we talk about CloudNative and the goal of it, the importance of it. Do you think that this event, in terms of what we were able to see, obviously being remote the event going on in Seattle, us being here in Palo Alto and Boston and guests on from Seattle and Germany and all over, did you hear the really the validation for why CloudNative Security why CloudNative is important for organizations whether it's a bank or a hospital or a retailer? Is that validation clear and present? >> Yeah, absolutely. I think it was implied. I don't think there was like anyone's trying to debate that. I think this conference was more of it's assumed and they were really trying to push the ability to make security less defensive, more offensive and more accelerated into the solving the problems with the businesses that are out there. So clearly the CloudNative community understands where the security challenges are and where they're emerging. So having a dedicated event will help address that. And they've got great co-chairs too that put it together. So I think that's very positive. >> Yeah. Do you think, is it possible, I mean, like you said several times today so eloquently the industry's on the defense when it comes to security and the hackers are on the offense. Is it really possible to make that switch or obviously get some balances. As technology advances and industry gets to take advantage of that, so do the hackers, is that balance achievable? >> Absolutely. I mean, I think totally achievable. The question's going to be what's the environment going to be like? And I remember as context to understanding whether it's viable or not, is to look at, just go back 13 years ago, I remember in 2010 Amazon was viewed as an unsecure environment. Everyone's saying, "Oh, the cloud is not secure." And I remember interviewing Steve Schmidt at AWS and we discussed specifically how Amazon Cloud was being leveraged by hackers. They made it more complex for the hackers. And he said, "This is just the beginning." It's kind of like barbed wire on a fence. It's yeah, you're not going to climb it so people can get over it. And so since then what's happened is the Cloud has become more secure than on premises for a lot of either you know, personnel reasons, culture reasons, not updating, you know, from patches to just being insecure to be more insecure. So that to me means that the flip the script can be flipped. >> Yeah. And I think with CloudNative they can build in automation and code to solve some of these problems and make it more complex for the hacker. >> Lisa: Yes. >> And increase the cost. >> Yeah, exactly. Make it more complex. Increase the cost. That'll be in interesting journey to follow. So John, here we are early February, 2023 theCUBE starting out strong as always. What year are we in, 12? Year 12? >> 13th year >> 13! What's next for theCUBE? What's coming up that excites you? >> Well, we're going to do a lot more events. We got the theCUBE in studio that I call theCUBE Center as kind of internal code word, but like, this is more about getting the word out that we can cover events remotely as events are starting to change with hybrid, digital is going to be a big part of that. So I think you're going to see a lot more CUBE on location. We're going to do, still do theCUBE and have theCUBE cover events from the studio to get deeper perspective because we can then bring people in remote through our our studio team. We can bring our CUBE alumni in. We have a corpus of content and experts to bring to table. So I think the coverage will be increased. The expertise and data will be flowing through theCUBE and so Cube Center, CUBE CUBE Studio. >> Lisa: Love it. >> Will be a integral part of our coverage. >> I love that. And we have such great conversations with guests in person, but also virtually, digitally as well. We still get the voices of the practitioners and the customers and the vendors and the partner ecosystem really kind of lauded loud and clear through theCUBE megaphone as I would say. >> And of course getting the clips out there, getting the highlights. >> Yeah. >> Getting more stories. No stories too small for theCUBE. We can make it easy to get the best content. >> The best content. John, it's been fun covering CloudNative security CON with you with you. And Dave and our guests, thank you so much for the opportunity and looking forward to the next event. >> John: All right. We'll see you at Amsterdam. >> Yeah, I'll be there. We want to thank you so much for watching TheCUBES's two day coverage of CloudNative Security CON 23. We're live in Palo Alto. You are live wherever you are and we appreciate your time and your view of this event. For John Furrier, Dave Vellante, I'm Lisa Martin. Thanks for watching guys. We'll see you at the next show.

(upbeat music) >> Hello everyone, welcome back to theCUBE's coverage of Cloud Native SecurityCon North America 2023. Obviously, CUBE's coverage with our CUBE Center Report. We're not there on the ground, but we have folks and our CUBE Alumni there. We have entrepreneurs there. Of course, we want to be there in person, but we're remote. We've got Ben Hirschberg, CTO and Co-Founder of Armo, a cloud native security startup, well positioned in this industry. He's there in Seattle. Ben, thank you for coming on and sharing what's going on with theCUBE. >> Yeah, it's great to be here, John. >> So we had written on you guys up on SiliconANGLE. Congratulations on your momentum and traction. But let's first get into what's going on there on the ground? What are some of the key trends? What's the most important story being told there? What is the vibe? What's the most important story right now? >> So I think, I would like to start here with the I think the most important thing was that I think the event is very successful. Usually, the Cloud Native Security Day usually was part of KubeCon in the previous years and now it became its own conference of its own and really kudos to all the organizers who brought this up in, actually in a short time. And it wasn't really clear how many people will turn up, but at the end, we see a really nice turn up and really great talks and keynotes around here. I think that one of the biggest trends, which haven't started like in this conference, but already we're talking for a while is supply chain. Supply chain is security. I think it's, right now, the biggest trend in the talks, in the keynotes. And I think that we start to see companies, big companies, who are adopting themselves into this direction. There is a clear industry need. There is a clear problem and I think that the cloud native security teams are coming up with tooling around it. I think for right now we see more tools than adoption, but the adoption is always following the tooling. And I think it already proves itself. So we have just a very interesting talk this morning about the OpenSSL vulnerability, which was I think around Halloween, which came out and everyone thought that it's going to be a critical issue for the whole cloud native and internet infrastructure and at the end it turned out to be a lesser problem, but the reason why I think it was understood that to be a lesser problem real soon was that because people started to use (indistinct) store software composition information in the environment so security teams could look into, look up in their systems okay, what, where they're using OpenSSL, which version they are using. It became really soon real clear that this version is not adopted by a wide array of software out there so the tech surface is relatively small and I think it already proved itself that the direction if everyone is talking about. >> Yeah, we agree, we're very bullish on this move from the Cloud Native Foundation CNCF that do the security conference. Amazon Web Services has re:Invent. That's their big show, but they also have re:Inforce, the security show, so clearly they work together. I like the decoupling, very cohesive. But you guys have Kubescape of Kubernetes security. Talk about the conversations that are there and that you're hearing around why there's different event what's different around KubeCon and CloudNativeCon than this Cloud Native SecurityCon. It's not called KubeSucSecCon, it's called Cloud Native SecurityCon. What's the difference? Are people confused? Is it clear? What's the difference between the two shows? What are you hearing? >> So I think that, you know, there is a good question. Okay, where is Cloud Native Computing Foundation came from? Obviously everyone knows that it was somewhat coupled with the adoption of Kubernetes. It was a clear understanding in the industry that there are different efforts where the industry needs to come together without looking be very vendor-specific and try to sort out a lot of issues in order to enable adoption and bring great value and I think that the main difference here between KubeCon and the Cloud Native Security Conference is really the focus, and not just on Kubernetes, but the whole ecosystem behind that. The way we are delivering software, the way we are monitoring software, and all where Kubernetes is only just, you know, maybe the biggest clog in the system, but, you know, just one of the others and it gives great overview of what you have in the whole ecosystem. >> Yeah, I think it's a good call. I would add that what I'm hearing too is that security is so critical to the business model of every company. It's so mainstream. The hackers have a great business model. They make money, their costs are lower than the revenue. So the business of hacking in breaches, ransomware all over the place is so successful that they're playing offense, everyone's playing defense, so it's about time we can get focus to really be faster and more nimble and agile on solving some of these security challenges in open source. So I think that to me is a great focus and so I give total props to the CNC. I call it the event operating system. You got the security group over here decoupled from the main kernel, but they work together. Good call and so this brings back up to some of the things that are going on so I have to ask you, as your startup as a CTO, you guys have the Kubescape platform, how do you guys fit into the landscape and what's different from your tools for Kubernetes environments versus what's out there? >> So I think that our journey is really interesting in the solution space because I think that our mode really tries to understand where security can meet the actual adoption because as you just said, somehow we have to sort out together how security is going to be automated and integrated in its best way. So Kubescape project started as a Kubernetes security posture tool. Just, you know, when people are really early in their adoption of Kubernetes systems, they want to understand whether the installation is is secure, whether the basic configurations are look okay, and giving them instant feedback on that, both in live systems and in the CICD, this is where Kubescape came from. We started as an open source project because we are big believers of open source, of the power of open source security, and I can, you know I think maybe this is my first interview when I can say that Kubescape was accepted to be a CNCF Sandbox project so Armo was actually donating the project to the CNCF, I think, which is a huge milestone and a great way to further the adoption of Kubernetes security and from now on we want to see where the users in Armo and Kubescape project want to see where the users are going, their Kubernetes security journey and help them to automatize, help them to to implement security more fast in the way the developers are using it working. >> Okay, if you don't mind, I want to just get clarification. What's the difference between the Armo platform and Kubescape because you have Kubescape Sandbox project and Armo platform. Could you talk about the differences and interaction? >> Sure, Kubescape is an open source project and Armo platform is actually a managed platform which runs Kubescape in the cloud for you because Kubescape is part, it has several parts. One part is, which is running inside the Kubernetes cluster in the CICD processes of the user, and there is another part which we call the backend where the results are stored and can be analyzed further. So Armo platform gives you managed way to run the backend, but I can tell you that backend is also, will be available within a month or two also for everyone to install on their premises as well, because again, we are an open source company and we are, we want to enable users, so the difference is that Armo platform is a managed platform behind Kubescape. >> How does Kubescape differ from closed proprietary sourced solutions? >> So I can tell you that there are closed proprietary solutions which are very good security solutions, but I think that the main difference, if I had to pick beyond the very specific technicalities is the worldview. The way we see that our user is not the CISO. Our user is not necessarily the security team. From our perspective, the user is the DevOps and the developers who are working on the Kubernetes cluster day to day and we want to enable them to improve their security. So actually our approach is more developer-friendly, if I would need to define it very shortly. >> What does this risk calculation score you guys have in Kubscape? That's come up and we cover that in our story. Can you explain to the folks how that fits in? Is it Kubescape is the platform and what's the benefit, what's the purpose? >> So the risk calculation is actually a score we are giving to clusters in order for the users to understand where they are standing in the general population, how they are faring against a perfect hardened cluster. It is based on the number of different tests we are making. And I don't want to go into, you know, the very specifics of the mathematical functions, but in general it takes into account how many functions are failing, security tests are failing inside your cluster. How many nodes you are having, how many workloads are having, and creating this number which enables you to understand where you are standing in the global, in the world. >> What's the customer value that you guys pitching? What's the pitch for the Armo platform? When you go and talk to a customer, are they like, "We need you." Do they come to you? Is it word of mouth? You guys have a strategy? What's the pitch? What's so appealing to the customers? Why are they enthusiastic about you guys? >> So John, I can tell you, maybe it's not so easy to to say the words, but I nearly 20 years in the industry and though I've been always around cyber and the defense industry and I can tell you that I never had this journey where before where I could say that the the customers are coming to us and not we are pitching to customers. Simply because people want to, this is very easy tool, very very easy to use, very understandable and it very helps the engineers to improve security posture. And they're coming to us and they're saying, "Well, awesome, okay, how we can like use it. Do you have a graphical interface?" And we are pointing them to the Armor platform and they are falling in love and coming to us even more and we can tell you that we have a big number of active users behind the platform itself. >> You know, one of the things that comes up every time at KubeCon and Cloud NativeCon when we're there, and we'll be in Amsterdam, so folks watching, you know, we'll see onsite, developer productivity is like the number one thing everyone talks about and security is so important. It's become by default a blocker or anchor or a drag on productivity. This is big, the things that you're mentioning, easy to use, engineering supporting it, developer adoption, you know we've always said on theCUBE, developers will be the de facto standards bodies by their choices 'cause developers make all the decisions. So if I can go faster and I can have security kind of programmed in, I'm not shifting left, it's just I'm just having security kind of in there. That's the dream state. Is that what you guys are trying to do here? Because that's the nirvana, everyone wants to do that. >> Yeah, I think your definition is like perfect because really we had like this, for a very long time we had this world where we decoupled security teams from developers and even for sometimes from engineering at all and I think for multiple reasons, we are more seeing a big convergence. Security teams are becoming part of the engineering and the engineering becoming part of the security and as you're saying, okay, the day-to-day world of developers are becoming very tangled up in the good way with security, so the think about it that today, one of my developers at Armo is creating a pull request. He's already, code is already scanned by security scanners for to test for different security problems. It's already, you know, before he already gets feedback on his first time where he's sharing his code and if there is an issue, he already can solve it and this is just solving issues much faster, much cheaper, and also you asked me about, you know, the wipe in the conference and we know no one can deny the current economic wipe we have and this also relates to security teams and security teams has to be much more efficient. And one of the things that everyone is talking, okay, we need more automation, we need more, better tooling and I think we are really fitting into this. >> Yeah, and I talked to venture capitalists yesterday and today, an angel investor. Best time for startup is right now and again, open source is driving a lot of value. Ben, it's been great to have you on and sharing with us what's going on on the ground there as well as talking about some of the traction you have. Just final question, how old's the company? How much funding do you have? Where you guys located? Put a plug in for the company. You guys looking to hire? Tell us about the company. Were you guys located? How much capital do you have? >> So, okay, the company's here for three years. We've passed a round last March with Tiger and Hyperwise capitals. We are located, most of the company's located today in Israel in Tel Aviv, but we have like great team also in Ukraine and also great guys are in Europe and right now also Craig Box joined us as an open source VP and he's like right now located in New Zealand, so we are a really global team, which I think it's really helps us to strengthen ourselves. >> Yeah, and I think this is the entrepreneurial equation for the future. It's really great to see that global. We heard that in Priyanka Sharma's keynote. It's a global culture, global community. >> Right. >> And so really, really props you guys. Congratulations on Armo and thanks for coming on theCUBE and sharing insights and expertise and also what's happening on the ground. Appreciate it, Ben, thanks for coming on. >> Thank you, John. >> Okay, cheers. Okay, this is CUB coverage here of the Cloud Native SecurityCon in North America 2023. I'm John Furrier for Lisa Martin, Dave Vellante. We're back with more of wrap up of the event after this short break. (gentle upbeat music)

(rousing music) >> Hello everyone. Welcome back to "theCUBE's" day one coverage of Cloud Native Security Con 23. This is going to be an exciting panel. I've got three great guests. I'm Lisa Martin, you know our esteemed analysts, John Furrier, and Dave Vellante well. And we're excited to welcome to "theCUBE" for the first time, Yves Sandfort, the CEO of Comdivision Group, who's coming to us from Germany. As you know, Cloud Native Security Con is a global event. Everyone welcome Yves, great to have you in particular. Welcome to "theCUBE." >> Great to be here. >> Thank you for inviting me. >> Yves, tell us a little bit, before we dig into really wanting to understand your perspectives on the event and get Dave and John's feedback as well, tell us a little bit about you. >> So yeah, talking about me, or talking about Comdivision real quick. We are in the business for over 27 years already. We started as a SaaS company, then became more like an architecture and, and Cloud Native company over the last few years. But what's interesting is, and I think that's, that's, that's really interesting when we look at our industry. It hasn't really, the requirements haven't really changed over the years. It's still security. We still have to figure out how we deal with security. We still have to figure out how we deal with compliance and everything else. And I think therefore, it's more and more important that we take these items more seriously. Also, based on the fact that when we look at it, how development and other things happen nowadays, it's, it's, everybody says it's like open source. It's great because everybody can look into the code. We, I think the last few years have shown us enough example that that's not necessarily solving all the issues, but it's also code and development has changed rapidly when we look at the Cloud Native approach, where it's far more about gluing the pieces together, versus the development pieces. When I was actually doing software development 25 years ago, and had to basically build my code because I didn't have that much internet access for it. So it has evolved, but even back then we had to deal with security and everything. >> Right. The focus on security is, is incredibly important, and the focus keeps growing as you mentioned. This is, guys, and I want to get your perspectives on this. We're going to start with John. This is the first time Cloud Native Security Con is its own event being extracted from, and amplified from KubeCon. John, I want to understand from your perspective, break down the event, what you see, what you've heard, and Cloud Native Security in general. What does this mean to companies? What does it mean to customers? Is this a reality? >> Well, I think that's the topic we want to discuss, and I think Yves background, you see the VMware certification, I love that. Because what VMware did with virtualization, was abstract that from server virtualization, kind of really changed the game on things, and you start to see Cloud Native kind of go that next level of how companies will be operating their business, not just digital transformation, as digital transformation goes to completion, it's total business transformation where IT is everywhere. And so you're starting to see the trends where, "Okay, that's happening." Now you're starting to see, that's Cloud Native Con, or KubeCon, AWS re:Invent, or whatever show, or whatever way you want to look at it. But in, in the past decade, past five years, security has always been front and center as almost a separate thing, and, in and of itself, but the same thing. So you're starting to see the breakout of security conversations around how to make things work. So a lot of operational conversations around what used to be DevOps makes infrastructure as code, and that was great, that fueled that. Then DevSecOps came. So the Cloud Native next level, is more application development at scale, developers driving the standards with developer first thinking, shifting left, I get all that. But down in the lower ends of the stack, you got real operational issues. DNS we've heard in the keynote, we heard about the Colonel, the Lennox Colonel. Things that need to be managed and taken care of at a security level. These are like, seem like in the weeds, but you're starting to see that happen. And the other thing that I think's real about Cloud Native Security Con that's going to be interesting to watch, is Amazon has pretty much canceled all their re:Invent like shows except for two; Re:Invent, which is their annual conference, and Re:Inforce, which is dedicated to securities. So Cloud Native, Linux, the Linux Foundation has now breaking out Cloud Native Con and KubeCon, and now Cloud Native Security Con. They can't call it KubeCon because it's not Kubernetes, but it's like security focus. I think this is the beginning of starting to see this new developer driving, developers driving the standards, and it has it implications, what used to be called IT ops, and that's like the VMwares of the world. You saw all the stuff that was not at developer focus, but more ops, becoming much more in the application. So I think, I think it's real. The question is where does it go? How fast does it develop? So to me, I think it's a real trend, and it's worthy of a breakout, but it's not yet clear of where the landing zone is for people to start doing it, how they get started, what are the best practices. Machine learning's going to be a big part of this. So to me it's totally cool, but I'm not yet seeing the beachhead. So that's kind of my take. >> Dave, our inventor and host of breaking analysis, what's your take? >> So when you, I think when you zoom out, there's some, there's a big macro change that's been going on. I think when you look back, let's say 10, 12 years ago, the, the need for speed far trumped the, the, the security aspect, the governance, the data privacy. It was like, "Yeah, the risks, they're not that great compared to our opportunity." That has completely changed because the risks are now so much higher. And so what's happening, I think there's a, there's a major effort amongst CIOs and CISOs to try to make security not a blocker because it use to be, it still is. "Okay, I got this great initiative." Eh, give it to the SecOps pros, and let them take it for a while before we can go to market. And so a huge challenge now is to simplify, automate, AI comes in, the whole supply chain security, so the, so the companies can not be facing so much friction. And that is non-trivial. I don't think we're anywhere close there, but I think the goal is by, within the next several years, we're going to be in a position, that security, we heard today, is, wasn't designed in to the initial internet protocols. It was bolted on. And so increasingly, the fundamental architecture of the internet, the Cloud, et cetera, is, is seeing designed in security, and, and that is an imperative, or else business is going to come to a grinding halt. >> Right. It's no longer, the bolt no longer works. Yves, what's your perspective on Cloud Native Security, where it stands today? What's in it for customers, whether we're talking about banks, or hospitals, or retailers, what do you think? >> I think when we, when we look at security in the, in the modern world, is we need to as, as Dave mentioned, we need to rethink how we apply it. Very often, security in the past has been always bolted on in the end. If we continue to do that, it'll become more and more difficult, because as companies evolve, and as companies want to bring products and software to market in a much faster and faster way, it's getting more and more difficult if we bolt on the security process at the end. It's like, developers build something and then someone checks security. That's not going to work any longer. Especially if we also consider now the changes in the industry. We had Stack Overflow over the last 10 years. If I would've had Stack Overflow 15, 20, what, 25 years ago when I was a developer, it would've changed a hell lot. Looking at it now, and looking at it what we had in the last few weeks, it's like where nearly all of my team members say is like finally I don't need any script kiddies anymore because I can't go to (indistinct) who writes the code for me. Which is on one end great, because it enables us to solve certain problems in a much higher pace. But the challenge with that is, if the people who just copy and past that code, don't understand the implications of that code, we have a much higher risk continuously. And what people thought was, is challenging with Stack Overflow. Imagine that something in one of these AI engines, is actually going ballistic, and it creates holes in nearly every one of these applications. And trust me, there will be enough developers who are going to use these tools to develop codes, the same as students in university are going to take this to write their essays and everything else. And so it's really important that every developer team basically has a security person within their team, and not a security at the end. So we build something, we check it, go through QA, and then it goes to security. Security needs to be at the forefront. And I think that's where we see Cloud Native Security Con, where we see AWS. I saw it during re:Invent already where they said is like, we have reinforced next year. I think this becomes more and more of a topic, and I think companies, as much as it is become a norm that you have a firewall and everything else, it needs to become a norm that when you are doing software development, and every development team needs to have a security person on that needs to be trained. >> I love that chat comment Dave, 'cause you and I were talking about this. And I think that is going to be the issue. Do we need security chat for the chat bot? And there's like a, like a recursive model there. The biases are built in. I think, and I think our interview with the Palo Alto Network's co-founder, Dave, when he talked about zero trust as a structured way to start things, but he was referencing that with Cloud, there's a chance to rethink or do a do-over in security. So, I think this is kind of to me, where this is all going. And I think you asked Pat Gelsinger what, year 2013, 2014, can, is security a do over? I think we're in that do over time. >> He said yes. >> He said yes. (laughing) He was right. But yeah, eight years later... But this is, how do you, zero trust gives you some structure, but how do you organize and redo security? Because to me, I think that's what's happening here. >> And John you heard, Zuk at Palo Alto Network said, "Yeah, the, the words security and architecture, they don't go together historically." And so it is a total, total retake. >> Well is that because there's too many tools out there and- >> Yeah. For sure. >> Yeah, well, first of all, a lot of hardware. And then yeah, a lot of tools. You even see IIOT and industry 40, you see IOT security coming up as another stove pipe, and that's not the right approach. And, and so- >> Well let me, let me ask you a question Dave, and Yves, if you don't mind. 'Cause I was just riffing on this yesterday about this. In the ML space, you're seeing the ML models, you're seeing proprietary models versus open source. Is security going to go down this proprietary security methods and open source? Because that's interesting, because the CNCF is run by the the Linux Foundation. So you can almost maybe see a model where there's more proprietary security methods than open source. Or is it, is that a non-issue? >> I would, I would, let me, if I, if I jump in here first, I think the last, especially last five or 10 years have clearly shown the, the whole and, and I invested early on in the, in the end 90s in several open source startups in the Bay area. So, I'm well behind the whole open source idea and, and mid (indistinct) and others back then several times. But the point is, I think what we have seen is open source is not in general, more secure or less secure, because code is too complex nowadays. You have millions of lines of code, and it's not that either one way or the other is going to solve it. The ways I think we are going to look at it is more is what's the role to market, because only because something is open source doesn't necessarily mean it's going to be available for everyone. And the same for proprietary source from that perspective, even though everybody mixes licensing and payments and all that all the time, but it doesn't necessarily have anything to do with it. But I think as we are going through it, and when we also look at the industry, security industry over the last 10 plus years has been primarily hardware focused. And a lot of these vendors have done a good business out of selling hardware boxes, putting software on top of it. Whereas in reality, those were still X86 standard boxes in the end. So it was not that we had specific security ethics or anything like that in there anymore. And so overall, the question of the market is going to change. And as we are looking into Cloud Native, think about someone like an AWS, do you really envision them to have a hardware box of every supplier in their data center, and that in every availability zone in every region? Same for Microsoft, same for Google, etc? So we need to have new ways on how we can apply security. And that applies both on the backend services, but also on the front end side. >> And if I, and if I could chime in, I think the, the good, I think the answer is, is, is no and yes. And what I mean by that is if you take, antivirus and known malware, I mean pretty much anybody today can, can solve that problem, it's the unknown malware. So I think the yes part of the answer is yes, it's, it's going to be proprietary, but in the sense we're going to use open source tooling, and then apply that in a proprietary way with, with specific algorithms and unique architectures that are going to solve problems. For example, XDR with, with unknown malware. So, and that's the, that's the hard part. As somebody said, I think this morning at the keynote, it's, it's all the stuff that, that the SecOps team couldn't find. That's the really hard part. >> (laughs) Well the question will be will, is the new IP, the ability to feed ChatGPT some magical spelled insertion query string that does the job, that's unique, that might be the new IP, the the question to ask. >> Well, that's what the hackers are going to do. And I, they're on offense. (John laughs) And the offense knows what play is coming. So, they're going to start. >> So guys, let's take this conversation up a level. I want to get your perspectives on what's in this for me as a customer? We know security is a board level conversation. We talk about this all the time. We also know that they're based on, I think David, was the conversations that you and I had, with Palo Alto Networks at Ignite in December. There's a, there's a lack of alignment between the executives and the board from a security perspective. When we talk about Cloud Native Security, we all talked about the value in that, what's in it for customers? I want to get your perspectives on should this be a board level conversation, and if so, how do you advise organizations, whether it is a hospital, or a bank, or an organization that is really affected by things like ransomware? How should they be thinking about this from an organizational perspective? >> Well, I'll start first, because we had this conversation during our Super Cloud event last month, and this comes up a lot. And this is, the CEO board level. Yes it is a board level conversation for security, as is application development as in terms of transforming their business to be competitive, not to be on the wrong side of history with this wave coming. So I think that's more of a management. But the issue is, they tell their people, "Go do it." And they're like, 'cause they get sold on the idea of, "Hey, won't you transform your business, and everything's going to be data driven, and machine learning's going to power your apps, get new customers, be profitable." "Oh, sign me up for that." When you have to implement this, it's really hard. And I think the core issue is, where are companies in their life cycle of the ability to execute and architect this thing properly as Dave said, Nick Zuk said, "You can't have architecture and security, you need platforms." So, I think the re-platforming, and the re-factoring of business is a big factor, and that's got to get down into the, the organizational shifts and the people to do it. So are there skills? Do I do a managed service? How do I architect it? Are there more services? Are there developers doing applications that are going to be more agile? So, this is not an easy thing. And to move a business from IT operations that is proven, to be positioned for this enablement, is just really difficult. And it's expensive. And if you screw it up, you could be, could be on the wrong side of things. So, to me, that's the big issue is, you sell the dream and then you got to implement it. And that's really difficult. >> Yves, give us your perspective on, based on John's comments, how do organizations shift so dramatically? There's a cultural element there as well, but there's also organizations that are, have competitive competitors in the rear view mirror, and there's time to waste. What are your thoughts on that? >> I think that's exactly the point. It's like, as an organization, you need to take the decision between the time, the risk, and all the other elements we have into this game. Because you can try to achieve 100% security, but that's exactly the same as trying to, to protect gold or anything else 100%. It's most likely not going to be from a risk perspective anyway sensible. And that's the same from a corporational perspective. When you look at building new internet services, or IOT services, or any kind of new shopping experience or whatever else, you need to balance out between the risks and the advantages out of it. And you also need to be accepting that you potentially on the way make mistakes, but then it's more important than ever that you are able to quickly fix any mistakes, and to adjust to anything what's happening in the market. Because as we are building all these new Cloud Native applications, and build up all these skill sets, one of the big scenarios is we are far more depending on individual building blocks. These building blocks come out of open source communities, which have a much different way. When we look back in software development, back then we had application servers from Oracle, Web Logic, whatsoever, they had a release cycles of every three to six months. As now we have to deal with open source, where sometimes release cycles are on a four week schedule, in between security patches. So you need to be much faster in adopting that, checking that, implementing that, getting things to work. So there is a security stretch from that perspective. There is a speech stretch on the other thing companies have to deal with, and on the other side it's always a measurement between the risk, and the security you can afford. Because reality is, you will not be 100% protected no matter what you do. So, you need to balance out what you as an organization can actually build on. But I think, coming back also to the point, it's on the bot level nowadays. It's like nearly every discussion we have with companies nowadays as they move into the Cloud, especially also here in Europe where for the last five years, it was always, it's like "It's data privacy." Data privacy is no longer, I mean, yes, for certain people, it's still the point, but for many more people it's like, "How protected is my data?" "What do we do in case of ransomware attack?" "What do we do in case of a denial of service?" All of these things become more vulnerable, where in the past you were discussing these things with a becking page, or, or like a stock exchange. They were, it's like, "What the hell is going to happen if we have a denial of service?" Now all of the sudden, this now affects nearly everyone in their storefronts and everything else, because everything is depending on it. >> Yeah, I think you're right on. You think about how cultural change occurs, it's bottom ups or, bottom up, top down or middle out. And what, what's happened with security is the people in the security team cared about it, they were the, everybody said, "Oh, it's their problem." And then it just did an end run to the board, kind of mid, early last decade. And then the board sort of pushed that down. And the line of business is realizing, "Holy cow. My business, my EBIT can be dramatically affected by this, so I care." Now it's this whole house, cultural team sport. I know it's sort of a, a cliche, but it, it's true. Everybody actually is beginning to care about security because the risks are now so high, and it's going to affect not only the bottom line of the company, the bottom line of the business, their job, it's, it's, it's virtually everywhere. It's a huge cultural shift that we're seeing. >> And that's a big challenge for organizations in any industry. And Yves, you talked about ransomware service. Every industry across the globe is vulnerable to this. But how can, maybe John, we'll start with you. How can Cloud Native Security help organizations if they're able to embrace it, operationally, culturally, dial down some of the vulnerabilities that just seem to keep growing? >> Well, I mean that's the big question. The breaches are, are critical. The governances also could be a way that anchors down growth. So I think the balance between the governance compliance piece of it is key, but making the developers faster and more productive is the key to me. And I think having the security paradigm where they're not blockers, as Dave said, is critical. So I love the whole shift left, but now that we have more data focused initiatives around how that, you can use data to understand the security issues, I think data and security are together, and I think there's a going to be a data operating system model emerging, where data and security will be almost one thing. And that will be set up by the security teams, and the data teams together. And that will feed guardrails into the developer environment. So the developer should feel no pain at all in doing this. So I think the best practice will end up being what we're seeing with supply chain, security, with making sure code's verified. And you're going to see the container, security side completely address has been, and KubeCon, we just, I asked Scott Johnson, the CEO of Docker, and I asked him directly, "Are you guys all tight on container security?" He said, yes, but other people are suggesting that's not true. There's a lot of issues with the container security. So, there's all kinds of areas where there's holes. So Cloud Native is cool on one hand, and very relevant, but if it's not shored up, it's going to be a problem. But I, so I think that's where the action will be, at the developer pipeline, in the containers, and the data. So, that will be very relevant, and if companies nail that, they'll be faster, they'll have better apps, and that'll be the differentiator. And again, if they don't on this next wave, they're going to be driftwood. >> Dave, how do they prevent becoming driftwood? >> Well, I think Cloud has had a huge impact. And a Cloud's by no means a panacea, but let's face it, it's dramatically improved a lot of companies security posture. Now there's still that shared responsibility. Even though an S3 bucket is encrypted, it's still your responsibility to make sure that it doesn't get decrypted by somebody who has access to it. So there are things like that, but to Yve's earlier point, that can be, that's done through software now, it's done through best practices. Those best practices can be shared. So the way you, you don't become driftwood, is you start to, you step back, rethink that security architecture as we were talking about earlier, take advantage of the Cloud, take advantage of Cloud Native, and all the, the rapid pace of innovation that's occurring there, and you don't use, it's called before, The audit is the last line of defense. That's no longer a check box item. "Oh yeah, we're in compliance." It's, this is a business imperative, and because we're going to reduce our expected loss and reduce our business risk. That's part of the business case today. >> Yeah. >> It's a huge, critically important part of the business case. Yves, question for you. If you're in an elevator with a CEO, a CFO, and a CISO, and they're talking about security and Cloud Native Security, what's your value proposition to them on a, on a say a 32nd elevator ride? >> Difficult story. I think at the moment, the most important part is, we need to get people to work together, and we need to train people to work more much better together. I think that's the overall most important part for all of these solutions, because in the end, security is always a person issue. If, we can have the best tools in the industry, as long as we don't get all of these teams to work together, then we have a problem. If the security team is always seen as the end of the solution to fix everything, that's not going to work because they always are the bad guys in the game. And so we need to bring the teams together. And once we have the teams work together, I think we have a far better track on, on maintaining security. >> John and Dave, I want to get your perspectives on what Yves just said. In all the experience that the two of you have as industry analysts here on "theCUBE," Wikibon, Siliconangle Media. How do you advise organizations to get those teams together? As Eve said, that alignment is critical, but John, we'll start with you, then Dave go to you. What's your advice for organizations that need to align those teams and really don't have a lot of time to wait to do it? >> (chuckling) That's a great question. I think, I think that's everyone pays hundreds of thousands of millions of dollars to get that advice from these consultants, organizations out there doing the transformations. But I think it comes down to personnel and commitment. I think if there's a C-level commitment to the effort, you'll see the institutional structure change. So you can see really getting behind it with their, with their wallet and their, and their support of either getting more personnel to support and assist, or manage services, or giving the power to the teams to execute and doing it in a way that, that's, that's well known and best practices. Start small, build out the pilots, build the platform, and then start getting it right. And I think that's the key. Not the magic wand, the old model of rolling out stuff in, in six month cycles. It's really, get the proof points, double down and change the culture, but also execute and have real metrics. And changing the architecture, like having more penetration tests as a service. Doing pen tests is like a joke now. So that doesn't make any sense. You got to have that built in almost every day, and every minute. So, these kinds of new techniques have to be implemented and have to be tried. So that's why these communities are growing. That's why I like what open source has been doing, and I like the open source as the place to have these conversations, because that's where the action will be for new stuff. And I think people will implement open source like they did before, but with different ways, better testing, better supply chain on the software side, verifying code. So, I see open source actually getting a tailwind from this, not a headwind. So, I'm bullish on the open source piece here on, on all levels, machine learning- >> Lisa, my answer is intramural sports. And it's 'cause I think it's cultural. And what I mean by that, is you take your your best and brightest security, and this is what frankly, a lot of CISOs do, an examples is Lena Smart, MongoDB. Take your best and brightest security pros, make them captains of the intramural teams, and pair them up with pods of individuals across the organization, which is most people who don't know anything about security, and put them together, so that they can, they, so that the folks that understand security can, can realize how little people know, what, what, what, how, what the worst practices that are out there in the reverse, how they can cross pollinate. And they do that on a regular basis, I know at Mongo and other companies. And that kind of cultural assimilation is a starting point for how you get security awareness up to your question around making it a team sport. >> Absolutely critical. Yves, I want to kind of wrap things with you. We've got a couple of minutes left. When you're really looking at the Cloud Native community, the growth of it, we talked about earlier in the program, Cloud Native Security Con being now extracted and elevated out of KubeCon, what are your thoughts on the groundswell that this community is generating around Cloud Native Security, the benefits that organizations will achieve from it? >> I think overall, when we have these securities conferences, or these security arms a bit spread out and separated out of the main conference, it helps to a certain degree, because especially in the security space, when you look at at other like black hat or white hat conferences and things like that in the past, although they were not focused on Cloud Native, a lot of these security folks didn't feel well taken care of in any of the other conferences because they were always these, it's like they are always blocking us, they're always making us problems, and all these kinds of things. Now that we really take the Cloud Native piece and the security piece together, or like AWS does it with re:Inforce, I think we will see more and more that people understand is that security is a permanent topic we need to cover, but we need to bring different people together, because security also has compliance and a lot of other components in there. So we will see at these conferences moving forward, also a different audience. It's not going to be only the Cloud Native developers. And if I see some of these security audiences, I can't really imagine them to really be at KubeCon because there is too much other things going on. And you couldn't really see much of that at re:Invent because re:Invent by itself has become a complete monster of a conference. It covers too many topics. And so having this very, very important security piece separated, also gives the opportunity, I think, that we can bring in the security people, but also have the type of board level discussions potentially, between the leaders of the industry, to also discuss on how we can evolve, how we can make things better, and how, how we can actually, yeah, evolve our industry for it. Because let's face it, that threat is not going to go away. It's, it's a business. And one of the last security conferences I was on, on the ransomware part, it was one of the topics someone said is like, "Look, currently on average, it takes a hacker group roughly around they said 15 to 20 K to break into a company, and they on average make 100K. It's a business, let's face it. And it's a business we don't like. And ethically, it's no discussion that this is not good, but that's something which is happening. People are making money with it. And as long as that's going to go on, and we have enough countries where these people can hide, it's going to stay and survive. And so, with that being said, it's important for us to really build an industry around this. But I also think it's good that we have separate conferences. In the past we had more the RSA conference, which tried to cover all of these areas. But that is not really fitting Cloud Native and everything else. So I think it's good that we have these new opportunities, the Cloud Native one, but also what AWS brings up for someone. >> Yves, you just nailed it. It just comes down to simple math. It's a fraction. Revenue over cost. And if you could increase the hacker's cost, increase the denominator, their ROI will go down. And that is the game. >> Great point, Dave. What I'm hearing guys, and we can talk about technology for days and days. I know all of you. But there's, there's a big component that, that the elevation of Cloud Native Security, on its own as standalone is critical, as is the people component. You guys all talked about that. We talked about the cultural change necessary for that. Hopefully what we're seeing with Cloud Native Security Con 23, this first event is going to give us more insight over the next couple of days, and the next months or so, as to how this elevation, and how the people can come together to really help organizations from a math perspective as, as Dave talked about, really dial down the risks there, understand more of the vulnerabilities so that ransomware as a service is not as lucrative as it is today. Guys, so much appreciate your time, really breaking down Cloud Native Security, the value in it from different perspectives, and what your thoughts are on where it's going. Thanks so much for your time. >> All right. Thanks. >> Thanks, Lisa. >> Thank you. >> Thanks, Yves. >> All right. For my guests, I'm Lisa Martin. You're watching theCUBE's day one coverage of Cloud Native Security Con 23. Thanks for watching. (rousing music)

>> Welcome back everyone to the closing remarks here before we kick off our ecosystem portion of the program. We're live in Palo Alto for theCUBE special presentation of Supercloud 2. It's the second edition, the first one was in August. I'm John Furrier with Dave Vellante. Here to wrap up with our special guest analyst George Gilbert, investor and industry legend former colleague of ours, analyst at Wikibon. George great to see you. Dave, you know, wrapping up this day what in a phenomenal program. We had a contribution from industry vendors, industry experts, practitioners and customers building and redefining their company's business model. Rolling out technology for Supercloud and multicloud and ultimately changing how they do data. And data was the theme today. So very, very great program. Before we jump into our favorite parts let's give a shout out to the folks who make this possible. Free contents our mission. We'll always stay true to that mission. We want to thank VMware, alkira, ChaosSearch, prosimo for being sponsors of this great program. We will have Supercloud 3 coming up in a month or so, or two months. We'll see. Or sooner, we don't know. But it'll be more about security, but a lot more momentum. Okay, so that's... >> And don't forget too that this program not going to end now. We've got a whole ecosystem speaks track so stay tuned for that. >> John: Yeah, we got another 20 interviews. Feels like it. >> Well, you're going to hear from Saks, Veronika Durgin. You're going to hear from Western Union, Harveer Singh. You're going to hear from Ionis Pharmaceuticals, Nick Taylor. Brian Gracely chimes in on Supecloud. So he's the man behind the cloud cast. >> Yeah, and you know, the practitioners again, pay attention to also to the cloud networking interviews. Lot of change going on there that's going to be disruptive and actually change the landscape as well. Again, as Supercloud progresses to be the next big thing. If you're not on this next wave, you'll drift what, as Pat Gelsinger says. >> Yep. >> To kick off the closing segments, George, Dave, this is a wave that's been identified. Again, people debate the word all you want Supercloud. It is a gateway to multicloud eventually it is the standard for new applications, new ways to do data. There's new computer science being generated and customer requirements being addressed. So it's the confluence of, you know, tectonic plates shifting in the industry, new computer science seeing things like AI and machine learning and data at the center of it and new infrastructure all kind of coming together. So, to me, that's my takeaway so far. That is the big story and it's going to change society and ultimately the business models of these companies. >> Well, we've had 10, you know, you think about it we came out of the financial crisis. We've had 10, 12 years despite the Covid of tech success, right? And just now CIOs are starting to hit the brakes. And so my point is you've had all this innovation building up for a decade and you've got this massive ecosystem that is running on the cloud and the ecosystem is saying, hey, we can have even more value by tapping best of of breed across clouds. And you've got customers saying, hey, we need help. We want to do more and we want to point our business and our intellectual property, our software tooling at our customers and monetize our data. So you have all these forces coming together and it's sort of entering a new era. >> George, I want to go to you for a second because you are big contributor to this event. Your interview with Bob Moglia with Dave was I thought a watershed moment for me to hear that the data apps, how databases are being rethought because we've been seeing a diversity of databases with Amazon Web services, you know, promoting no one database rules of the world. Now it's not one database kind of architecture that's puling these new apps. What's your takeaway from this event? >> So if you keep your eye on this North Star where instead of building apps that are based on code you're building apps that are defined by data coming off of things that are linked to the real world like people, places, things and activities. Then the idea is, and the example we use is, you know, Uber but it could be, you know, amazon.com is defined by stuff coming off data in the Amazon ecosystem or marketplace. And then the question is, and everyone was talking at different angles on this, which was, where's the data live? How much do you hide from the developer? You know, and when can you offer that? You know, and you started with Walmart which was describing apps, traditional apps that are just code. And frankly that's easier to make that cross cloud and you know, essentially location independent. As soon as you have data you need data management technology that a customer does not have the sophistication to build. And then the argument was like, so how much can you hide from the developer who's building data apps? Tristan's version was you take the modern data stack and you start adding these APIs that define business concepts like bookings, billings and revenue, you know, or in the Uber example like drivers and riders, you know, and ETA's and prices. But those things execute still on the data warehouse or data lakehouse. Then Bob Muglia was saying you're not really hiding enough from the developer because you still got to say how to do all that. And his vision is not only do you hide where the data is but you hide how to sort of get at all that code by just saying what you want. You define how a car and how a driver and how a rider works. And then those things automatically figure out underneath the cover. >> So huge challenges, right? There's governance, there's security, they could be big blockers to, you know, the Supercloud but the industry's going to be attacking that problem. >> Well, what's your take? What's your favorite segment? Zhamak Dehghani came on, she's starting in that company, exclusive news. That was big notable moment for theCUBE. She launched her company. She pioneered the data mesh concept. And I think what George is saying and what data mesh points to is something that we've been saying for a long time. That data is now going to flip the script on how apps behave. And the Uber example I think is illustrated 'cause people can relate to Uber. But imagine that for every business whether it's a manufacturing business or retail or oil and gas or FinTech, they can look at their business like a game almost gamify it with data, riders, cars you know, moving data around the value of data. This is something that Adam Selipsky teased out at AWS, Dave. So what's your takeaway from this Supercloud? Where are we in your mind? Well big thing is data products and decentralizing your data architecture, but putting data in the hands of domain experts who can actually monetize the data. And I think that's, to me that's really exciting. Because look, data products financial industry has always been doing building data products. Mortgage backed securities is a data product. But why should the financial industry have all the fun? I mean virtually every organization can tap its ecosystem build data products, take its internal IP and processes and software and point it to the world and actually begin to make money out of it. >> Okay, so let's go around the horn. I'll start, I'll get you guys some time to think. Next question, what did you learn today? I learned that I think it's an infrastructure game and talking to Kit Colbert at VMware, I think it's all about infrastructure refactoring and I think the data's going to be an ingredient that's going to be operating system like. I think you're going to see the infrastructure influencing operations that will enable Superclouds to be real. And developers won't even know what a Supercloud is because they'll be using it. It's the operations focus is going to be very critical. Just like DevOps movements started Cloud native I think you're going to see a data native movement and I think infrastructure is critical as people go to the next level. That's my big takeaway today. And I'll say the data conversation is at the center. I think security, data are going to be always active horizontally scalable concepts, but every company's going to reset their infrastructure, how it looks and if it's not set up for data and or things that there need to be agile on, it's going to be a non-starter. So I think that's the cloud NextGen, distributed computing. >> I mean, what came into focus for me was I think the hyperscaler is going to continue to do their thing, you know, and be very, very successful and they're each coming at it from different approaches. We talk about this all the time in theCUBE. Amazon the best infrastructure, you know, Google's got its you know, data and AI thing and it's playing catch up and Microsoft's got this massive estate. Okay, cool. Check. The next wave of innovation which is coming from data, I've always said follow the data. That's where the where the money's going to be is going to come from other places. People want to be able to, organizations want to be able to share data across clouds across their organization, outside of their ecosystem and make money with that data sharing. They don't want to FTP it anymore. I got it. You take it. They want to work with live data in real time and I think the edge, we didn't talk much about the edge today is going to even take that to a new level real time inferencing at the edge, AI and and being able to do new things with data that we haven't even seen. But playing around with ChatGPT, it's blowing our mind. And I think you're right, it's like when we first saw the browser, holy crap, this is going to change the world. >> Yeah. And the ChatGPT by the way is going to create a wave of machine learning and data refactoring for sure. But also Howie Liu had an interesting comment, he was asked by a VC how much to replicate that and he said it's in the hundreds of millions, not billions. Now if you asked that same question how much does it cost to replicate AWS? The CapEx alone is unstoppable, they're already done. So, you know, the hyperscalers are going to continue to boom. I think they're going to drive the infrastructure. I think Amazon's going to be really strong at silicon and physics and squeeze every ounce atom out of every physical thing and then get latency as your bottleneck and the rest is all going to be... >> That never blew me away, a hundred million to create kind of an open AI, you know, competitor. Look at companies like Lacework. >> John: Some people have that much cash on the balance sheet. >> These are security companies that have raised a billion dollars, right? To compete. You know, so... >> If you're not shifting left what do you do with data, shift up? >> But, you know. >> What did you learn, George? >> I'm listening to you and I think you're helping me crystallize something which is the software infrastructure to enable the data apps is wide open. The way Zhamak described it is like if you want a data product like a sales and operation plan, that is built on other data products, like a sales plan which has a forecast in it, it has a production plan, it has a procurement plan and then a sales and operation plan is actually a composition of all those and they call each other. Now in her current platform, you need to expose to the developer a certain amount of mechanics on how to move all that data, when to move it. Like what happens if something fails. Now Muglia is saying I can hide that completely. So all you have to say is what you want and the underlying machinery takes care of everything. The problem is Muglia stuff is still a few years off. And Tristan is saying, I can give you much of that today but it's got to run in the data warehouse. So this trade offs all different ways. But again, I agree with you that the Cloud platform vendors or the ecosystem participants who can run across Cloud platforms and private infrastructure will be the next platform. And then the cloud platform is sort of where you run the big honking centralized stuff where someone else manages the operations. >> Sounds like middleware to me, Dave >> And key is, I'll just end with this. The key is being able to get to the data, whether it's in a data warehouse or a data lake or a S3 bucket or an object store, Oracle database, whatever. It's got to be inclusive that is critical to execute on the vision that you just talked about 'cause that data's in different systems and you're not going to put it all into some new system. >> So creating middleware in the cloud that sounds what it sounds like to me. >> It's like, you discovered PaaS >> It's a super PaaS. >> But it's platform services 'cause PaaS connotes like a tightly integrated platform. >> Well this is the real thing that's going on. We're going to see how this evolves. George, great to have you on, Dave. Thanks for the summary. I enjoyed this segment a lot today. This ends our stage performance live here in Palo Alto. As you know, we're live stage performance and syndicate out virtually. Our afternoon program's going to kick in now you're going to hear some great interviews. We got ChaosSearch. Defining the network Supercloud from prosimo. Future of Cloud Network, alkira. We got Saks, a retail company here, Veronika Durgin. We got Dave with Western Union. So a lot of customers, a pharmaceutical company Warner Brothers, Discovery, media company. And then you know, what is really needed for Supercloud, good panels. So stay with us for the afternoon program. That's part two of Supercloud 2. This is a wrap up for our stage live performance. I'm John Furrier with Dave Vellante and George Gilbert here wrapping up. Thanks for watching and enjoy the program. (bright music)

>>Hello and welcome back to the Cube's coverage of AWS Reinvent 2022. I'm John Furrier, host of the Cube. We got a great conversation with Patrick Kauflin, vice president of Go to Market Strategy and specialization at Splunk. We're talking about the open cybersecurity scheme of framework, also known as the O C sf, a joint strategic collaboration between Splunk and aws. It's got a lot of traction momentum. Patrick, thanks for coming on the cube for reinvent coverage. >>John, great to be here. I'm excited for this. >>You know, I love this open source movement and open source and continues to add value, almost sets the standards. You know, we were talking at the CNCF Linux Foundation this past fall about how standards are coming outta open source. Not so much the the classic standards groups, but you start to see the developers voting with their code groups deciding what to adopt de facto standards and security is a real key part of that where data becomes key for resilience. And this has been the top conversation at reinvent and all around the industry, is how to make data a key part of building into cyber resilience. So I wanna get your thoughts about the problem that you see that's emerging that you guys are solving with this group kind of collaboration around the ocs f >>Yeah, well look, John, I I think, I think you, you've already, you've already hit the high notes there. Data is proliferating across the enterprise. The attack surface area is rapidly expanding. The threat landscape is ever changing. You know, we, we just had a, a lot of scares around open SSL before that we had vulnerabilities and, and Confluence and Atlassian, and you go back to log four J and SolarWinds before that and, and challenges with the supply chain. In this year in particular, we've had a, a huge acceleration in, in concerns and threat vectors around operational technology. In our customer base alone, we saw a huge uptake, you know, and double digit percentage of customers that we're concerned about the traditional vectors like, like ransomware, like business email compromise, phishing, but also from insider threat and others. So you've got this, this highly complex environment where data continues to proliferate and flow through new applications, new infrastructure, new services, driving different types of outcomes in the digitally transformed enterprise of today. >>And, and what happens there is, is our customers, particularly in security, are, are left with having to stitch all of this together. And they're trying to get visibility across multiple different services, infrastructure applications across a number of different point solutions that they've bought to help them protect, defend, detect, and respond better. And it's a massive challenge. And you know, when our, when our customers come to us, they are often looking for ways to drive more consolidation across a variety of different solutions. They're looking to drive better outcomes in terms of speed to detection. How do I detect faster? How do I bind the thing that when bang in the night faster? How do I then fix it quickly? And then how do I layer in some automation so hopefully I don't have to do it again? Now, the challenge there that really OCF Ocsf helps to, to solve is to do that effectively, to detect and to respond at the speed at which attackers are demanding. >>Today we have to have normalization of data across this entire landscape of tools, infrastructure, services. We have to have integration to have visibility, and these tools have to work together. But the biggest barrier to that is often data is stored in different structures and in different formats across different solution providers, across different tools that are, that are, that our customers are using. And that that lack of data, normalization, chokes the integration problem. And so, you know, several years ago, a number of very smart people, and this was, this was a initiative s started by Splunk and AWS came together and said, look, we as an industry have to solve this for our customers. We have to start to shoulder this burden for our customers. We can't, we can't make our customers have to be systems integrators. That's not their job. Our job is to help make this easier for them. And so OCS was born and over the last couple of years we've built out this, this collaboration to not just be AWS and Splunk, but over 50 different organizations, cloud service providers, solution providers in the cybersecurity space have come together and said, let's decide on a single unified schema for how we're gonna represent event data in this industry. And I'm very proud to be here today to say that we've launched it and, and I can't wait to see where we go next. >>Yeah, I mean, this is really compelling. I mean, it's so much packed in that, in that statement, I mean, data normalization, you mentioned chokes, this the, the solution and integration as you call it. But really also it's like data's not just stored in silos. It may not even be available, right? So if you don't have availability of data, that's an important point. Number two, you mentioned supply chain, there's physical supply chain that's coming up big time at reinvent this time as well as in open source, the software supply chain. So you now have the perimeter's been dead for multiple years. We've been talking with that for years, everybody knows that. But now combined with the supply chain problem, both physical and software, there's so much more to go on. And so, you know, the leaders in the industry, they're not sitting on their hands. They know this, but they're just overloaded. So, so how do leaders deal with this right now before we get into the ocs f I wanna just get your thoughts on what's the psychology of the, of the business leader who's facing this landscape? >>Yeah, well, I mean unfortunately too many leaders feel like they have to face these trade offs between, you know, how and where they are really focusing cyber resilience investments in the business. And, and often there is a siloed approach across security, IT developer operations or engineering rather than the ability to kind of drive visibility integration and, and connection of outcomes across those different functions. I mean, the truth is the telemetry that, that you get from an application for application performance monitoring or infrastructure monitoring is often incredibly valuable when there's a security incident and vice versa. Some of the security data that, that you may see in a security operation center can be incredibly valuable in trying to investigate a, a performance degradation in an application and understanding where that may come from. And so what we're seeing is this data layer is collapsing faster than the org charts are or the budget line items are in the enterprise. And so at Splunk here, you know, we believe security resilience is, is fundamentally a data problem. And one of the things that we do often is, is actually help connect the dots for our customers and bring our customers together across the silos they may have internally so that they can start to see a holistic picture of what resilience means for their enterprise and how they can drive faster detection outcomes and more automation coverage. >>You know, we recently had an event called Super Cloud, we're going into the next gen kind of a cloud, how data and security are all kind of part of this NextGen application. It's not just us. And we had a panel that was titled The Innovators Dilemma, kind of talk about you some of the challenges. And one of the panelists said, it's not the innovator's dilemma, it's the integrator's dilemma. And you mentioned that earlier, and I think this a key point right now into integration is so critical, not having the data and putting pieces together now open source is becoming a composability market. And I think having things snap together and work well, it's a platform system conversation, not a tool conversation. So I really wanna get into where the OCS f kind of intersects with this area people are working on. It's not just solution architects or cloud cloud native SREs, especially where DevSecOps is. So this that's right, this intersection is critical. How does Ocsf integrate into that integration of the data making that available to make machine learning and automation smarter and more relevant? >>Right, right. Well look, I mean, I I think that's a fantastic question because, you know, we talk about, we use Bud buzzwords like machine learning and, and AI all the time. And you know, I know they're all over the place here at Reinvent and, and the, there's so much promise and hope out there around these technologies and these innovations. However, machine learning AI is only as effective as the data is clean and normalized. And, and we will not realize the promise of these technologies for outcomes in resilience unless we have better ways to normalize data upstream and better ways to integrate that data to the downstream tools where detection and response is happening. And so Ocsf was really about the industry coming together and saying, this is no longer the job of our customers. We are going to create a unified schema that represents the, an event that we will all bite down on. >>Even some of us are competitors, you know, this is, this is that, that no longer matters because at the point, the point is how do we take this burden off of our customers and how do we make the industry safer together? And so 15 initial members came together along with AWS and Splunk to, to start to create that, that initial schema and standardize it. And if you've ever, you know, if you've ever worked with a bunch of technical grumpy security people, it's kind of hard to drive consensus about around just about anything. But, but I, I'm really happy to see how quickly this, this organization has come together, has open sourced the schema, and, and, and just as you said, like I think this, this unlocks the potential for real innovation that's gonna be required to keep up with the bad guys. But right now is getting stymied and held back by the lack of normalization and the lack of integration. >>I've always said Splunk was a, it eats data for breakfast, lunch, and dinner and turns it into insights. And I think you bring up the silo thing. What's interesting is the cross company sharing, I think this hits point on, so I see this as a valuable opportunity for the industry. What's the traction on that? Because, you know, to succeed it does take a village, it takes a community of security practitioners and, and, and architects and developers to kind of coalesce around this defacto movement has been, has been the uptake been good? How's traction? Can you share your thoughts on how this is translating across companies? >>Yeah, absolutely. I mean, look, I, I think cybersecurity has a, has a long track record of, of, of standards development. There's been some fantastic standards recently. Things like sticks and taxi for threat intelligence. There's been things like the, you know, the Mir attack framework coming outta mi mir and, and, and the adoption, the traction that we've seen with Attack in particular has been amazing to, to watch how that has kind of roared onto the scene in the last couple of years and has become table stakes for how you do security operations and incident response. And, you know, I think with ocs f we're gonna see something similar here, but, you know, we are in literally the first innings of, of this. So right now, you know, we're architecting this into our, into every part of our sort of backend systems here at Polan. I know our our collaborators at AWS and elsewhere are doing it too. >>And so I think it starts with bringing this standard now that the standard exists on a, you know, in schema format and there, there's, you know, confluence and Jira tickets around it, how do we then sort of build this into the code of, of the, the collaborators that have been leading the way on this? And you know, it's not gonna happen overnight, but I think in the coming quarters you'll start to see this schema be the standard across the leaders in this space. Companies like Splunk and AWS and others who are leading the way. And often that's what helps drive adoption of a standard is if you can get the, the big dogs, so to speak, to, to, to embrace it. And, and, you know, there's no bigger one than aws and I think there's no, no more important one than Splunk in the cybersecurity space. And so as we adopt this, we hope others will follow. And, and like I said, we've got over 50 organizations contributing to it today. And so I think we're off to a running >>Start. You know, it's interesting, choking innovation or having things kind of get, get slowed down has really been a problem. We've seen successes recently over the past few years. Like Kubernetes has really unlocked and accelerated the cloud native worlds of runtime with containers to, to kind of have the consensus of the community to say, Hey, if we just do this, it gets better. I think this is really compelling with the o the ocs F because if people can come together around this and get unified as well as all the other official standards, things can go highly accelerated. So I think, I think it looks really good and I think it's great initiative and I really appreciate your insight on that, on, on your relationship with Amazon. Okay. It's not just a partnership, it's a strategic collaboration. Could you share that relationship dynamic, how to start, how's it going, what's strategic about it? Share to the audience kind of the relationship between Splunk and a on this important OCS ocsf initiative. >>Look, I, I mean I think this, this year marks the, the 10th year anniversary that, that Splunk and AWS have been collaborating in a variety of different ways. I, I think our, our companies have a fantastic and, and long standing relationship and we've, we've partnered on a number of really important projects together that bring value obviously to our individual companies, but also to our shared customers. When I think about some of the most important customers at Splunk that I spend a significant amount of time with, I I I know how many of those are, are AWS customers as well, and I know how important AWS is to them. So I think it's, it's a, it's a collaboration that is rooted in, in a respect for each other's technologies and innovation, but also in a recognition that, that our shared customers want to see us work better together over time. And it's not, it's not two companies that have kind of decided in a back room that they should work together. It's actually our customers that are, that are pushing us. And I think we're, we're both very customer centric organizations and I think that has helped us actually be better collaborators and better partners together because we're, we're working back backwards from our customers >>As security becomes a physical and software approach. We've seen the trend where even Steven Schmidt at Amazon Web Services is, is the cso, he is not the CSO anymore. So, and I asked him why, he says, well, security's also physical stuff too. So, so he's that's right. Whole lens is now expanded. You mentioned supply chain, physical, digital, this is an important inflection point. Can you summarize in your mind why open cybersecurity schema for is important? I know the unification, but beyond that, what, why is this so important? Why should people pay attention to this? >>You know, I, if, if you'll let me be just a little abstract in meta for a second. I think what's, what's really meaningful at the highest level about the O C S F initiative, and that goes beyond, I think, the tactical value it will provide to, to organizations and to customers in terms of making them safer over the coming years and, and decades. I think what's more important than that is it's really the, one of the first times that you've seen the industry come together and say, we got a problem. We need to solve. That, you know, doesn't really have anything to do with, with our own economics. Our customers are, are hurt. And yeah, some of us may be competitors, you know, we got different cloud service providers that are participating in this along with aws. We got different cybersecurity solution providers participating in this along with Splunk. >>But, but folks who've come together and say, we can actually solve this problem if, if we're able to kind of put aside our competitive differences in the markets and approach this from the perspective of what's best for information security as a whole. And, and I think that's what I'm most proud of and, and what I hope we can do more of in other places in this industry, because I think that kind of collaboration from real market leaders can actually change markets. It can change the, the, the trend lines in terms of how we are keeping up with the bad guys. And, and I'd like to see a lot more of >>That. And we're seeing a lot more new kind of things emerging in the cloud next kind of this next generation architecture and outcomes are happening. I think it's interesting, you know, we always talk about sustainability, supply chain sustainability about making the earth a better place. But you're hitting on this, this meta point about businesses are under threat of going under. I mean, we want to keep businesses to businesses to be sustainable, not just, you know, the, the environment. So if a business goes outta business business, which they, their threats here are, can be catastrophic for companies. I mean, there is, there is a community responsibility to protect businesses so they can sustain and and stay Yeah. Stay producing. This is a real key point. >>Yeah. Yeah. I mean, look, I think, I think one of the things that, you know, we, we, we complain a lot of in, in cyber security about the lack of, of talent, the talent shortage in cyber security. And every year we kinda, we kind of whack ourselves over the head about how hard it is to bring people into this industry. And it's true. But one of the things that I think we forget, John, is, is how important mission is to so many people in what they do for a living and how they work. And I think one of the things that cybersecurity is strongest in information Security General and has been for decades is this sense of mission and people work in this industry be not because it's, it's, it's always the, the, the most lucrative, but because it, it really drives a sense of safety and security in the enterprises and the fabric of the economy that we use every day to go through our lives. And when I think about the spun customers and AWS customers, I think about the, the different products and tools that power my life and, and we need to secure them. And, and sometimes that means coming to work every day at that company and, and doing your job. And sometimes that means working with others better, faster, and stronger to help drive that level of, of, of maturity and security that this industry >>Needs. It's a human, is a human opportunity, human problem and, and challenge. That's a whole nother segment. The role of the talent and the human machines and with scale. Patrick, thanks so much for sharing the information and the insight on the Open cybersecurity schema frame and what it means and why it's important. Thanks for sharing on the Cube, really appreciate it. >>Thanks for having me, John. >>Okay, this is AWS Reinvent 2022 coverage here on the Cube. I'm John Furry, you're the host. Thanks for watching.

(outro music) >> Hey, I'm John Furrier, here with an exclusive interview with Ali Ghodsi, who's the CEO of Databricks. Ali, great to see you. Preview for reinvent. We're going to launch this story, exclusive Databricks material on the notes, after the keynotes prior to the keynotes and after the keynotes that reinvent. So great to see you. You know, you've been a partner of AWS for a very, very long time. I think five years ago, I think I first interviewed you, you were one of the first to publicly declare that this was a place to build a company on and not just post an application, but refactor capabilities to create, essentially a platform in the cloud, on the cloud. Not just an ISV; Independent Software Vendor, kind of an old term, we're talking about real platform like capability to change the game. Can you talk about your experience as an AWS partner? >> Yeah, look, so we started in 2013. I swiped my personal credit card on AWS and some of my co-founders did the same. And we started building. And we were excited because we just thought this is a much better way to launch a company because you can just much faster get time to market and launch your thing and you can get the end users much quicker access to the thing you're building. So we didn't really talk to anyone at AWS, we just swiped a credit card. And eventually they told us, "Hey, do you want to buy extra support?" "You're asking a lot of advanced questions from us." "Maybe you want to buy our advanced support." And we said, no, no, no, no. We're very advanced ourselves, we know what we're doing. We're not going to buy any advanced support. So, you know, we just built this, you know, startup from nothing on AWS without even talking to anyone there. So at some point, I think around 2017, they suddenly saw this company with maybe a hundred million ARR pop up on their radar and it's driving massive amounts of compute, massive amounts of data. And it took a little bit in the beginning just us to get to know each other because as I said, it's like we were not on their radar and we weren't really looking, we were just doing our thing. And then over the years the partnership has deepened and deepened and deepened and then with, you know, Andy (indistinct) really leaning into the partnership, he mentioned us at Reinvent. And then we sort of figured out a way to really integrate the two service, the Databricks platform with AWS . And today it's an amazing partnership. You know, we directly connected with the general managers for the services. We're connected at the CEO level, you know, the sellers get compensated for pushing Databricks, we're, we have multiple offerings on their marketplace. We have a native offering on AWS. You know, we're prominently always sort of marketed and you know, we're aligned also vision wise in what we're trying to do. So yeah, we've come a very, very long way. >> Do you consider yourself a SaaS app or an ISV or do you see yourself more of a platform company because you have customers. How would you categorize your category as a company? >> Well, it's a data platform, right? And actually the, the strategy of the Databricks is take what's otherwise five, six services in the industry or five, six different startups, but do them as part of one data platform that's integrated. So in one word, the strategy of data bricks is "unification." We call it the data lake house. But really the idea behind the data lake house is that of unification, or in more words it's, "The whole is greater than the sum of its parts." So you could actually go and buy five, six services out there or actually use five, six services from the cloud vendors, stitch it together and it kind of resembles Databricks. Our power is in doing those integrated, together in a way in which it's really, really easy and simple to use for end users. So yeah, we're a data platform. I wouldn't, you know, ISV that's a old term, you know, Independent Software Vendor. You know, I think, you know, we have actually a whole slew of ISVs on top of Databricks, that integrate with our platform. And you know, in our marketplace as well as in our partner connect, we host those ISVs that then, you know, work on top of the data that we have in the Databricks, data lake house. >> You know, I think one of the things your journey has been great to document and watch from the beginning. I got to give you guys credit over there and props, congratulations. But I think you're the poster child as a company to what we see enterprises doing now. So go back in time when you guys swiped a credit card, you didn't need attending technical support because you guys had brains, you were refactoring, rethinking. It wasn't just banging out software, you had, you were doing some complex things. It wasn't like it was just write some software hosted on server. It was really a lot more. And as a result your business worth billions of dollars. I think 38 billion or something like that, big numbers, big numbers of great revenue growth as well, billions in revenue. You have customers, you have an ecosystem, you have data applications on top of Databricks. So in a way you're a cloud on top of the cloud. So is there a cloud on top of the cloud? So you have ISVs, Amazon has ISVs. Can you take us through what this means and at this point in history, because this seems to be an advanced version of benefits of platforming and refactoring, leveraging say AWS. >> Yeah, so look, when we started, there was really only one game in town. It was AWS. So it was one cloud. And the strategy of the company then was, well Amazon had this beautiful set of services that they're building bottom up, they have storage, compute, networking, and then they have databases and so on. But it's a lot of services. So let us not directly compete with AWS and try to take out one of their services. Let's not do that because frankly we can't. We were not of that size. They had the scale, they had the size and they were the only cloud vendor in town. So our strategy instead was, let's do something else. Let's not compete directly with say, a particular service they're building, let's take a different strategy. What if we had a unified holistic data platform, where it's just one integrated service end to end. So think of it as Microsoft office, which contains PowerPoint, and Word, and Excel and even Access, if you want to use it. What if we build that and AWS has this really amazing knack for releasing things, you know services, lots of them, every reinvent. And they're sort of a DevOps person's dream and you can stitch these together and you know you have to be technical. How do we elevate that and make it simpler and integrate it? That was our original strategy and it resonated with a segment of the market. And the reason it worked with AWS so that we wouldn't butt heads with AWS was because we weren't a direct replacement for this service or for that service, we were taking a different approach. And AWS, because credit goes to them, they're so customer obsessed, they would actually do what's right for the customer. So if the customer said we want this unified thing, their sellers would actually say, okay, so then you should use Databricks. So they truly are customer obsessed in that way. And I really mean it, John. Things have changed over the years. They're not the only cloud anymore. You know, Azure is real, GCP is real, there's also Alibaba. And now over 70% of our customers are on more than one cloud. So now what we hear from them is, not only want, do we want a simplified, unified thing, but we want it also to work across the clouds. Because those of them that are seriously considering multiple clouds, they don't want to use a service on cloud one and then use a similar service on cloud two. But it's a little bit different. And now they have to do twice the work to make it work. You know, John, it's hard enough as it is, like it's this data stuff and analytics. It's not a walk in the park, you know. You hire an administrator in the back office that clicks a button and its just, now you're a data driven digital transformed company. It's hard. If you now have to do it again on the second cloud with different set of services and then again on a third cloud with a different set of services. That's very, very costly. So the strategy then has changed that, how do we take that unified simple approach and make it also the same and standardize across the clouds, but then also integrate it as far down as we can on each of the clouds. So that you're not giving up any of the benefits that the particular cloud has. >> Yeah, I think one of the things that we see, and I want get your reaction to this, is this rise of the super cloud as we call it. I think you were involved in the Sky paper that I saw your position paper came out after we had introduced Super Cloud, which is great. Congratulations to the Berkeley team, wearing the hat here. But you guys are, I think a driver of this because you're creating the need for these things. You're saying, okay, we went on one cloud with AWS and you didn't hide that. And now you're publicly saying there's other clouds too, increased ham for your business. And customers have multiple clouds in their infrastructure for the best of breed that they have. Okay, get that. But there's still a challenge around the innovation, growth that's still around the corner. We still have a supply chain problem, we still have skill gaps. You know, you guys are unique at Databricks as other these big examples of super clouds that are developing. Enterprises don't have the Databricks kind of talent. They need, they need turnkey solutions. So Adam and the team at Amazon are promoting, you know, more solution oriented approaches higher up on the stack. You're starting to see kind of like, I won't say templates, but you know, almost like application specific headless like, low code, no code capability to accelerate clients who are wanting to write code for the modern error. Right, so this kind of, and then now you, as you guys pointed out with these common services, you're pushing the envelope. So you're saying, hey, I need to compete, I don't want to go to my customers and have them to have a staff or this cloud and this cloud and this cloud because they don't have the staff. Or if they do, they're very unique. So what's your reaction? Because this kind is the, it kind of shows your leadership as a partner of AWS and the clouds, but also highlights I think what's coming. But you share your reaction. >> Yeah, look, it's, first of all, you know, I wish I could take credit for this but I can't because it's really the customers that have decided to go on multiple clouds. You know, it's not Databricks that you know, push this or some other vendor, you know, that, Snowflake or someone who pushed this and now enterprises listened to us and they picked two clouds. That's not how it happened. The enterprises picked two clouds or three clouds themselves and we can get into why, but they did that. So this largely just happened in the market. We as data platforms responded to what they're then saying, which is they're saying, "I don't want to redo this again on the other cloud." So I think the writing is on the wall. I think it's super obvious what's going to happen next. They will say, "Any service I'm using, it better work exactly the same on all the clouds." You know, that's what's going to happen. So in the next five years, every enterprise will say, "I'm going to use the service, but you better make sure that this service works equally well on all of the clouds." And obviously the multicloud vendors like us, are there to do that. But I actually think that what you're going to see happening is that you're going to see the cloud vendors changing the existing services that they have to make them work on the other clouds. That's what's goin to happen, I think. >> Yeah, and I think I would add that, first of all, I agree with you. I think that's going to be a forcing function. Because I think you're driving it. You guys are in a way, one, are just an actor in the driving this because you're on the front end of this and there are others and there will be people following. But I think to me, I'm a cloud vendor, I got to differentiate. Adam, If I'm Adam Saleski, I got to say, "Hey, I got to differentiate." So I don't wan to get stuck in the middle, so to speak. Am I just going to innovate on the hardware AKA infrastructure or am I going to innovate at the higher level services? So what we're talking about here is the tail of two clouds within Amazon, for instance. So do I innovate on the silicon and get low level into the physics and squeeze performance out of the hardware and infrastructure? Or do I focus on ease of use at the top of the stack for the developers? So again, there's a channel of two clouds here. So I got to ask you, how do they differentiate? Number one and number two, I never heard a developer ever say, "I want to run my app or workload on the slower cloud." So I mean, you know, back when we had PCs you wanted to go, "I want the fastest processor." So again, you can have common level services, but where is that performance differentiation with the cloud? What do the clouds do in your opinion? >> Yeah, look, I think it's pretty clear. I think that it's, this is, you know, no surprise. Probably 70% or so of the revenue is in the lower infrastructure layers, compute, storage, networking. And they have to win that. They have to be competitive there. As you said, you can say, oh you know, I guess my CPUs are slower than the other cloud, but who cares? I have amazing other services which only work on my cloud by the way, right? That's not going to be a winning recipe. So I think all three are laser focused on, we going to have specialized hardware and the nuts and bolts of the infrastructure, we can do it better than the other clouds for sure. And you can see lots of innovation happening there, right? The Graviton chips, you know, we see huge price performance benefits in those chips. I mean it's real, right? It's basically a 20, 30% free lunch. You know, why wouldn't you, why wouldn't you go for it there? There's no downside. You know, there's no, "got you" or no catch. But we see Azure doing the same thing now, they're also building their own chips and we know that Google builds specialized machine learning chips, TPU, Tenor Processing Units. So their legs are focused on that. I don't think they can give up that or focused on higher levels if they had to pick bets. And I think actually in the next few years, most of us have to make more, we have to be more deliberate and calculated in the picks we do. I think in the last five years, most of us have said, "We'll do all of it." You know. >> Well you made a good bet with Spark, you know, the duke was pretty obvious trend that was, everyone was shut on that bandwagon and you guys picked a big bet with Spark. Look what happened with you guys? So again, I love this betting kind of concept because as the world matures, growth slows down and shifts and that next wave of value coming in, AKA customers, they're going to integrate with a new ecosystem. A new kind of partner network for AWS and the other clouds. But with aws they're going to need to nurture the next Databricks. They're going to need to still provide that SaaS, ISV like experience for, you know, a basic software hosting or some application. But I go to get your thoughts on this idea of multiple clouds because if I'm a developer, the old days was, old days, within our decade, full stack developer- >> It was two years ago, yeah (John laughing) >> This is a decade ago, full stack and then the cloud came in, you kind had the half stack and then you would do some things. It seems like the clouds are trying to say, we want to be the full stack or not. Or is it still going to be, you know, I'm an application like a PC and a Mac, I'm going to write the same application for both hardware. I mean what's your take on this? Are they trying to do full stack and you see them more like- >> Absolutely. I mean look, of course they're going, they have, I mean they have over 300, I think Amazon has over 300 services, right? That's not just compute, storage, networking, it's the whole stack, right? But my key point is, I think they have to nail the core infrastructure storage compute networking because the three clouds that are there competing, they're formidable companies with formidable balance sheets and it doesn't look like any of them is going to throw in the towel and say, we give up. So I think it's going to intensify. And given that they have a 70% revenue on that infrastructure layer, I think they, if they have to pick their bets, I think they'll focus it on that infrastructure layer. I think the layer above where they're also placing bets, they're doing that, the full stack, right? But there I think the demand will be, can you make that work on the other clouds? And therein lies an innovator's dilemma because if I make it work on the other clouds, then I'm foregoing that 70% revenue of the infrastructure. I'm not getting it. The other cloud vendor is going to get it. So should I do that or not? Second, is the other cloud vendor going to be welcoming of me making my service work on their cloud if I am a competing cloud, right? And what kind of terms of service are I giving me? And am I going to really invest in doing that? And I think right now we, you know, most, the vast, vast, vast majority of the services only work on the one cloud that you know, it's built on. It doesn't work on others, but this will shift. >> Yeah, I think the innovators dilemma is also very good point. And also add, it's an integrators dilemma too because now you talk about integration across services. So I believe that the super cloud movement's going to happen before Sky. And I think what explained by that, what you guys did and what other companies are doing by representing advanced, I call platform engineering, refactoring an existing market really fast, time to value and CAPEX is, I mean capital, market cap is going to be really fast. I think there's going to be an opportunity for those to emerge that's going to set the table for global multicloud ultimately in the future. So I think you're going to start to see the same pattern of what you guys did get in, leverage the hell out of it, use it, not in the way just to host, but to refactor and take down territory of markets. So number one, and then ultimately you get into, okay, I want to run some SLA across services, then there's a little bit more complication. I think that's where you guys put that beautiful paper out on Sky Computing. Okay, that makes sense. Now if you go to today's market, okay, I'm betting on Amazon because they're the best, this is the best cloud win scenario, not the most robust cloud. So if I'm a developer, I want the best. How do you look at their bet when it comes to data? Because now they've got machine learning, Swami's got a big keynote on Wednesday, I'm expecting to see a lot of AI and machine learning. I'm expecting to hear an end to end data story. This is what you do, so as a major partner, how do you view the moves Amazon's making and the bets they're making with data and machine learning and AI? >> First I want to lift off my hat to AWS for being customer obsessed. So I know that if a customer wants Databricks, I know that AWS and their sellers will actually help us get that customer deploy Databricks. Now which of the services is the customer going to pick? Are they going to pick ours or the end to end, what Swami is going to present on stage? Right? So that's the question we're getting. But I wanted to start with by just saying, their customer obsessed. So I think they're going to do the right thing for the customer and I see the evidence of it again and again and again. So kudos to them. They're amazing at this actually. Ultimately our bet is, customers want this to be simple, integrated, okay? So yes there are hundreds of services that together give you the end to end experience and they're very customizable that AWS gives you. But if you want just something simply integrated that also works across the clouds, then I think there's a special place for Databricks. And I think the lake house approach that we have, which is an integrated, completely integrated, we integrate data lakes with data warehouses, integrate workflows with machine learning, with real time processing, all these in one platform. I think there's going to be tailwinds because I think the most important thing that's going to happen in the next few years is that every customer is going to now be obsessed, given the recession and the environment we're in. How do I cut my costs? How do I cut my costs? And we learn this from the customers they're adopting the lake house because they're thinking, instead of using five vendors or three vendors, I can simplify it down to one with you and I can cut my cost. So I think that's going to be one of the main drivers of why people bet on the lake house because it helps them lower their TCO; Total Cost of Ownership. And it's as simple as that. Like I have three things right now. If I can get the same job done of those three with one, I'd rather do that. And by the way, if it's three or four across two clouds and I can just use one and it just works across two clouds, I'm going to do that. Because my boss is telling me I need to cut my budget. >> (indistinct) (John laughing) >> Yeah, and I'd rather not to do layoffs and they're asking me to do more. How can I get smaller budgets, not lay people off and do more? I have to cut, I have to optimize. What's happened in the last five, six years is there's been a huge sprawl of services and startups, you know, you know most of them, all these startups, all of them, all the activity, all the VC investments, well those companies sold their software, right? Even if a startup didn't make it big, you know, they still sold their software to some vendors. So the ecosystem is now full of lots and lots and lots and lots of different software. And right now people are looking, how do I consolidate, how do I simplify, how do I cut my costs? >> And you guys have a great solution. You're also an arms dealer and a innovator. So I have to ask this question, because you're a professor of the industry as well as at Berkeley, you've seen a lot of the historical innovations. If you look at the moment we're in right now with the recession, okay we had COVID, okay, it changed how people work, you know, people working at home, provisioning VLAN, all that (indistinct) infrastructure, okay, yeah, technology and cloud health. But we're in a recession. This is the first recession where the Amazon and the other cloud, mainly Amazon Web Services is a major economic puzzle in the piece. So they were never around before, even 2008, they were too small. They're now a major economic enabler, player, they're serving startups, enterprises, they have super clouds like you guys. They're a force and the people, their customers are cutting back but also they can also get faster. So agility is now an equation in the economic recovery. And I want to get your thoughts because you just brought that up. Customers can actually use the cloud and Databricks to actually get out of the recovery because no one's going to say, stop making profit or make more profit. So yeah, cut costs, be more efficient, but agility's also like, let's drive more revenue. So in this digital transformation, if you take this to conclusion, every company transforms, their company is the app. So their revenue is tied directly to their technology deployment. What's your reaction and comment to that because this is a new historical moment where cloud and scale and data, actually could be configured in a way to actually change the nature of a business in such a short time. And with the recession looming, no one's got time to wait. >> Yeah, absolutely. Look, the secular tailwind in the market is that of, you know, 10 years ago it was software is eating the world, now it's AI's going to eat all of software software. So more and more we're going to have, wherever you have software, which is everywhere now because it's eaten the world, it's going to be eaten up by AI and data. You know, AI doesn't exist without data so they're synonymous. You can't do machine learning if you don't have data. So yeah, you're going to see that everywhere and that automation will help people simplify things and cut down the costs and automate more things. And in the cloud you can also do that by changing your CAPEX to OPEX. So instead of I invest, you know, 10 million into a data center that I buy, I'm going to have headcount to manage the software. Why don't we change this to OPEX? And then they are going to optimize it. They want to lower the TCO because okay, it's in the cloud. but I do want the costs to be much lower that what they were in the previous years. Last five years, nobody cared. Who cares? You know what it costs. You know, there's a new brave world out there. Now there's like, no, it has to be efficient. So I think they're going to optimize it. And I think this lake house approach, which is an integration of the lakes and the warehouse, allows you to rationalize the two and simplify them. It allows you to basically rationalize away the data warehouse. So I think much faster we're going to see the, why do I need the data warehouse? If I can get the same thing done with the lake house for fraction of the cost, that's what's going to happen. I think there's going to be focus on that simplification. But I agree with you. Ultimately everyone knows, everybody's a software company. Every company out there is a software company and in the next 10 years, all of them are also going to be AI companies. So that is going to continue. >> (indistinct), dev's going to stop. And right sizing right now is a key economic forcing function. Final question for you and I really appreciate you taking the time. This year Reinvent, what's the bumper sticker in your mind around what's the most important industry dynamic, power dynamic, ecosystem dynamic that people should pay attention to as we move from the brave new world of okay, I see cloud, cloud operations. I need to really make it structurally change my business. How do I, what's the most important story? What's the bumper sticker in your mind for Reinvent? >> Bumper sticker? lake house 24. (John laughing) >> That's data (indistinct) bumper sticker. What's the- >> (indistinct) in the market. No, no, no, no. You know, it's, AWS talks about, you know, all of their services becoming a lake house because they want the center of the gravity to be S3, their lake. And they want all the services to directly work on that, so that's a lake house. We're Bumper see Microsoft with Synapse, modern, you know the modern intelligent data platform. Same thing there. We're going to see the same thing, we already seeing it on GCP with Big Lake and so on. So I actually think it's the how do I reduce my costs and the lake house integrates those two. So that's one of the main ways you can rationalize and simplify. You get in the lake house, which is the name itself is a (indistinct) of two things, right? Lake house, "lake" gives you the AI, "house" give you the database data warehouse. So you get your AI and you get your data warehousing in one place at the lower cost. So for me, the bumper sticker is lake house, you know, 24. >> All right. Awesome Ali, well thanks for the exclusive interview. Appreciate it and get to see you. Congratulations on your success and I know you guys are going to be fine. >> Awesome. Thank you John. It's always a pleasure. >> Always great to chat with you again. >> Likewise. >> You guys are a great team. We're big fans of what you guys have done. We think you're an example of what we call "super cloud." Which is getting the hype up and again your paper speaks to some of the innovation, which I agree with by the way. I think that that approach of not forcing standards is really smart. And I think that's absolutely correct, that having the market still innovate is going to be key. standards with- >> Yeah, I love it. We're big fans too, you know, you're doing awesome work. We'd love to continue the partnership. >> So, great, great Ali, thanks. >> Take care (outro music)

(outro music) >> Hey, I'm John Furrier, here with an exclusive interview with Ali Ghodsi, who's the CEO of Databricks. Ali, great to see you. Preview for reinvent. We're going to launch this story, exclusive Databricks material on the notes, after the keynotes prior to the keynotes and after the keynotes that reinvent. So great to see you. You know, you've been a partner of AWS for a very, very long time. I think five years ago, I think I first interviewed you, you were one of the first to publicly declare that this was a place to build a company on and not just post an application, but refactor capabilities to create, essentially a platform in the cloud, on the cloud. Not just an ISV; Independent Software Vendor, kind of an old term, we're talking about real platform like capability to change the game. Can you talk about your experience as an AWS partner? >> Yeah, look, so we started in 2013. I swiped my personal credit card on AWS and some of my co-founders did the same. And we started building. And we were excited because we just thought this is a much better way to launch a company because you can just much faster get time to market and launch your thing and you can get the end users much quicker access to the thing you're building. So we didn't really talk to anyone at AWS, we just swiped a credit card. And eventually they told us, "Hey, do you want to buy extra support?" "You're asking a lot of advanced questions from us." "Maybe you want to buy our advanced support." And we said, no, no, no, no. We're very advanced ourselves, we know what we're doing. We're not going to buy any advanced support. So, you know, we just built this, you know, startup from nothing on AWS without even talking to anyone there. So at some point, I think around 2017, they suddenly saw this company with maybe a hundred million ARR pop up on their radar and it's driving massive amounts of compute, massive amounts of data. And it took a little bit in the beginning just us to get to know each other because as I said, it's like we were not on their radar and we weren't really looking, we were just doing our thing. And then over the years the partnership has deepened and deepened and deepened and then with, you know, Andy (indistinct) really leaning into the partnership, he mentioned us at Reinvent. And then we sort of figured out a way to really integrate the two service, the Databricks platform with AWS . And today it's an amazing partnership. You know, we directly connected with the general managers for the services. We're connected at the CEO level, you know, the sellers get compensated for pushing Databricks, we're, we have multiple offerings on their marketplace. We have a native offering on AWS. You know, we're prominently always sort of marketed and you know, we're aligned also vision wise in what we're trying to do. So yeah, we've come a very, very long way. >> Do you consider yourself a SaaS app or an ISV or do you see yourself more of a platform company because you have customers. How would you categorize your category as a company? >> Well, it's a data platform, right? And actually the, the strategy of the Databricks is take what's otherwise five, six services in the industry or five, six different startups, but do them as part of one data platform that's integrated. So in one word, the strategy of data bricks is "unification." We call it the data lake house. But really the idea behind the data lake house is that of unification, or in more words it's, "The whole is greater than the sum of its parts." So you could actually go and buy five, six services out there or actually use five, six services from the cloud vendors, stitch it together and it kind of resembles Databricks. Our power is in doing those integrated, together in a way in which it's really, really easy and simple to use for end users. So yeah, we're a data platform. I wouldn't, you know, ISV that's a old term, you know, Independent Software Vendor. You know, I think, you know, we have actually a whole slew of ISVs on top of Databricks, that integrate with our platform. And you know, in our marketplace as well as in our partner connect, we host those ISVs that then, you know, work on top of the data that we have in the Databricks, data lake house. >> You know, I think one of the things your journey has been great to document and watch from the beginning. I got to give you guys credit over there and props, congratulations. But I think you're the poster child as a company to what we see enterprises doing now. So go back in time when you guys swiped a credit card, you didn't need attending technical support because you guys had brains, you were refactoring, rethinking. It wasn't just banging out software, you had, you were doing some complex things. It wasn't like it was just write some software hosted on server. It was really a lot more. And as a result your business worth billions of dollars. I think 38 billion or something like that, big numbers, big numbers of great revenue growth as well, billions in revenue. You have customers, you have an ecosystem, you have data applications on top of Databricks. So in a way you're a cloud on top of the cloud. So is there a cloud on top of the cloud? So you have ISVs, Amazon has ISVs. Can you take us through what this means and at this point in history, because this seems to be an advanced version of benefits of platforming and refactoring, leveraging say AWS. >> Yeah, so look, when we started, there was really only one game in town. It was AWS. So it was one cloud. And the strategy of the company then was, well Amazon had this beautiful set of services that they're building bottom up, they have storage, compute, networking, and then they have databases and so on. But it's a lot of services. So let us not directly compete with AWS and try to take out one of their services. Let's not do that because frankly we can't. We were not of that size. They had the scale, they had the size and they were the only cloud vendor in town. So our strategy instead was, let's do something else. Let's not compete directly with say, a particular service they're building, let's take a different strategy. What if we had a unified holistic data platform, where it's just one integrated service end to end. So think of it as Microsoft office, which contains PowerPoint, and Word, and Excel and even Access, if you want to use it. What if we build that and AWS has this really amazing knack for releasing things, you know services, lots of them, every reinvent. And they're sort of a DevOps person's dream and you can stitch these together and you know you have to be technical. How do we elevate that and make it simpler and integrate it? That was our original strategy and it resonated with a segment of the market. And the reason it worked with AWS so that we wouldn't butt heads with AWS was because we weren't a direct replacement for this service or for that service, we were taking a different approach. And AWS, because credit goes to them, they're so customer obsessed, they would actually do what's right for the customer. So if the customer said we want this unified thing, their sellers would actually say, okay, so then you should use Databricks. So they truly are customer obsessed in that way. And I really mean it, John. Things have changed over the years. They're not the only cloud anymore. You know, Azure is real, GCP is real, there's also Alibaba. And now over 70% of our customers are on more than one cloud. So now what we hear from them is, not only want, do we want a simplified, unified thing, but we want it also to work across the clouds. Because those of them that are seriously considering multiple clouds, they don't want to use a service on cloud one and then use a similar service on cloud two. But it's a little bit different. And now they have to do twice the work to make it work. You know, John, it's hard enough as it is, like it's this data stuff and analytics. It's not a walk in the park, you know. You hire an administrator in the back office that clicks a button and its just, now you're a data driven digital transformed company. It's hard. If you now have to do it again on the second cloud with different set of services and then again on a third cloud with a different set of services. That's very, very costly. So the strategy then has changed that, how do we take that unified simple approach and make it also the same and standardize across the clouds, but then also integrate it as far down as we can on each of the clouds. So that you're not giving up any of the benefits that the particular cloud has. >> Yeah, I think one of the things that we see, and I want get your reaction to this, is this rise of the super cloud as we call it. I think you were involved in the Sky paper that I saw your position paper came out after we had introduced Super Cloud, which is great. Congratulations to the Berkeley team, wearing the hat here. But you guys are, I think a driver of this because you're creating the need for these things. You're saying, okay, we went on one cloud with AWS and you didn't hide that. And now you're publicly saying there's other clouds too, increased ham for your business. And customers have multiple clouds in their infrastructure for the best of breed that they have. Okay, get that. But there's still a challenge around the innovation, growth that's still around the corner. We still have a supply chain problem, we still have skill gaps. You know, you guys are unique at Databricks as other these big examples of super clouds that are developing. Enterprises don't have the Databricks kind of talent. They need, they need turnkey solutions. So Adam and the team at Amazon are promoting, you know, more solution oriented approaches higher up on the stack. You're starting to see kind of like, I won't say templates, but you know, almost like application specific headless like, low code, no code capability to accelerate clients who are wanting to write code for the modern error. Right, so this kind of, and then now you, as you guys pointed out with these common services, you're pushing the envelope. So you're saying, hey, I need to compete, I don't want to go to my customers and have them to have a staff or this cloud and this cloud and this cloud because they don't have the staff. Or if they do, they're very unique. So what's your reaction? Because this kind is the, it kind of shows your leadership as a partner of AWS and the clouds, but also highlights I think what's coming. But you share your reaction. >> Yeah, look, it's, first of all, you know, I wish I could take credit for this but I can't because it's really the customers that have decided to go on multiple clouds. You know, it's not Databricks that you know, push this or some other vendor, you know, that, Snowflake or someone who pushed this and now enterprises listened to us and they picked two clouds. That's not how it happened. The enterprises picked two clouds or three clouds themselves and we can get into why, but they did that. So this largely just happened in the market. We as data platforms responded to what they're then saying, which is they're saying, "I don't want to redo this again on the other cloud." So I think the writing is on the wall. I think it's super obvious what's going to happen next. They will say, "Any service I'm using, it better work exactly the same on all the clouds." You know, that's what's going to happen. So in the next five years, every enterprise will say, "I'm going to use the service, but you better make sure that this service works equally well on all of the clouds." And obviously the multicloud vendors like us, are there to do that. But I actually think that what you're going to see happening is that you're going to see the cloud vendors changing the existing services that they have to make them work on the other clouds. That's what's goin to happen, I think. >> Yeah, and I think I would add that, first of all, I agree with you. I think that's going to be a forcing function. Because I think you're driving it. You guys are in a way, one, are just an actor in the driving this because you're on the front end of this and there are others and there will be people following. But I think to me, I'm a cloud vendor, I got to differentiate. Adam, If I'm Adam Saleski, I got to say, "Hey, I got to differentiate." So I don't wan to get stuck in the middle, so to speak. Am I just going to innovate on the hardware AKA infrastructure or am I going to innovate at the higher level services? So what we're talking about here is the tail of two clouds within Amazon, for instance. So do I innovate on the silicon and get low level into the physics and squeeze performance out of the hardware and infrastructure? Or do I focus on ease of use at the top of the stack for the developers? So again, there's a channel of two clouds here. So I got to ask you, how do they differentiate? Number one and number two, I never heard a developer ever say, "I want to run my app or workload on the slower cloud." So I mean, you know, back when we had PCs you wanted to go, "I want the fastest processor." So again, you can have common level services, but where is that performance differentiation with the cloud? What do the clouds do in your opinion? >> Yeah, look, I think it's pretty clear. I think that it's, this is, you know, no surprise. Probably 70% or so of the revenue is in the lower infrastructure layers, compute, storage, networking. And they have to win that. They have to be competitive there. As you said, you can say, oh you know, I guess my CPUs are slower than the other cloud, but who cares? I have amazing other services which only work on my cloud by the way, right? That's not going to be a winning recipe. So I think all three are laser focused on, we going to have specialized hardware and the nuts and bolts of the infrastructure, we can do it better than the other clouds for sure. And you can see lots of innovation happening there, right? The Graviton chips, you know, we see huge price performance benefits in those chips. I mean it's real, right? It's basically a 20, 30% free lunch. You know, why wouldn't you, why wouldn't you go for it there? There's no downside. You know, there's no, "got you" or no catch. But we see Azure doing the same thing now, they're also building their own chips and we know that Google builds specialized machine learning chips, TPU, Tenor Processing Units. So their legs are focused on that. I don't think they can give up that or focused on higher levels if they had to pick bets. And I think actually in the next few years, most of us have to make more, we have to be more deliberate and calculated in the picks we do. I think in the last five years, most of us have said, "We'll do all of it." You know. >> Well you made a good bet with Spark, you know, the duke was pretty obvious trend that was, everyone was shut on that bandwagon and you guys picked a big bet with Spark. Look what happened with you guys? So again, I love this betting kind of concept because as the world matures, growth slows down and shifts and that next wave of value coming in, AKA customers, they're going to integrate with a new ecosystem. A new kind of partner network for AWS and the other clouds. But with aws they're going to need to nurture the next Databricks. They're going to need to still provide that SaaS, ISV like experience for, you know, a basic software hosting or some application. But I go to get your thoughts on this idea of multiple clouds because if I'm a developer, the old days was, old days, within our decade, full stack developer- >> It was two years ago, yeah (John laughing) >> This is a decade ago, full stack and then the cloud came in, you kind had the half stack and then you would do some things. It seems like the clouds are trying to say, we want to be the full stack or not. Or is it still going to be, you know, I'm an application like a PC and a Mac, I'm going to write the same application for both hardware. I mean what's your take on this? Are they trying to do full stack and you see them more like- >> Absolutely. I mean look, of course they're going, they have, I mean they have over 300, I think Amazon has over 300 services, right? That's not just compute, storage, networking, it's the whole stack, right? But my key point is, I think they have to nail the core infrastructure storage compute networking because the three clouds that are there competing, they're formidable companies with formidable balance sheets and it doesn't look like any of them is going to throw in the towel and say, we give up. So I think it's going to intensify. And given that they have a 70% revenue on that infrastructure layer, I think they, if they have to pick their bets, I think they'll focus it on that infrastructure layer. I think the layer above where they're also placing bets, they're doing that, the full stack, right? But there I think the demand will be, can you make that work on the other clouds? And therein lies an innovator's dilemma because if I make it work on the other clouds, then I'm foregoing that 70% revenue of the infrastructure. I'm not getting it. The other cloud vendor is going to get it. So should I do that or not? Second, is the other cloud vendor going to be welcoming of me making my service work on their cloud if I am a competing cloud, right? And what kind of terms of service are I giving me? And am I going to really invest in doing that? And I think right now we, you know, most, the vast, vast, vast majority of the services only work on the one cloud that you know, it's built on. It doesn't work on others, but this will shift. >> Yeah, I think the innovators dilemma is also very good point. And also add, it's an integrators dilemma too because now you talk about integration across services. So I believe that the super cloud movement's going to happen before Sky. And I think what explained by that, what you guys did and what other companies are doing by representing advanced, I call platform engineering, refactoring an existing market really fast, time to value and CAPEX is, I mean capital, market cap is going to be really fast. I think there's going to be an opportunity for those to emerge that's going to set the table for global multicloud ultimately in the future. So I think you're going to start to see the same pattern of what you guys did get in, leverage the hell out of it, use it, not in the way just to host, but to refactor and take down territory of markets. So number one, and then ultimately you get into, okay, I want to run some SLA across services, then there's a little bit more complication. I think that's where you guys put that beautiful paper out on Sky Computing. Okay, that makes sense. Now if you go to today's market, okay, I'm betting on Amazon because they're the best, this is the best cloud win scenario, not the most robust cloud. So if I'm a developer, I want the best. How do you look at their bet when it comes to data? Because now they've got machine learning, Swami's got a big keynote on Wednesday, I'm expecting to see a lot of AI and machine learning. I'm expecting to hear an end to end data story. This is what you do, so as a major partner, how do you view the moves Amazon's making and the bets they're making with data and machine learning and AI? >> First I want to lift off my hat to AWS for being customer obsessed. So I know that if a customer wants Databricks, I know that AWS and their sellers will actually help us get that customer deploy Databricks. Now which of the services is the customer going to pick? Are they going to pick ours or the end to end, what Swami is going to present on stage? Right? So that's the question we're getting. But I wanted to start with by just saying, their customer obsessed. So I think they're going to do the right thing for the customer and I see the evidence of it again and again and again. So kudos to them. They're amazing at this actually. Ultimately our bet is, customers want this to be simple, integrated, okay? So yes there are hundreds of services that together give you the end to end experience and they're very customizable that AWS gives you. But if you want just something simply integrated that also works across the clouds, then I think there's a special place for Databricks. And I think the lake house approach that we have, which is an integrated, completely integrated, we integrate data lakes with data warehouses, integrate workflows with machine learning, with real time processing, all these in one platform. I think there's going to be tailwinds because I think the most important thing that's going to happen in the next few years is that every customer is going to now be obsessed, given the recession and the environment we're in. How do I cut my costs? How do I cut my costs? And we learn this from the customers they're adopting the lake house because they're thinking, instead of using five vendors or three vendors, I can simplify it down to one with you and I can cut my cost. So I think that's going to be one of the main drivers of why people bet on the lake house because it helps them lower their TCO; Total Cost of Ownership. And it's as simple as that. Like I have three things right now. If I can get the same job done of those three with one, I'd rather do that. And by the way, if it's three or four across two clouds and I can just use one and it just works across two clouds, I'm going to do that. Because my boss is telling me I need to cut my budget. >> (indistinct) (John laughing) >> Yeah, and I'd rather not to do layoffs and they're asking me to do more. How can I get smaller budgets, not lay people off and do more? I have to cut, I have to optimize. What's happened in the last five, six years is there's been a huge sprawl of services and startups, you know, you know most of them, all these startups, all of them, all the activity, all the VC investments, well those companies sold their software, right? Even if a startup didn't make it big, you know, they still sold their software to some vendors. So the ecosystem is now full of lots and lots and lots and lots of different software. And right now people are looking, how do I consolidate, how do I simplify, how do I cut my costs? >> And you guys have a great solution. You're also an arms dealer and a innovator. So I have to ask this question, because you're a professor of the industry as well as at Berkeley, you've seen a lot of the historical innovations. If you look at the moment we're in right now with the recession, okay we had COVID, okay, it changed how people work, you know, people working at home, provisioning VLAN, all that (indistinct) infrastructure, okay, yeah, technology and cloud health. But we're in a recession. This is the first recession where the Amazon and the other cloud, mainly Amazon Web Services is a major economic puzzle in the piece. So they were never around before, even 2008, they were too small. They're now a major economic enabler, player, they're serving startups, enterprises, they have super clouds like you guys. They're a force and the people, their customers are cutting back but also they can also get faster. So agility is now an equation in the economic recovery. And I want to get your thoughts because you just brought that up. Customers can actually use the cloud and Databricks to actually get out of the recovery because no one's going to say, stop making profit or make more profit. So yeah, cut costs, be more efficient, but agility's also like, let's drive more revenue. So in this digital transformation, if you take this to conclusion, every company transforms, their company is the app. So their revenue is tied directly to their technology deployment. What's your reaction and comment to that because this is a new historical moment where cloud and scale and data, actually could be configured in a way to actually change the nature of a business in such a short time. And with the recession looming, no one's got time to wait. >> Yeah, absolutely. Look, the secular tailwind in the market is that of, you know, 10 years ago it was software is eating the world, now it's AI's going to eat all of software software. So more and more we're going to have, wherever you have software, which is everywhere now because it's eaten the world, it's going to be eaten up by AI and data. You know, AI doesn't exist without data so they're synonymous. You can't do machine learning if you don't have data. So yeah, you're going to see that everywhere and that automation will help people simplify things and cut down the costs and automate more things. And in the cloud you can also do that by changing your CAPEX to OPEX. So instead of I invest, you know, 10 million into a data center that I buy, I'm going to have headcount to manage the software. Why don't we change this to OPEX? And then they are going to optimize it. They want to lower the TCO because okay, it's in the cloud. but I do want the costs to be much lower that what they were in the previous years. Last five years, nobody cared. Who cares? You know what it costs. You know, there's a new brave world out there. Now there's like, no, it has to be efficient. So I think they're going to optimize it. And I think this lake house approach, which is an integration of the lakes and the warehouse, allows you to rationalize the two and simplify them. It allows you to basically rationalize away the data warehouse. So I think much faster we're going to see the, why do I need the data warehouse? If I can get the same thing done with the lake house for fraction of the cost, that's what's going to happen. I think there's going to be focus on that simplification. But I agree with you. Ultimately everyone knows, everybody's a software company. Every company out there is a software company and in the next 10 years, all of them are also going to be AI companies. So that is going to continue. >> (indistinct), dev's going to stop. And right sizing right now is a key economic forcing function. Final question for you and I really appreciate you taking the time. This year Reinvent, what's the bumper sticker in your mind around what's the most important industry dynamic, power dynamic, ecosystem dynamic that people should pay attention to as we move from the brave new world of okay, I see cloud, cloud operations. I need to really make it structurally change my business. How do I, what's the most important story? What's the bumper sticker in your mind for Reinvent? >> Bumper sticker? lake house 24. (John laughing) >> That's data (indistinct) bumper sticker. What's the- >> (indistinct) in the market. No, no, no, no. You know, it's, AWS talks about, you know, all of their services becoming a lake house because they want the center of the gravity to be S3, their lake. And they want all the services to directly work on that, so that's a lake house. We're Bumper see Microsoft with Synapse, modern, you know the modern intelligent data platform. Same thing there. We're going to see the same thing, we already seeing it on GCP with Big Lake and so on. So I actually think it's the how do I reduce my costs and the lake house integrates those two. So that's one of the main ways you can rationalize and simplify. You get in the lake house, which is the name itself is a (indistinct) of two things, right? Lake house, "lake" gives you the AI, "house" give you the database data warehouse. So you get your AI and you get your data warehousing in one place at the lower cost. So for me, the bumper sticker is lake house, you know, 24. >> All right. Awesome Ali, well thanks for the exclusive interview. Appreciate it and get to see you. Congratulations on your success and I know you guys are going to be fine. >> Awesome. Thank you John. It's always a pleasure. >> Always great to chat with you again. >> Likewise. >> You guys are a great team. We're big fans of what you guys have done. We think you're an example of what we call "super cloud." Which is getting the hype up and again your paper speaks to some of the innovation, which I agree with by the way. I think that that approach of not forcing standards is really smart. And I think that's absolutely correct, that having the market still innovate is going to be key. standards with- >> Yeah, I love it. We're big fans too, you know, you're doing awesome work. We'd love to continue the partnership. >> So, great, great Ali, thanks. >> Take care (outro music)