(upbeat music) >> Welcome everyone to theCUBE's presentation of the AWS Startup Showcase AI Machine Learning Top Startups Building Generative AI on AWS. This is season 3, episode 1 of the ongoing series covering the exciting startup from the AWS ecosystem to talk about AI and machine learning. I'm your host, John Furrier. I'm joined by two great guests here, Adam Wenchel, who's the CEO of Arthur, and Chief Scientist of Arthur, John Dickerson. Talk about how they help people build better LLM AI systems to get them into the market faster. Gentlemen, thank you for coming on. >> Yeah, thanks for having us, John. >> Well, I got to say I got to temper my enthusiasm because the last few months explosion of interest in LLMs with ChatGPT, has opened the eyes to everybody around the reality of that this is going next gen, this is it, this is the moment, this is the the point we're going to look back and say, this is the time where AI really hit the scene for real applications. So, a lot of Large Language Models, also known as LLMs, foundational models, and generative AI is all booming. This is where all the alpha developers are going. This is where everyone's focusing their business model transformations on. This is where developers are seeing action. So it's all happening, the wave is here. So I got to ask you guys, what are you guys seeing right now? You're in the middle of it, it's hitting you guys right on. You're in the front end of this massive wave. >> Yeah, John, I don't think you have to temper your enthusiasm at all. I mean, what we're seeing every single day is, everything from existing enterprise customers coming in with new ways that they're rethinking, like business things that they've been doing for many years that they can now do an entirely different way, as well as all manner of new companies popping up, applying LLMs to everything from generating code and SQL statements to generating health transcripts and just legal briefs. Everything you can imagine. And when you actually sit down and look at these systems and the demos we get of them, the hype is definitely justified. It's pretty amazing what they're going to do. And even just internally, we built, about a month ago in January, we built an Arthur chatbot so customers could ask questions, technical questions from our, rather than read our product documentation, they could just ask this LLM a particular question and get an answer. And at the time it was like state of the art, but then just last week we decided to rebuild it because the tooling has changed so much that we, last week, we've completely rebuilt it. It's now way better, built on an entirely different stack. And the tooling has undergone a full generation worth of change in six weeks, which is crazy. So it just tells you how much energy is going into this and how fast it's evolving right now. >> John, weigh in as a chief scientist. I mean, you must be blown away. Talk about kid in the candy store. I mean, you must be looking like this saying, I mean, she must be super busy to begin with, but the change, the acceleration, can you scope the kind of change you're seeing and be specific around the areas you're seeing movement and highly accelerated change? >> Yeah, definitely. And it is very, very exciting actually, thinking back to when ChatGPT was announced, that was a night our company was throwing an event at NeurIPS, which is maybe the biggest machine learning conference out there. And the hype when that happened was palatable and it was just shocking to see how well that performed. And then obviously over the last few months since then, as LLMs have continued to enter the market, we've seen use cases for them, like Adam mentioned all over the place. And so, some things I'm excited about in this space are the use of LLMs and more generally, foundation models to redesign traditional operations, research style problems, logistics problems, like auctions, decisioning problems. So moving beyond the already amazing news cases, like creating marketing content into more core integration and a lot of the bread and butter companies and tasks that drive the American ecosystem. And I think we're just starting to see some of that. And in the next 12 months, I think we're going to see a lot more. If I had to make other predictions, I think we're going to continue seeing a lot of work being done on managing like inference time costs via shrinking models or distillation. And I don't know how to make this prediction, but at some point we're going to be seeing lots of these very large scale models operating on the edge as well. So the time scales are extremely compressed, like Adam mentioned, 12 months from now, hard to say. >> We were talking on theCUBE prior to this session here. We had theCUBE conversation here and then the Wall Street Journal just picked up on the same theme, which is the printing press moment created the enlightenment stage of the history. Here we're in the whole nother automating intellect efficiency, doing heavy lifting, the creative class coming back, a whole nother level of reality around the corner that's being hyped up. The question is, is this justified? Is there really a breakthrough here or is this just another result of continued progress with AI? Can you guys weigh in, because there's two schools of thought. There's the, "Oh my God, we're entering a new enlightenment tech phase, of the equivalent of the printing press in all areas. Then there's, Ah, it's just AI (indistinct) inch by inch. What's your guys' opinion? >> Yeah, I think on the one hand when you're down in the weeds of building AI systems all day, every day, like we are, it's easy to look at this as an incremental progress. Like we have customers who've been building on foundation models since we started the company four years ago, particular in computer vision for classification tasks, starting with pre-trained models, things like that. So that part of it doesn't feel real new, but what does feel new is just when you apply these things to language with all the breakthroughs and computational efficiency, algorithmic improvements, things like that, when you actually sit down and interact with ChatGPT or one of the other systems that's out there that's building on top of LLMs, it really is breathtaking, like, the level of understanding that they have and how quickly you can accelerate your development efforts and get an actual working system in place that solves a really important real world problem and makes people way faster, way more efficient. So I do think there's definitely something there. It's more than just incremental improvement. This feels like a real trajectory inflection point for the adoption of AI. >> John, what's your take on this? As people come into the field, I'm seeing a lot of people move from, hey, I've been coding in Python, I've been doing some development, I've been a software engineer, I'm a computer science student. I'm coding in C++ old school, OG systems person. Where do they come in? Where's the focus, where's the action? Where are the breakthroughs? Where are people jumping in and rolling up their sleeves and getting dirty with this stuff? >> Yeah, all over the place. And it's funny you mentioned students in a different life. I wore a university professor hat and so I'm very, very familiar with the teaching aspects of this. And I will say toward Adam's point, this really is a leap forward in that techniques like in a co-pilot for example, everybody's using them right now and they really do accelerate the way that we develop. When I think about the areas where people are really, really focusing right now, tooling is certainly one of them. Like you and I were chatting about LangChain right before this interview started, two or three people can sit down and create an amazing set of pipes that connect different aspects of the LLM ecosystem. Two, I would say is in engineering. So like distributed training might be one, or just understanding better ways to even be able to train large models, understanding better ways to then distill them or run them. So like this heavy interaction now between engineering and what I might call traditional machine learning from 10 years ago where you had to know a lot of math, you had to know calculus very well, things like that. Now you also need to be, again, a very strong engineer, which is exciting. >> I interviewed Swami when he talked about the news. He's ahead of Amazon's machine learning and AI when they announced Hugging Face announcement. And I reminded him how Amazon was easy to get into if you were developing a startup back in 2007,8, and that the language models had that similar problem. It's step up a lot of content and a lot of expense to get provisioned up, now it's easy. So this is the next wave of innovation. So how do you guys see that from where we are right now? Are we at that point where it's that moment where it's that cloud-like experience for LLMs and large language models? >> Yeah, go ahead John. >> I think the answer is yes. We see a number of large companies that are training these and serving these, some of which are being co-interviewed in this episode. I think we're at that. Like, you can hit one of these with a simple, single line of Python, hitting an API, you can boot this up in seconds if you want. It's easy. >> Got it. >> So I (audio cuts out). >> Well let's take a step back and talk about the company. You guys being featured here on the Showcase. Arthur, what drove you to start the company? How'd this all come together? What's the origination story? Obviously you got a big customers, how'd get started? What are you guys doing? How do you make money? Give a quick overview. >> Yeah, I think John and I come at it from slightly different angles, but for myself, I have been a part of a number of technology companies. I joined Capital One, they acquired my last company and shortly after I joined, they asked me to start their AI team. And so even though I've been doing AI for a long time, I started my career back in DARPA. It was the first time I was really working at scale in AI at an organization where there were hundreds of millions of dollars in revenue at stake with the operation of these models and that they were impacting millions of people's financial livelihoods. And so it just got me hyper-focused on these issues around making sure that your AI worked well and it worked well for your company and it worked well for the people who were being affected by it. At the time when I was doing this 2016, 2017, 2018, there just wasn't any tooling out there to support this production management model monitoring life phase of the life cycle. And so we basically left to start the company that I wanted. And John has a his own story. I'll let let you share that one, John. >> Go ahead John, you're up. >> Yeah, so I'm coming at this from a different world. So I'm on leave now from a tenured role in academia where I was leading a large lab focusing on the intersection of machine learning and economics. And so questions like fairness or the response to the dynamism on the underlying environment have been around for quite a long time in that space. And so I've been thinking very deeply about some of those more like R and D style questions as well as having deployed some automation code across a couple of different industries, some in online advertising, some in the healthcare space and so on, where concerns of, again, fairness come to bear. And so Adam and I connected to understand the space of what that might look like in the 2018 20 19 realm from a quantitative and from a human-centered point of view. And so booted things up from there. >> Yeah, bring that applied engineering R and D into the Capital One, DNA that he had at scale. I could see that fit. I got to ask you now, next step, as you guys move out and think about LLMs and the recent AI news around the generative models and the foundational models like ChatGPT, how should we be looking at that news and everyone watching might be thinking the same thing. I know at the board level companies like, we should refactor our business, this is the future. It's that kind of moment, and the tech team's like, okay, boss, how do we do this again? Or are they prepared? How should we be thinking? How should people watching be thinking about LLMs? >> Yeah, I think they really are transformative. And so, I mean, we're seeing companies all over the place. Everything from large tech companies to a lot of our large enterprise customers are launching significant projects at core parts of their business. And so, yeah, I would be surprised, if you're serious about becoming an AI native company, which most leading companies are, then this is a trend that you need to be taking seriously. And we're seeing the adoption rate. It's funny, I would say the AI adoption in the broader business world really started, let's call it four or five years ago, and it was a relatively slow adoption rate, but I think all that kind of investment in and scaling the maturity curve has paid off because the rate at which people are adopting and deploying systems based on this is tremendous. I mean, this has all just happened in the few months and we're already seeing people get systems into production. So, now there's a lot of things you have to guarantee in order to put these in production in a way that basically is added into your business and doesn't cause more headaches than it solves. And so that's where we help customers is where how do you put these out there in a way that they're going to represent your company well, they're going to perform well, they're going to do their job and do it properly. >> So in the use case, as a customer, as I think about this, there's workflows. They might have had an ML AI ops team that's around IT. Their inference engines are out there. They probably don't have a visibility on say how much it costs, they're kicking the tires. When you look at the deployment, there's a cost piece, there's a workflow piece, there's fairness you mentioned John, what should be, I should be thinking about if I'm going to be deploying stuff into production, I got to think about those things. What's your opinion? >> Yeah, I'm happy to dive in on that one. So monitoring in general is extremely important once you have one of these LLMs in production, and there have been some changes versus traditional monitoring that we can dive deeper into that LLMs are really accelerated. But a lot of that bread and butter style of things you should be looking out for remain just as important as they are for what you might call traditional machine learning models. So the underlying environment of data streams, the way users interact with these models, these are all changing over time. And so any performance metrics that you care about, traditional ones like an accuracy, if you can define that for an LLM, ones around, for example, fairness or bias. If that is a concern for your particular use case and so on. Those need to be tracked. Now there are some interesting changes that LLMs are bringing along as well. So most ML models in production that we see are relatively static in the sense that they're not getting flipped in more than maybe once a day or once a week or they're just set once and then not changed ever again. With LLMs, there's this ongoing value alignment or collection of preferences from users that is often constantly updating the model. And so that opens up all sorts of vectors for, I won't say attack, but for problems to arise in production. Like users might learn to use your system in a different way and thus change the way those preferences are getting collected and thus change your system in ways that you never intended. So maybe that went through governance already internally at the company and now it's totally, totally changed and it's through no fault of your own, but you need to be watching over that for sure. >> Talk about the reinforced learnings from human feedback. How's that factoring in to the LLMs? Is that part of it? Should people be thinking about that? Is that a component that's important? >> It certainly is, yeah. So this is one of the big tweaks that happened with InstructGPT, which is the basis model behind ChatGPT and has since gone on to be used all over the place. So value alignment I think is through RLHF like you mentioned is a very interesting space to get into and it's one that you need to watch over. Like, you're asking humans for feedback over outputs from a model and then you're updating the model with respect to that human feedback. And now you've thrown humans into the loop here in a way that is just going to complicate things. And it certainly helps in many ways. You can ask humans to, let's say that you're deploying an internal chat bot at an enterprise, you could ask humans to align that LLM behind the chatbot to, say company values. And so you're listening feedback about these company values and that's going to scoot that chatbot that you're running internally more toward the kind of language that you'd like to use internally on like a Slack channel or something like that. Watching over that model I think in that specific case, that's a compliance and HR issue as well. So while it is part of the greater LLM stack, you can also view that as an independent bit to watch over. >> Got it, and these are important factors. When people see the Bing news, they freak out how it's doing great. Then it goes off the rails, it goes big, fails big. (laughing) So these models people see that, is that human interaction or is that feedback, is that not accepting it or how do people understand how to take that input in and how to build the right apps around LLMs? This is a tough question. >> Yeah, for sure. So some of the examples that you'll see online where these chatbots go off the rails are obviously humans trying to break the system, but some of them clearly aren't. And that's because these are large statistical models and we don't know what's going to pop out of them all the time. And even if you're doing as much in-house testing at the big companies like the Go-HERE's and the OpenAI's of the world, to try to prevent things like toxicity or racism or other sorts of bad content that might lead to bad pr, you're never going to catch all of these possible holes in the model itself. And so, again, it's very, very important to keep watching over that while it's in production. >> On the business model side, how are you guys doing? What's the approach? How do you guys engage with customers? Take a minute to explain the customer engagement. What do they need? What do you need? How's that work? >> Yeah, I can talk a little bit about that. So it's really easy to get started. It's literally a matter of like just handing out an API key and people can get started. And so we also offer alternative, we also offer versions that can be installed on-prem for models that, we find a lot of our customers have models that deal with very sensitive data. So you can run it in your cloud account or use our cloud version. And so yeah, it's pretty easy to get started with this stuff. We find people start using it a lot of times during the validation phase 'cause that way they can start baselining performance models, they can do champion challenger, they can really kind of baseline the performance of, maybe they're considering different foundation models. And so it's a really helpful tool for understanding differences in the way these models perform. And then from there they can just flow that into their production inferencing, so that as these systems are out there, you have really kind of real time monitoring for anomalies and for all sorts of weird behaviors as well as that continuous feedback loop that helps you make make your product get better and observability and you can run all sorts of aggregated reports to really understand what's going on with these models when they're out there deciding. I should also add that we just today have another way to adopt Arthur and that is we are in the AWS marketplace, and so we are available there just to make it that much easier to use your cloud credits, skip the procurement process, and get up and running really quickly. >> And that's great 'cause Amazon's got SageMaker, which handles a lot of privacy stuff, all kinds of cool things, or you can get down and dirty. So I got to ask on the next one, production is a big deal, getting stuff into production. What have you guys learned that you could share to folks watching? Is there a cost issue? I got to monitor, obviously you brought that up, we talked about the even reinforcement issues, all these things are happening. What is the big learnings that you could share for people that are going to put these into production to watch out for, to plan for, or be prepared for, hope for the best plan for the worst? What's your advice? >> I can give a couple opinions there and I'm sure Adam has. Well, yeah, the big one from my side is, again, I had mentioned this earlier, it's just the input data streams because humans are also exploring how they can use these systems to begin with. It's really, really hard to predict the type of inputs you're going to be seeing in production. Especially, we always talk about chatbots, but then any generative text tasks like this, let's say you're taking in news articles and summarizing them or something like that, it's very hard to get a good sampling even of the set of news articles in such a way that you can really predict what's going to pop out of that model. So to me, it's, adversarial maybe isn't the word that I would use, but it's an unnatural shifting input distribution of like prompts that you might see for these models. That's certainly one. And then the second one that I would talk about is, it can be hard to understand the costs, the inference time costs behind these LLMs. So the pricing on these is always changing as the models change size, it might go up, it might go down based on model size, based on energy cost and so on, but your pricing per token or per a thousand tokens and that I think can be difficult for some clients to wrap their head around. Again, you don't know how these systems are going to be used after all so it can be tough. And so again that's another metric that really should be tracked. >> Yeah, and there's a lot of trade off choices in there with like, how many tokens do you want at each step and in the sequence and based on, you have (indistinct) and you reject these tokens and so based on how your system's operating, that can make the cost highly variable. And that's if you're using like an API version that you're paying per token. A lot of people also choose to run these internally and as John mentioned, the inference time on these is significantly higher than a traditional classifi, even NLP classification model or tabular data model, like orders of magnitude higher. And so you really need to understand how that, as you're constantly iterating on these models and putting out new versions and new features in these models, how that's affecting the overall scale of that inference cost because you can use a lot of computing power very quickly with these profits. >> Yeah, scale, performance, price all come together. I got to ask while we're here on the secret sauce of the company, if you had to describe to people out there watching, what's the secret sauce of the company? What's the key to your success? >> Yeah, so John leads our research team and they've had a number of really cool, I think AI as much as it's been hyped for a while, it's still commercial AI at least is really in its infancy. And so the way we're able to pioneer new ways to think about performance for computer vision NLP LLMs is probably the thing that I'm proudest about. John and his team publish papers all the time at Navs and other places. But I think it's really being able to define what performance means for basically any kind of model type and give people really powerful tools to understand that on an ongoing basis. >> John, secret sauce, how would you describe it? You got all the action happening all around you. >> Yeah, well I going to appreciate Adam talking me up like that. No, I. (all laughing) >> Furrier: Robs to you. >> I would also say a couple of other things here. So we have a very strong engineering team and so I think some early hires there really set the standard at a very high bar that we've maintained as we've grown. And I think that's really paid dividends as scalabilities become even more of a challenge in these spaces, right? And so that's not just scalability when it comes to LLMs, that's scalability when it comes to millions of inferences per day, that kind of thing as well in traditional ML models. And I think that's compared to potential competitors, that's really... Well, it's made us able to just operate more efficiently and pass that along to the client. >> Yeah, and I think the infancy comment is really important because it's the beginning. You really is a long journey ahead. A lot of change coming, like I said, it's a huge wave. So I'm sure you guys got a lot of plannings at the foundation even for your own company, so I appreciate the candid response there. Final question for you guys is, what should the top things be for a company in 2023? If I'm going to set the agenda and I'm a customer moving forward, putting the pedal to the metal, so to speak, what are the top things I should be prioritizing or I need to do to be successful with AI in 2023? >> Yeah, I think, so number one, as we talked about, we've been talking about this entire episode, the things are changing so quickly and the opportunities for business transformation and really disrupting different applications, different use cases, is almost, I don't think we've even fully comprehended how big it is. And so really digging in to your business and understanding where I can apply these new sets of foundation models is, that's a top priority. The interesting thing is I think there's another force at play, which is the macroeconomic conditions and a lot of places are, they're having to work harder to justify budgets. So in the past, couple years ago maybe, they had a blank check to spend on AI and AI development at a lot of large enterprises that was limited primarily by the amount of talent they could scoop up. Nowadays these expenditures are getting scrutinized more. And so one of the things that we really help our customers with is like really calculating the ROI on these things. And so if you have models out there performing and you have a new version that you can put out that lifts the performance by 3%, how many tens of millions of dollars does that mean in business benefit? Or if I want to go to get approval from the CFO to spend a few million dollars on this new project, how can I bake in from the beginning the tools to really show the ROI along the way? Because I think in these systems when done well for a software project, the ROI can be like pretty spectacular. Like we see over a hundred percent ROI in the first year on some of these projects. And so, I think in 2023, you just need to be able to show what you're getting for that spend. >> It's a needle moving moment. You see it all the time with some of these aha moments or like, whoa, blown away. John, I want to get your thoughts on this because one of the things that comes up a lot for companies that I talked to, that are on my second wave, I would say coming in, maybe not, maybe the front wave of adopters is talent and team building. You mentioned some of the hires you got were game changing for you guys and set the bar high. As you move the needle, new developers going to need to come in. What's your advice given that you've been a professor, you've seen students, I know a lot of computer science people want to shift, they might not be yet skilled in AI, but they're proficient in programming, is that's going to be another opportunity with open source when things are happening. How do you talk to that next level of talent that wants to come in to this market to supplement teams and be on teams, lead teams? Any advice you have for people who want to build their teams and people who are out there and want to be a coder in AI? >> Yeah, I've advice, and this actually works for what it would take to be a successful AI company in 2023 as well, which is, just don't be afraid to iterate really quickly with these tools. The space is still being explored on what they can be used for. A lot of the tasks that they're used for now right? like creating marketing content using a machine learning is not a new thing to do. It just works really well now. And so I'm excited to see what the next year brings in terms of folks from outside of core computer science who are, other engineers or physicists or chemists or whatever who are learning how to use these increasingly easy to use tools to leverage LLMs for tasks that I think none of us have really thought about before. So that's really, really exciting. And so toward that I would say iterate quickly. Build things on your own, build demos, show them the friends, host them online and you'll learn along the way and you'll have somebody to show for it. And also you'll help us explore that space. >> Guys, congratulations with Arthur. Great company, great picks and shovels opportunities out there for everybody. Iterate fast, get in quickly and don't be afraid to iterate. Great advice and thank you for coming on and being part of the AWS showcase, thanks. >> Yeah, thanks for having us on John. Always a pleasure. >> Yeah, great stuff. Adam Wenchel, John Dickerson with Arthur. Thanks for coming on theCUBE. I'm John Furrier, your host. Generative AI and AWS. Keep it right there for more action with theCUBE. Thanks for watching. (upbeat music)

(gentle upbeat music) >> Hey, friends of theCUBE. It's Lisa Martin live at Stanford University covering the Eighth Annual Women In Data Science. But you've been a Cube fan for a long time. So you know that we've been here since the beginning of WiDS, which is 2015. We always loved to come and cover this event. We learned great things about data science, about women leaders, underrepresented minorities. And this year we have a special component. We've got two grad students from Stanford's Master's program and Data Journalism joining. One of my them is here with me, Hannah Freitag, my co-host. Great to have you. And we are pleased to welcome from Intuit for the first time, Shir Meir Lador Group Manager at Data Science. Shir, it's great to have you. Thank you for joining us. >> Thank you for having me. >> And I was just secrets girl talking with my boss of theCUBE who informed me that you're in great company. Intuit's Chief Technology Officer, Marianna Tessel is an alumni of theCUBE. She was on at our Supercloud event in January. So welcome back into it. >> Thank you very much. We're happy to be with you. >> Tell us a little bit about what you're doing. You're a data science group manager as I mentioned, but also you've had you've done some cool things I want to share with the audience. You're the co-founder of the PyData Tel Aviv Meetups the co-host of the unsupervised podcast about data science in Israel. You give talks, about machine learning, about data science. Tell us a little bit about your background. Were you always interested in STEM studies from the time you were small? >> So I was always interested in mathematics when I was small, I went to this special program for youth going to university. So I did my test in mathematics earlier and studied in university some courses. And that's when I understood I want to do something in that field. And then when I got to go to university, I went to electrical engineering when I found out about algorithms and how interested it is to be able to find solutions to problems, to difficult problems with math. And this is how I found my way into machine learning. >> Very cool. There's so much, we love talking about machine learning and AI on theCUBE. There's so much potential. Of course, we have to have data. One of the things that I love about WiDS and Hannah and I and our co-host Tracy, have been talking about this all day is the impact of data in everyone's life. If you break it down, I was at Mobile World Congress last week, all about connectivity telecom, and of course we have these expectation that we're going to be connected 24/7 from wherever we are in the world and we can do whatever we want. I can do an Uber transaction, I can watch Netflix, I can do a bank transaction. It all is powered by data. And data science is, some of the great applications of it is what it's being applied to. Things like climate change or police violence or health inequities. Talk about some of the data science projects that you're working on at Intuit. I'm an intuit user myself, but talk to me about some of those things. Give the audience really a feel for what you're doing. >> So if you are a Intuit product user, you probably use TurboTax. >> I do >> In the past. So for those who are not familiar, TurboTax help customers submit their taxes. Basically my group is in charge of getting all the information automatically from your documents, the documents that you upload to TurboTax. We extract that information to accelerate your tax submission to make it less work for our customers. So- >> Thank you. >> Yeah, and this is why I'm so proud to be working at this team because our focus is really to help our customers to simplify all the you know, financial heavy lifting with taxes and also with small businesses. We also do a lot of work in extracting information from small business documents like bill, receipts, different bank statements. Yeah, so this is really exciting for me, the opportunity to work to apply data science and machine learning to solution that actually help people. Yeah >> Yeah, in the past years there have been more and more digital products emerging that needs some sort of data security. And how did your team, or has your team developed in the past years with more and more products or companies offering digital services? >> Yeah, so can you clarify the question again? Sorry. >> Yeah, have you seen that you have more customers? Like has your team expanded in the past years with more digital companies starting that need kind of data security? >> Well, definitely. I think, you know, since I joined Intuit, I joined like five and a half years ago back when I was in Tel Aviv. I recently moved to the Bay Area. So when I joined, there were like a dozens of data scientists and machine learning engineers on Intuit. And now there are a few hundreds. So we've definitely grown with the year and there are so many new places we can apply machine learning to help our customers. So this is amazing, so much we can do with machine learning to get more money in the pocket of our customers and make them do less work. >> I like both of those. More money in my pocket and less work. That's awesome. >> Exactly. >> So keep going Intuit. But one of the things that is so cool is just the the abstraction of the complexity that Intuit's doing. I upload documents or it scans my receipts. I was just in Barcelona last week all these receipts and conversion euros to dollars and it takes that complexity away from the end user who doesn't know all that's going on in the background, but you're making people's lives simpler. Unfortunately, we all have to pay taxes, most of us should. And of course we're in tax season right now. And so it's really cool what you're doing with ML and data science to make fundamental processes to people's lives easier and just a little bit less complicated. >> Definitely. And I think that's what's also really amazing about Intuit it, is how it combines human in the loop as well as AI. Because in some of the tax situation it's very complicated maybe to do it yourself. And then there's an option to work with an expert online that goes on a video with you and helps you do your taxes. And the expert's work is also accelerated by AI because we build tools for those experts to do the work more efficiently. >> And that's what it's all about is you know, using data to be more efficient, to be faster, to be smarter, but also to make complicated processes in our daily lives, in our business lives just a little bit easier. One of the things I've been geeking out about recently is ChatGPT. I was using it yesterday. I was telling everyone I was asking it what's hot in data science and I didn't know would it know what hot is and it did, it gave me trends. But one of the things that I was so, and Hannah knows I've been telling this all day, I was so excited to learn over the weekend that the the CTO of OpenAI is a female. I didn't know that. And I thought why are we not putting her on a pedestal? Because people are likening ChatGPT to like the launch of the iPhone. I mean revolutionary. And here we have what I think is exciting for all of us females, whether you're in tech or not, is another role model. Because really ultimately what WiDS is great at doing is showcasing women in technical roles. Because I always say you can't be what you can't see. We need to be able to see more role models, female role role models, underrepresented minorities of course men, because a lot of my sponsors and mentors are men, but we need more women that we can look up to and see ah, she's doing this, why can't I? Talk to me about how you stay the course in data science. What excites you about the potential, the opportunities based on what you've already accomplished what inspires you to continue and be one of those females that we say oh my God, I could be like Shir. >> I think that what inspires me the most is the endless opportunities that we have. I think we haven't even started tapping into everything that we can do with generative AI, for example. There's so much that can be done to further help you know, people make more money and do less work because there's still so much work that we do that we don't need to. You know, this is with Intuit, but also there are so many other use cases like I heard today you know, with the talk about the police. So that was really exciting how you can apply machine learning and data to actually help people, to help people that been through wrongful things. So I was really moved by that. And I'm also really excited about all the medical applications that we can have with data. >> Yeah, yeah. It's true that data science is so diverse in terms of what fields it can cover but it's equally important to have diverse teams and have like equity and inclusion in your teams. Where is Intuit at promoting women, non-binary minorities in your teams to progress data science? >> Yeah, so I have so much to say on this. >> Good. >> But in my work in Tel Aviv, I had the opportunity to start with Intuit women in data science branch in Tel Aviv. So that's why I'm super excited to be here today for that because basically this is the original conference, but as you know, there are branches all over the world and I got the opportunity to lead the Tel Aviv branch with Israel since 2018. And we've been through already this year it's going to be it's next week, it's going to be the sixth conference. And every year our number of submission to make talk in the conference doubled itself. >> Nice. >> We started with 20 submission, then 50, then 100. This year we have over 200 submissions of females to give talk at the conference. >> Ah, that's fantastic. >> And beyond the fact that there's so much traction, I also feel the great impact it has on the community in Israel because one of the reason we started WiDS was that when I was going to conferences I was seeing so little women on stage in all the technical conferences. You know, kind of the reason why I guess you know, Margaret and team started the WiDS conference. So I saw the same thing in Israel and I was always frustrated. I was organizing PyData Meetups as you mentioned and I was always having such a hard time to get female speakers to talk. I was trying to role model, but that's not enough, you know. We need more. So once we started WiDS and people saw you know, so many examples on the stage and also you know females got opportunity to talk in a place for that. Then it also started spreading and you can see more and more female speakers across other conferences, which are not women in data science. So I think just the fact that Intuits started this conference back in Israel and also in Bangalore and also the support Intuit does for WiDS in Stanford here, it shows how much WiDS values are aligned with our values. Yeah, and I think that to chauffeur that I think we have over 35% females in the data science and machine learning engineering roles, which is pretty amazing I think compared to the industry. >> Way above average. Yeah, absolutely. I was just, we've been talking about some of the AnitaB.org stats from 2022 showing that 'cause usually if we look at the industry to you point, over the last, I don't know, probably five, 10 years we're seeing the number of female technologists around like a quarter, 25% or so. 2022 data from AnitaB.org showed that that number is now 27.6%. So it's very slowly- >> It's very slowly increasing. >> Going in the right direction. >> Too slow. >> And that representation of women technologists increase at every level, except intern, which I thought was really interesting. And I wonder is there a covid relation there? >> I don't know. >> What do we need to do to start opening up the the top of the pipeline, the funnel to go downstream to find kids like you when you were younger and always interested in engineering and things like that. But the good news is that the hiring we've seen improvements, but it sounds like Intuit is way ahead of the curve there with 35% women in data science or technical roles. And what's always nice and refreshing that we've talked, Hannah about this too is seeing companies actually put action into initiatives. It's one thing for a company to say we're going to have you know, 50% females in our organization by 2030. It's a whole other ball game to actually create a strategy, execute on it, and share progress. So kudos to Intuit for what it's doing because that is more companies need to adopt that same sort of philosophy. And that's really cultural. >> Yeah. >> At an organization and culture can be hard to change, but it sounds like you guys kind of have it dialed in. >> I think we definitely do. That's why I really like working and Intuit. And I think that a lot of it is with the role modeling, diversity and inclusion, and by having women leaders. When you see a woman in leadership position, as a woman it makes you want to come work at this place. And as an evidence, when I build the team I started in Israel at Intuit, I have over 50% women in my team. >> Nice. >> Yeah, because when you have a woman in the interviewers panel, it's much easier, it's more inclusive. That's why we always try to have at least you know, one woman and also other minorities represented in our interviews panel. Yeah, and I think that in general it's very important as a leader to kind of know your own biases and trying to have defined standard and rubrics in how you evaluate people to avoid for those biases. So all of that inclusiveness and leadership really helps to get more diversity in your teams. >> It's critical. That thought diversity is so critical, especially if we talk about AI and we're almost out of time, I just wanted to bring up, you brought up a great point about the diversity and equity. With respect to data science and AI, we know in AI there's biases in data. We need to have more inclusivity, more representation to help start shifting that so the biases start to be dialed down and I think a conference like WiDS and it sounds like someone like you and what you've already done so far in the work that you're doing having so many females raise their hands to want to do talks at events is a good situation. It's a good scenario and hopefully it will continue to move the needle on the percentage of females in technical roles. So we thank you Shir for your time sharing with us your story, what you're doing, how Intuit and WiDS are working together. It sounds like there's great alignment there and I think we're at the tip of the iceberg with what we can do with data science and inclusion and equity. So we appreciate all of your insights and your time. >> Thank you very much. >> All right. >> I enjoyed very, very much >> Good. We hope, we aim to please. Thank you for our guests and for Hannah Freitag. This is Lisa Martin coming to you live from Stanford University. This is our coverage of the eighth Annual Women in Data Science Conference. Stick around, next guest will be here in just a minute.

(lively music) >> Hello, everyone. Welcome back to the Supercloud presentation here. I'm theCUBE, I'm John Furrier, your host. What a great segment here. We're going to unpack the networking aspect of the cloud, how that translates into what Supercloud architecture and platform deployment scenarios look like. And demystify multi-cloud, hybridcloud. We've got two great experts. Amir Khan, the Co-Founder and CEO of Alkira, Atif Khan, Co-Founder and CTO of Alkira. These guys been around since 2018 with the startup, but before that story, history in the tech industry. I mean, routing early days, multiple waves, multiple cycles. >> Welcome three decades. >> Welcome to Supercloud. >> Thanks. >> Thanks for coming on. >> Thank you so much for having us. >> So, let's get your take on Supercloud because it's been one of those conversations that really galvanized the industry because it kind of highlights almost this next wave, this next side of the street that everyone's going to be on that's going to be successful. The laggards on the legacy seem to be stuck on the old model. SaaS is growing up, it's ISVs, it's ecosystems, hyperscale, full hybrid. And then multi-cloud around the corners cause all this confusion, everyone's hand waving. You know, this is a solution, that solution, where are we? What do you guys see as this supercloud dynamic? >> So where we start from is always focusing on the customer problem. And in 2018 when we identified the problem, we saw that there were multiple clouds with many diverse ways of doing things from the network perspective, and customers were struggling with that. So we delved deeper into that and looked at each one of the cloud architectures completely independent. And there was no common solution and customers were struggling with that from the perspective. They wanted to be in multiple clouds, either through mergers and acquisitions or running an application which may be more cost effective to run in something or maybe optimized for certain reasons to run in a different cloud. But from the networking perspective, everything needed to come together. So that's, we are starting to define it as a supercloud now, but basically, it's a common infrastructure across all clouds. And then integration of high lift services like, you know, security or IPAM services or many other types of services like inter-partner routing and stuff like that. So, Amir, you agree then that multi-cloud is simply a default result of having whatever outcomes, either M&A, some productivity software, maybe Azure. >> Yes. >> Amazon has this and then I've got on-premise application, so it's kinds mishmash. >> So, I would qualify it with hybrid multi-cloud because everything is going to be interconnected. >> John: Got it. >> Whether it's on-premise, remote users or clouds. >> But have CTO perspective, obviously, you got developers, multiple stacks, got AWS, Azure and GCP, other. Not everyone wants to kind of like go all in, but yet they don't want to hedge too much because it's a resource issue. And I got to learn this stack, I got to learn that stack. So then now, you have this default multi-cloud, hybrid multi-cloud, then it's like, okay, what do I do? How do you spread that around? Is it dangerous? What's the the approach technically? What's some of the challenges there? >> Yeah, certainly. John, first, thanks for having us here. So, before I get to that, I'll just add a little bit to what Amir was saying, like how we started, what we were seeing and how it, you know, correlates with the supercloud. So, as you know, before this company, Alkira, we were doing, we did the SD-WAN company, which was Viptela. So there, we started seeing when people started deploying SD-WAN at like a larger scale. We started like, you know, customers coming to us and saying they needed connectivity into the cloud from the SD-WAN. They wanted to extend the SD-WAN fabric to the cloud. So we came up with an architecture, which was like later we started calling them Cloud onRamps, where we built, you know, a transit VPC and put like the virtual instances of SD-WAN appliances extended from there to the cloud. But before we knew, like it started becoming very complicated for the customers because it wasn't just connectivity, it also required, you know, other use cases. You had to instantiate or bring in security appliances in there. You had to secure all of that stuff. There were requirements for, you know, different regions. So you had to bring up the same thing in different regions. Then multiple clouds, what did you do? You had to replicate the same thing in multiple clouds. And now if there was was requirement between clouds, how were you going to do it? You had to route traffic from somewhere, and come up with all those routing controls and stuff. So, it was very complicated. >> Like spaghetti code, but on network. >> The games begin, in fact, one of our customers called it spaghetti mess. And so, that's where like we thought about where was the industry going and which direction the industry was going into? And we came up with the Alkira where what we are doing is building a common infrastructure across multiple clouds, across in, you know, on-prem locations, be it data centers or physical sites, branches sites, et cetera, with integrated security and network networking services inside. And, you know, nowadays, networking is not only about connectivity, you have to secure everything. So, security has to be built in. Redundancy, high availability, disaster recovery. So all of that needs to be built in. So that's like, you know, kind of a definition of like what we thought at that time, what is turning into supercloud now. >> Yeah. It's interesting too, you mentioned, you know, VPCs is not, configuration of loans a hassle. Nevermind the manual mistakes could be made, but as you decide to do something you got to, "Oh, we got to get these other things." A lot of the hyper scales and a lot of the alpha cloud players now, and cloud native folks, they're kind of in that mode of, "Wow, look at what we've built." Now, they're got to maintain, how do I refresh it? Like, how do I keep the talent? So they got this similar chaotic environment where it's like, okay, now they're already already through, so I think they're going to be okay. But then some people want to bypass it completely. So there's a lot of customers that we see out there that fit the makeup of, I'm cloud first, I've lifted and shifted, I move some stuff to the cloud. But I want to bypass all that learnings from all the people that are gone through the past three years. Can I just skip that and go to a multi-cloud or coherent infrastructure? What do you think about that? What's your view? >> So yeah, so if you look at these enterprises, you know, many of them just to find like the talent, which for one cloud as far as the IT staff is concerned, it's hard enough. And now, when you have multiple clouds, it's hard to find people the talent which is, you know, which has expertise across different clouds. So that's where we come into the picture. So our vision was always to simplify all of this stuff. And simplification, it cannot be just simplification because you cannot just automate the workflows of the cloud providers underneath. So you have to, you know, provide your full data plane on top of it, fed full control plane, management plane, policy and management on top of it. And coming back to like your question, so these nowadays, those people who are working on networking, you know, before it used to be like CLI. You used to learn about Cisco CLI or Juniper CLI, and you used to work on it. Nowadays, it's very different. So automation, programmability, all of that stuff is the key. So now, you know, Ops guys, the DevOps guys, so these are the people who are in high demand. >> So what do you think about the folks out there that are saying, okay, you got a lot of fragmentation. I got the stacks, I got a lot of stove pipes, if you will, out there on the stack. I got to learn this from Azure. Can you guys have with your product abstract the way that's so developers don't need to know the ins and outs of stack's, almost like a gateway, if you will, the old days. But like I'm a developer or team develop, why should I have to learn the management layer of Azure? >> That's exactly what we started, you know, out with to solve. So it's, what we have built is a platform and the platform sits inside the cloud. And customers are able to build their own network or a virtual network on top using that platform. So the platform has its own data plane, own control plane and management plane with a policy layer on top of it. So now, it's the platform which is sitting in different clouds, but from a customer's point of view, it's one way of doing networking. One way of instantiating or bringing in services or security services in the middle. Whether those are our security services or whether those are like services from our partners, like Palo Alto or Checkpoint or Cisco. >> So you guys brought the SD-WAN mojo and refactored it for the cloud it sounds like. >> No. >> No? (chuckles) >> We cannot said. >> All right, explain. >> It's way more than that. >> I mean, SD-WAN was wan. I mean, you're talking about wide area networks, talking about connected, so explain the difference. >> SD-WAN was primarily done for one major reason. MPLS was expensive, very strong SLAs, but very low speed. Internet, on the other hand, you sat at home and you could access your applications much faster. No SLA, very low cost, right? So we wanted to marry the two together so you could have a purely private infrastructure and a public infrastructure and secure both of them by creating a common secure fabric across all those environments. And then seamlessly tying it into your internal branch and data center and cloud network. So, it merely brought you to the edge of the cloud. It didn't do anything inside the cloud. Now, the major problem resides inside the clouds where you have to optimize the clouds themselves. Take a step back. How were the clouds built? Basically, the cloud providers went to the Ciscos and Junipers and the rest of the world, built the network in the data centers or across wide area infrastructure, and brought it all together and tried to create a virtualized layer on top of that. But there were many limitations of this underlying infrastructure that they had built. So number of routes per region, how inter region connectivity worked, or how many routes you could carry to the VPCs of V nets? That all those were becoming no common policy across, you know, these environments, no segmentation across these environments, right? So the networking constructs that the enterprise customers were used to as enterprise class carry class capabilities, they did not exist in the cloud. So what did the customer do? They ended up stitching it together all manually. And that's why Atif was alluding to earlier that it became a spaghetti mess for the customers. And then what happens is, as a result, day two operations, you know, troubleshooting, everything becomes a nightmare. So what do you do? You have to build an infrastructure inside the cloud. Cloud has enough raw capabilities to build the solutions inside there. Netflix's of the world. And many different companies have been born in the cloud and evolved from there. So why could we not take the raw capabilities of the clouds and build a network cloud or a supercloud on top of these clouds to optimize the whole infrastructure and seamlessly connecting it into the on-premise and remote user locations, right? So that's your, you know, hybrid multi-cloud solution. >> Well, great call out on the SD-WAN in common versus cloud. 'Cause I think this is important because you're building a network layer in the cloud that spans out so the customers don't have to get into the, there's a gap in the system that I'm used to, my operating environment, of having lockdown security and network. >> So yeah. So what you do is you use the raw capabilities like bandwidth or virtual machines, or you know, containers, or, you know, different types of serverless capabilities. And you bring it all together in a way to solve the networking problems, thereby creating a supercloud, which is an abstraction layer which hides all the complexity of the underlying clouds from the customer, right? And it provides a common infrastructure across all environments to that customer, right? That's the beauty of it. And it does it in a way that it looks like, if they have the networking knowledge, they can apply it to this new environment and carry it forward. One way of doing security across all clouds and hybrid environments. One way of doing routing. One way of doing large-scale network address translation. One way of doing IPAM services. So people are tired of doing individual things and individual clouds and on-premise locations, right? So now they're getting something common. >> You guys brought that, you brought all that to bear and flexible for the customer to essentially self-serve their network cloud. >> Yes, yeah. Is that the wave? >> And nowadays, from business perspective, agility is the key, right? You have to move at the pace of the business. If you don't, you are losing. >> So, would it be safe to say that you guys have a network supercloud? >> Absolutely, yeah. >> We, pretty much, yeah. Absolutely. >> What does that mean to our customer? What's in it for them? What's the benefit to the customer? I got a network supercloud, it connects, provides SLA, all the capabilities I need. What do they get? What's the end point for them? What's the end? >> Atif, maybe you can talk some examples. >> The IT infrastructure is all like distributed now, right? So you have applications running in data centers. You have applications running in one cloud. Other cloud, public clouds, enterprises are depending on so many SaaS applications. So now, these are, you can call these endpoints. So a supercloud or a network cloud, from our perspective, it's a cloud in the middle or a network in the middle, which provides connectivity from any endpoint to any endpoint. So, you are able to connect to the supercloud or network cloud in one way no matter where you are. So now, whichever cloud you are in, whichever cloud you need to connect to. And also, it's not just connecting to the cloud. So you need to do a lot of stuff, a lot of networking inside the cloud also. So now, as Amir was saying, every cloud has its own from a networking, you know, the concept perspective or the construct, they are different. There are limitations in there also. So this supercloud, which is sitting on top, basically, your platform is sitting into the cloud, but the supercloud is built on top of using your platform. So that abstracts all those complexities, all those limitations. So now your limitations are whatever the limitations of that platform are. So now your platform, that platform is in our control. So we can keep building it, we can keep scaling it horizontally. Because one of the things is that, you know, in this cloud era, one of the things is autoscaling these services. So why can't the network now autoscale also, just like your other services. >> Network autoscaling is a genius idea, and I think that's a killer. I want to ask the the follow on question because I think, first of all, I love what you guys are doing. So, I think it's a great example of this new innovation. It's not obvious until you see it, right? Geographical is huge. So, you know, single instance, global instances, multiple instances, you're seeing global. How do you guys look at that global equation? Because as companies expand their clouds into geos, and then ultimately, you know, it's obviously continent, region and locales. You're going to have geographic issues. So, this is an extension of your network cloud? >> Amir: It is the extension of the network cloud because if you look at this hyperscalers, they're sitting pretty much everywhere in the globe. So, wherever their regions are, the beauty of building a supercloud is that you can by definition, be available in those regions. It literally takes a day or two of testing for our stack to run in those regions, to make sure there are no nuances that we run into, you know, for that region. The moment we bring it up in that region, all customers can onboard into that solution. So literally, what used to take months or years to build a global infrastructure, now, you can configure it in 10 minutes basically, and bring it up in less than one hour. Since when did we see any solution- >> And by the way, >> that can come up with. >> when the edge comes out too, you're going to start to see more clouds get bolted on. >> Exactly. And you can expand to the edge of the network. That's why we call cloud the new edge, right? >> John: Yeah, it is. Now, I think you guys got a good solutions, network clouds, superclouds, good. So the question on the premise side, so I get the cloud play. It's very cool. You can expand out. It's a nice layer. I'm sure you manage the SLAs between latency and all kinds of things. Knowing when not to do things. Physics or physics. Okay. Now, you've got the on-premise. What's the on-premise equation look like? >> So on-premise, the kind of customers, we are working with large enterprises, mid-size enterprises. So they have on-prem networks, they have deployed, in many cases, they have deployed SD-WAN. In many cases, they have MPLS. They have data centers also. And a lot of these companies are, you know, moving the applications from the data center into the cloud. But we still have large enterprise- >> But for you guys, you can sit there too with non server or is it a box or what is it? >> It's a software stack, right? So, we are a software company. >> Okay, so no box. >> No box. >> Okay, got it. >> No box. >> It's even better. So, we can connect any, as I mentioned, any endpoint, whether it's data centers. So, what happens is usually these enterprises from the data centers- >> John: It's a cloud endpoint for you. >> Cloud endpoint for us. And they need highspeed connectivity into the cloud. And our network cloud is sitting inside the or supercloud is sitting inside the cloud. So we need highspeed connectivity from the data centers. This is like multi-gig type of connectivity. So we enable that connectivity as a service. And as Amir was saying, you are able to bring it up in minutes, pretty much. >> John: Well, you guys have a great handle on supercloud. I really appreciate you guys coming on. I have to ask you guys, since you have so much experience in the industry, multiple inflection points you've guys lived through and we're all old, and we can remember those glory days. What's the big deal going on right now? Because you can connect the dots and you can imagine, okay, like a Lambda function spinning up some connectivity. I need instant access to a new route, throw some, I need to send compute to an edge point for process data. A lot of these kind of ad hoc services are going to start flying around, which used to be manually configured as you guys remember. >> Amir: And that's been the problem, right? The shadow IT, that was the biggest problem in the enterprise environment. So that's what we are trying to get the customers away from. Cloud teams came in, individuals or small groups of people spun up instances in the cloud. It was completely disconnected from the on-premise environment or the existing IT environment that the customer had. So, how do you bring it together? And that's what we are trying to solve for, right? At a large scale, in a carrier cloud center (indistinct). >> What do you call that? Shift right or shift left? Shift left is in the cloud native world security. >> Amir: Yes. >> Networking and security, the two hottest areas. What are you shifting? Up or down? I mean, the network's moving up the stack. I mean, you're seeing the run times at Kubernetes later' >> Amir: Right, right. It's true we're end-to-end virtualization. So you have plumbing, which is the physical infrastructure. Then on top of that, now for the first time, you have true end-to-end virtualization, which the cloud-like constructs are providing to us. We tried to virtualize the routers, we try to virtualize instances at the server level. Now, we are bringing it all together in a truly end-to-end virtualized manner to connect any endpoint anywhere across the globe. Whether it's on-premise, home, multiple clouds, or SaaS type environments. >> Yeah. If you talk about the technical benefits beyond virtualizations, you kind of see in virtualization be abstracted away. So you got end-to-end virtualization, but you don't need to know virtualization to take advantage of it. >> Exactly. Exactly. >> What are some of the tech involved where, what's the trend around on top of virtual? What's the easy button for that? >> So there are many, many use cases from the customers and they're, you know, some of those use cases, they used to deliver out of their data centers before. So now, because you, know, it takes a long time to spend something up in the data center and stuff. So the trend is and what enterprises are looking for is agility. And to achieve that agility, they are moving those services or those use cases into the cloud. So another technical benefit of like something like a supercloud and what we are doing is we allow customers to, you know, move their services from existing data centers into the cloud as well. And I'll give you some examples. You know, these enterprises have, you know, tons of partners. They provide connectivity to their partners, to select resources. It used to happen inside the data center. You would bring in connectivity into the data center and apply like tons of ACLs and whatnot to make sure that you are able to only connect. And now those use cases are, they need to be enabled inside the cloud. And the customer's customers are also, it's not just coming from the on-prem, they're coming from the cloud as well. So, if they're coming from the cloud as well as from on-prem, so you need like an infrastructure like supercloud, which is sitting inside the cloud and is able to handle all these use cases. So all of these use cases have to be, so that requires like moving those services from the data center into the cloud or into the supercloud. So, they're, oh, as we started building this service over the last four years, we have come across so many use cases. And to deliver those use cases, you have to have a platform. So you have to have your own platform because otherwise you are depending on somebody else's, you know, capabilities. And every time their capabilities change, you have to change. >> John: I'm glad you brought up the platform 'cause I want to get your both reaction to this. So Bob Muglia just said on theCUBE here at Supercloud, that supercloud is a platform that provides programmatically consistent services hosted on heterogeneous cloud providers. So the question is, is supercloud a platform or an architecture in your view? >> That's an interesting view on things, you know? I mean, if you think of it, you have to design or architect a solution before we turn it into a platform. >> John: It's a trick question actually. >> So it's a, you know, so we look at it as that you have to have an architectural approach end to end, right? And then you build a solution based on that approach. So, I don't think that they are mutually exclusive. I think they go hand in hand. It's an architecture that you turn into a solution and provide that agility and high availability and disaster recovery capability that it built into that. >> It's interesting that these definitions might be actually redefined with this new configuration. >> Amir: Yes. >> Because architecture and platform used to mean something, like, aight here's a platform, you buy this platform. >> And then you architecture solution. >> Architect it via vendor. >> Right, right, right. >> Okay. And they have to deal with that architecture in the place of multiple superclouds. If you have too many stove pipes, then what's the purpose of supercloud? >> Right, right, right. And because, you know, historically, you built a router and you sold it to the customer. And the poor customer was supposed to install it all, you know, and interconnect all those things. And if you have 40, 50,000 router network, which we saw in our lifetime, 'cause there used to be many more branches when we were growing up in the networking industry, right? You had to create hierarchy and all kinds of things to figure out how to solve that problem. We are no longer living in that world anymore. You cannot deploy individual virtual instances. And that's what approach a lot of people are taking, which is a pure overly network. You cannot take that approach anymore. You have to evolve the architecture and then build the solution based on that architecture so that it becomes a platform which is readily available, highly scalable, and available. And at the same time, it's very, very easy to deploy. It's a SaaS type solution, right? >> So you're saying, do the architecture to get the solution for the platform that the customer has. >> Amir: Yes. >> They're not buying a platform, they end up with a platform- >> With the platform. >> as a result of Supercloud path. All right. So that's what's, so you mentioned, that's a great point. I want to double click on what you just said. 'Cause I like that what you said. What's the deployment strategy in your mind for supercloud? I'm an architect. I'm at an enterprise in the Midwest. I'm an insurance company, got some cloud action going on. I'm mostly on-premise. I've got the mandate to transform the company. We have apps. We'll be fully transformed in five years. What's my strategy? What do I do? >> Amir: The resources. >> What's the deployment strategy? Single global instance, code in every region, on every cloud? >> It needs to be a solution which is available as a SaaS service, right? So from the customer's perspective, they are onboarding into the supercloud. And then the supercloud is allowing them to do whatever they used to do, you know, historically and in the new world, right? That needs to come together. And that's what we have built is that, we have brought everything together in a way that what used to take months or years, and now taking an hour or two hours, and then people test it for a week or so and deploy it in production. >> I want to bring up something we were talking about before we were on camera about the TCP/IP, the OSI model. That was a concept that destroyed the proprietary narcissist. Work operating systems of the mini computers, which brought in an era of tech prosperity for generations. TCP/IP was kind of the magical moment that allowed for that kind of super networking connection. Inter networking is what's called as a category. It feels like something's going on here with supercloud. The way you describe it, it feels like there's this unification idea. Like the reality is we've got multiple stuff sitting around by default, you either clean it up or get rid of it, right? Or it's almost a, it's either a nuance, a new nuisance or chaos. >> Yeah. And we live in the new world now. We don't have the luxury of time. So we need to move as fast as possible to solve the business problems. And that's what we are running into. If we don't have automated solutions which scale, which solve our problems, then it's going to be a problem. And that's why SaaS is so important in today's world. Why should we have to deploy the network piecemeal? Why can't we have a solution? We solve our problem as we move forward and we accomplish what we need to accomplish and move forward. >> And we don't really need standards here, dude. It's not that we need a standards body if you have unification. >> So because things move so fast, there's no time to create a standards body. And that's why you see companies like ours popping up, which are trying to create a common infrastructure across all clouds. Otherwise if we vent the standardization path may take long. Eventually, we should be going in that direction. But we don't have the luxury of time. That's what I was trying to get to. >> Well, what's interesting is, is that to your point about standards and ratification, what ratifies a defacto anything? In the old days there was some technical bodies involved, but here, I think developers drive everything. So if you look at the developers and how they're voting with their code. They're instantly, organically defining everything as a collective intelligence. >> And just like you're putting out the paper and making it available, everybody's contributing to that. That's why you need to have APIs and terra form type constructs, which are available so that the customers can continue to improve upon that. And that's the Net DevOps, right? So that you need to have. >> What was once sacrilege, just sayin', in business school, back in the days when I got my business degree after my CS degree was, you know, no one wants to have a better mousetrap, a bad business model to have a better mouse trap. In this case, the better mouse trap, the better solution actually could be that thing. >> It is that thing. >> I mean, that can trigger, tips over the industry. >> And that that's where we are seeing our customers. You know, I mean, we have some publicly referenceable customers like Coke or Warner Music Group or, you know, multiple others and chart industries. The way we are solving the problem. They have some of the largest environments in the industry from the cloud perspective. And their whole network infrastructure is running on the Alkira infrastructure. And they're able to adopt new clouds within days rather than waiting for months to architect and then deploy and then figure out how to manage it and operate it. It's available as a service. >> John: And we've heard from your customer, Warner, they were just on the program. >> Amir: Yes. Okay, okay. >> So they're building a supercloud. So superclouds aren't just for tech companies. >> Amir: No. >> You guys build a supercloud for networking. >> Amir: It is. >> But people are building their own superclouds on top of all this new stuff. Talk about that dynamic. >> Healthcare providers, financials, high-tech companies, even startups. One of our startup customers, Tekion, right? They have these dealerships that they provide sales and support services to across the globe. And for them to be able to onboard those dealerships, it is 80% less time to production. That is real money, right? So, maybe Atif can give you a lot more examples of customers who are deploying. >> Talk about some of the customer activity. What are they like? Are they laggards, they innovators? Are they trying to hit the easy button? Are they coming in late or are you got some high customers? >> Actually most of our customers, all of our customers or customers in general. I don't think they have a choice but to move in this direction because, you know, the cloud has, like everything is quick now. So the cloud teams are moving faster in these enterprises. So now that they cannot afford the network nor to keep up pace with the cloud teams. So, they don't have a choice but to go with something similar where you can, you know, build your network on demand and bring up your network as quickly as possible to meet all those use cases. So, I'll give you an example. >> John: So the demand's high for what you guys do. >> Demand is very high because the cloud teams have- >> John: Yeah. They're going fast. >> They're going fast and there's no stopping. And then network teams, they have to keep up with them. And you cannot keep deploying, you know, networks the way you used to deploy back in the day. And as far as the use cases are concerned, there are so many use cases which our customers are using our platform for. One of the use cases, I'll give you an example of these financial customers. Some of the financial customers, they have their customers who they provide data, like stock exchanges, that provide like market data information to their customers out of data centers part. But now, their customers are moving into the cloud as well. So they need to come in from the cloud. So when they're coming in from the cloud, you cannot be giving them data from your data center because that takes time, and your hair pinning everything back. >> Moving data is like moving, moving money, someone said. >> Exactly. >> Exactly. And the other thing is like you have to optimize your traffic flows in the cloud as well because every time you leave the cloud, you get charged a lot. So, you don't want to leave the cloud unless you have to leave the cloud, your traffic. So, you have to come up or use a service which allows you to optimize all those traffic flows as well, you know? >> My final question to you guys, first of all, thanks for coming on Supercloud Program. Really appreciate it. Congratulations on your success. And you guys have a great positioning and I'm a big fan. And I have to ask, you guys are agile, nimble startup, smart on the cutting edge. Supercloud concept seems to resonate with people who are kind of on the front range of this major wave. While all the incumbents like Cisco, Microsoft, even AWS, they're like, I think they're looking at it, like what is that? I think it's coming up really fast, this trend. Because I know people talk about multi-cloud, I get that. But like, this whole supercloud is not just SaaS, it's more going on there. What do you think is going on between the folks who get it, supercloud, get the concept, and some are who are scratching their heads, whether it's the Ciscos or someone, like I don't get it. Why is supercloud important for the folks that aren't really seeing it? >> So first of all, I mean, the customers, what we saw about six months, 12 months ago, were a little slower to adopt the supercloud kind of concept. And there were leading edge customers who were coming and adopting it. Now, all of a sudden, over the last six to nine months, we've seen a flurry of customers coming in and they are from all disciplines or all very diverse set of customers. And they're starting to see the value of that because of the practical implications of what they're doing. You know, these shadow IT type environments are no longer working and there's a lot of pressure from the management to move faster. And then that's where they're coming in. And perhaps, Atif, if you can give a few examples of. >> Yeah. And I'll also just add to your point earlier about the network needing to be there 'cause the cloud teams are like, let's go faster. And the network's always been slow because, but now, it's been almost turbocharged. >> Atif: Yeah. Yeah, exactly. And as I said, like there was no choice here. You had to move in this industry. And the other thing I would add a little bit is now if you look at all these enterprises, most of their traffic is from, even from which is coming from the on-prem, it's going to the cloud SaaS applications or public clouds. And it's more than 50% of traffic, which is leaving your, you know, what you used to call, your network or the private network. So now it's like, you know, before it used to just connect sites to data centers and sites together. Now, it's a cloud as well as the SaaS application. So it's either internet bound or the public cloud bound. So now you have to build a network quickly, which caters to all these use cases. And that's where like something- >> And you guys, your solution to me is you eliminate all that work for the customer. Now, they can treat the cloud like a bag of Legos. And do their thing. Well, I oversimplify. Well, you know I'm talking about. >> Atif: Right, exactly. >> And to answer your question earlier about what about the big companies coming in and, you know, now they slow to adopt? And, you know, what normally happens is when Cisco came up, right? There used to be 16 different protocols suites. And then we finally settled on TCP/IP and DECnet or AppleTalk or X&S or, you know, you name it, right? Those companies did not adapt to the networking the way it was supposed to be done. And guess what happened, right? So if the companies in the networking space do not adopt this new concept or new way of doing things, I think some of them will become extinct over time. >> Well, I think the force and function too is the cloud teams as well. So you got two evolutions. You got architectural relevance. That's real as impact. >> It's very important. >> Cost, speed. >> And I look at it as a very similar disruption to what Cisco's the world, very early days did to, you know, bring the networking out, right? And it became the internet. But now we are going through the cloud. It's the cloud era, right? How does the cloud evolve over the next 10, 15, 20 years? Everything's is going to be offered as a service, right? So slowly data centers go away, the network becomes a plumbing thing. Very, you know, simple to deploy. And everything on top of that is virtualized in the cloud-like manners. >> And that makes the networks hardened and more secure. >> More secure. >> It's a great way to be secure. You remember the glory days, we'll go back 15 years. The Cisco conversation was, we got to move up to stack. All the manager would fight each other. Now, what does that actually mean? Stay where we are. Stay in your lane. This is kind of like the network's version of moving up the stack because not so much up the stack, but the cloud is everywhere. It's almost horizontally scaled. >> It's extending into the on-premise. It is already moving towards the edge, right? So, you will see a lot- >> So, programmability is a big program. So you guys are hitting programmability, compatibility, getting people into an environment they're comfortable operating. So the Ops people love it. >> Exactly. >> Spans the clouds to a level of SLA management. It might not be perfectly spanning applications, but you can actually know latencies between clouds, measure that. And then so you're basically managing your network now as the overall infrastructure. >> Right. And it needs to be a very intelligent infrastructure going forward, right? Because customers do not want to wait to be able to troubleshoot. They don't want to be able to wait to deploy something, right? So, it needs to be a level of automation. >> Okay. So the question for you guys both on we'll end on is what is the enablement that, because you guys are a disruptive enabler, right? You create this fabric. You're going to enable companies to do stuff. What are some of the things that you see and your customers might be seeing as things that they're going to do as a result of having this enablement? So what are some of those things? >> Amir: Atif, perhaps you can talk through the some of the customer experience on that. >> It's agility. And we are allowing these customers to move very, very quickly and build these networks which meet all these requirements inside the cloud. Because as Amir was saying, in the cloud era, networking is changing. And if you look at, you know, going back to your comment about the existing networking vendors. Some of them still think that, you know, just connecting to the cloud using some concepts like Cloud OnRamp is cloud networking, but it's changing now. >> John: 'Cause there's apps that are depending upon. >> Exactly. And it's all distributed. Like IT infrastructure, as I said earlier, is all distributed. And at the end of the day, you have to make sure that wherever your user is, wherever your app is, you are able to connect them securely. >> Historically, it used to be about building a router bigger and bigger and bigger and bigger, you know, and then interconnecting those routers. Now, it's all about horizontal scale. You don't need to build big, you need to scale it, right? And that's what cloud brings to the customer. >> It's a cultural change for Cisco and Juniper because they have to understand that they're still could be in the game and still win. >> Exactly. >> The question I have for you, what are your customers telling you that, what's some of the anecdotal, like, 'cause you guys have a good solution, is it, "Oh my god, you guys saved my butt." Or what are some of the commentary that you hear from the customers in terms of praise and and glory from your solution? >> Oh, some even say, when we do our demo and stuff, they say it's too hard to believe. >> Believe. >> Like, too hard. It's hard, you know, it's >> I dont believe you. They're skeptics. >> I don't believe you that because now you're able to bring up a global network within minutes. With networking services, like let's say you have APAC, you know, on-prem users, cloud also there, cloud here, users here, you can bring up a global network with full routed connectivity between all these endpoints with security services. You can bring up like a firewall from a third party or our services in the middle. This is a matter of minutes now. And this is all high speed connectivity with SLAs. Imagine like before connecting, you know, Singapore to U.S. East or Hong Kong to Frankfurt, you know, if you were putting your infrastructure in columns like E-connects, you would have to go, you know, figure out like, how am I going to- >> Seal line In, connect to it? Yeah. A lot of hassles, >> If you had to put like firewalls in the middle, segmentation, you had to, you know, isolate different entities. >> That's called heavy lifting. >> So what you're seeing is, you know, it's like customer comes in, there's a disbelief, can you really do that? And then they try it out, they go, "Wow, this works." Right? It's deployed in a small environment. And then all of a sudden they start taking off, right? And literally we have seen customers go from few thousand dollars a month or year type deployments to multi-million dollars a year type deployments in very, very short amount of time, in a few months. >> And you guys are pay as you go? >> Pay as you go. >> Pay as go usage cloud-based compatibility. >> Exactly. And it's amazing once they get to deploy the solution. >> What's the variable on the cost? >> On the cost? >> Is it traffic or is it. >> It's multiple different things. It's packaged into the overall solution. And as a matter of fact, we end up saving a lot of money to the customers. And not only in one way, in multiple different ways. And we do a complete TOI analysis for the customers. So it's bandwidth, it's number of connections, it's the amount of compute power that we are using. >> John: Similar things that they're used to. >> Just like the cloud constructs. Yeah. >> All right. Networking supercloud. Great. Congratulations. >> Thank you so much. >> Thanks for coming on Supercloud. >> Atif: Thank you. >> And looking forward to seeing more of the demand. Translate, instant networking. I'm sure it's going to be huge with the edge exploding. >> Oh yeah, yeah, yeah, yeah. >> Congratulations. >> Thank you so much. >> Thank you so much. >> Okay. So this is Supercloud 2 event here in Palo Alto. I'm John Furrier. The network Supercloud is here. Checkout Alkira. I'm John Furry, the host. Thanks for watching. (lively music)

(upbeat music) >> Hey, everyone, welcome back to Las Vegas, "theCube" is on our fourth day of covering AWS re:Invent, live from the Venetian Expo Center. This week has been amazing. We've created a ton of content, as you know, 'cause you've been watching. But, there's been north of 55,000 people here, hundreds of thousands online. We've had amazing conversations across the AWS ecosystem. Lisa Martin, Paul Gillan. Paul, what's your, kind of, take on day four of the conference? It's still highly packed. >> Oh, there's lots of people here. (laughs) >> Yep. Unusual for the final day of a conference. I think Werner Vogels, if I'm pronouncing it right kicked things off today when he talked about asymmetry and how the world is, you know, asymmetric. We build symmetric software, because it's convenient to do so, but asymmetric software actually scales and evolves much better. And I think that that was a conversation starter for a lot of what people are talking about here today, which is how the cloud changes the way we think about building software. >> Absolutely does. >> Our next guest, Holger Mueller, that's one of his key areas of focus. And Holger, welcome, thanks for joining us on the "theCube". >> Thanks for having me. >> What did you take away from the keynote this morning? >> Well, how do you feel on the final day of the marathon, right? We're like 23, 24 miles. Hit the ball yesterday, right? >> We are going strong Holger. And, of course, >> Yeah. >> you guys, we can either talk about business transformation with cloud or the World Cup. >> Or we can do both. >> The World Cup, hands down. World Cup. (Lisa laughs) Germany's out, I'm unbiased now. They just got eliminated. >> Spain is out now. >> What will the U.S. do against Netherlands tomorrow? >> They're going to win. What's your forecast? U.S. will win? >> They're going to win 2 to 1. >> What do you say, 2:1? >> I'm optimistic, but realistic. >> 3? >> I think Netherlands. >> Netherlands will win? >> 2 to nothing. >> Okay, I'll vote for the U.S.. >> Okay, okay >> 3:1 for the U.S.. >> Be optimistic. >> Root for the U.S.. >> Okay, I like that. >> Hope for the best wherever you work. >> Tomorrow you'll see how much soccer experts we are. >> If your prediction was right. (laughs) >> (laughs) Ja, ja. Or yours was right, right, so. Cool, no, but the event, I think the event is great to have 50,000 people. Biggest event of the year again, right? Not yet the 70,000 we had in 2019. But it's great to have the energy. I've never seen the show floor going all the way down like this, right? >> I haven't either. >> I've never seen that. I think it's a record. Often vendors get the space here and they have the keynote area, and the entertainment area, >> Yeah. >> and the food area, and then there's an exposition, right? This is packed. >> It's packed. >> Maybe it'll pay off. >> You don't see the big empty booths that you often see. >> Oh no. >> Exactly, exactly. You know, the white spaces and so on. >> No. >> Right. >> Which is a good thing. >> There's lots of energy, which is great. And today's, of course, the developer day, like you said before, right now Vogels' a rockstar in the developer community, right. Revered visionary on what has been built, right? And he's becoming a little professorial is my feeling, right. He had these moments before too, when it was justifying how AWS moved off the Oracle database about the importance of data warehouses and structures and why DynamoDB is better and so on. But, he had a large part of this too, and this coming right across the keynotes, right? Adam Selipsky talking about Antarctica, right? Scott against almonds and what went wrong. He didn't tell us, by the way, which often the tech winners forget. Scott banked on technology. He had motorized sleds, which failed after three miles. So, that's not the story to tell the technology. Let everything down. Everybody went back to ponies and horses and dogs. >> Maybe goes back to these asynchronous behavior. >> Yeah. >> The way of nature. >> And, yesterday, Swami talking about the bridges, right? The root bridges, right? >> Right. >> So, how could Werner pick up with his video at the beginning. >> Yeah. >> And then talk about space and other things? So I think it's important to educate about event-based architecture, right? And we see this massive transformation. Modern software has to be event based, right? Because, that's how things work and we didn't think like this before. I see this massive transformation in my other research area in other platforms about the HR space, where payrolls are being rebuilt completely. And payroll used to be one of the three peaks of ERP, right? You would size your ERP machine before the cloud to financial close, to run the payroll, and to do an MRP manufacturing run if you're manufacturing. God forbid you run those three at the same time. Your machine wouldn't be able to do that, right? So it was like start the engine, start the boosters, we are running payroll. And now the modern payroll designs like you see from ADP or from Ceridian, they're taking every payroll relevant event. You check in time wise, right? You go overtime, you take a day of vacation and right away they trigger and run the payroll, so it's up to date for you, up to date for you, which, in this economy, is super important, because we have more gig workers, we have more contractors, we have employees who are leaving suddenly, right? The great resignation, which is happening. So, from that perspective, it's the modern way of building software. So it's great to see Werner showing that. The dirty little secrets though is that is more efficient software for the cloud platform vendor too. Takes less resources, gets less committed things, so it's a much more scalable architecture. You can move the events, you can work asynchronously much better. And the biggest showcase, right? What's the biggest transactional showcase for an eventually consistent asynchronous transactional application? I know it's a mouthful, but we at Amazon, AWS, Amazon, right? You buy something on Amazon they tell you it's going to come tomorrow. >> Yep. >> They don't know it's going to come tomorrow by that time, because it's not transactionally consistent, right? We're just making every ERP vendor, who lives in transactional work, having nightmares of course, (Lisa laughs) but for them it's like, yes we have the delivery to promise, a promise to do that, right? But they come back to you and say, "Sorry, we couldn't make it, delivery didn't work and so on. It's going to be a new date. We are out of the product.", right? So these kind of event base asynchronous things are more and more what's going to scale around the world. It's going to be efficient for everybody, it's going to be better customer experience, better employee experience, ultimately better user experience, it's going to be better for the enterprise to build, but we have to learn to build it. So big announcement was to build our environment to build better eventful applications from today. >> Talk about... This is the first re:Invent... Well, actually, I'm sorry, it's the second re:Invent under Adam Selipsky. >> Right. Adam Selipsky, yep. >> But his first year. >> Right >> We're hearing a lot of momentum. What's your takeaway with what he delivered with the direction Amazon is going, their vision? >> Ja, I think compared to the Jassy times, right, we didn't see the hockey stick slide, right? With a number of innovations and releases. That was done in 2019 too, right? So I think it's a more pedestrian pace, which, ultimately, is good for everybody, because it means that when software vendors go slower, they do less width, but more depth. >> Yeah. >> And depth is what customers need. So Amazon's building more on the depth side, which is good news. I also think, and that's not official, right, but Adam Selipsky came from Tableau, right? >> Yeah. So he is a BI analytics guy. So it's no surprise we have three data lake offerings, right? Security data lake, we have a healthcare data lake and we have a supply chain data lake, right? Where all, again, the epigonos mentioned them I was like, "Oh, my god, Amazon's coming to supply chain.", but it's actually data lakes, which is an interesting part. But, I think it's not a surprise that someone who comes heavily out of the analytics BI world, it's off ringside, if I was pitching internally to him maybe I'd do something which he's is familiar with and I think that's what we see in the major announcement of his keynote on Tuesday. >> I mean, speaking of analytics, one of the big announcements early on was Amazon is trying to bridge the gap between Aurora. >> Yep. >> And Redshift. >> Right. >> And setting up for continuous pipelines, continuous integration. >> Right. >> Seems to be a trend that is common to all database players. I mean, Oracle is doing the same thing. SAP is doing the same thing. MariaDB. Do you see the distinction between transactional and analytical databases going away? >> It's coming together, right? Certainly coming together, from that perspective, but there's a fundamental different starting point, right? And with the big idea part, right? The universal database, which does everything for you in one system, whereas the suite of specialized databases, right? Oracle is in the classic Oracle database in the universal database camp. On the other side you have Amazon, which built a database. This is one of the first few Amazon re:Invents. It's my 10th where there was no new database announced. Right? >> No. >> So it was always add another one specially- >> I think they have enough. >> It's a great approach. They have enough, right? So it's a great approach to build something quick, which Amazon is all about. It's not so great when customers want to leverage things. And, ultimately, which I think with Selipsky, AWS is waking up to the enterprise saying, "I have all this different database and what is in them matters to me." >> Yeah. >> "So how can I get this better?" So no surprise between the two most popular database, Aurora and RDS. They're bring together the data with some out of the box parts. I think it's kind of, like, silly when Swami's saying, "Hey, no ETL.". (chuckles) Right? >> Yeah. >> There shouldn't be an ETL from the same vendor, right? There should be data pipes from that perspective anyway. So it looks like, on the overall value proposition database side, AWS is moving closer to the universal database on the Oracle side, right? Because, if you lift, of course, the universal database, under the hood, you see, well, there's different database there, different part there, you do something there, you have to configure stuff, which is also the case but it's one part of it, right, so. >> With that shift, talk about the value that's going to be in it for customers regardless of industry. >> Well, the value for customers is great, because when software vendors, or platform vendors, go in depth, you get more functionality, you get more maturity you get easier ways of setting up the whole things. You get ways of maintaining things. And you, ultimately, get lower TCO to build them, which is super important for enterprise. Because, here, this is the developer cloud, right? Developers love AWS. Developers are scarce, expensive. Might not be want to work for you, right? So developer velocity getting more done with same amount of developers, getting less done, less developers getting more done, is super crucial, super important. So this is all good news for enterprise banking on AWS and then providing them more efficiency, more automation, out of the box. >> Some of your customer conversations this week, talk to us about some of the feedback. What's the common denominator amongst customers right now? >> Customers are excited. First of all, like, first event, again in person, large, right? >> Yeah. >> People can travel, people meet each other, meet in person. They have a good handle around the complexity, which used to be a huge challenge in the past, because people say, "Do I do this?" I know so many CXOs saying, "Yeah, I want to build, say, something in IoT with AWS. The first reference built it like this, the next reference built it completely different. The third one built it completely different again. So now I'm doubting if my team has the skills to build things successfully, because will they be smart enough, like your teams, because there's no repetitiveness and that repetitiveness is going to be very important for AWS to come up with some higher packaging and version numbers.", right? But customers like that message. They like that things are working better together. They're not missing the big announcement, right? One of the traditional things of AWS would be, and they made it even proud, as a system, Jassy was saying, "If we look at the IT spend and we see something which is, like, high margin for us and not served well and we announced something there, right?" So Quick Start, Workspaces, where all liaisons where AWS went after traditional IT spend and had an offering. We haven't had this in 2019, we don't have them in 2020. Last year and didn't have it now. So something is changing on the AWS side. It's a little bit too early to figure out what, but they're not chewing off as many big things as they used in the past. >> Right. >> Yep. >> Did you get the sense that... Keith Townsend, from "The CTO Advisor", was on earlier. >> Yep. >> And he said he's been to many re:Invents, as you have, and he said that he got the sense that this is Amazon's chance to do a victory lap, as he called it. That this is a way for Amazon to reinforce the leadership cloud. >> Ja. >> And really, kind of, establish that nobody can come close to them, nobody can compete with them. >> You don't think that- >> I don't think that's at all... I mean, love Keith, he's a great guy, but I don't think that's the mindset at all, right? So, I mean, Jassy was always saying, "It's still the morning of the day in the cloud.", right? They're far away from being done. They're obsessed over being right. They do more work with the analysts. We think we got something right. And I like the passion, from that perspective. So I think Amazon's far from being complacent and the area, which is the biggest bit, right, the biggest. The only thing where Amazon truly has floundered, always floundered, is the AI space, right? So, 2018, Werner Vogels was doing more technical stuff that "Oh, this is all about linear regression.", right? And Amazon didn't start to put algorithms on silicon, right? And they have a three four trail and they didn't announce anything new here, behind Google who's been doing this for much, much longer than TPU platform, so. >> But they have now. >> They're keen aware. >> Yep. >> They now have three, or they own two of their own hardware platforms for AI. >> Right. >> They support the Intel platform. They seem to be catching up in that area. >> It's very hard to catch up on hardware, right? Because, there's release cycles, right? And just the volume that, just talking about the largest models that we have right now, to do with the language models, and Google is just doing a side note of saying, "Oh, we supported 50 less or 30 less, not little spoken languages, which I've never even heard of, because they're under banked and under supported and here's the language model, right? And I think it's all about little bit the organizational DNA of a company. I'm a strong believer in that. And, you have to remember AWS comes from the retail side, right? >> Yeah. >> Their roll out of data centers follows their retail strategy. Open secret, right? But, the same thing as the scale of the AI is very very different than if you take a look over at Google where it makes sense of the internet, right? The scale right away >> Right. >> is a solution, which is a good solution for some of the DNA of AWS. Also, Microsoft Azure is good. There has no chance to even get off the ship of that at Google, right? And these leaders with Google and it's not getting smaller, right? We didn't hear anything. I mean so much focused on data. Why do they focus so much on data? Because, data is the first step for AI. If AWS was doing a victory lap, data would've been done. They would own data, right? They would have a competitor to BigQuery Omni from the Google side to get data from the different clouds. There's crickets on that topic, right? So I think they know that they're catching up on the AI side, but it's really, really hard. It's not like in software where you can't acquire someone they could acquire in video. >> Not at Core Donovan. >> Might play a game, but that's not a good idea, right? So you can't, there's no shortcuts on the hardware side. As much as I'm a software guy and love software and don't like hardware, it's always a pain, right? There's no shortcuts there and there's nothing, which I think, has a new Artanium instance, of course, certainly, but they're not catching up. The distance is the same, yep. >> One of the things is funny, one of our guests, I think it was Tuesday, it was, it was right after Adam's keynote. >> Sure. >> Said that Adam Selipsky stood up on stage and talked about data for 52 minutes. >> Yeah. Right. >> It was timed, 52 minutes. >> Right. >> Huge emphasis on that. One of the things that Adam said to John Furrier when they were able to sit down >> Yeah >> a week or so ago at an event preview, was that CIOs and CEOs are not coming to Adam to talk about technology. They want to talk about transformation. They want to talk about business transformation. >> Sure, yes, yes. >> Talk to me in our last couple of minutes about what CEOs and CIOs are coming to you saying, "Holger, help us figure this out. We have to transform the business." >> Right. So we advise, I'm going quote our friends at Gartner, once the type A company. So we'll use technology aggressively, right? So take everything in the audience with a grain of salt, followers are the laggards, and so on. So for them, it's really the cusp of doing AI, right? Getting that data together. It has to be in the cloud. We live in the air of infinite computing. The cloud makes computing infinite, both from a storage, from a compute perspective, from an AI perspective, and then define new business models and create new best practices on top of that. Because, in the past, everything was fine out on premise, right? We talked about the (indistinct) size. Now in the cloud, it's just the business model to say, "Do I want to have a little more AI? Do I want a to run a little more? Will it give me the insight in the business?". So, that's the transformation that is happening, really. So, bringing your data together, this live conversation data, but not for bringing the data together. There's often the big win for the business for the first time to see the data. AWS is banking on that. The supply chain product, as an example. So many disparate systems, bring them them together. Big win for the business. But, the win for the business, ultimately, is when you change the paradigm from the user showing up to do something, to software doing stuff for us, right? >> Right. >> We have too much in this operator paradigm. If the user doesn't show up, doesn't find the click, doesn't find where to go, nothing happens. It can't be done in the 21st century, right? Software has to look over your shoulder. >> Good point. >> Understand one for you, autonomous self-driving systems. That's what CXOs, who're future looking, will be talked to come to AWS and all the other cloud vendors. >> Got it, last question for you. We're making a sizzle reel on Instagram. >> Yeah. >> If you had, like, a phrase, like, or a 30 second pitch that would describe re:Invent 2022 in the direction the company's going. What would that elevator pitch say? >> 30 second pitch? >> Yeah. >> All right, just timing. AWS is doing well. It's providing more depth, less breadth. Making things work together. It's catching up in some areas, has some interesting offerings, like the healthcare offering, the security data lake offering, which might change some things in the industry. It's staying the course and it's going strong. >> Ah, beautifully said, Holger. Thank you so much for joining Paul and me. >> Might have been too short. I don't know. (laughs) >> About 10 seconds left over. >> It was perfect, absolutely perfect. >> Thanks for having me. >> Perfect sizzle reel. >> Appreciate it. >> We appreciate your insights, what you're seeing this week, and the direction the company is going. We can't wait to see what happens in the next year. And, yeah. >> Thanks for having me. >> And of course, we've been on so many times. We know we're going to have you back. (laughs) >> Looking forward to it, thank you. >> All right, for Holger Mueller and Paul Gillan, I'm Lisa Martin. You're watching "theCube", the leader in live enterprise and emerging tech coverage. (upbeat 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 ascendancy of AWS under the leadership of Andy jassy was marked by a tsunami of data and corresponding cloud services to leverage that data now those Services they mainly came in the form of Primitives I.E basic building blocks that were used by developers to create more sophisticated capabilities AWS in the 2020s being led by CEO Adam solipski will be marked by four high-level Trends in our opinion one A Rush of data that will dwarf anything we've previously seen two a doubling or even tripling down on the basic elements of cloud compute storage database security Etc three a greater emphasis on end-to-end integration of AWS services to simplify and accelerate customer adoption of cloud and four significantly deeper business integration of cloud Beyond it as an underlying element of organizational operations hello and welcome to this week's wikibon Cube insights powered by ETR in this breaking analysis we extract and analyze nuggets from John furrier's annual sit-down with the CEO of AWS we'll share data from ETR and other sources to set the context for the market and competition in cloud and we'll give you our glimpse of what to expect at re invent in 2022. now before we get into the core of our analysis Alibaba has announced earnings they always announced after the big three you know a month later and we've updated our Q3 slash November hyperscale Computing forecast for the year as seen here and we're going to spend a lot of time on this as most of you have seen the bulk of it already but suffice to say alibaba's cloud business is hitting that same macro Trend that we're seeing across the board but a more substantial slowdown than we expected and more substantial than its peers they're facing China headwinds they've been restructuring its Cloud business and it's led to significantly slower growth uh in in the you know low double digits as opposed to where we had it at 15 this puts our year-end estimates for 2022 Revenue at 161 billion still a healthy 34 growth with AWS surpassing 80 billion in 2022 Revenue now on a related note one of the big themes in Cloud that we've been reporting on is how customers are optimizing their Cloud spend it's a technique that they use and when the economy looks a little shaky and here's a graphic that we pulled from aws's website which shows the various pricing plans at a high level as you know they're much more granular than that and more sophisticated but Simplicity we'll just keep it here basically there are four levels first one here is on demand I.E pay by the drink now we're going to jump down to what we've labeled as number two spot instances that's like the right place at the right time I can use that extra capacity in the moment the third is reserved instances or RIS where I pay up front to get a discount and the fourth is sort of optimized savings plans where customers commit to a one or three year term and for a better price now you'll notice we labeled the choices in a different order than AWS presented them on its website and that's because we believe that the order that we chose is the natural progression for customers this started on demand they maybe experiment with spot instances they move to reserve instances when the cloud bill becomes too onerous and if you're large enough you lock in for one or three years okay the interesting thing is the order in which AWS presents them we believe that on-demand accounts for the majority of AWS customer spending now if you think about it those on-demand customers they're also at risk customers yeah sure there's some switching costs like egress and learning curve but many customers they have multiple clouds and they've got experience and so they're kind of already up to a learning curve and if you're not married to AWS with a longer term commitment there's less friction to switch now AWS here presents the most attractive plan from a financial perspective second after on demand and it's also the plan that makes the greatest commitment from a lock-in standpoint now In fairness to AWS it's also true that there is a trend towards subscription-based pricing and we have some data on that this chart is from an ETR drill down survey the end is 300. pay attention to the bars on the right the left side is sort of busy but the pink is subscription and you can see the trend upward the light blue is consumption based or on demand based pricing and you can see there's a steady Trend toward subscription now we'll dig into this in a later episode of Breaking analysis but we'll share with you a little some tidbits with the data that ETR provides you can select which segment is and pass or you can go up the stack Etc but so when you choose is and paths 44 of customers either prefer or are required to use on-demand pricing whereas around 40 percent of customers say they either prefer or are required to use subscription pricing again that's for is so now the further mu you move up the stack the more prominent subscription pricing becomes often with sixty percent or more for the software-based offerings that require or prefer subscription and interestingly cyber security tracks along with software at around 60 percent that that prefer subscription it's likely because as with software you're not shutting down your cyber protection on demand all right let's get into the expectations for reinvent and we're going to start with an observation in data in this 2018 book seeing digital author David michella made the point that whereas most companies apply data on the periphery of their business kind of as an add-on function successful data companies like Google and Amazon and Facebook have placed data at the core of their operations they've operationalized data and they apply machine intelligence to that foundational element why is this the fact is it's not easy to do what the internet Giants have done very very sophisticated engineering and and and cultural discipline and this brings us to reinvent 2022 in the future of cloud machine learning and AI will increasingly be infused into applications we believe the data stack and the application stack are coming together as organizations build data apps and data products data expertise is moving from the domain of Highly specialized individuals to Everyday business people and we are just at the cusp of this trend this will in our view be a massive theme of not only re invent 22 but of cloud in the 2020s the vision of data mesh We Believe jamachtagani's principles will be realized in this decade now what we'd like to do now is share with you a glimpse of the thinking of Adam solipsky from his sit down with John Furrier each year John has a one-on-one conversation with the CEO of AWS AWS he's been doing this for years and the outcome is a better understanding of the directional thinking of the leader of the number one Cloud platform so we're now going to share some direct quotes I'm going to run through them with some commentary and then bring in some ETR data to analyze the market implications here we go this is from solipsky quote I.T in general and data are moving from departments into becoming intrinsic parts of how businesses function okay we're talking here about deeper business integration let's go on to the next one quote in time we'll stop talking about people who have the word analyst we inserted data he meant data data analyst in their title rather will have hundreds of millions of people who analyze data as part of their day-to-day job most of whom will not have the word analyst anywhere in their title we're talking about graphic designers and pizza shop owners and product managers and data scientists as well he threw that in I'm going to come back to that very interesting so he's talking about here about democratizing data operationalizing data next quote customers need to be able to take an end-to-end integrated view of their entire data Journey from ingestion to storage to harmonizing the data to being able to query it doing business Intelligence and human-based Analysis and being able to collaborate and share data and we've been putting together we being Amazon together a broad Suite of tools from database to analytics to business intelligence to help customers with that and this last statement it's true Amazon has a lot of tools and you know they're beginning to become more and more integrated but again under jassy there was not a lot of emphasis on that end-to-end integrated view we believe it's clear from these statements that solipsky's customer interactions are leading him to underscore that the time has come for this capability okay continuing quote if you have data in one place you shouldn't have to move it every time you want to analyze that data couldn't agree more it would be much better if you could leave that data in place avoid all the ETL which has become a nasty three-letter word more and more we're building capabilities where you can query that data in place end quote okay this we see a lot in the marketplace Oracle with mySQL Heatwave the entire Trend toward converge database snowflake [ __ ] extending their platforms into transaction and analytics respectively and so forth a lot of the partners are are doing things as well in that vein let's go into the next quote the other phenomenon is infusing machine learning into all those capabilities yes the comments from the michelleographic come into play here infusing Ai and machine intelligence everywhere next one quote it's not a data Cloud it's not a separate Cloud it's a series of broad but integrated capabilities to help you manage the end-to-end life cycle of your data there you go we AWS are the cloud we're going to come back to that in a moment as well next set of comments around data very interesting here quote data governance is a huge issue really what customers need is to find the right balance of their organization between access to data and control and if you provide too much access then you're nervous that your data is going to end up in places that it shouldn't shouldn't be viewed by people who shouldn't be viewing it and you feel like you lack security around that data and by the way what happens then is people overreact and they lock it down so that almost nobody can see it it's those handcuffs there's data and asset are reliability we've talked about that for years okay very well put by solipsky but this is a gap in our in our view within AWS today and we're we're hoping that they close it at reinvent it's not easy to share data in a safe way within AWS today outside of your organization so we're going to look for that at re invent 2022. now all this leads to the following statement by solipsky quote data clean room is a really interesting area and I think there's a lot of different Industries in which clean rooms are applicable I think that clean rooms are an interesting way of enabling multiple parties to share and collaborate on the data while completely respecting each party's rights and their privacy mandate okay again this is a gap currently within AWS today in our view and we know snowflake is well down this path and databricks with Delta sharing is also on this curve so AWS has to address this and demonstrate this end-to-end data integration and the ability to safely share data in our view now let's bring in some ETR spending data to put some context around these comments with reference points in the form of AWS itself and its competitors and partners here's a chart from ETR that shows Net score or spending momentum on the x-axis an overlap or pervasiveness in the survey um sorry let me go back up the net scores on the y-axis and overlap or pervasiveness in the survey is on the x-axis so spending momentum by pervasiveness okay or should have share within the data set the table that's inserted there with the Reds and the greens that informs us to how the dots are positioned so it's Net score and then the shared ends are how the plots are determined now we've filtered the data on the three big data segments analytics database and machine learning slash Ai and we've only selected one company with fewer than 100 ends in the survey and that's databricks you'll see why in a moment the red dotted line indicates highly elevated customer spend at 40 percent now as usual snowflake outperforms all players on the y-axis with a Net score of 63 percent off the charts all three big U.S cloud players are above that line with Microsoft and AWS dominating the x-axis so very impressive that they have such spending momentum and they're so large and you see a number of other emerging data players like rafana and datadog mongodbs there in the mix and then more established players data players like Splunk and Tableau now you got Cisco who's gonna you know it's a it's a it's a adjacent to their core networking business but they're definitely into you know the analytics business then the really established players in data like Informatica IBM and Oracle all with strong presence but you'll notice in the red from the momentum standpoint now what you're going to see in a moment is we put red highlights around databricks Snowflake and AWS why let's bring that back up and we'll explain so there's no way let's bring that back up Alex if you would there's no way AWS is going to hit the brakes on innovating at the base service level what we call Primitives earlier solipsky told Furrier as much in their sit down that AWS will serve the technical user and data science Community the traditional domain of data bricks and at the same time address the end-to-end integration data sharing and business line requirements that snowflake is positioned to serve now people often ask Snowflake and databricks how will you compete with the likes of AWS and we know the answer focus on data exclusively they have their multi-cloud plays perhaps the more interesting question is how will AWS compete with the likes of Specialists like Snowflake and data bricks and the answer is depicted here in this chart AWS is going to serve both the technical and developer communities and the data science audience and through end-to-end Integrations and future services that simplify the data Journey they're going to serve the business lines as well but the Nuance is in all the other dots in the hundreds or hundreds of thousands that are not shown here and that's the AWS ecosystem you can see AWS has earned the status of the number one Cloud platform that everyone wants to partner with as they say it has over a hundred thousand partners and that ecosystem combined with these capabilities that we're discussing well perhaps behind in areas like data sharing and integrated governance can wildly succeed by offering the capabilities and leveraging its ecosystem now for their part the snowflakes of the world have to stay focused on the mission build the best products possible and develop their own ecosystems to compete and attract the Mind share of both developers and business users and that's why it's so interesting to hear solipski basically say it's not a separate Cloud it's a set of integrated Services well snowflake is in our view building a super cloud on top of AWS Azure and Google when great products meet great sales and marketing good things can happen so this will be really fun to watch what AWS announces in this area at re invent all right one other topic that solipsky talked about was the correlation between serverless and container adoption and you know I don't know if this gets into there certainly their hybrid place maybe it starts to get into their multi-cloud we'll see but we have some data on this so again we're talking about the correlation between serverless and container adoption but before we get into that let's go back to 2017 and listen to what Andy jassy said on the cube about serverless play the clip very very earliest days of AWS Jeff used to say a lot if I were starting Amazon today I'd have built it on top of AWS we didn't have all the capability and all the functionality at that very moment but he knew what was coming and he saw what people were still able to accomplish even with where the services were at that point I think the same thing is true here with Lambda which is I think if Amazon were starting today it's a given they would build it on the cloud and I think we with a lot of the applications that comprise Amazon's consumer business we would build those on on our serverless capabilities now we still have plenty of capabilities and features and functionality we need to add to to Lambda and our various serverless services so that may not be true from the get-go right now but I think if you look at the hundreds of thousands of customers who are building on top of Lambda and lots of real applications you know finra has built a good chunk of their market watch application on top of Lambda and Thompson Reuters has built you know one of their key analytics apps like people are building real serious things on top of Lambda and the pace of iteration you'll see there will increase as well and I really believe that to be true over the next year or two so years ago when Jesse gave a road map that serverless was going to be a key developer platform going forward and so lipsky referenced the correlation between serverless and containers in the Furrier sit down so we wanted to test that within the ETR data set now here's a screen grab of The View across 1300 respondents from the October ETR survey and what we've done here is we've isolated on the cloud computing segment okay so you can see right there cloud computing segment now we've taken the functions from Google AWS Lambda and Microsoft Azure functions all the serverless offerings and we've got Net score on the vertical axis we've got presence in the data set oh by the way 440 by the way is highly elevated remember that and then we've got on the horizontal axis we have the presence in the data center overlap okay that's relative to each other so remember 40 all these guys are above that 40 mark okay so you see that now what we're going to do this is just for serverless and what we're going to do is we're going to turn on containers to see the correlation and see what happens so watch what happens when we click on container boom everything moves to the right you can see all three move to the right Google drops a little bit but all the others now the the filtered end drops as well so you don't have as many people that are aggressively leaning into both but all three move to the right so watch again containers off and then containers on containers off containers on so you can see a really major correlation between containers and serverless okay so to get a better understanding of what that means I call my friend and former Cube co-host Stu miniman what he said was people generally used to think of VMS containers and serverless as distinctly different architectures but the lines are beginning to blur serverless makes things simpler for developers who don't want to worry about underlying infrastructure as solipsky and the data from ETR indicate serverless and containers are coming together but as Stu and I discussed there's a spectrum where on the left you have kind of native Cloud VMS in the middle you got AWS fargate and in the rightmost anchor is Lambda AWS Lambda now traditionally in the cloud if you wanted to use containers developers would have to build a container image they have to select and deploy the ec2 images that they or instances that they wanted to use they have to allocate a certain amount of memory and then fence off the apps in a virtual machine and then run the ec2 instances against the apps and then pay for all those ec2 resources now with AWS fargate you can run containerized apps with less infrastructure management but you still have some you know things that you can you can you can do with the with the infrastructure so with fargate what you do is you'd build the container images then you'd allocate your memory and compute resources then run the app and pay for the resources only when they're used so fargate lets you control the runtime environment while at the same time simplifying the infrastructure management you gotta you don't have to worry about isolating the app and other stuff like choosing server types and patching AWS does all that for you then there's Lambda with Lambda you don't have to worry about any of the underlying server infrastructure you're just running code AS functions so the developer spends their time worrying about the applications and the functions that you're calling the point is there's a movement and we saw in the data towards simplifying the development environment and allowing the cloud vendor AWS in this case to do more of the underlying management now some folks will still want to turn knobs and dials but increasingly we're going to see more higher level service adoption now re invent is always a fire hose of content so let's do a rapid rundown of what to expect we talked about operate optimizing data and the organization we talked about Cloud optimization there'll be a lot of talk on the show floor about best practices and customer sharing data solipsky is leading AWS into the next phase of growth and that means moving beyond I.T transformation into deeper business integration and organizational transformation not just digital transformation organizational transformation so he's leading a multi-vector strategy serving the traditional peeps who want fine-grained access to core services so we'll see continued Innovation compute storage AI Etc and simplification through integration and horizontal apps further up to stack Amazon connect is an example that's often cited now as we've reported many times databricks is moving from its stronghold realm of data science into business intelligence and analytics where snowflake is coming from its data analytics stronghold and moving into the world of data science AWS is going down a path of snowflake meet data bricks with an underlying cloud is and pass layer that puts these three companies on a very interesting trajectory and you can expect AWS to go right after the data sharing opportunity and in doing so it will have to address data governance they go hand in hand okay price performance that is a topic that will never go away and it's something that we haven't mentioned today silicon it's a it's an area we've covered extensively on breaking analysis from Nitro to graviton to the AWS acquisition of Annapurna its secret weapon new special specialized capabilities like inferential and trainium we'd expect something more at re invent maybe new graviton instances David floyer our colleague said he's expecting at some point a complete system on a chip SOC from AWS and maybe an arm-based server to eventually include high-speed cxl connections to devices and memories all to address next-gen applications data intensive applications with low power requirements and lower cost overall now of course every year Swami gives his usual update on machine learning and AI building on Amazon's years of sagemaker innovation perhaps a focus on conversational AI or a better support for vision and maybe better integration across Amazon's portfolio of you know large language models uh neural networks generative AI really infusing AI everywhere of course security always high on the list that reinvent and and Amazon even has reinforce a conference dedicated to it uh to security now here we'd like to see more on supply chain security and perhaps how AWS can help there as well as tooling to make the cio's life easier but the key so far is AWS is much more partner friendly in the security space than say for instance Microsoft traditionally so firms like OCTA and crowdstrike in Palo Alto have plenty of room to play in the AWS ecosystem we'd expect of course to hear something about ESG it's an important topic and hopefully how not only AWS is helping the environment that's important but also how they help customers save money and drive inclusion and diversity again very important topics and finally come back to it reinvent is an ecosystem event it's the Super Bowl of tech events and the ecosystem will be out in full force every tech company on the planet will have a presence and the cube will be featuring many of the partners from the serial floor as well as AWS execs and of course our own independent analysis so you'll definitely want to tune into thecube.net and check out our re invent coverage we start Monday evening and then we go wall to wall through Thursday hopefully my voice will come back we have three sets at the show and our entire team will be there so please reach out or stop by and say hello all right we're going to leave it there for today many thanks to Stu miniman and David floyer for the input to today's episode of course John Furrier for extracting the signal from the noise and a sit down with Adam solipski thanks to Alex Meyerson who was on production and manages the podcast Ken schiffman as well Kristen Martin and Cheryl Knight helped get the word out on social and of course in our newsletters Rob hoef is our editor-in-chief over at siliconangle does some great editing thank thanks to all of you remember all these episodes are available as podcasts wherever you listen you can pop in the headphones go for a walk just search breaking analysis podcast I published each week on wikibon.com at siliconangle.com or you can email me at david.valante at siliconangle.com or DM me at di vallante or please comment on our LinkedIn posts and 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 we'll see it reinvent or we'll see you next time on breaking analysis [Music]

foreign [Music] my name is Savannah Peterson and I am very excited to be coming to you today from the cube in Palo Alto we're going to be talking about kubecon giving a little preview of the hype and what you might be able to expect in Detroit with the one and only co-founder and CEO of the cube and siliconangle John ferriere John hello how are you today thanks for hosting and doing the preview with me my goodness a pleasure I we got acquainted this time last year how do you think the ecosystem has changed are you excited well first of all I missed kubecon Valencia because I had covid I was so excited to be there this big trip plan and then couldn't make it but so much has gone on I mean we've been at every kubecon the cube was there at the beginning when openstack was still going on kubernetes just started came out of Google we were there having beers with Lou Tucker and a bunch of The Luminaries when it all kind of came together and then watch it year by year progress through and how it's changed the industry and mainly how open source has been really the wave behind it combining with the Linux foundation and then cncf and then open source movement and good kubernetes has been amazing and under it all containers has been the real driver and all this so you know Docker containers Docker was a well-funded company they had to Pivot and were restructured now they're pure open source so containers have gone Supernova on top of that kubernetes and with that's a complete ecosystem of opportunity to create the next operating system in in software development so to me kubecon is at the center of software software 2030 what do you want to call it super cloud it's that it's really action it's not where the old school is it's where the new school is excellent so what has you most excited this year what's the biggest change from this time last year and now well two things I'm looking at this year uh carefully both from an editorial lens and also from a sponsorship lenses where is the funding going on the sponsorships because again a very diverse ecosystem of Builders but also vendors so I'm going to see how that Dynamics going on but also on the software side a lot of white space going on in the stack or in the map if you will you know the run times you've got observability you got a lot of competition maybe projects might be growing some Rising some falling maybe merge together I'm going to see how that but there's a lot of white spaces developing so I'm curious to see what's new on that area and then service meshes is a big deal this year so I'm looking for what's going on so it's been kind of a I won't say cold war but kind of like uh you know where is this going to go and because it's a super important part of of the of the orchestration and managing containers and so be very interested to see how service mesh does istio and other versions out there have been around for a while so that and also the other controversy is the number of stars on GitHub a project may have so sometimes that carries a lot of weight but we're going to look at which ones are rising which ones are falling again um which ones are getting the most votes by the developers vote with their code yeah absolutely well we did definitely miss you down in Los Angeles but it will be great to be in Detroit what has you most excited do you think that we're going to see the number of people in person that we have in the past I know you've seen it since the beginning so I think this year is going to be explosive from that psychology angle because I think it was really weird because La was on they were a bold to make that move we're all there is first conference back it was a lot a lot of like badges don't touch me only handshakes fist pumps but it was at the beginning of the covid second wave right so it was kind of still not yet released where everyone's was not worried about it so I think it's in the past year in the past eight months I mean I've been places with no masks people have no masks Vegas other places so I think it's going to be a year where it will be a lot more people in person because the growth and the opportunities are so big it's going to drive a lot of people in person just like Amazon reinvent those yeah absolutely and as the most important and prominent event in the kubernetes space I think everyone's very excited to to get back together when we think about this space do you think there that anyone's the clear winner yet or do you think it's still a bit of a open territory in terms of the companies and Partnerships I think Red Hat has done a great job and they're you know I think they're going to see how well they can turn this into gold for them because they've positioned themselves very well open shift years ago was kind of waffling I won't say it in a bad way but like but once they got view on containers and kubernetes red has done an exceptional job in how they position their company being bought by ibms can be very interesting to see how that influences change so if Red Hat can stay red hat I think IBM will win I think customers that's one company I like the startups we're seeing companies like platform nine Rafi systems young companies coming out in the kubernetes as a service space because I think whoever can make kubernetes easier because I think that's the hard part right now even though that the show is called kubecon is a lot more than kubernetes I think the container layer what docker's doing has been exceptional that's the real action the question is how does that impact the kubernetes layers so kubernetes is not a done deal yet I think it hasn't really crossed the chasm yet it's certainly popular but not every company is adopting it so we're starting to see that we need to see more adoption of kubernetes seeing that happen it's going to decide who the winners are totally agree with that if you look at the data a lot of companies are and people are excited about kubernetes but they haven't taken the plunge to shifting over their stack or fully embracing it because of that complexity so I'm very curious to see what we learn this week about who those players might be moving forward how does it feel to be in Detroit when was the last time you were here I was there in 2007 was the last time I was in that town so uh we'll see what's like wow yeah but things have changed yeah the lions are good this year they've got great hockey goalies there so you know all right you've heard that sports fans let John know what you're thinking your Sports predictions for this season I love that who do you hope to get to meet while we're at the show I want to meet more end user customers we're gonna have Envoy again on the cube I think Red Hat was going to be a big sponsor this year they've been great um we're looking for end user project most looking for some editorial super cloud like um commentary because the cncf is kind of the developer Tech Community that's powering in my opinion this next wave of software development Cloud native devops is now Cloud native developers devops is kind of going away that's killed I.T in my opinion data and security Ops is the new kind of Ops the new it so it's good to see how devops turns into more of a software engineering meet supercloud so I think you're going to start to see the infrastructure become more programmable it's infrastructure as code so I think if anything I'm more excited to hear more stories about how infrastructure as code is now the new standard so if when that truly happens the super cloud model be kicking into high gear I love that let's you touched on it a little bit right there but I want to dig in a bit since you've been around since the beginning what is it that you appreciate or enjoy so much about the kubernetes community and the people around this I think there are authentic people and I think they're they're building they're also Progressive they're very diverse um they're open and inclusive they try stuff and um they can be critical but they're not jerks about it so when people try something um they're open-minded of a failure so it's a classic startup mentality I think that is embodied throughout the Linux Foundation but CNC in particular has to bridge the entrepreneurial and corporate Vibe so they've done an exceptional job doing that and that's what I like about this money making involved but there's also a lot of development and Innovation that comes out of it so the next big name and startup could come out of this community and that's what I hope to see coming out here is that next brand that no one's heard of that just comes out of nowhere and just takes a big position in the marketplace so that's going to be interesting to see hopefully we have on our stage there yeah that's the goal we're going to interview them all a year from now when we're sitting here again what do you hope to be able to say about this space or this event that we might not be able to say today I think it's going to be more of clarity around um the new modern software development techniques software next gen using AI more faster silicon chips you see Amazon with what they're doing the custom silicon more processing but I think Hardware matters we've been talking a lot about that I think I think it's we're going to shift from what's been innovative and what's changed I think I think if you look at what's been going on in the industry outside of crypto the infrastructure hasn't really changed much except for AWS what they've done so I'm expecting to see more Innovations at the physics level way down in the chips and then that lower end of the stack is going to be dominated by either one of the three clouds probably AWS and then the middle layer is going to be this where the abstraction is around making infrastructure as code really happen I think that's going to be Clarity coming out of this year next year we should have some visibility into the vertical applications and of the AI and machine learning absolutely digging in on that actually even more because I like what you're saying a lot what verticals do you think that kubernetes is going to impact the most looking even further out than say a year I mean I think that hot ones Healthcare fintech are obvious to get the most money they're spending I think they're the ones who are already kind of creating these super cloud models where they're actually changed over their their spending from capex to Opex and they're driving top line revenue as part of that so you're seeing companies that wants customers of the I.T vendors are now becoming the providers that's a big super cloud Trend we see the other verticals are going to be served by a lot of men in Surprise oil and gas you know all the classic versus Healthcare I mentioned that one those are the classic verticals retail is going to I think be massively huge as you get more into the internet of things that's truly internet based you're going to start to see a lot more Edge use cases so Telecom I think it's going to be completely disrupted by new brands so I think once that you see see how that plays out but all verticals are going to be disrupted just a casual statement to say yeah yeah no doubt in my mind that's great I'm personally really excited about the edge applications that are possible here and can't wait to see can't wait to see what happens next I'm curious as to your thoughts how based given your history here and we don't have to say number of years that you've been participating in in Cape Cod but give them your history what's the evolution looked like from that Community perspective when you were all just starting out having that first drink did you anticipate that we would be here with thousands of people in Detroit you know I knew the moment was happening around um 2017-2018 Dan Coney no longer with us he passed away I ran into him randomly in China and it was like what are you doing here he was with a bunch of Docker guys so they were already investing in so I knew that the cncf was a great Steward for this community because they were already doing the work Dan led a great team at that time and then they were they were they were kicking ass and they were just really setting the foundation they dig in they set the architecture perfectly so I knew that that was a moment that was going to be pretty powerful at the early days when we were talking about kubernetes before it even started we were always always talking about if this this could be the tcpip of of cloud then we could have kind of a de facto interoperability and Lou Tucker was working for Cisco at the time and we were called it interclouding inter-networking what that did during the the revolution Cloud yeah the revolution of the client server and PC Revolution was about connectivity and so tcpip was the disruptive enable that created massive amounts of wealth created a lot of companies created a whole generation of companies so I think this next inflection point is kind of happening right now I think kubernetes is one step of this abstraction layer but you start to see companies like snowflake who's built on AWS and then moved to multiple clouds Goldman Sachs Capital One you're going to see insurance companies so we believe that the rise of the super cloud is here that's going to be Cloud 3.0 that's software 3.0 it's software three what do you want to call it it's not yesterday's Cloud lift and shift and run a SAS application it's a true Enterprise digital digital transformation so that's that's kind of the trend that we see riding in now and so you know if you're not on that side of the street you're going to get washed away from that wave so it's going to be interesting to see how how it all plays out so it's fun to watch who's on the wrong side it is very fun I hope you all are listening to this really powerful advice from John he's dropping some serious knowledge bombs on us well holding the back for kubecon because we've got we got all the great guests coming on and that's where all the content comes from I mean the best part of the community is that they're sharing yeah absolutely so just for old time's sake and it's because it's how I met your fabulous team last year Define kubernetes for the audience kubernetes is like what someone said it was a magical Christmas I heard that was a well good explanation with that when I heard that one um you mean the technical definition or like the business definition or maybe both you can give us an interpretive dance if you'd like I mean the simplest way to describe kubernetes is an orchestration layer that orchestrates containers that are containing applications and it's a way to keep things running and runtime assembly of like the of the data so if you've got you're running containers you can containerize applications kubernetes gives you that capability to run applications at scale which feeds into uh the development uh cycle of the pipelining of apps so if you're writing applications and you want to scale up it's a fast way to stand up massive amounts of scale using containers and kubernetes so a variety of other things that are in the in the in the system too so that was pretty good there's a lot more under the hood but that's the oversimplified version I think that's what we were going for I think it's actually I mean it's harder to oversimplify it sometimes in this case it connects it connects well it's the connective tissue between all the container applications yes last question for you John we are here at the cube we're very excited to be headed to Detroit very soon what can people expect from the cube at coupon this year so we'll be broadcasting Wednesday Thursday and Friday we'll be there early I'll be there Monday and Tuesday we'll do our normal kind of hanging around getting some scoop on the on the ground floor you'll see us there Monday and Tuesday probably in the in the lounge too um come up and say hi to us um again we're looking for more stories this year we believe this is the year that you're going to hear a lot more storytelling coming out of this community as people get more proof points so come up to us share your email your your handle give us yours give us your story we'll publish it we think we think this is going to be the year that cloud native developers start showing the signs of the of the rise of the supercloud that's going to come out of this this community so you know if you got something to say you know we're open to share stories so we're here all that speaking of John how can people say hi to you and the team on Twitter at Furrier at siliconangle at thecube thecube.net siliconangle.com LinkedIn Dave vellantis they were open on all channels all right signal Instagram WhatsApp perfect well pick your channel we really hope to hear from you John thank you so much for joining us for this preview session and thank you for tuning in my name is Savannah Peterson here in Palo Alto at thecube Studios looking forward to Detroit we can't wait to hear your thoughts do let us know in the comments and let us know if you're headed to Michigan cheers [Music] thank you

>>Okay, welcome back everyone. There's the cubes coverage of VMware Explorer, 22 formerly world. We've been here since 2010 and world 2010 to now it's 2022. And it's VMware Explorer. We're here at the CEO, regular writer. Welcome back to the cube. Great to see you in person. >>Yeah. Great to be here in person, >>Dave and I are, are proud to say that we've been to 12 straight years of covering VMware's annual conference. And thank you. We've seen the change in the growth over time and you know, it's kind of, I won't say pinch me moment, but it's more of a moment of there's the VMware that's grown into the cloud after your famous deal with Andy jazzy in 2016, we've been watching what has been a real sea change and VMware since taking that legacy core business and straightening out the cloud strategy in 2016, and then since then an acceleration of, of cloud native, like direction under your leadership at VMware. Now you're the CEO take us through that because this is where we are right now. We are here at the pinnacle of VMware 2.0 or cloud native VMware, as you point out on your keynote, take us through that history real quick. Cuz I think it's important to know that you've been the architect of a lot of this change and it's it's working. >>Yeah, definitely. We are super excited because like I said, it's working, the history is pretty simple. I mean we tried running our own cloud cloud air. We cloud air didn't work so well. Right. And then at that time, customers really gave us strong feedback that the hybrid they wanted was a Amazon together. Right. And so that's what we went back and did and the andjay announcement, et cetera. And then subsequently as we were continue to build it out, I mean, once that happened, we were able to go work with the Satia and Microsoft and others to get the thing built out all over. Then the next question was okay, Hey, that's great for the workloads that are running on vSphere. What's the story for workloads that are gonna be cloud native and benefit a lot from being cloud native. So that's when we went the Tansu route and the Kubernetes route, we did a couple of acquisitions and then we started that started paying off now with the Tansu portfolio. And last but not the least is once customers have this distributed portfolio now, right. Increasingly everything is becoming multi-cloud. How do you manage and connect and secure. So that's what you start seeing that you saw the management announcement, networking and security and everything else is cooking. And you'll see more stuff there. >>Yeah know, we've been talking about super cloud. It's kinda like a multi-cloud on steroids kind a little bit different pivot of it. And we're seeing some use cases. >>No, no, it's, it's a very great, it's a, it's pretty close to what we talk about. >>Awesome. I mean, and we're seeing this kind of alignment in the industry. It's kind of open, but I have to ask you, when did you, you have the moment where you said multicloud is the game changer moment. When did you have, because you guys had hybrid, which is really early as well. When was the Raghu? When did you have the moment where you said, Hey, multicloud is what's happening. That's we're doubling down on that go. >>I mean, if you think about the evolution of the cloud players, right. Microsoft really started picking up around the 2018 timeframe. I mean, I'm talking about Azure, right? >>In a big way. >>Yeah. In a big way. Right. When that happened and then Google got really serious, it became pretty clear that this was gonna be looking more like the old database market than it looked like a single player cloud market. Right. Equally sticky, but very strong players all with lots of IP creation capability. So that's when we said, okay, from a supplier side, this is gonna become multi. And from a customer side that has always been their desire. Right. Which is, Hey, I don't want to get locked into anybody. I want to do multiple things. And the cloud vendors also started leveraging that OnPrem. Microsoft said, Hey, if you're a windows customer, your licensing is gonna be better off if you go to Azure. Right. Oracle did the same thing. So it just became very clear. >>I am, I have gone make you laugh. I always go back to the software mainframe because I, I think you were here. Right. I mean, you're, you're almost 20 years in. Yeah. And I, the reason I appreciate that is because, well, that's technically very challenging. How do you make virtualization overhead virtually non-existent how do you run any workload? Yeah. How do you recover from, I mean, that's was not trivial. Yeah. Okay. So what's the technical, you know, analog today, the real technical challenge. When you think about cross cloud services. >>Yeah. I mean, I think it's different for each of these layers, right? So as I was alluding to for management, I mean, you can go each one of them by themselves, there is one way of Mo doing multi-cloud, which is multiple clouds. Right. You could say, look, I'm gonna build a great product for AWS. And then I'm gonna build a great product for Azure. I'm gonna build a great product for Google. That's not what aria is. Aria is a true multi-cloud, which means it pulls data in from multiple places. Right? So there are two or three, there are three things that aria has done. That's I think is super interesting. One is they're not trying to take all the data and bring it in. They're trying to federate the data sources. And secondly, they're doing it in real time and they're able to construct this graph of a customer's cloud resources. >>Right. So to keep the graph constructed and pulling data, federating data, I think that's a very interesting concept. The second thing that, like I said is it's a real time because in the cloud, a container might come and go like that. Like that is a second technical challenge. The third it's not as much a technical challenge, but I really like what they have done for the interface they've used GraphQL. Right? So it's not about if you remember in the old world, people talk about single pan or glass, et cetera. No, this is nothing to do with pan or glass. This is a data model. That's a graph and a query language that's suited for that. So you can literally think of whatever you wanna write. You can write and express it in GraphQL and pull all sorts of management applications. You can say, Hey, I can look at cost. I can look at metrics. I can look at whatever it is. It's not five different types of applications. It's one, that's what I think had to do it at scale is the other problem. And, and >>The, the technical enable there is just it's good software. It's a protocol. It's >>No, no, it's, it's, it's it's software. It's a data model. And it's the Federation architecture that they've got, which is open. Right. You can pull in data from Datadog, just as well as from >>Pretty >>Much anything data from VR op we don't care. Right? >>Yeah. Yeah. So rego, I have to ask you, I'm glad you like the Supercloud cuz you know, we, we think multi-cloud still early, but coming fast. I mean, everyone has multiple clouds, but spanning this idea of spanning across has interesting sequences. Do you data, do you do computer both and a lot of good things happening. Kubernetes been containers, all that good stuff. Okay. How do you see the first rev of multi-cloud evolving? Like is it what happens? What's the sequence, what's the order of operations for a client standpoint? Customer standpoint of, of multicloud or Supercloud because we think we're seeing it as a refactoring of something like snowflake, they're a data base, they're a data warehouse on the cloud. They, they say data cloud they'd they like they'll tell us no, you, we're not a data. We're not a data warehouse. We're data cloud. Okay. You're a data warehouse refactored for the CapEx from Amazon and cooler, newer things. Yeah, yeah, yeah. That's a behavior change. Yeah. But it's still a data warehouse. Yeah. How do you see this multi-cloud environment? Refactoring? Is there something that you see that might be different? That's the same if you know what I'm saying? Like what's what, what's the ne the new thing that's happening with multi-cloud, that's different than just saying I'm I'm doing SAS on the cloud. >>Yeah. So I would say, I would point to a, a couple of things that are different. Firstly, my, the answer depends on which category you are in. Like the category that snowflake is in is very different than Kubernetes or >>Something or Mongo DB, right? >>Yeah. Or Mongo DB. So, so it is not appropriate to talk about one multi-cloud approach across data and compute and so, so on and so forth. So I'll talk about the spaces that we play. Right. So step one, for most customers is two application architectures, right? The cloud native architecture and an enterprise native architecture and tying that together either through data or through networks or through et cetera. So that's where most of the customers are. Right. And then I would say step two is to bring these things together in a more, in a closer fashion and that's where we are going. And that is why you saw the cloud universal announcement and that's already, you've seen the Tansu announcement, et cetera. So it's really, the step one was two distinct clouds. That is just two separate islands. >>So the other thing that we did, that's really what my, the other thing that I'd like to get to your reaction on, cause this is great. You're like a masterclass in the cube here. Yeah, totally is. We see customers becoming super clouds because they're getting the benefit of, of VMware, AWS. And so if I'm like a media company or insurance company, if I have scale, if I continue to invest in, in cloud native development, I do all these things. I'm gonna have a da data scale advantage, possibly agile, which means I can build apps and functionality very quick for customers. I might become my own cloud within the vertical. Exactly. And so I could then service other people in the insurance vertical if I'm the insurance company with my technology and create a separate power curve that never existed before. Cause the CapEx is off the table, it's operating expense. Yep. That runs into the income statement. Yep. This is a fundamental business model shift and an advantage of this kind of scenario. >>And that's why I don't think snowflakes, >>What's your reaction to that? Cuz that's something that, that is not really, talk's highly nuanced and situational. But if Goldman Sachs builds the biggest cloud on the planet for financial service for their own benefit, why wouldn't they >>Exactly. >>And they're >>Gonna build it. They sort of hinted at it that when they were up on stage on AWS, right. That is just their first big step. I'm pretty sure over time they would be using other clouds. Think >>They already are on >>Prem. Yeah. On prem. Exactly. They're using VMware technology there. Right? I mean think about it, AWS. I don't know how many billions of dollars they're spending on AWS R and D Microsoft is doing the same thing. Google's doing the same thing we are doing. Not as much as them that you're doing oral chair. Yeah. If you are a CIO, you would be insane not to take advantage of all of this IP that's getting created and say, look, I'm just gonna bet on one. Doesn't make any sense. Right. So that's what you're seeing. And then >>I think >>The really smart companies, like you talked about would say, look, I will do something for my industry that uses these underlying clouds as the substrate, but encapsulates my IP and my operating model that I then offer to other >>Partners. Yeah. And their incentive for differentiation is scale. Yeah. And capability. And that's a super cloud. That's a, or would be say it environment. >>Yeah. But this is why this, >>It seems like the same >>Game, but >>This, I mean, I think it environment is different than >>Well, I mean it advantage to help the business, the old day service, you >>Said snowflake guys out the marketing guys. So you, >>You said snowflake data warehouse. See, I don't think it's in data warehouse. It's not, that's like saying, you >>Know, I, over >>VMware is a virtualization company or service now is a help desk tool. I, this is the change. Yes. That's occurring. Yes. And that you're enabling. So take the Goldman Sachs example. They're gonna run OnPrem. They're gonna use your infrastructure to do selfer. They're gonna build on AWS CapEx. They're gonna go across clouds and they're gonna need some multi-cloud services. And that's your opportunity. >>Exactly. That's that's really, when you, in the keynote, I talked about cloud universal. Right? So think of a future where we can go to a customer and say, Mr. Customer buy thousand scores, a hundred thousand cores, whatever capacity you can use it, any which way you want on any application platform. Right. And it could be OnPrem. It could be in the cloud, in the cloud of their choice in multiple clouds. And this thing can be fungible and they can tie it to the right services. If they like SageMaker they could tie it to Sage or Aurora. They could tie it to Aurora, cetera, et cetera. So I think that's really the foundation that we are setting. Well, I think, I >>Mean, you're building a cloud across clouds. I mean, that's the way I look at it. And, and that's why it's, to me, the, the DPU announcement, the project Monterey coming to fruition is so important. Yeah. Because if you don't have that, if you're not on that new Silicon curve yep. You're gonna be left behind. Oh, >>Absolutely. It allows us to build things that you would not otherwise be able to do, >>Not to pat ourselves on the back Ragu. But we, in what, 2013 day we said, feel >>Free. >>We, we said with Lou Tucker when OpenStack was crashing. Yeah. Yeah. And then Kubernetes was just a paper. We said, this could be the interoperability layer. Yeah. You got it. And you could have inter clouding cuz there was no clouding. I was gonna riff on inter networking. But if you remember inter networking during the OSI model, TCP and IP were hardened after the physical data link layer was taken care of. So that enabled an entire new industry that was open, open interconnect. Right. So we were saying inter clouding. So what you're kind of getting at with cross cloud is you're kind of creating this routing model if you will. Not necessarily routing, but like connection inter clouding, we called it. I think it's kinda a terrible name. >>What you said about Kubernetes is super critical. It is turning out to be the infrastructure API so long. It has been an infrastructure API for a certain cluster. Right. But if you think about what we said about VSE eight with VSE eight Kubernetes becomes the data center API. Now we sort of glossed over the point of the keynote, but you could do operations storage, anything that you can do on vSphere, you can do using a Kubernetes API. Yeah. And of course you can do all the containers in the Kubernetes clusters and et cetera, is what you could always do. Now you could do that on a VMware environment. OnPrem, you could do that on EKS. Now Kubernetes has become the standard programming model for infrastructure across. It >>Was the great equalizer. Yeah. You, we used to say Amazon turned the data center through an API. It turns, turns of like a lot of APIs and a lot of complexity. Right. And Kubernetes changed. >>Well, the role, the role of defacto standards played a lot into the T C P I P revolution before it became a standard standard. What the question Raghu, as you look at, we had submit on earlier, we had tutorial on as well. What's the disruptive enabler from a defacto. What in your mind, what should, because Kubernetes became kind of defacto, even though it was in the CNCF and in an open source open, it wasn't really standard standard. There's no like standards, body, but what de facto thing has to happen in your mind's eye around making inter clouding or connecting clouds in a, in a way that's gonna create extensibility and growth. What do you see as a de facto thing that the industry should rally around? Obviously Kubernetes is one, is there something else that you see that's important for in an open way that the industry can discuss and, and get behind? >>Yeah. I mean, there are things like identity, right? Which are pretty critical. There is connectivity and networking. So these are all things that the industry can rally around. Right. And that goes along with any modern application infrastructure. So I would say those are the building blocks that need to happen on the data side. Of course there are so many choices as well. So >>How about, you know, security? I think about, you know, when after stuck net, the, the whole industry said, Hey, we have to do a better job of collaborating. And then when you said identity, it just sort of struck me. But then a lot of people tried to sort of monetize private reporting and things like that. So you do you see a movement within the technology industry to do a better job of collaborating to, to solve the acute, you know, security problems? >>Yeah. I think the customer pressure and government pressure right. Causes that way. Yeah. Even now, even in our current universe, you see, there is a lot of behind the scenes collaboration amongst the security teams of all of the tech companies that is not widely seen or known. Right. For example, my CISO knows the AWS CSO or the Microsoft CSO and they all talk and they share the right information about vulnerability attacks and so on and so forth. So there's already a certain amount of collaboration that's happening and that'll only increase. Do, >>Do you, you know, I was somewhat surprised. I didn't hear more in your face about security would, is that just because you had such a strong multi-cloud message that you wanted to get, get across, cuz your security story is very strong and deep. When you get into the DPU side of things, the, you know, the separation of resources and the encryption and I'll end to end >>I'm well, we have a phenomenal security story. Yeah. Yeah. Tell security story and yes. I mean I'll need guilty to the fact that in the keynote you have yeah, yeah, sure time. But what we are doing with NSX and you will hear about some NSX projects as you, if you have time to go to some of the, the sessions. Yeah. There's one called project, not star. Another is called project Watchman or watch, I think it's called, we're all dealing with this. That is gonna strengthen the security story even more. Yeah. >>We think security and data is gonna be a big part of it. Right. As CEO, I have to ask you now that you're the CEO, first of all, I'd love to talk about product with you cuz you're yeah. Yeah. We just great conversation. We want to kind of read thet leaves and ask pointed questions cuz we're putting the puzzle together in real time here with the audience. But as CEO, now you have a lot of discussions around the business. You, the Broadcom thing happening, you got the rename here, you got multi-cloud all good stuff happening. Dave and I were chatting before we came on this morning around the marketplace, around financial valuations and EBIDA numbers. When you have so much strategic Goodwill and investment in the oven right now with the, with the investments in cloud native multi-year investments on a trajectory, you got economies of scale there. >>It's just now coming out to be harvest and more behind it. Yeah. As you come into the Broadcom and or the new world wave that's coming, how do you talk about that value? Cuz you can't really put a number on it yet because there's no customers on it. I mean some customers, but you can't probably some for form. It's not like sales numbers. Yeah. Yeah. How do you make the argument to the PE type folks out there? Like EBIDA and then all the strategic value. What's the, what's the conversation like if you can share any, I know it's obviously public company, all the things going down, but like how do you talk about strategic value to numbers folks? >>Yeah. I mean, we are not talking to PE guys at all. Right. I mean the only conversation we have is helping Broadcom with >>Yeah. But, but number people who are looking at the number, EBIDA kind of, >>Yeah. I mean, you'd be surprised if, for, for example, even with Broadcom, they look at the business holistically as what are the prospects of this business becoming a franchise that is durable and could drive a lot of value. Right. So that's how they look at it holistically. It's not a number driven. >>They do. They look at that. >>Yeah. Yeah, absolutely. So I think it's a misperception to say, Hey, it's a numbers driven conversation. It's a business driven conversation where, I mean, and Hawk's been public about it. He says, look, I look at businesses. Can they be leaders in their market? Yeah. Because leaders get, as we all know a disproportionate share of the economic value, is it a durable franchise that's gonna last 10 years or more, right. Obviously with technology changes in between, but 10 years or more >>Or 10, you got your internal, VMware talent customers and >>Partners. Yeah. Significant competitive advantage. So that's, that's really where the conversation starts and the numbers fall out of it. Got it. >>Okay. So I think >>There's a track record too. >>That culture >>That VMware has, you've always had an engineering culture. That's turned, you know, ideas and problems into products that, that have been very successful. >>Well, they had different engineering cultures. They're chips. You guys are software. Right. You guys know >>Software. Yeah. Mean they've been very successful with Broadcom, the standalone networking company since they took it over. Right. I mean, it's, there's a lot of amazing innovation going on there. >>Yeah. Not, not that I'm smiling. I want to kind of poke at this question question. I'll see if I get an answer out of you, when you talk to Hawk tan, does he feel like he bought a lot more than he thought or does he, did he, does he know it's all here? So >>The last two months, I mean, they've been going through a very deliberate process of digging into each business and certainly feels like he got a phenomenal asset base. Yeah. He said that to me even today after the keynote, right. Is the amazing amount of product capability that he's seeing in every one of our businesses. And that's been the constant frame. >>But congratulations on that. >>I've heard, I've heard Hawk talk about the shift to, to Mer merchant Silicon. Yeah. From custom Silicon. But I wanted to ask you when you look at things like AWS nitro yeah. And graviton and train and the advantage that AWS has with custom Silicon, you see Google and Microsoft sort of Alibaba following suit. Would it benefit you to have custom Silicon for, for DPU? I mean, I guess you, you know, to have a tighter integration or do you feel like with the relationships that you have that doesn't buy you anything? >>Yeah. I mean we have pretty strong relationships with in fact fantastic relationships with the Invidia and Intel and AMD >>Benon and AMD now. >>Yeah. Yeah. I mean, we've been working with the Pendo team in their previous incarnations for years. Right, right. When they were at Cisco and then same thing with the, we know the Melanox team as well as the invi original teams and Intel is the collaboration right. From the get go of the company. So we don't feel a need for any of that. We think, I mean, it's clear for those cloud folks, right. They're going towards a vertical integration model and select portions of their stack, like you talked about, but there is always a room for horizontal integration model. Right. And that's what we are a part of. Right. So there'll be a number of DPU pro vendors. There'll be a number of CPU vendors. There'll be a number of other storage, et cetera, et cetera. And we think that is goodness in an alternative model compared to a vertically integr >>And yeah. What this trade offs, right. It's not one or the other, I mean I used to tell, talk to Al Shugar about this all the time. Right. I mean, if vertically integrated, there may be some cost advantages, but then you've got flexibility advantages. If you're using, you know, what the industry is building. Right. And those are the tradeoffs, so yeah. Yeah. >>Greg, what are you excited about right now? You got a lot going on obviously great event. Branding's good. Love the graphics. I was kind of nervous about the name changed. I likem world, but you know, that's, I'm kind of like it >>Doesn't readily roll off your phone. Yeah. >>I know. We, I had everyone miscue this morning already and said VMware Explorer. So >>You pay Laura fine. Yeah. >>Now, I >>Mean a quarter >>Curse jar, whatever I did wrong. I don't believe it. Only small mistake that's because the thing wasn't on. Okay. Anyway, what's on your plate. What's your, what's some of the milestones. Do you share for your employees, your customers and your partners out there that are watching that might wanna know what's next in the whole Broadcom VMware situation. Is there a timeline? Can you talk publicly about what? To what people can expect? >>Yeah, no, we, we talk all the time in the company about that. Right? Because even if there is no news, you need to talk about what is where we are. Right. Because this is such a big transaction and employees need to know where we are at every minute of the day. Right? Yeah. So, so we definitely talk about that. We definitely talk about that with customers too. And where we are is that the, all the processes are on track, right? There is a regulatory track going on. And like I alluded to a few minutes ago, Broadcom is doing what they call the discovery phase of the integration planning, where they learn about the business. And then once that is done, they'll figure out what the operating model is. What Broadcom is said publicly is that the acquisition will close in their fiscal 23, which starts in November of this year, runs through October of next year. >>So >>Anywhere window, okay. As to where it is in that window. >>All right, Raghu, thank you so much for taking valuable time out of your conference time here for the queue. I really appreciate Dave and I both appreciate your friendship. Congratulations on the success as CEO, cuz we've been following your trials and tribulations and endeavors for many years and it's been great to chat with you. >>Yeah. Yeah. It's been great to chat with you, not just today, but yeah. Over a period of time and you guys do great work with this, so >>Yeah. And you guys making, making all the right calls at VMware. All right. More coverage. I'm shot. Dave ante cube coverage day one of three days of world war cup here in Moscone west, the cube coverage of VMware Explorer, 22 be right back.

>>Hi, everyone. Welcome to this program. Sponsored by HPE. I'm your host, Lisa Martin. We're here talking about being confident and trusting your server security with HPE. I have two guests here with me to talk about this important topic. Cole Humphreys joins us global server security product manager at HPE and Anne Potton trusted supply chain program lead at HPE guys. It's great to have you on the program. Welcome. >>Hi, thanks. Thank you. It's nice to be here, Anne. >>Let's talk about really what's going on there. Some of the trends, some of the threats there's so much change going on. What is HPE seeing? >>Yes. Good question. Thank you. Yeah. You know, cyber security threats are increasing everywhere and it's causing disruption to businesses and governments alike worldwide. You know, the global pandemic has caused limited employee availability. Originally this has led to material shortages and these things opens the door perhaps even wider for more counterfeit parts and products to enter the market. And these are challenges for consumers everywhere. In addition to this, we're seeing the geopolitical environment has changed. We're seeing, you know, rogue nation states using cybersecurity warfare tactics to immobilize an entity's ability to operate and perhaps even use their tactics for revenue generation, the Russian invasion of Ukraine as one example, but businesses are also under attack. You know, for example, we saw solar winds, software supply chain was attacked two years ago, which unfortunately went a notice for several months and then this was followed by the colonial pipeline attack and numerous others. >>You know, it just seems like it's almost a daily occurrence that we hear of a cyber attack on the evening news. And in fact, it's estimated that the cyber crime cost will reach over 10 and a half trillion dollars by 2025 and will be even more profitable than the global transfer of all major illegal drugs combined. This is crazy, you know, the macro environment in which companies operate in has changed over the years. And you know, all of these things together and coming from multiple directions presents a cybersecurity challenge for an organization and in particular it's supply chain. And this is why HPE is taking proactive steps to mitigate supply chain risk so that we can provide our customers with the most secure products and services. >>So Cole, let's bring you into the conversation and did a great job of summarizing the major threats that are going on the tumultuous landscape. Talk to us Cole about the security gap. What is it? What is HPE seeing and why are organizations in this situation? >>Hi, thanks Lisa. You know, what we're seeing is as this threat landscape increases to, you know, disrupt or attempt to disrupt our customers and our partners and ourselves, I, it's a kind of a double edge if you will, because you're seeing the increase in attacks, but what you're not seeing is that equal to growth of the skills and the experiences required to address the scale. So it really puts the pressure on companies because you have a skill gap, a talent gap, if you will. There's, you know, for example, there are projected to be three and a half million cyber roles open in the next few years, right? So all this scale is growing and people are just trying to keep up, but the gap is growing just literally the people to stop the bad actors from attacking the data and, and to complicate matters. You're also seeing a dynamic change of the who and the, how the attacks are happening, right? >>The classic attacks that you've seen, you know, and the SDK and all the, you know, the history books, those are not the standard plays anymore. You'll have, you know, nation states going after commercial entities and, you know, criminal syndicates and alluded to that. There's more money in it than the international drug trade. So you can imagine the amount of criminal interest in getting this money. So you put all that together. And the increasing of attacks, it just is really pressing down is, is literally, I mean, the reports we're reading over half of everyone, obviously the most critical infrastructure cares, but even just mainstream computing requirements need to have their data protected, help me protect my workloads and they don't have the people in house, right? So that's where partnership is needed, right? And that's where we believe, you know, our approach with our partner ecosystem is it's not HPE delivering everything ourself, but all of us in this together is really what we believe. The only way we're gonna be able to get this done. >>So collets double click on that HPE and its partner ecosystem can provide expertise that companies and every industry are lacking. You're delivering HPE as a 360 degree approach to security. Talk about what that 360 degree approach encompasses. >>Thank you. It is, it is an approach, right? Because I feel that security is a, it is a, it is a thread that will go through the entire construct of a technical solution, right there. Isn't a, oh, if you just buy this one server with this one feature, you don't have to worry about anything else. It's really it's everywhere. And at least the way we believe it, it's everywhere. And it in a 360 degree approach, the way we like to frame it is it's, it's this beginning with our supply chain, right? We take a lot of pride in the designs, you know, the really smart engineering teams, the design, our technology, our awesome world class global operations team, working in concert to deliver some of these technologies into the market. That is a huge, you know, great capability, but also a huge risk to customers, cuz that is the most vulnerable place that if you inject some sort of malware or, or tampering at that point, you know, the rest of the story really becomes mute because you've already defeated, right? >>And then you move in to you physically deployed that through our global operations. Now you're in an operating environment. That's where automation becomes key, right? We have software innovations in, you know, our ILO product of management inside those single servers. And we have really cool new grain lake for compute operations management services out there that give customers more control back and more information to deal with this scaling problem. And then lastly, as you begin to wrap up, you know, the natural life cycle and you need to move to new platforms and new technologies, right? We think about the exit of that life cycle and how do we make sure we dispose of the data and, and move those products into a secondary life cycle so that we can move back into this kind of circular 360 degree approach. We don't wanna leave our customers hanging anywhere in this entire journey. >>That 360 degree approach is so critical, especially given as we've talked about already in this segment, the changes, the dynamics in the environment. And as Cole said, this is this 360 degree approach that HPE is delivering is beginning in the manufacturing supply chain seems like the first line of defense against cyber attackers talked to us about why that's important. And where did the impetus come from? Was that COVID was that customer demand? >>Yep. Yep. Yeah. The supply chain is critical. Thank you. So in 2018, we, we could see all of these cybersecurity issues starting to emerge and predicted that this would be a significant challenge for our industry. So we formed a strategic initiative called the trusted supply chain program designed to mitigate cybersecurity risk in the supply chain and really starting at the product with the product life cycle, starting at the product design phase and moving through sourcing and manufacturing, how we deliver products to our customers and ultimately a product's end of life that Cole mentioned. So in doing this, we're able to provide our customers with the most secure products and services, whether they're buying their servers from, for their data center or using our own GreenLake services. So just to give you some examples, something that is foundational to our trusted supply chain program, we've built a very robust cybersecurity supply chain risk management program that includes assessing our risk at our all factories and our suppliers. >>Okay. We're also looking at strengthening our software supply chain by developing mechanisms to identify software vulnerabilities and hardening our own software build environments to protect against counterfeit parts that I mentioned in the beginning from entering our supply chain, we've recently started a blockchain program so that we can identify component provenance and trace part parts back to their original manufacturers. So our security efforts, you know, continue even after product manufacturing, we offer three different levels of secure delivery services for our customers, including, you know, a dedicated truck and driver or perhaps even an exclusive use vehicle. We can tailor our delivery services to whatever the customer needs. And then when a product is at its end of life, products are either recycled or disposed using our approved vendors. So our servers are also equipped with the one button secure erase that erases every bite of data, including firmware data and talking about products, we've taken additional steps to provide additional security features for our products. >>Number one, we can provide platform certificates that allow the user to cryptographically verify that their server hasn't been tampered with from the time it left the manufacturing facility to the time that it arrives at the customer's factory facility. In addition to that, we've launched a dedicated line of trusted supply chain servers with additional security features, including secure configuration lock chassis intrusion detection. And these are assembled at our us factory by us vetted employees. So lots of exciting things happening within the supply chain, not just to shore up our own supply chain risk, but also to provide our customer the most. So that announcement. >>All right, thank you. You know, they've got great setup though, because I think you gotta really appreciate the whole effort that we're putting into, you know, bringing these online. But one of the just transparently the gaps we had as we proved this out was as you heard, this initial proof was delivered with assembly in the us factory employees, you know, fantastic program really successful in all our target industries and, and even expanding to places we didn't really expect it to, but it's kind of going to the point of security. Isn't just for one industry or one set of customers, right? We're seeing it in our partners. We're seeing it in different industries than we have in the past. And, but the challenge was we couldn't get this global right out the gate, right? This has been a really heavy transparently, a us federal activated focus, right? >>If, if you've been tracked in what's going on since may of last year, there's been a call to action to improve a nation cybersecurity. So we've been all in on that and we have an opinion and we're working hard on that, but we're a global company, right? How can we get this out to the rest of the world? Well guess what, this month we figured it out and well, let's take a lot more than those month. We did a lot of work that we figured it out and we have launched a comparable service globally called server security optimization service, right? HPE server security optimization service for proli. I like to call it, you know, S S O S sauce, right? Do you wanna be clever HPE sauce that we can now deploy globally? We get that product hardened in the supply chain, right? Because if you take the best of your supply chain and you take your technical innovations, that you've innovated into the server, you can deliver a better experience for your customers, right? >>So the supply chain equals server technology and our awesome, you know, services teams deliver supply chain security at that last mile. And we can deliver it in the European markets. And now in the Asia Pacific markets right now, we could always just, we could ship it from the us to other markets. So we could always fulfill this promise, but I think it's just having that local access into your partner ecosystem and stuff just makes more sense, but it is big deal for us because now we have activated a meaningful supply chain security benefit for our entire global network of partners and customers, and we're excited about it. And we hope our customers are too. >>That's huge Cole. And, and in terms of this significance of the impact that HPE is delivering through its partner ecosystem globally as the supply chain continues to be one of the terms on everyone's lips here, I'm curious Cole, we just couple months ago, we're at discover. Can you talk about what HPE is doing here from a, a security perspective, this global approach that it's taking as it relates to what HPE was talking about at discover, in terms of we wanna secure the enterprise to deliver these experiences from edge to cloud. >>You know, I feel like for, for me, and, and I think you look at the shared responsibility models and you know, other frameworks out there, the way we're the way I believe it to be is this is it's, it's a solution, right? There's not one thing, you know, if you use HPE supply chain, the end, or if you buy an HPE pro line the end, right. It is an integrated connectedness with our, as a service platform, our service and support commitments, you know, our extensive partner ecosystem, our alliances, all of that comes together to ultimately offer that assurance to a customer. And I think these are specific, meaningful proof points in that chain of custody, right? That chain of trust, if you will, because as the world becomes more, zero trust, we are gonna have to prove ourselves more, right. And these are those kind of technical I credentials and identities and, you know, capabilities that a modern approach to security need. >>Excellent, great work there. And let's go ahead and, and take us home, take the audience through what you think ultimately, what HPE is doing, really infusing security at that 360 degree approach level that we talked about. What are some of the key takeaways that you want the audience that's watching here today to walk away with? >>Right. Right. Thank you. Yeah. You know, with the increase in cyber security threats, everywhere affecting all businesses globally, it's gonna require everyone in our industry to continue to evolve in our supply chain security in our product security in order to protect our customers in our business, continuity protecting our supply chain is something that HPE is very committed to and takes very seriously. So, you know, I think regardless of whether our customers are looking for an on-prem solution or a GreenLake service, you know, HPE is proactively looking for in mitigating any security risk in this supply chain so that we can provide our customers with the most secure products and services. >>Awesome. Ann and Cole. Thank you so much for joining me today, talking about what HPE is doing here and why it's important as our program is called to be confident and trust your server security with HPE and how HPE is doing that. Appreciate your insights on your time. >>Thank you so much for having thank >>You, Lisa, >>For Cole Humphreys and Anne Potton I'm Lisa Martin. We wanna thank you for watching this segment in our series. Be confident and trust your server security with HPE. We'll see you soon.

(upbeat music) >> Hey everyone. And welcome to this CUBE Conversation which is part of the AWS startup showcase. Season two, episode four of our ongoing series. The theme of this episode is cybersecurity, detect and protect against threats. I'm your host, Lisa Martin, and I'm pleased to be joined by the founder and CEO of Hunters.AI, Uri May. Uri, welcome to theCUBE. It's great to have you here. >> Thank you, Lisa. It's great to be here. >> Tell me a little bit about your background and the founders story. This company was only founded in 2018, so you're quite young. But gimme that backstory about what you saw in the market that really determined, this is needed. >> Yeah, absolutely. So, I mean, I think the biggest thing for us was the understanding that significant things have happened in the cybersecurity landscape for customers and technology stayed the same. I mean, we tried on solving the same... We tried on solving a big problem with the same old tools when we actually noticed that the problem has changed significantly. And we saw that change happening in two different dimensions. The first is the types of attacks that we're defending against. A decade ago, we were mostly focused on these highly sophisticated nation state efforts that included unknown techniques and tactics and highly sophisticated kind of methods. Nowadays, we're talking a lot about cyber crime gangs, whoops of people that are financially motivated or using off the shelf tools, of the shelf malware, coordinating in the dark web, attacking for money and ransom basically, versus sophisticated intelligence kind of objectives. And in the same time of that happening, we also saw what we like to refer to as explosion of the securities stack. So some of our customers are using more than 60 or 70 different security tools that are generating sometimes tens of terabytes a day of flows. That explosion of data, together with a very persistent and consistent threat that is continuously affecting customers, create a very different environment, where you need to analyze a big variety of data and you need to constantly defend yourself against stuff that are happening all the time. And that was kind of like our wake moment when we understand that the tools that are out there now might have been the right tools a decade ago, they are probably not the right tools to solve the problem now. So yeah, I think that that was kind of what led us to Hunters. And in the same time, and I think that that's my personal kind of story behind it. We used to talk a lot about the fact that we want to solve a fundamental problem. And we, as part of the ideation around Hunters and us zooming in on exactly the areas that we want to focus on in security, we talked with a lot of CSOs, we talked with a lot of industry experts, everyone directed us to the security operation center. I mean the notion that there's a lot of tools and there's always going to be a lot of tools, but eventually decisions are being made by people that are running security operation center, that are actually acting as the first line of defense. And that's where you feel that the processes are woke. That's where you feel that that technology doesn't really meet the rabel, and the rabel doesn't really meet the hold. And for us, it was a very clear sign that this is where we need to focus on. And that set us on a journey to explore red hunting and then understand that we can solve something bigger than that. And then eventually get to where we are today, which is go to market around. So holistic a platform that can help SOC analysts doing the day to day job defending the organizations. >> So you saw back in 2018, probably even before that that the SIEM market was prime and right for disruption. And only in a four year time period, there's been some pretty significant milestones and accomplishment that the team at Hunters has made in that short timeframe. Talk to me about some of those big milestones that the company has reached in just four years. >> Yeah, I think that the biggest thing and I know that it's going to sound like a cliche, but we're actually believing that I think it's the team. I mean, we're able to go to an organization of around 150 employees. All over the world, the course, I think I mean the last time that I checked, like 15 countries. That's the most amazing feeling that you can have. That ability to attract people to a single mission from all over the world and to get them collaborate and do amazing things and achieve unbelievable accomplishment. I think that's the biggest thing. The other thing for us was customers. I mean, think about it like, SIEM it's such a central and critical system. So for us as a young startup from Tel Aviv to go out to Enterprise America and convince the biggest enterprise around the world to rip and replace the the existing solutions that are being built by the biggest software brands out there and install Hunters instead, that's a huge leap of trust, that we are very grateful for, and we're trying to handle with a lot of care and a lot of responsibility. And obviously, I think that other than that, is all of the investors that we were able to attract that basically enabled all of that customer acquisition and team building and product development. And we're very fortunate to work with the biggest names out there, both from a strategic perspective and also from tier one VCs from mainly from the U.S., but from all over the world, actually that are backing us. >> Great customers, solid foundation. Hunters is built for the clouds, is powered by Snowflake. This is AWS built. Talk to me about what's in it for me from an AWS customer perspective. What's that value in it for them? >> Yeah, so I think that the most important thing, in my opinion, at least, is the security value that you're getting from it. Other than the fact that Hunters is a multi-tenant SaaS application running in AWS, it's also a system that is highly tuned and specifically built to be very effective against detecting threats inside AWS environments. So we invested a lot of time in research, in analyzing the way attackers are operating inside cloud environments, specifically in AWS. And then we model these techniques and tactics and procedures into the system. We're leveraging data sets like AWS CloudRail and CloudWatch and VPC Flow Logs, obviously AWS GuardDuty which is an amazing detection system that AWS offer to its customer, and we're able to leverage it, correlate it with other signals. And at the same time, there's also the commercial aspect and the business aspect. I mean, we're allowing AWS customers to leverage the AWS credits to the marketplace to fund same projects like Hunters that comes with a lot of efficiencies also. And with a lot of additional capabilities like I mentioned earlier. >> So let's crack open Hunters.AI. What makes this approach different? You talked about the challenges that you guys saw in the market that were gaps there, and why technology needed to come in from a disruption standpoint. But describe the differentiators. When you're talking to perspective customers, what are those key differentiators that Hunters brings to the table? >> Yeah, absolutely. So we like to divide it into three main pillars. The first pillar is everything that we do with data, that is very different from our competitors. We believe that data should be completely liberated from the analytical layer. And that's why we're storing data in a dedicated data warehouse. Snowflake, as you mentioned earlier, is one of our go to data warehouses. And that give customers the ability to own their own data. So you as a customer can opt in into using Hunters on top of your Snowflake. It's not the only way. You can also get Snowflake bundled as part of that, your Hunter subscription, but for some customers that ability to reduce vendor lock risk on data on your own and also level security data for other kind of workflows is something that is really huge. So that's the first thing that is very different. The second thing is what we like to call security engineering as a service. So when you buy Hunters, you don't just buy a data platform. You actually buy a system, a SOC platform that is already populated with use cases. So what we are saying is that in today's world the threats that we're handling as a SOC, as security operations center professionals are actually shared by 80% of the customers out there. So 80% of the customers share around 80% of the threat. And what we're basically saying is let us as a vendor, solve the detection response around that 80%. So you as a customer could focus on the 20% that is unique to your environment. Then in a lot of cases generate 80% of the impact. So that means that you are getting a lot of rebuilt tools and detections, data modeling to your integrations, automatic investigations, scoring correlations. All of these things are being continuously deployed and delivered by us because we're multi tenant SaaS. And also allowing you again to get this effortless tail key kind of solution that is very different from your experience with your current SIEM tools that usually involves a lot of tuning, professional services, configuration, et cetera. And the last aspect of it, is everything that we're doing around automation. We're leveraging very unique graph technology and what we call automatic investigation enrichments that allows us to take all of these signals that we're extracting from all over the attacks, of say AWS included, but also the endpoint and the email and the network and IOT environments and whatever automatically investigate them, load them into a graph and then automatically correlate them to what we call stones, which are basically representation of incidents that are happening across your tax office. And that's a very unique capability that we bring into the table that demonstrates our focus on the analytical lens. So it's not just log aggregation, and querying and dashboarding kind of system. It's actually a security analytic system that is able to drive real insights on top of the data that you're plugging into it. >> So talk to me, Uri, when you're in customer conversations these days the market is there's so many dynamics and flux that customers are dealing with. Obviously, the threat landscape continues to expand and really become quite amorphous as that perimeter blends. What are some of the specific challenges that security operation center or SOC teams come to you saying, help us eliminate this. We have so many tools, we've probably got limited resources. What are those challenges and how does Hunters really wipe those off the plate? >> Yeah, so I think the first and foremost has to do with the second pillar that I mentioned earlier and that's security engineering. So for most security operations centers and most organizations around the world, the feeling is that they're kind of like stuck on this third wheel. They keep on buying tools and then implementing these tools and then writing rules and then generating noise and then fine tuning the rules. And then testing the rules and understanding that the fine tuning actually generated misdetections. And they're kind of like stuck on this vicious side. And no one can really help because a lot of the stuff that they're building, they're building it in their environment. And what we're saying is that, let us do it for you. Well, that 80% that we've mentioned earlier and allows you to really focus on the stuff that you're doing and even offset your talent. So, we're not talking about really a talent reduction. Because everyone needs more talent in cybersecurity nowadays but we're talking a lot about offset. I mean, if we had a team of five people investing efforts in building walls, building automation, and now three or four of these people can go and do advanced investigations, instant response, threat hunting interval, that's meaningful. For a lot of SOCs, in a lot of cases that means either identifying and analyzing a threat in time or missing it. So, I mean, I think that that's the biggest thing. And the other thing has to do with the first thing that I mentioned earlier, and these are the data challenges. Data challenges in terms of cost, performance, the ability to absorb data sets that today's tools can't really support. I mean, for example, one of the biggest data sets that we're loading that is tremendously helpful is raw data for EDR products. Raw data for EDR products in large enterprises can get to 10, 15, 20 terabytes a day. In today's SIEMs and SOC platforms that the customers are using, this thing is just as prohibited from SOC. They can't really analyze it because it's so costly. So what we're saying is a lot of what we're seeing is a lot of customers, either not analyzing it at all, or saving it for a very little amount of time, account of days. Because they can't support the retention around it. So the ability to store huge data sets for longer period of time makes it something that a lot of big enterprises need. And to be honest, I think that in the next couple of years they would also be forced to have these kind of capabilities, even from a compliance perspective. >> So in terms of outcomes, I'm hearing reduction in costs really helping security teams utilize their resources, the ability to analyze growing volumes of data. That's only going to continue to increase as we know. Is there a customer story, Uri that you have that really, where the value proposition of Hunters really shines through? >> Yeah, I think that one thing comes to mind from those hospitality vertical and actually it's a reference customer. I mean, we can share the name. His name is booking.com. It's also publicly shown on our website. And they think the coolest thing that we were able to do with booking is give them that capability to stay up to date with the threats that they're facing. So it's not just that we saved a lot of efforts from them because we came with a lot of out of the box capabilities that they can use. We also kept them up to date with everything that they were facing. And there was a couple of cases, where we were able to detect threats that were very recently from threat perspective. Based on our ability to invest research time and efforts in everything that is going on in the ecosystem and the feedback that we got from the customer, and it's not a single of feedback. Like we're getting it a lot, is that, without you guys we wouldn't be able to do the effective research and then the implementation of this and the threat modeling and the implementation of these things in time. And walking with you kind of like made the difference between analyzing it and reacting in time and potentially blocking like a very serious bridge versus maybe finding out when it's too late. >> Huge impact there. And I'm kind of thinking, Hunters aim, might be one of the reasons that booking.com's tagline it's booking.com, booking.yeah. Yeah, we're secure. We know if we can demonstrate that to everyone that uses our service. I noticed kind of wrapping things up here, Uri. I noticed that back in I think it was January of 2022, Hunters raised about 60 million in series C. You talked about kind of being in the GTM phase, where are some of those strategic investments? What have you been doing, focusing on this year and what's to come as we round out 22? >> Yeah, absolutely. So, I mean, there's a lot of building going on. Yeah. Still, right. I mean, we're getting into that scale mode and scale phase but we're very much also building our capabilities, building our infrastructure, building our teams, building our business processes. So there's a lot of efforts going into that, but in the same time, I mean, we've being able to vary, to depending our relationship with DataBlitz which is a very important partner of us. And we got some big news coming up on that. And they were a strategic investor that participated in our series C. And in the same time we're walking in the air market which is a very interesting market for us. And we get a lot of support from one other strategic investor that joined the series C, Deutsche Telekom. And they are a huge provider in IT and security in email, other than doing a lot of other things and including T-systems and T-Mobile and everything that has to do with that. So we're getting a lot of support from them. And regardless, I think, and that ties back to what we've mentioned earlier, the ability for us to come to really big customers with the quality of investors that we have is a very important external validation. It's basically saying like this company is here to stay. We're aiming at disrupting the market. We're building something big. You can count on us by replacing this critical system that we're talking about. And sometimes it makes a difference, like sometimes for some of the customers, it means that this is something that I can rely on. Like it's not a startup that is going to be sold two months after I'm deploying it. And it's not a founder that is going to disappear on me. And for a lot of customers, these things happen, especially in an ecosystem like cybersecurity, that is so big with such a huge variety of different systems. So, yeah, I think that we're getting ready for that scale mode and hopefully it'll happen sooner than what we think. >> A lot of growth already as we mentioned in the beginning of the program. Since just 2018 it sounds like from a foundation perspective, you guys are strong, you're rocking away and ready to really take things into 2023 with such force. Uri, thank you so much for joining me on the program, talking about what Hunters.AI is up to and how you're different and why you're disrupting the SIEM market. We appreciate your insights and your time. >> Absolutely. Lisa, the pleasure was all mine. Thank you for having me. >> Likewise. For Uri May, I'm Lisa Martin. Thank you for watching our CUBE Conversation as part of the AWS startup showcase. Keep it right here for more actions on theCUBE, your leader in tech coverage. (upbeat music)

(upbeat music) >> Hi, everyone, welcome to this program sponsored by HPE. I'm your host, Lisa Martin. We're here talking about being confident and trusting your server security with HPE. I have two guests here with me to talk about this important topic. Cole Humphreys joins us, global server security product manager at HPE, and Ann Potten, trusted supply chain program lead at HPE. Guys, it's great to have you on the program, welcome. >> Hi, thanks. >> Thank you. It's nice to be here. >> Ann let's talk about really what's going on there. Some of the trends, some of the threats, there's so much change going on. What is HPE seeing? >> Yes, good question, thank you. Yeah, you know, cybersecurity threats are increasing everywhere and it's causing disruption to businesses and governments alike worldwide. You know, the global pandemic has caused limited employee availability originally, this has led to material shortages, and these things opens the door perhaps even wider for more counterfeit parts and products to enter the market, and these are challenges for consumers everywhere. In addition to this, we're seeing the geopolitical environment has changed. We're seeing rogue nation states using cybersecurity warfare tactics to immobilize an entity's ability to operate, and perhaps even use their tactics for revenue generation. The Russian invasion of Ukraine is one example. But businesses are also under attack, you know, for example, we saw SolarWinds' software supply chain was attacked two years ago, which unfortunately went unnoticed for several months. And then, this was followed by the Colonial Pipeline attack and numerous others. You know, it just seems like it's almost a daily occurrence that we hear of a cyberattack on the evening news. And, in fact, it's estimated that the cyber crime cost will reach over $10.5 trillion by 2025, and will be even more profitable than the global transfer of all major illegal drugs combined. This is crazy. You know, the macro environment in which companies operate in has changed over the years. And, you know, all of these things together and coming from multiple directions presents a cybersecurity challenge for an organization and, in particular, its supply chain. And this is why HPE is taking proactive steps to mitigate supply chain risk, so that we can provide our customers with the most secure products and services. >> So, Cole, let's bring you into the conversation. Ann did a great job of summarizing the major threats that are going on, the tumultuous landscape. Talk to us, Cole, about the security gap. What is it, what is HPE seeing, and why are organizations in this situation? >> Hi, thanks, Lisa. You know, what we're seeing is as this threat landscape increases to, you know, disrupt or attempt to disrupt our customers, and our partners, and ourselves, it's a kind of a double edge, if you will, because you're seeing the increase in attacks, but what you're not seeing is an equal to growth of the skills and the experiences required to address the scale. So it really puts the pressure on companies, because you have a skill gap, a talent gap, if you will, you know, for example, there are projected to be 3 1/2 million cyber roles open in the next few years, right? So all this scale is growing, and people are just trying to keep up, but the gap is growing, just literally the people to stop the bad actors from attacking the data. And to complicate matters, you're also seeing a dynamic change of the who and the how the attacks are happening, right? The classic attacks that you've seen, you know, in the espionage in all the, you know, the history books, those are not the standard plays anymore. You'll have, you know, nation states going after commercial entities and, you know, criminal syndicates, as Ann alluded to, that there's more money in it than the international drug trade, so you can imagine the amount of criminal interest in getting this money. So you put all that together and the increasing of attacks it just is really pressing down as literally, I mean, the reports we're reading over half of everyone. Obviously, the most critical infrastructure cares, but even just mainstream computing requirements need to have their data protected, "Help me protect my workloads," and they don't have the people in-house, right? So that's where partnership is needed, right? And that's where we believe, you know, our approach with our partner ecosystem this is not HPE delivering everything ourself, but all of us in this together is really what we believe the only way we're going to be able to get this done. >> So, Cole, let's double-click on that, HPE and its partner ecosystem can provide expertise that companies in every industry are lacking. You're delivering HPE as a 360-degree approach to security. Talk about what that 360-degree approach encompasses. >> Thank you, it is an approach, right? Because I feel that security it is a thread that will go through the entire construct of a technical solution, right? There isn't a, "Oh, if you just buy this one server with this one feature, you don't have to worry about anything else." It's really it's everywhere, at least the way we believe it, it's everywhere. And in a 360-degree approach, the way we like to frame it, is it's this beginning with our supply chain, right? We take a lot of pride in the designs, you know, the really smart engineering teams, the designer, technology, our awesome, world-class global operations team working in concert to deliver some of these technologies into the market, that is, you know, a great capability, but also a huge risk to customers. 'Cause that is the most vulnerable place that if you inject some sort of malware or tampering at that point, you know, the rest of the story really becomes mute, because you've already defeated, right? And then, you move in to you physically deployed that through our global operations, now you're in an operating environment. That's where automation becomes key, right? We have software innovations in, you know, our iLO product of management inside those single servers, and we have really cool new GreenLake for compute operations management services out there that give customers more control back and more information to deal with this scaling problem. And then, lastly, as you begin to wrap up, you know, the natural life cycle, and you need to move to new platforms and new technologies, we think about the exit of that life cycle, and how do we make sure we dispose of the data and move those products into a secondary life cycle, so that we can move back into this kind of circular 360-degree approach. We don't want to leave our customers hanging anywhere in this entire journey. >> That 360-degree approach is so critical, especially given, as we've talked about already in this segment, the changes, the dynamics in the environment. Ann, as Cole said, this 360-degree approach that HPE is delivering is beginning in the manufacturing supply chain, seems like the first line of defense against cyberattackers. Talk to us about why that's important and where did the impetus come from? Was that COVID, was that customer demand? >> Yep, yep. Yeah, the supply chain is critical, thank you. So in 2018, we could see all of these cybersecurity issues starting to emerge and predicted that this would be a significant challenge for our industry. So we formed a strategic initiative called the Trusted Supply Chain Program designed to mitigate cybersecurity risk in the supply chain, and really starting with the product life cycle, starting at the product design phase and moving through sourcing and manufacturing, how we deliver products to our customers and, ultimately, a product's end of life that Cole mentioned. So in doing this, we're able to provide our customers with the most secure products and services, whether they're buying their servers for their data center or using our own GreenLake services. So just to give you some examples, something that is foundational to our Trusted Supply Chain Program we've built a very robust cybersecurity supply chain risk management program that includes assessing our risk at all factories and our suppliers, okay? We're also looking at strengthening our software supply chain by developing mechanisms to identify software vulnerabilities and hardening our own software build environments. To protect against counterfeit parts, that I mentioned in the beginning, from entering our supply chain, we've recently started a blockchain program so that we can identify component provenance and trace parts back to their original manufacturers. So our security efforts, you know, continue even after product manufacturing. We offer three different levels of secured delivery services for our customers, including, you know, a dedicated truck and driver, or perhaps even an exclusive use vehicle. We can tailor our delivery services to whatever the customer needs. And then, when a product is at its end of life, products are either recycled or disposed using our approved vendors. So our servers are also equipped with the One-Button Secure Erase that erases every byte of data, including firmware data. And talking about products, we've taken additional steps to provide additional security features for our products. Number one, we can provide platform certificates that allow the user to cryptographically verify that their server hasn't been tampered with from the time it left the manufacturing facility to the time that it arrives at the customer's facility. In addition to that, we've launched a dedicated line of trusted supply chain servers with additional security features, including Secure Configuration Lock, Chassis Intrusion Detection, and these are assembled at our U.S. factory by U.S. vetted employees. So lots of exciting things happening within the supply chain not just to shore up our own supply chain risk, but also to provide our customers with the most secure product. And so with that, Cole, do you want to make our big announcement? >> All right, thank you. You know, what a great setup though, because I think you got to really appreciate the whole effort that we're putting into, you know, bringing these online. But one of the, just transparently, the gaps we had as we proved this out was, as you heard, this initial proof was delivered with assembly in the U.S. factory employees. You know, fantastic program, really successful in all our target industries and even expanding to places we didn't really expect it to. But it's kind of going to the point of security isn't just for one industry or one set of customers, right? We're seeing it in our partners, we're seeing it in different industries than we have in the past. But the challenge was we couldn't get this global right out the gate, right? This has been a really heavy, transparently, a U.S. federal activated focus, right? If you've been tracking what's going on since May of last year, there's been a call to action to improve the nation's cybersecurity. So we've been all in on that, and we have an opinion and we're working hard on that, but we're a global company, right? How can we get this out to the rest of the world? Well, guess what? This month we figured it out and, well, it's take a lot more than this month, we did a lot of work, but we figured it out. And we have launched a comparable service globally called Server Security Optimization Service, right? HPE Server Security Optimization Service for ProLiant. I like to call it, you know, SSOS Sauce, right? Do you want to be clever? HPE Sauce that we can now deploy globally. We get that product hardened in the supply chain, right? Because if you take the best of your supply chain and you take your technical innovations that you've innovated into the server, you can deliver a better experience for your customers, right? So the supply chain equals server technology and our awesome, you know, services teams deliver supply chain security at that last mile, and we can deliver it in the European markets and now in the Asia Pacific markets, right? We could ship it from the U.S. to other markets, so we could always fulfill this promise, but I think it's just having that local access into your partner ecosystem and stuff just makes more sense. But it is a big deal for us because now we have activated a meaningful supply chain security benefit for our entire global network of partners and customers and we're excited about it, and we hope our customers are too. >> That's huge, Cole and Ann, in terms of the significance of the impact that HPE is delivering through its partner ecosystem globally as the supply chain continues to be one of the terms on everyone's lips here. I'm curious, Cole, we just couple months ago, we're at Discover, can you talk about what HPE is doing here from a security perspective, this global approach that it's taking as it relates to what HPE was talking about at Discover in terms of we want to secure the enterprise to deliver these experiences from edge to cloud. >> You know, I feel like for me, and I think you look at the shared-responsibility models and, you know, other frameworks out there, the way I believe it to be is it's a solution, right? There's not one thing, you know, if you use HPE supply chain, the end, or if you buy an HPE ProLiant, the end, right? It is an integrated connectedness with our as-a-service platform, our service and support commitments, you know, our extensive partner ecosystem, our alliances, all of that comes together to ultimately offer that assurance to a customer, and I think these are specific meaningful proof points in that chain of custody, right? That chain of trust, if you will. Because as the world becomes more zero trust, we are going to have to prove ourselves more, right? And these are those kind of technical credentials, and identities and, you know, capabilities that a modern approach to security need. >> Excellent, great work there. Ann, let's go ahead and take us home. Take the audience through what you think, ultimately, what HPE is doing really infusing security at that 360-degree approach level that we talked about. What are some of the key takeaways that you want the audience that's watching here today to walk away with? >> Right, right, thank you. Yeah, you know, with the increase in cybersecurity threats everywhere affecting all businesses globally, it's going to require everyone in our industry to continue to evolve in our supply chain security and our product security in order to protect our customers and our business continuity. Protecting our supply chain is something that HPE is very committed to and takes very seriously. So, you know, I think regardless of whether our customers are looking for an on-prem solution or a GreenLake service, you know, HPE is proactively looking for and mitigating any security risk in the supply chain so that we can provide our customers with the most secure products and services. >> Awesome, Anne and Cole, thank you so much for joining me today talking about what HPE is doing here and why it's important, as our program is called, to be confident and trust your server security with HPE, and how HPE is doing that. Appreciate your insights and your time. >> Thank you so much for having us. >> Thank you, Lisa. >> For Cole Humphreys and Anne Potten, I'm Lisa Martin, we want to thank you for watching this segment in our series, Be Confident and Trust Your Server Security with HPE. We'll see you soon. (gentle upbeat music)

(upbeat music) >> We're here on theCube covering AWS Storage Day 2022. Kevin Miller joins us. He's the vice president and general manager of Amazon S3. Hello, Kevin, good to see you again. >> Hey Dave, it's great to see you as always. >> It seems like just yesterday we were celebrating the 15th anniversary of S3, and of course the launch of the modern public cloud, which started there. You know, when you think back Kevin, over the past year, what are some of the trends that you're seeing and hearing from customers? What do they want to see AWS focus more on? What's the direction that you're setting? >> Yeah, well Dave, really I think there's probably three trends that we're seeing really pop this year. I think one just given the kind of macroeconomic situation right now is cost optimization. That's not a surprise. Everyone's just taking a closer look at what they're using, and where they might be able to pair back. And you know, I think that's a place that obviously S3 has a long history of helping customers save money. Whether it's through our new storage classes, things like our Glacier Instant Retrieval, storage class that we launched to reinvent last year. Or things like our S3 storage lens capability to really dig in and help customers identify where their costs are are being spent. But so certainly every, you know, a lot of customers are focused on that right now, and for obvious reasons. I think the second thing that we're seeing is, just a real focus on simplicity. And it kind of goes hand in hand with cost optimization, because what a lot of customers are looking for is, how do I take the staff that I have, and do more this year. Right, continue to innovate, continue to bring new applications or top line generating revenue applications to the market, but not have to add a lot of extra headcount to do that. And so, what they're looking for is management and simplicity. How do I have all of this IT infrastructure, and not have to have people spending a lot of their time going into kind of routine maintenance and operations. And so that's an area that we're spending a lot of time. We think we have a lot of capability today, but looking at ways that we can continue to simplify, make it easier for customers to manage their infrastructure. Things like our S3 intelligent tiering storage class, which just automatically gives cost savings for data that's not routinely accessed. And so that's a big focus for us this year as well. And then I think the last and probably third thing I would highlight is an emerging theme or it's been a theme, but really continuing to increase in volume, is all around sustainability. And you know, our customers are looking for us to give them the data and the assurances for them, for their own reports and their own understanding of how sustainable is my infrastructure. And so within AWS, of course, you know we're on a path towards operating with 100% renewable energy by 2025. As well as helping the overall Amazon goal of achieving net zero carbon by 2040. So those are some big lofty goals. We've been giving customers greater insights with our carbon footprint tool. And we think that, you know the cloud continues to be just a great place to run and reduce customer's carbon footprint for the similar you know, storage capacity or similar compute capacity. But that's just going to continue to be a trend and a theme that we're looking at ways that we can continue to help customers do more to aggressively drive down their carbon footprint. >> I mean, it makes sense. It's like you're partnering up with the cloud, you know, you did same thing on security, you know, there's that shared responsibility model, same thing now with ESG. And on the macro it's interesting Kevin, this is the first time I can remember where, you know it used to be, if there's a downturn it's cost optimization, you go to simplicity. But at the same time with digital, you know, the rush to digital, people still are thinking about, okay how do I invest in the future? So but let's focus on cost for a moment then we'll come back to sort of the data value. Can you tell us how AWS helps customers save on storage, you know, beyond just the price per terabyte actions that you could take. I mean I love that, you guys should keep doing that. >> Absolutely. >> But what other knobs are you turning? >> Yeah, right and we've had obviously something like 15 cost reductions or price reductions over the years, and we're just going to continue to use that lever where we can, but it's things like the launch of our Glacier Instant Retrieval storage class that we did last year at Reinvent, where that's now you know, 4/10ths of a cent per gigabyte month. For data that customers access pretty infrequently maybe a few times a year, but they can now access that data immediately and just pay a small retrieval fee when they access that data. And so that's an example of a new capability that reduces customer's total cost of ownership, but is not just a straight up price reduction. I mentioned S3 Intelligent-Tiering, that's another case where, you know, when we launch Glacier Instant Retrieval, we integrated that with Intelligent-Tiering as well. So we have the archive instant access tier within Intelligent-Tiering. And so now data that's not accessed for 90 days is just automatically put into AIA and and then results in a reduced storage cost to customers. So again, leaning into this idea that customers are telling us, "Just do, you know what should be done "for my data to help me reduce cost, can you just do it, "and sort of give me the right defaults." And that's what we're trying to do with things like Intelligent-Tiering. We've also, you know, outside of the S3 part of our portfolio, we've been adding similar kinds of capabilities within some of our file services. So things like our, you know elastic file service launched a one zone storage class as well as an intelligent tiering capability to just automatically help customers save money. I think in some cases up to 92% on their their EFS storage costs with this automatic intelligent tiering capability. And then the last thing I would say is that we also are just continuing to help customers in other ways, like I said, our storage lens is a great way for customers to really dig in and figure out. 'Cause you know, often customers will find that they may have, you know, certain data sets that someone's forgotten about or, they're capturing more data than they expected perhaps in a logging application or something that ends up generating a lot more data than they expected. And so storage lens helps them really zoom in very quickly on, you know this is the data, here's how frequently it's being accessed and then they can make decisions about use that data I keep, how long do I keep it? Maybe that's good candidates to move down into one of our very cold storage classes like Glacier Deep Archive, where they they still have the data, but they don't expect to need to actively retrieve it on a regular basis. >> SDL bromide, if you can measure it, you can manage it. So if I can see it, visualize it, that I can take actions. When you think about S3- >> That's right. it's always been great for archival workloads but you made some updates to Glacier that changed the way that we maybe think about archive data. Can you talk about those changes specifically, what it means for how customers should leverage AWS services going forward? >> Yeah, and actually, you know, Glacier's coming up on its 10 year anniversary in August, so we're pretty excited about that. And you know, but there's just been a real increase in the pace of innovation, I think over the last three or four years there. So we launched the Glacier Deep Archive capability in 2019, 2018, I guess it was. And then we launched Glacier Instant Retrieval of course last year. So really what we're seeing is we now have three storage classes that cover are part of the Glacier family. So everything from millisecond retrieval for that data, that needs to be accessed quickly when it is accessed, but isn't being accessed, you know, regularly. So maybe a few times a year. And there's a lot of use cases that we're seeing really quickly emerge for that. Everything from, you know, user generated content like photos and videos, to big broadcaster archives and particularly in media and entertainment segment. Seeing a lot of interest in Glaciers Instant Retrieval because that data is pretty cold on a regular basis. But when they want to access it, they want a huge amount of data, petabytes of data potentially back within seconds, and that's the capability we can provide with Glacier Instant Retrieval. And then on the other end of the spectrum, with Glacier Deep Archive, again we have customers that have huge archives of data that they be looking to have that 3-AZ durability that we provide with Glacier, and make sure that data is protected. But really, you know expect to access it once a year if ever. Now it could be a backup copy of data or secondary or tertiary copy of data, could be data that they just don't have an active use for it. And I think that's one of the things we're starting to see grow a lot, is customers that have shared data sets where they may not need that data right now but they do want to keep it because as they think about, again these like new applications that can drive top line growth, they're finding that they may go back to that data six months or nine months from now and start to really actively use it. So if they want that option value to keep that data so they can use it down the road, Glacier Deep Archive, or Glacier Flexible Retrieval, which is kind of our storage class right in the middle of the road. Those are great options for customers to keep the data, keep it safe and secure, but then have it, you know pretty accessible when they're ready to get it back. >> Got it, thank you for that. So, okay, so customers have choices. I want to get into some of the competitive differentiators. And of course we were talking earlier about cost optimization, which is obviously an important topic given the macro environment you know, but there's more. And so help us understand what's different about AWS in terms of helping customers get value from their data, cost reduction as a component of value, part of the TCO, for sure. But just beyond being a cloud bit bucket, you know just a storage container in the cloud, what are some of the differentiators that you can talk to? >> Yeah, well Dave, I mean, I think that when it comes to value, I think there's tremendous benefits in AWS, well beyond just cost reduction. I think, you know, part of it is S3 now has built, I think, an earned reputation for being resilient, for storing, you know, at massive scale giving customers that confidence that they will be able to scale up. You know, we store more than 200 trillion objects. We regularly peak at over 100 million requests per second. So customers can build on S3 and Glacier with the confidence that we're going to be there to help their applications grow and scale over time. And then I think that in all of the applications both first party and third party, the customers can use, and services that they can use to build modern applications is an incredible benefit. So whether it's all of our serverless offerings, things like Lambda or containers and everything we have to manage that. Or whether it's the deep analytics and machine learning capabilities we have to help really extract, you know value and insight from data in near real time. You know, we're just seeing an incredible number of customers build those kinds of applications where they're processing data and feeding their results right back into their business right away. So I'm just going to briefly mention a couple, like, you know one example is ADP that really helps their customers measure, compare and sort of analyze their workforce. They have a couple petabytes of data, something like 25 billion individual data points and they're just processing that data continuously through their analytics and machine learning applications to then again, give those insights back to their customers. Another good example is AstraZeneca. You know, they are processing petabytes and petabytes of genomic sequencing data. And they have a goal to analyze 2 million genomes over the next four years. And so they're just really scaling up on AWS, both from a pure storage point of view, but more importantly, from all of the compute and analytics capability on top that is really critical to achieving that goal. And then, you know, beyond the first party services we have as I mentioned, it's really our third party, right? The AWS partner network provides customers an incredible range of choice in off the shelf applications that they can quickly provision and make use of the data to drive those business insights. And I think today the APN has something like 100,000 partners over in 150 countries. And we specifically have a storage competency partner where customers can go to get those applications that directly work, you know, on top of their data. And really, like I said, drive some of that insight. So, you know, I think it's that overall benefit of being able to really do a lot more with their data than just have it sit idle. You know, that's where I think we see a lot of customers interested in driving additional value. >> I'm glad you mentioned the ecosystem, and I'm glad you mentioned the storage competency as well. So there are other storage partners that you have, even though you're a head of a big storage division. And then I think there's some other under the cover things too. I've recently wrote, actually have written about this a lot. Things like nitro and rethinking virtualization and how to do, you know offloads. The security that comes, you know fundamentally as part of the platform is, I think architecturally is something that leads the way in the industry for sure. So there's a lot we could unpack, but you've fundamentally changed the storage market over the last 16 years. And again, I've written about this extensively. We used to think about storage in blocks or you got, you know, somebody who's really good in files, there were companies that dominated each space with legacy on-prem storage. You know, when you think about object storage Kevin, it was a niche, right? It was something used for archival, it was known for its simple, get put syntax, great for cheap and deep storage, and S3 changed that. Why do you think that's happened and S3 has evolved, the object has evolved the way it has, and what's the future hold for S3? >> Yeah I mean, you know, Dave, I think that probably the biggest overall trend there is that customers are looking to build cloud native applications. Where as much of that application is managed as they can have. They don't want to have to spend time managing the underlying infrastructure, the compute and storage and everything that goes around it. And so a fully managed service like S3, where there's no provisioning storage capacity, there's, you know we provide the resiliency and the durability that just really resonates with customers. And I think that increasingly, customers are seeing that they want to innovate across the entire range of business. So it's not about a central IT team anymore, it's about engineers that are embedded within lines of business, innovating around what is critical to achieve their business results. So, you know, if they're in a manufacturing segment, how can we pull data from sensors and other instrumentation off of our equipment and then make better decisions about when we need to do predictive maintenance, how quickly we can run our manufacturing line, looking for inefficiencies. And so we've developed around our managed offerings like S3, we've just developed, you know, customers who are investing and executing on plans and you know transformations. That really give them, you know put digital technology directly into the line of business that they're looking for. And I think that trend is just going to continue. People sometimes ask me, well "I mean, 16 years, you know, isn't S3 done?" And I would say, "By no stretcher are we done." We have plenty of feedback from customers on ways that we can continue to simplify, reduce the kinds of things they need to do, when they're looking for example and rolling out new security policies and parameters across their entire organization. So raising the bar there, finding, you know, raising the bar on how they can efficiently manage their storage and reduce costs. So I think we have plenty of innovation ahead of us to continue to help customers provide that fully managed capability. >> Yeah I often say Kevin, the next 10 years ain't going to be like the last in cloud. So I really thank you for coming on theCube and sharing your insights, really appreciate it. >> Absolutely Dave, thanks for having me. >> You're welcome. Okay keep it right there for more coverage of AWS Storage Day 2022 in theCube. (calm bright music)

>> From the theCUBE studios in Palo Alto in Boston, bringing you data driven insights from theCUBE and ETR. This is "Breaking Analysis" with Dave Vellante. >> Welcome to this week's Wikibon, theCUBE's insights powered by ETR. As we exited the isolation economy last year, supercloud is a term that we introduced to describe something new that was happening in the world of cloud. In this Breaking Analysis, we address the 10 most frequently asked questions we get around supercloud. Okay, let's review these frequently asked questions on supercloud that we're going to try to answer today. Look at an industry that's full of hype and buzzwords. Why the hell does anyone need a new term? Aren't hyperscalers building out superclouds? We'll try to answer why the term supercloud connotes something different from hyperscale clouds. And we'll talk about the problems that superclouds solve specifically. And we'll further define the critical aspects of a supercloud architecture. We often get asked, isn't this just multi-cloud? Well, we don't think so, and we'll explain why in this Breaking Analysis. Now in an earlier episode, we introduced the notion of super PaaS. Well, isn't a plain vanilla PaaS already a super PaaS? Again, we don't think so, and we'll explain why. Who will actually build and who are the players currently building superclouds? What workloads and services will run on superclouds? And 8-A or number nine, what are some examples that we can share of supercloud? And finally, we'll answer what you can expect next from us on supercloud? Okay, let's get started. Why do we need another buzzword? Well, late last year, ahead of re:Invent, we were inspired by a post from Jerry Chen called "Castles in the Cloud." Now in that blog post, he introduced the idea that there were sub-markets emerging in cloud that presented opportunities for investors and entrepreneurs that the cloud wasn't going to suck the hyperscalers. Weren't going to suck all the value out of the industry. And so we introduced this notion of supercloud to describe what we saw as a value layer emerging above the hyperscalers CAPEX gift, we sometimes call it. Now it turns out, that we weren't the only ones using the term as both Cornell and MIT have used the phrase in somewhat similar, but different contexts. The point is something new was happening in the AWS and other ecosystems. It was more than IaaS and PaaS, and wasn't just SaaS running in the cloud. It was a new architecture that integrates infrastructure, platform and software as services to solve new problems that the cloud vendors in our view, weren't addressing by themselves. It seemed to us that the ecosystem was pursuing opportunities across clouds that went beyond conventional implementations of multi-cloud. And we felt there was a structural change going on at the industry level, the supercloud, metaphorically was highlighting. So that's the background on why we felt a new catch phrase was warranted, love it or hate it. It's memorable and it's what we chose. Now to that last point about structural industry transformation. Andy Rappaport is sometimes and often credited with identifying the shift from the vertically integrated IBM mainframe era to the fragmented PC microprocesor-based era in his HBR article in 1991. In fact, it was David Moschella, who at the time was an IDC Analyst who first introduced the concept in 1987, four years before Rappaport's article was published. Moschella saw that it was clear that Intel, Microsoft, Seagate and others would replace the system vendors, and put that forth in a graphic that looked similar to the first two on this chart. We don't have to review the shift from IBM as the center of the industry to Wintel, that's well understood. What isn't as well known or accepted is what Moschella put out in his 2018 book called "Seeing Digital" which introduced the idea of "The Matrix" that's shown on the right hand side of this chart. Moschella posited that new services were emerging built on top of the internet and hyperscale clouds that would integrate other innovations and would define the next era of computing. He used the term Matrix because the conceptual depiction included not only horizontal technology rose like the cloud and the internet, but for the first time included connected industry verticals, the columns in this chart. Moschella pointed out that whereas historically, industry verticals had a closed value chain or stack and ecosystem of R&D, and production, and manufacturing, and distribution. And if you were in that industry, the expertise within that vertical generally stayed within that vertical and was critical to success. But because of digital and data, for the first time, companies were able to traverse industries, jump across industries and compete because data enabled them to do that. Examples, Amazon and content, payments, groceries, Apple, and payments, and content, and so forth. There are many examples. Data was now this unifying enabler and this marked a change in the structure of the technology landscape. And supercloud is meant to imply more than running in hyperscale clouds, rather it's the combination of multiple technologies enabled by CloudScale with new industry participants from those verticals, financial services and healthcare, manufacturing, energy, media, and virtually all in any industry. Kind of an extension of every company is a software company. Basically, every company now has the opportunity to build their own cloud or supercloud. And we'll come back to that. Let's first address what's different about superclouds relative to hyperscale clouds? You know, this one's pretty straightforward and obvious, I think. Hyperscale clouds, they're walled gardens where they want your data in their cloud and they want to keep you there. Sure, every cloud player realizes that not all data will go to their particular cloud so they're meeting customers where their data lives with initiatives like Amazon Outposts and Azure Arc, and Google Anthos. But at the end of the day, the more homogeneous they can make their environments, the better control, security, cost, and performance they can deliver. The more complex the environment, the more difficult it is to deliver on their brand promises. And of course, the lesser margin that's left for them to capture. Will the hyperscalers get more serious about cross-cloud services? Maybe, but they have plenty of work to do within their own clouds and within enabling their own ecosystems. They had a long way to go a lot of runway. So let's talk about specifically, what problems superclouds solve? We've all seen the stats from IDC or Gartner, or whomever the customers on average use more than one cloud. You know, two clouds, three clouds, five clouds, 20 clouds. And we know these clouds operate in disconnected silos for the most part. And that's a problem because each cloud requires different skills because the development environment is different as is the operating environment. They have different APIs, different primitives, and different management tools that are optimized for each respective hyperscale cloud. Their functions and value props don't extend to their competitors' clouds for the most part. Why would they? As a result, there's friction when moving between different clouds. It's hard to share data, it's hard to move work. It's hard to secure and govern data. It's hard to enforce organizational edicts and policies across these clouds, and on-prem. Supercloud is an architecture designed to create a single environment that enables management of workloads and data across clouds in an effort to take out complexity, accelerate application development, streamline operations and share data safely, irrespective of location. It's pretty straightforward, but non-trivial, which is why I always ask a company's CEO and executives if stock buybacks and dividends will yield as much return as building out superclouds that solve really specific and hard problems, and create differential value. Okay, let's dig a bit more into the architectural aspects of supercloud. In other words, what are the salient attributes of supercloud? So first and foremost, a supercloud runs a set of specific services designed to solve a unique problem and it can do so in more than one cloud. Superclouds leverage the underlying cloud native tooling of a hyperscale cloud, but they're optimized for a specific objective that aligns with the problem that they're trying to solve. For example, supercloud might be optimized for lowest cost or lowest latency, or sharing data, or governing, or securing that data, or higher performance for networking, for example. But the point is, the collection of services that is being delivered is focused on a unique value proposition that is not being delivered by the hyperscalers across clouds. A supercloud abstracts the underlying and siloed primitives of the native PaaS layer from the hyperscale cloud and then using its own specific platform as a service tooling, creates a common experience across clouds for developers and users. And it does so in a most efficient manner, meaning it has the metadata knowledge and management capabilities that can optimize for latency, bandwidth, or recovery, or data sovereignty, or whatever unique value that supercloud is delivering for the specific use case in their domain. And a supercloud comprises a super PaaS capability that allows ecosystem partners through APIs to add incremental value on top of the supercloud platform to fill gaps, accelerate features, and of course innovate. The services can be infrastructure-related, they could be application services, they could be data services, security services, user services, et cetera, designed and packaged to bring unique value to customers. Again, that hyperscalers are not delivering across clouds or on-premises. Okay, so another common question we get is, isn't that just multi-cloud? And what we'd say to that is yes, but no. You can call it multi-cloud 2.0, if you want, if you want to use it, it's kind of a commonly used rubric. But as Dell's Chuck Whitten proclaimed at Dell Technologies World this year, multi-cloud by design, is different than multi-cloud by default. Meaning to date, multi-cloud has largely been a symptom of what we've called multi-vendor or of M&A, you buy a company and they happen to use Google Cloud, and so you bring it in. And when you look at most so-called, multi-cloud implementations, you see things like an on-prem stack, which is wrapped in a container and hosted on a specific cloud or increasingly a technology vendor has done the work of building a cloud native version of their stack and running it on a specific cloud. But historically, it's been a unique experience within each cloud with virtually no connection between the cloud silos. Supercloud sets out to build incremental value across clouds and above hyperscale CAPEX that goes beyond cloud compatibility within each cloud. So if you want to call it multi-cloud 2.0, that's fine, but we chose to call it supercloud. Okay, so at this point you may be asking, well isn't PaaS already a version of supercloud? And again, we would say no, that supercloud and its corresponding superPaaS layer which is a prerequisite, gives the freedom to store, process and manage, and secure, and connect islands of data across a continuum with a common experience across clouds. And the services offered are specific to that supercloud and will vary by each offering. Your OpenShift, for example, can be used to construct a superPaaS, but in and of itself, isn't a superPaaS, it's generic. A superPaaS might be developed to support, for instance, ultra low latency database work. It would unlikely again, taking the OpenShift example, it's unlikely that off-the-shelf OpenShift would be used to develop such a low latency superPaaS layer for ultra low latency database work. The point is supercloud and its inherent superPaaS will be optimized to solve specific problems like that low latency example for distributed databases or fast backup and recovery for data protection, and ransomware, or data sharing, or data governance. Highly specific use cases that the supercloud is designed to solve for. Okay, another question we often get is who has a supercloud today and who's building a supercloud, and who are the contenders? Well, most companies that consider themselves cloud players will, we believe, be building or are building superclouds. Here's a common ETR graphic that we like to show with Net Score or spending momentum on the Y axis and overlap or pervasiveness in the ETR surveys on the X axis. And we've randomly chosen a number of players that we think are in the supercloud mix, and we've included the hyperscalers because they are enablers. Now remember, this is a spectrum of maturity it's a maturity model and we've added some of those industry players that we see building superclouds like CapitalOne, Goldman Sachs, Walmart. This is in deference to Moschella's observation around The Matrix and the industry structural changes that are going on. This goes back to every company, being a software company and rather than pattern match an outdated SaaS model, we see new industry structures emerging where software and data, and tools, specific to an industry will lead the next wave of innovation and bring in new value that traditional technology companies aren't going to solve, and the hyperscalers aren't going to solve. You know, we've talked a lot about Snowflake's data cloud as an example of supercloud. After being at Snowflake Summit, we're more convinced than ever that they're headed in this direction. VMware is clearly going after cross-cloud services you know, perhaps creating a new category. Basically, every large company we see either pursuing supercloud initiatives or thinking about it. Dell showed project Alpine at Dell Tech World, that's a supercloud. Snowflake introducing a new application development capability based on their superPaaS, our term of course, they don't use the phrase. Mongo, Couchbase, Nutanix, Pure Storage, Veeam, CrowdStrike, Okta, Zscaler. Yeah, all of those guys. Yes, Cisco and HPE. Even though on theCUBE at HPE Discover, Fidelma Russo said on theCUBE, she wasn't a fan of cloaking mechanisms, but then we talked to HPE's Head of Storage Services, Omer Asad is clearly headed in the direction that we would consider supercloud. Again, those cross-cloud services, of course, their emphasis is connecting as well on-prem. That single experience, which traditionally has not existed with multi-cloud or hybrid. And we're seeing the emergence of companies, smaller companies like Aviatrix and Starburst, and Clumio and others that are building versions of superclouds that solve for a specific problem for their customers. Even ISVs like Adobe, ADP, we've talked to UiPath. They seem to be looking at new ways to go beyond the SaaS model and add value within their cloud ecosystem specifically, around data as part of their and their customers digital transformations. So yeah, pretty much every tech vendor with any size or momentum and new industry players are coming out of hiding, and competing. Building superclouds that look a lot like Moschella's Matrix, with machine intelligence and blockchains, and virtual realities, and gaming, all enabled by the internet and hyperscale cloud CAPEX. So it's moving fast and it's the future in our opinion. So don't get too caught up in the past or you'll be left behind. Okay, what about examples? We've given a number in the past, but let's try to be a little bit more specific. Here are a few we've selected and we're going to answer the two questions in one section here. What workloads and services will run in superclouds and what are some examples? Let's start with analytics. Our favorite example is Snowflake, it's one of the furthest along with its data cloud, in our view. It's a supercloud optimized for data sharing and governance, query performance, and security, and ecosystem enablement. When you do things inside of that data cloud, what we call a super data cloud. Again, our term, not theirs. You can do things that you could not do in a single cloud. You can't do this with Redshift, You can't do this with SQL server and they're bringing new data types now with merging analytics or at least accommodate analytics and transaction type data, and bringing open source tooling with things like Apache Iceberg. And so it ticks the boxes we laid out earlier. I would say that a company like Databricks is also in that mix doing it, coming at it from a data science perspective, trying to create that consistent experience for data scientists and data engineering across clouds. Converge databases, running transaction and analytic workloads is another example. Take a look at what Couchbase is doing with Capella and how it's enabling stretching the cloud to the edge with ARM-based platforms and optimizing for low latency across clouds, and even out to the edge. Document database workloads, look at MongoDB, a very developer-friendly platform that with the Atlas is moving toward a supercloud model running document databases very, very efficiently. How about general purpose workloads? This is where VMware comes into to play. Very clearly, there's a need to create a common operating environment across clouds and on-prem, and out to the edge. And I say VMware is hard at work on that. Managing and moving workloads, and balancing workloads, and being able to recover very quickly across clouds for everyday applications. Network routing, take a look at what Aviatrix is doing across clouds, industry workloads. We see CapitalOne, it announced its cost optimization platform for Snowflake, piggybacking on Snowflake supercloud or super data cloud. And in our view, it's very clearly going to go after other markets is going to test it out with Snowflake, running, optimizing on AWS and it's going to expand to other clouds as Snowflake's business and those other clouds grows. Walmart working with Microsoft to create an on-premed Azure experience that's seamless. Yes, that counts, on-prem counts. If you can create that seamless and continuous experience, identical experience from on-prem to a hyperscale cloud, we would include that as a supercloud. You know, we've written about what Goldman is doing. Again, connecting its on-prem data and software tooling, and other capabilities to AWS for scale. And we can bet dollars to donuts that Oracle will be building a supercloud in healthcare with its Cerner acquisition. Supercloud is everywhere you look. So I'm sorry, naysayers it's happening all around us. So what's next? Well, with all the industry buzz and debate about the future, John Furrier and I, have decided to host an event in Palo Alto, we're motivated and inspired to further this conversation. And we welcome all points of view, positive, negative, multi-cloud, supercloud, hypercloud, all welcome. So theCUBE on Supercloud is coming on August 9th, out of our Palo Alto studios, we'll be running a live program on the topic. We've reached out to a number of industry participants, VMware, Snowflake, Confluent, Sky High Security, Gee Rittenhouse's new company, HashiCorp, CloudFlare. We've hit up Red Hat and we expect many of these folks will be in our studios on August 9th. And we've invited a number of industry participants as well that we're excited to have on. From industry, from financial services, from healthcare, from retail, we're inviting analysts, thought leaders, investors. We're going to have more detail in the coming weeks, but for now, if you're interested, please reach out to me or John with how you think you can advance the discussion and we'll see if we can fit you in. So mark your calendars, stay tuned for more information. Okay, that's it for today. Thanks to Alex Myerson who handles production and manages the podcast for Breaking Analysis. And I want to thank Kristen Martin and Cheryl Knight, they help get the word out on social and in our newsletters. And Rob Hof is our editor in chief over at SiliconANGLE, who does a lot of editing and appreciate you posting on SiliconANGLE, Rob. Thanks to all of you. Remember, all these episodes are available as podcasts wherever you listen. All you got to do is search Breaking Analysis podcast. It publish each week on wikibon.com and siliconangle.com. You can email me directly at david.vellante@siliconangle.com or DM me @DVellante, or comment on my LinkedIn post. And please do check out ETR.ai for the best survey data. And the enterprise tech business will be at AWS NYC Summit next Tuesday, July 12th. So if you're there, please do stop by and say hello to theCUBE, it's at the Javits Center. This is Dave Vellante for theCUBE insights powered by ETR. Thanks for watching. And we'll see you next time on "Breaking Analysis." (bright music)

>> From theCUBE Studios in Palo Alto and Boston, bringing you data-driven insights from theCUBE and ETR. This is "Breaking Analysis" with Dave Vallante. >> Welcome to this week's Wikibon CUBE Insights powered by ETR. As we exited the isolation economy last year, Supercloud is a term that we introduced to describe something new that was happening in the world of cloud. In this "Breaking Analysis," we address the 10 most frequently asked questions we get around Supercloud. Okay, let's review these frequently asked questions on Supercloud that we're going to try to answer today. Look at an industry that's full of hype and buzzwords. Why the hell does anyone need a new term? Aren't hyperscalers building out Superclouds? We'll try to answer why the term Supercloud connotes something different from hyperscale clouds. And we'll talk about the problems that Superclouds solve specifically, and we'll further define the critical aspects of a Supercloud architecture. We often get asked, "Isn't this just multi-cloud?" Well, we don't think so, and we'll explain why in this "Breaking Analysis." Now, in an earlier episode, we introduced the notion of super PaaS. Well, isn't a plain vanilla PaaS already a super PaaS? Again, we don't think so, and we'll explain why. Who will actually build and who are the players currently building Superclouds? What workloads and services will run on Superclouds? And eight A or number nine, what are some examples that we can share of Supercloud? And finally, we'll answer what you can expect next from us on Supercloud. Okay, let's get started. Why do we need another buzzword? Well, late last year ahead of re:Invent, we were inspired by a post from Jerry Chen called castles in the cloud. Now, in that blog post, he introduced the idea that there were submarkets emerging in cloud that presented opportunities for investors and entrepreneurs. That the cloud wasn't going to suck the hyperscalers, weren't going to suck all the value out of the industry. And so we introduced this notion of Supercloud to describe what we saw as a value layer emerging above the hyperscalers CAPEX gift, we sometimes call it. Now, it turns out that we weren't the only ones using the term, as both Cornell and MIT, have used the phrase in somewhat similar, but different contexts. The point is, something new was happening in the AWS and other ecosystems. It was more than IS and PaaS, and wasn't just SaaS running in the cloud. It was a new architecture that integrates infrastructure, platform and software as services, to solve new problems that the cloud vendors, in our view, weren't addressing by themselves. It seemed to us that the ecosystem was pursuing opportunities across clouds that went beyond conventional implementations of multi-cloud. And we felt there was a structural change going on at the industry level. The Supercloud metaphorically was highlighting. So that's the background on why we felt a new catch phrase was warranted. Love it or hate it, it's memorable and it's what we chose. Now, to that last point about structural industry transformation. Andy Rapaport is sometimes and often credited with identifying the shift from the vertically integrated IBM mainframe era to the fragmented PC microprocesor based era in his HBR article in 1991. In fact, it was David Moschella, who at the time was an IDC analyst who first introduced the concept in 1987, four years before Rapaport's article was published. Moschella saw that it was clear that Intel, Microsoft, Seagate and others would replace the system vendors and put that forth in a graphic that looked similar to the first two on this chart. We don't have to review the shift from IBM as the center of the industry to Wintel. That's well understood. What isn't as well known or accepted is what Moschella put out in his 2018 book called "Seeing Digital" which introduced the idea of the matrix that's shown on the right hand side of this chart. Moschella posited that new services were emerging, built on top of the internet and hyperscale clouds that would integrate other innovations and would define the next era of computing. He used the term matrix, because the conceptual depiction included, not only horizontal technology rows, like the cloud and the internet, but for the first time included connected industry verticals, the columns in this chart. Moschella pointed out that, whereas historically, industry verticals had a closed value chain or stack and ecosystem of R&D and production and manufacturing and distribution. And if you were in that industry, the expertise within that vertical generally stayed within that vertical and was critical to success. But because of digital and data, for the first time, companies were able to traverse industries jump across industries and compete because data enabled them to do that. Examples, Amazon and content, payments, groceries, Apple and payments, and content and so forth. There are many examples. Data was now this unifying enabler and this marked a change in the structure of the technology landscape. And Supercloud is meant to imply more than running in hyperscale clouds. Rather, it's the combination of multiple technologies, enabled by cloud scale with new industry participants from those verticals; financial services, and healthcare, and manufacturing, energy, media, and virtually all and any industry. Kind of an extension of every company is a software company. Basically, every company now has the opportunity to build their own cloud or Supercloud. And we'll come back to that. Let's first address what's different about Superclouds relative to hyperscale clouds. Now, this one's pretty straightforward and obvious, I think. Hyperscale clouds, they're walled gardens where they want your data in their cloud and they want to keep you there. Sure, every cloud player realizes that not all data will go to their particular cloud. So they're meeting customers where their data lives with initiatives like Amazon Outposts and Azure Arc and Google Antos. But at the end of the day, the more homogeneous they can make their environments, the better control, security, costs, and performance they can deliver. The more complex the environment, the more difficult it is to deliver on their brand promises. And, of course, the less margin that's left for them to capture. Will the hyperscalers get more serious about cross cloud services? Maybe, but they have plenty of work to do within their own clouds and within enabling their own ecosystems. They have a long way to go, a lot of runway. So let's talk about specifically, what problems Superclouds solve. We've all seen the stats from IDC or Gartner or whomever, that customers on average use more than one cloud, two clouds, three clouds, five clouds, 20 clouds. And we know these clouds operate in disconnected silos for the most part. And that's a problem, because each cloud requires different skills, because the development environment is different as is the operating environment. They have different APIs, different primitives, and different management tools that are optimized for each respective hyperscale cloud. Their functions and value props don't extend to their competitors' clouds for the most part. Why would they? As a result, there's friction when moving between different clouds. It's hard to share data. It's hard to move work. It's hard to secure and govern data. It's hard to enforce organizational edicts and policies across these clouds and on-prem. Supercloud is an architecture designed to create a single environment that enables management of workloads and data across clouds in an effort to take out complexity, accelerate application development, streamline operations, and share data safely, irrespective of location. It's pretty straightforward, but non-trivial, which is why I always ask a company's CEO and executives if stock buybacks and dividends will yield as much return as building out Superclouds that solve really specific and hard problems and create differential value. Okay, let's dig a bit more into the architectural aspects of Supercloud. In other words, what are the salient attributes of Supercloud? So, first and foremost, a Supercloud runs a set of specific services designed to solve a unique problem, and it can do so in more than one cloud. Superclouds leverage the underlying cloud native tooling of a hyperscale cloud, but they're optimized for a specific objective that aligns with the problem that they're trying to solve. For example, Supercloud might be optimized for lowest cost or lowest latency or sharing data or governing or securing that data or higher performance for networking, for example. But the point is, the collection of services that is being delivered is focused on a unique value proposition that is not being delivered by the hyperscalers across clouds. A Supercloud abstracts the underlying and siloed primitives of the native PaaS layer from the hyperscale cloud, and then using its own specific platform as a service tooling, creates a common experience across clouds for developers and users. And it does so in the most efficient manner, meaning it has the metadata knowledge and management capabilities that can optimize for latency, bandwidth, or recovery or data sovereignty, or whatever unique value that Supercloud is delivering for the specific use case in their domain. And a Supercloud comprises a super PaaS capability that allows ecosystem partners through APIs to add incremental value on top of the Supercloud platform to fill gaps, accelerate features, and of course, innovate. The services can be infrastructure related, they could be application services, they could be data services, security services, user services, et cetera, designed and packaged to bring unique value to customers. Again, that hyperscalers are not delivering across clouds or on premises. Okay, so another common question we get is, "Isn't that just multi-cloud?" And what we'd say to that is yeah, "Yes, but no." You can call it multi-cloud 2.0, if you want. If you want to use, it's kind of a commonly used rubric. But as Dell's Chuck Whitten proclaimed at Dell Technologies World this year, multi-cloud, by design, is different than multi-cloud by default. Meaning, to date, multi-cloud has largely been a symptom of what we've called multi-vendor or of M&A. You buy a company and they happen to use Google cloud. And so you bring it in. And when you look at most so-called multi-cloud implementations, you see things like an on-prem stack, which is wrapped in a container and hosted on a specific cloud. Or increasingly, a technology vendor has done the work of building a cloud native version of their stack and running it on a specific cloud. But historically, it's been a unique experience within each cloud, with virtually no connection between the cloud silos. Supercloud sets out to build incremental value across clouds and above hyperscale CAPEX that goes beyond cloud compatibility within each cloud. So, if you want to call it multi-cloud 2.0, that's fine, but we chose to call it Supercloud. Okay, so at this point you may be asking, "Well isn't PaaS already a version of Supercloud?" And again, we would say, "No." That Supercloud and its corresponding super PaaS layer, which is a prerequisite, gives the freedom to store, process, and manage and secure and connect islands of data across a continuum with a common experience across clouds. And the services offered are specific to that Supercloud and will vary by each offering. OpenShift, for example, can be used to construct a super PaaS, but in and of itself, isn't a super PaaS, it's generic. A super PaaS might be developed to support, for instance, ultra low latency database work. It would unlikely, again, taking the OpenShift example, it's unlikely that off the shelf OpenShift would be used to develop such a low latency, super PaaS layer for ultra low latency database work. The point is, Supercloud and its inherent super PaaS will be optimized to solve specific problems like that low latency example for distributed databases or fast backup in recovery for data protection and ransomware, or data sharing or data governance. Highly specific use cases that the Supercloud is designed to solve for. Okay, another question we often get is, "Who has a Supercloud today and who's building a Supercloud and who are the contenders?" Well, most companies that consider themselves cloud players will, we believe, be building or are building Superclouds. Here's a common ETR graphic that we like to show with net score or spending momentum on the Y axis, and overlap or pervasiveness in the ETR surveys on the X axis. And we've randomly chosen a number of players that we think are in the Supercloud mix. And we've included the hyperscalers because they are enablers. Now, remember, this is a spectrum of maturity. It's a maturity model. And we've added some of those industry players that we see building Superclouds like Capital One, Goldman Sachs, Walmart. This is in deference to Moschella's observation around the matrix and the industry structural changes that are going on. This goes back to every company being a software company. And rather than pattern match and outdated SaaS model, we see new industry structures emerging where software and data and tools specific to an industry will lead the next wave of innovation and bring in new value that traditional technology companies aren't going to solve. And the hyperscalers aren't going to solve. We've talked a lot about Snowflake's data cloud as an example of Supercloud. After being at Snowflake Summit, we're more convinced than ever that they're headed in this direction. VMware is clearly going after cross cloud services, perhaps creating a new category. Basically, every large company we see either pursuing Supercloud initiatives or thinking about it. Dell showed Project Alpine at Dell Tech World. That's a Supercloud. Snowflake introducing a new application development capability based on their super PaaS, our term, of course. They don't use the phrase. Mongo, Couchbase, Nutanix, Pure Storage, Veeam, CrowdStrike, Okta, Zscaler. Yeah, all of those guys. Yes, Cisco and HPE. Even though on theCUBE at HPE Discover, Fidelma Russo said on theCUBE, she wasn't a fan of cloaking mechanisms. (Dave laughing) But then we talked to HPE's head of storage services, Omer Asad, and he's clearly headed in the direction that we would consider Supercloud. Again, those cross cloud services, of course, their emphasis is connecting as well on-prem. That single experience, which traditionally has not existed with multi-cloud or hybrid. And we're seeing the emergence of smaller companies like Aviatrix and Starburst and Clumio and others that are building versions of Superclouds that solve for a specific problem for their customers. Even ISVs like Adobe, ADP, we've talked to UiPath. They seem to be looking at new ways to go beyond the SaaS model and add value within their cloud ecosystem, specifically around data as part of their and their customer's digital transformations. So yeah, pretty much every tech vendor with any size or momentum, and new industry players are coming out of hiding and competing, building Superclouds that look a lot like Moschella's matrix, with machine intelligence and blockchains and virtual realities and gaming, all enabled by the internet and hyperscale cloud CAPEX. So it's moving fast and it's the future in our opinion. So don't get too caught up in the past or you'll be left behind. Okay, what about examples? We've given a number in the past but let's try to be a little bit more specific. Here are a few we've selected and we're going to answer the two questions in one section here. What workloads and services will run in Superclouds and what are some examples? Let's start with analytics. Our favorite example of Snowflake. It's one of the furthest along with its data cloud, in our view. It's a Supercloud optimized for data sharing and governance, and query performance, and security, and ecosystem enablement. When you do things inside of that data cloud, what we call a super data cloud. Again, our term, not theirs. You can do things that you could not do in a single cloud. You can't do this with Redshift. You can't do this with SQL server. And they're bringing new data types now with merging analytics or at least accommodate analytics and transaction type data and bringing open source tooling with things like Apache Iceberg. And so, it ticks the boxes we laid out earlier. I would say that a company like Databricks is also in that mix, doing it, coming at it from a data science perspective trying to create that consistent experience for data scientists and data engineering across clouds. Converge databases, running transaction and analytic workloads is another example. Take a look at what Couchbase is doing with Capella and how it's enabling stretching the cloud to the edge with arm based platforms and optimizing for low latency across clouds, and even out to the edge. Document database workloads, look at Mongo DB. A very developer friendly platform that where the Atlas is moving toward a Supercloud model, running document databases very, very efficiently. How about general purpose workloads? This is where VMware comes into play. Very clearly, there's a need to create a common operating environment across clouds and on-prem and out to the edge. And I say, VMware is hard at work on that, managing and moving workloads and balancing workloads, and being able to recover very quickly across clouds for everyday applications. Network routing, take a look at what Aviatrix is doing across clouds. Industry workloads, we see Capital One. It announced its cost optimization platform for Snowflake, piggybacking on Snowflake's Supercloud or super data cloud. And in our view, it's very clearly going to go after other markets. It's going to test it out with Snowflake, optimizing on AWS, and it's going to expand to other clouds as Snowflake's business and those other clouds grows. Walmart working with Microsoft to create an on-premed Azure experience that's seamless. Yes, that counts, on-prem counts. If you can create that seamless and continuous experience, identical experience from on-prem to a hyperscale cloud, we would include that as a Supercloud. We've written about what Goldman is doing. Again, connecting its on-prem data and software tooling, and other capabilities to AWS for scale. And you can bet dollars to donuts that Oracle will be building a Supercloud in healthcare with its Cerner acquisition. Supercloud is everywhere you look. So I'm sorry, naysayers, it's happening all around us. So what's next? Well, with all the industry buzz and debate about the future, John Furrier and I have decided to host an event in Palo Alto. We're motivated and inspired to further this conversation. And we welcome all points of view, positive, negative, multi-cloud, Supercloud, HyperCloud, all welcome. So theCUBE on Supercloud is coming on August 9th out of our Palo Alto studios. We'll be running a live program on the topic. We've reached out to a number of industry participants; VMware, Snowflake, Confluent, Skyhigh Security, G. Written House's new company, HashiCorp, CloudFlare. We've hit up Red Hat and we expect many of these folks will be in our studios on August 9th. And we've invited a number of industry participants as well that we're excited to have on. From industry, from financial services, from healthcare, from retail, we're inviting analysts, thought leaders, investors. We're going to have more detail in the coming weeks, but for now, if you're interested, please reach out to me or John with how you think you can advance the discussion, and we'll see if we can fit you in. So mark your calendars, stay tuned for more information. Okay, that's it for today. Thanks to Alex Myerson who handles production and manages the podcast for "Breaking Analysis." And I want to thank Kristen Martin and Cheryl Knight. They help get the word out on social and in our newsletters. And Rob Hof is our editor in chief over at SiliconANGLE, who does a lot of editing and appreciate you posting on SiliconANGLE, Rob. Thanks to all of you. Remember, all these episodes are available as podcasts wherever you listen. All you got to do is search, breaking analysis podcast. I publish each week on wikibon.com and siliconangle.com. Or you can email me directly at david.vellante@siliconangle.com. Or DM me @DVallante, or comment on my LinkedIn post. And please, do check out etr.ai for the best survey data in the enterprise tech business. We'll be at AWS NYC summit next Tuesday, July 12th. So if you're there, please do stop by and say hello to theCUBE. It's at the Javits Center. This is Dave Vallante for theCUBE Insights, powered by ETR. Thanks for watching. And we'll see you next time on "Breaking Analysis." (slow music)

>>The cube presents HPE discover 2022 brought to you by HPE. >>Hey everyone. Welcome to Las Vegas. It's the cube live on the show floor at HPE discover 2022, the first in person discover in three years, there are about 8,000 people here. The keynote was standing room only Lisa Martin here. I got a powerhouse group joining me for this keynote analysis. Dave ante joins us, Keith Townsend, John farrier, guys. Lot of news. It's all about HPE GreenLake. What were some of the things Dave, that stuck out to you? >>Well, I'll tell you right now, I gotta just quote, Antonio OIR said, Neri said four years ago, I declared that the enterprise of the future would be edge centric, cloud enabled and data driven. As a result, we launched HPE GreenLake. It kind of declared victory. Now I would say that what they're talking about and what they announced, I would consider table stakes. You know, I wish it started in 2014. I wish Antonio took over in 2015 instead of 2018, but I have to give credit, he's brought a focus and uh, and a, he think he's amped it up, John. I mean, if he's really prioritizing, uh, the, as a service they're going on in all in they're burning the boats, uh, and it's good. They got a lot of work to do. They >>Got a lot of work to do three years ago, John Antonio stood on this very stage saying we, and by 2022, we're gonna be delivering our entire portfolio as a service here we are with GreenLake. What I wanna get your thoughts on Keith's as well. >>Yeah. Well, first of all, I think that the crowded house was, uh, and a sign of people wanna come back together. So it's, to me, that was the first good news I saw, which was the HP community, their customer base. They're all here. They're glad to be back and forth. So it shows that they, their customer base it's resonating their value proposition of annual recurring revenue as a service plus the contract values with GreenLake are up. So this resonance with the customers, Dave, on the new operating model, that's a great check the box there. Um, I would say that I don't think HP's, as far along as Antonio had hopes, he'd be the pandemic was a setback. Um, but GreenLake is a real shining star. It's, uh, it's producing some green if you will money for them in terms of contracts, but they still got a lot more work to do because they're in a really interesting zone, Dave, because edge the cloud, although relevant and accurate where the, the shift is going, are they really there with, with the goods? And to me, I'm looking forward to seeing this discover if they have it or not. Certainly the messaging's good, but we're gonna UN UN unpeel that onion back and look at it. But >>Keith they're on the curve, right? At least they're on the cloud curve. >>They're absolutely on the curve. They have APIs, they have consistent developer experience. They announced the developer portal. They're developer centric. You can now consume your three par storage array services via a Terraform, uh, provider. They speak the language of cloud practitioners. You might struggle a little bit if I'm a small startup, you know, why would I look towards HPE? They kind of answered that a little bit. They had evil genius as a customer on stage, not a huge organization. A lot of the pushback they've been given is that if I may startup, I can simply go to a AWS portal, launch, a free trial service and run it. HPE kind of buried the lead. They now have, at least they announced preannounced the capability to, to trial GreenLake. So they're moving in the right direction. But you know, it's, it's it's table states. Well, >>Here's the thing. Here's the dynamic day that's going on. This is something that we've got got we're first of we've been covering HPE HP for now 11 years with the cube and look at Amazon's success and look at where Amazon's struggling. If you can say that they're having crossed overs to the enterprise, uh, cuz the enterprises are now just getting up to speed. You're seeing the rise of lack of talent. It certainly changing, uh, cyber security. You can't find talent. Kubernetes, good luck with that. Try to find someone. So you're seeing the enterprise aren't really geared up or staffed up for doing what I call, you know, high end cloud. So the rise of managed services is, is what we're seeing out there right now. You want Kubernetes clusters is a great set of managed services. You want other services? So that's the tell sign that the enterprises H HP's customers are now walking before they can run. They're crawling, they're now they're walking. So it's they have time to get in the Amazon lane in my opinion. Well, you >>Think about the hallmarks of cloud, obviously there's as a service, there's consumption based pricing. There's a developer, you know, friendliness, uh, there's ecosystem, which is really, really important. I think today, a lot of the ecosystem is partners, resellers and managed service providers. And to your point, Keith table stakes are things like single sign on being able to have, you know, a console being able to do it from a, from a URL to your point about startups is really interesting because that's one of the other hallmarks of cloud is you attract startups. And Lisa, we were at the snowflake summit and I asked the same question, can snowflake attract startups with their own super cloud. And what you saw was ecosystem partners developing in the snowflake cloud and monetizing. And that's something that we're waiting to see here. And I, I think they know >>You're suggesting way you suggesting that HP's gonna attract startups. >>Well, >>I, I think that's a sign if they can do that. That's a sign. And, and right now, I mean, you heard the example that Keith Keith gave. Uh, but, but not, not many. >>Yeah. I'm hoping that H I don't think HP is gonna ever attract startups, but I think the opportunity GreenLake affords the ecosystem is build clouds or purpose driven clouds around GreenLake. Mm-hmm <affirmative> whether it's the agreement with Equinix or all the cos and semi clouds, I think GreenLake gets most small CSPs, a leg up or 80% of the way there, where they can add that 20% of the IP and build services around GreenLake. And then that can attract the, the startup >>Or entrepreneurs. So the, the big question is, okay, where are these developers gonna come from? They could come from incumbents inside of companies. You know, the, the, the DevOps crowd from the enterprise, the really ops dev crowd. Right? I mean, yeah, don't you see that as a sort of a form of innovation startup, even though it's not a true startup. >>Yeah. Even though it's not, >>So Todd's making faces over there, we <laugh> >>Look, it, look it, they have >>Listen, if they don't, if they can't >>Do that, no, this is their focus is not startups. I agree with Keith on this one, they have to take care of business, home Depot. They have big customers and they have a lot of SMBs as well. They've got a great channel. H HP's got amazing infrastructure and, and client action going on. They gotta get the operating model, right job one as a service ARR, and then contract value and, and nail that with GreenLake. >>Who's their ideal customer profile. >>Their ideal is their install base. Look what Microsoft did with 365, they were going down. Their stock price was 26. At one point go to the, they went to the cloud 365, moved everything to the cloud and look at the success they're having. HP has the same kind of installed base. They gotta bring them along. They gotta get the operating model, right. And the developers that they're targeting are the ones inside the company and, or manage services that they're gonna go to the ecosystem for. That's where the cloud native comes in. That's where thing kind of comes together. So to me, I'm bullish on the operating model, but I'm skeptical that HP can get that cloud native developer. I haven't seen it yet. I'm looking for it. We're gonna look for it here. >>A key to that is going to be consistently. I, the, one of the things I'm looking for on the tech side, I, I hate to compare what HPE is doing to what VMware did with vCloud error years ago, but vCloud error on the outside looked >>Wonderful. Yes, >>It did. Once you tried to use it, it was just flaky underneath. And that's the part I'm looking to see customers pounding on it and saying, you know what API call after API I call, can I, uh, provision 10,000 pods a day? Does it scale down? Does it scale? And is it consistent? Is it >>Fragile Al roo she's co seasoned veteran? Uh, she was at V VMware cloud. She saw that movie. She gets a Mulligan, Dave. So I think her leadership is impressive. And I think she could bring a lot to the table to your point about don't make that same mistake and they gotta get this architecture, right. If they get the operating model right with GreenLake, they can double down on that and enable the developers that are driving the digital transformation. That to me is the, the key positions that they have to nail. And they do that. The rest is just fringe work. In my opinion, >>The reason why Alma was brought in, sorry, Lisa, it was, and then you gotta chime in here was to really build out that platform so that internal people at HPE can actually build value on top of it and the ecosystem that's her priority. >>We're gonna hear a lot from the ecosystem in the next couple of days, but I wanna get your perspective on, you've been following HPE a long time, all three of you. What are some of the things that you're hearing right now that are differentiators? We were just at Dell technologies. We talking about apex. We saw the big announcement they had with snowflake. We were at snowflake two weeks ago. I wanna get all three of your opinions on what are you seeing? Where is HP leading? >>I mean, HPE and Dell will, both with Dell, with apex are go, they're both gonna differentiate with their strengths. And, you know, for Dell, that's their breadth and their, their portfolio. And for, for HPE, that's their sort of open posture. I mean, John, you, you know this well, uh, that's their, their ecosystem, which I know has to evolve. And to me, their focus, you know, Antonio laid out some of the key differentiators. I, I, I think some of them were kind of, you know, pushing the envelope a little bit. Uh, but, but I think they're focus on as a service burning the, the, the boats telling wall street, this is our business. I think that's their differentiator. Is that they're, they're all in. >>Yeah. I, I think they, they try to highlight it by re announcing their private cloud service. I don't even know why they needed to announce that they have a private cloud. GreenLake is a cloud it's is a private cloud >>With block storage, hit disaster recovery. It's like good >>With like everything you get. But I think the, the key is, is that all of that is available today and you can get it in all kinds of frame of, of formats and, and frames specifically, if I'm a customer and I wanna get outta the data center and you, you know, Dave, we go back and forth about this all the time, and I wanna repatriate some workloads to Kubernetes on prem. I don't need to spend up another data center. I can go to Equinix, get GreenLake min IO, object storage on the back end, HPE lighthouse, all those services that I need for Kubernetes and repatriate my workloads without buying a new data center. And I get it as a service. I can get that Dave from HPE GreenLake, Dell apex is on the way. The >>Other thing they're differentiating with Aruba, that's something that Dell doesn't have. Yeah. And, and that is their edge play, I think is stronger than >>Of the others. Mean the, to me, the differentiator for HP is their, their history. Their channel's amazing. They got great Salesforce and they have serious customers and they have serious customers that have serious problems, uh, cyber security, uh, infrastructure, the security paradigm's changed. Uh, the deployment is changed how they deploy applications in their customer base. So they gotta step up to that challenge. And I think their differentiator is gonna be their size, their field and their ability to bring that operating model. And the hybrid model is a steady state. That's clear multi-cloud is just hybrids stitched together, but hybrid cloud, which is basically on premises and cloud to edge operating model is the number one thing that they need to nail. And if they nail that right, they will have a poll position that they could accelerate on. And again, I'm really gonna be watching how well they could enable cloud native developers, okay. To build modern agile applications while solving those serious problems with those serious customers. So again, I think hybrids spun in their direction. I'm not gonna say they got lucky, cuz they've always been on the hybrid bandwagon since we've been covering them. But I thought they'd be for a long day, but they're lucky to have hybrid. That's good for them. And I think do what Microsoft did convert their customers over and they do that, right? >>I think the key to that is gonna be ecosystem. Again, the developers need to see, especially the data piece, they talk about the cloud operating model. I think they're really moving that direction. The data piece to me is the weakest. Like they'll, they'll make claims that we can do anything that the cloud can do. You can't run snowflake, can't run data bricks, can't run Mongo Atlas. So they gotta figure out that data layer and that's optionality of, of data stores. And they don't have that today. >>Yeah. They, they, they have an announcement coming and I can't pre-announce it, but they're, they've, I've deemed them against it. They have the vision, Emeral data services, their data fabric multi-protocol access is a great start. They need the data network behind it. They need the ability to build a super cloud, a across multiple cloud providers, bringing some Google infos love inside of, uh, right next to your data. They have the hardware, they have the infrastructure, but they don't have the services. >>That's a key thing. I think one, you just brought up great point, Keith, and that is, is that at the end of the day, Dave, we're in a market now where agility and speed can be accomplished by startups or any company and HP's customers. Okay. Can move fast too. Okay. And so whoever can extend that value. If HPE can enable value creation for their customers, that's gonna be truly their, their task at hand, they got the channel, they got some leverage, but at the end of the day, the customers have alternatives now and they can move faster to get the value that they need to solve their serious problems. Uh, like cyber, like scalable infrastructure, like infrastructures code, like data ops, like AI ops, it's all here. And it's all coming really fast. Can GreenLake carry the day. And >>By the way, everything we just said about GreenLake in terms of table stakes and everything else, it applies for Dell. >>Yeah, absolutely. >>No question. It does guys. We have, and jam packed three days. We're gonna be talking with the ecosystem. We're gonna be talking with HPE leaders with customers. You're gonna hear all of these, uh, all this information unpacked over the next three days. We will be right back with our first guest for Dave ante, Keith Townson and John furrier. I'm Lisa Martin. Our first guest joins us momentarily.

>>Okay, welcome back. Everyone. Live cube coverage here in Las Vegas for Amazon re Mars hot event, machine learning, automation, robotics, and space. Two days of live coverage. We're talking to all the hot technologists. We got all the action startups and segment on sustainability and F pan hero for vet global lead, Amazon sustainability data initiative. Thanks for coming on the cube. Can I get that right? Can >>You, you, you did. >>Absolutely. Okay, great. <laugh> thank >>You. >>Great to see you. We met at the analyst, um, mixer and, um, blown away by the story going on at Amazon around sustainability data initiative, because we were joking. Everything's a data problem now, cuz that's cliche. But in this case you're using data in your program and it's really kind of got a bigger picture. Take a minute to explain what your project is, scope of it on the sustainability. >>Yeah, absolutely. And thank you for the opportunity to be here. Yeah. Um, okay. So, um, I, I lead this program that we launched several years back in 2018 more specifically, and it's a tech for good program. And when I say the tech for good, what that means is that we're trying to bring our technology and our infrastructure and lend that to the world specifically to solve the problems related to sustainability. And as you said, sustainability, uh, inherently needs data. You need, we need data to understand the baseline of where we are and also to understand the progress that we are making towards our goals. Right? But one of the big challenges that the data that we need is spread everywhere. Some of it is too large for most people to be able to, um, access and analyze. And so, uh, what we're trying to tackle is really the data problem in the sustainability space. >>Um, what we do more specifically is focus on Democrat democratizing access to data. So we work with a broader community and we try to understand what are those foundational data sets that most people need to use in the space to solve problems like climate change or food security or think about sustainable development goals, right? Yeah. Yeah. Like all the broad space. Um, and, and we basically then work with the data providers, bring the data to the cloud, make it free and open to everybody in the world. Um, I don't know how deep you want me to go into it. There's many other layers into that. So >>The perspective is zooming out. You're, you're, you're looking at creating a system where the democratizing data means making it freely available so that practitioners or citizens, data, Wrangler, people interested in helping the world could get access to it and then maybe collaborate with people around the world. Is that right? >>Absolutely. So one of the advantages of using the cloud for this kind of, uh, effort is that, you know, cloud is virtually accessible from anywhere where you have, you know, internet or bandwidth, right? So, uh, when, when you put data in the cloud in a centralized place next to compute, it really, uh, removes the, the need for everybody to have their own copy. Right. And to bring it into that, the traditional way is that you bring the data next to your compute. And so we have this multiple copies of data. Some of them are on the petabyte scale. There's obviously the, the carbon footprint associated with the storage, but there's also the complexity that not everybody's able to actually analyze and have that kind of storage. So by putting it in the cloud, now anyone in the world independent of where of their computer capabilities can have access to the same type of data to solve >>The problems. You don't remember doing a report on this in 2018 or 2017. I forget what year it was, but it was around public sector where it was a movement with universities and academia, where they were doing some really deep compute where Amazon had big customers. And there was a movement towards a open commons of data, almost like a national data set like a national park kind of vibe that seems to be getting momentum. In fact, this kind of sounds like what you're doing some similar where it's open to everybody. It's kinda like open source meets data. >>Uh, exactly. And, and the truth is that these data, the majority of it's and we primarily work with what we call authoritative data providers. So think of like NASA Noah, you came me office organizations whose mission is to create the data. So they, their mandate is actually to make the data public. Right. But in practice, that's not really the case. Right. A lot of the data is stored like in servers or tapes or not accessible. Um, so yes, you bring the data to the cloud. And in this model that we use, Amazon never actually touches the data and that's very intentional so that we preserve the integrity of the data. The data provider owns the data in the cloud. We cover all the costs, but they commit to making it public in free to anybody. Um, and obviously the computer is next to it. So that's, uh, evaluated. >>Okay. Anna. So give me some examples of, um, some successes. You've had some of the challenges and opportunities you've overcome, take me through some of the activities because, um, this is really needed, right? And we gotta, sustainability is top line conversation, even here at the conference, re Mars, they're talking about saving climate change with space mm-hmm <affirmative>, which is legitimate. And they're talking about all these new things. So it's only gonna get bigger. Yeah. This data, what are some of the things you're working on right now that you can share? >>Yeah. So what, for me, honestly, the most exciting part of all of this is, is when I see the impact that's creating on customers and the community in general, uh, and those are the stories that really bring it home, the value of opening access to data. And, and I would just say, um, the program actually offers in addition to the data, um, access to free compute, which is very important as well. Right? You put the data in the cloud. It's great. But then if you wanna analyze that, there's the cost and we want to offset that. So we have a, basically an open call for proposals. Anybody can apply and we subsidize that. But so what we see by putting the data in the cloud, making it free and putting the compute accessible is that like we see a lot, for instance, startups, startups jump on it very easily because they're very nimble. They, we basically remove all the cost of investing in the acquisition and storage of the data. The data is connected directly to the source and they don't have to do anything. So they easily build their applications on top of it and workloads and turn it on and off if you know, >>So they don't have to pay for it. >>They have to pay, they basically just pay for the computes whenever they need it. Right. So all the data is covered. So that makes it very visible for, for a lot of startups. And then we see anything like from academia and nonprofits and governments working extensively on the data, what >>Are some of the coolest things you've seen come out of the woodwork in terms of, you know, things that built on top of the, the data, the builders out there are creative, all that heavy, lifting's gone, they're being creative. I'm sure there's been some surprises, um, or obvious verticals that jump healthcare jumps out at me. I'm not sure if FinTech has a lot of data in there, but it's healthcare. I can see, uh, a big air vertical, obviously, you know, um, oil and gas, probably concern. Um, >>So we see it all over the space, honestly. But for instance, one of the things that is very, uh, common for people to use this, uh, Noah data like weather data, because no, basically weather impacts almost anything we do, right? So you have this forecast of data coming into the cloud directly streamed from Noah. And, um, a lot of applications are built on top of that. Like, um, forecasting radiation, for instance, for the solar industry or helping with navigation. But I would say some of the stories I love to mention because are very impactful are when we take data to remote places that traditionally did not have access to any data. Yeah. And for instance, we collaborate with a, with a program, a nonprofit called digital earth Africa where they, this is a basically philanthropically supported program to bring earth observations to the African continents in making it available to communities and governments and things like illegal mining fighting, illegal mining are the forestation, you know, for mangroves to deep forest. Um, it's really amazing what they are doing. And, uh, they are managing >>The low cost nature of it makes it a great use case there >>Yes. Cloud. So it makes it feasible for them to actually do this work. >>Yeah. You mentioned the Noah data making me think of the sale drone. Mm-hmm <affirmative> my favorite, um, use case. Yes. Those sales drones go around many them twice on the queue at reinvent over the years. Yeah. Um, really good innovation. That vibe is here too at the show at Remar this week at the robotics showcases you have startups and growing companies in the ML AI areas. And you have that convergence of not obvious to many, but here, this culture is like, Hey, we have, it's all coming together. Mm-hmm <affirmative>, you know, physical, industrial space is a function of the new O T landscape. Mm-hmm <affirmative>. I mean, there's no edge in space as they say, right. So the it's unlimited edge. So this kind of points to the major trend. It's not stopping this innovation, but sustainability has limits on earth. We have issues. >>We do have issues. And, uh, and I, I think that's one of my hopes is that when we come to the table with the resources and the skills we have and others do as well, we try to remove some of these big barriers, um, that make it things harder for us to move forward as fast as we need to. Right. We don't have time to spend that. Uh, you know, I've been accounted that 80% of the effort to generate new knowledge is spent on finding the data you need and cleaning it. Uh, we, we don't have time for that. Right. So can we remove that UN differentiated, heavy lifting and allow people to start at a different place and generate knowledge and insights faster. >>So that's key, that's the key point having them innovate on top of it, right. What are some things that you wanna see happen over the next year or two, as you look out, um, hopes, dreams, KPIs, performance metrics, what are you, what are you driving to? What's your north star? What are some of those milestones? >>Yeah, so some, we are investing heavily in some areas. Uh, we support, um, you know, we support broadly sustainability, which as, you know, it's like, it's all over, <laugh> the space, but, uh, there's an area that is, uh, becoming more and more critical, which is climate risk. Um, climate risk, you know, for obvious reasons we are experienced, but also there's more regulatory pressures on, uh, business and companies in general to disclose their risks, not only the physical, but also to transition risks. And that's a very, uh, data heavy and compute heavy space. Right. And so we are very focusing in trying to bring the right data and the right services to support that kind of, of activity. >>What kind of break was you looking for? >>Um, so I think, again, it goes back to this concept that there's all that effort that needs to be done equally by so many people that we are all repeating the effort. So I'll put a plug here actually for a project we are supporting, which is called OS climates. Um, I don't know if you're familiar with it, but it's the Linux foundation effort to create an open source platform for climate risk. And so they, they bought the SMP global Airbus, you know, Alliance all these big companies together. And we are one of the funding partners to basically do that basic line work. What are the data that is needed? What are the basic tools let's put it there and do the pre-competitive work. So then you can do the build the, the, the competitive part on top of it. So >>It's kinda like a data clean room. >>It kind of is right. But we need to do those things, right. So >>Are they worried about comp competitive data or is it more anonymized out? How do you, >>It has both actually. So we are primarily contributing, contributing with the open data part, but there's a lot of proprietary data that needs to be behind the whole, the walls. So, yeah, >>You're on the cutting edge of data engineering because, you know, web and ad tech technologies used to be where all that data sharing was done. Mm-hmm <affirmative> for the commercial reasons, you know, the best minds in our industry quoted by a cube alumni are working on how to place ads better. Yeah. Jeff Acker, founder of Cloudera said that on the cube. Okay. And he was like embarrassed, but the best minds are working on how to make ads get more efficient. Right. But that tech is coming to problem solving and you're dealing with data exchange data analysis from different sources, third parties. This is a hard problem. >>Well, it is a hard problem. And I'll, I'll my perspective is that the hardest problem with sustainability is that it goes across all kinds of domains. Right. We traditionally been very comfortable working in our little, you know, swimming lanes yeah. Where we don't need to deal with interoperability and, uh, extracting knowledge. But sustainability, you, you know, you touch the economic side, it touches this social or the environmental, it's all connected. Right. And you cannot just work in the little space and then go sets the impact in the other one. So it's going to force us to work in a different way. Right. It's, uh, big data complex data yeah. From different domains. And we need to somehow make sense of all of it. And there's the potential of AI and ML and things like that that can really help us right. To go beyond the, the modeling approaches we've been done so >>Far. And trust is a huge factor in all this trust. >>Absolutely. And, and just going back to what I said before, that's one of the main reasons why, when we bring data to the cloud, we don't touch it. We wanna make sure that anybody can trust that the data is nowhere data or NASA data, but not Amazon data. >>Yes. Like we always say in the cube, you should own your data plane. Don't give it up. <laugh> well, that's cool. Great. Great. To hear the update. Is there any other projects that you're working on you think might be cool for people that are watching that you wanna plug or point out because this is an area people are, are leaning into yeah. And learning more young, younger talents coming in. Um, I, whether it's university students to people on side hustles want to play with data, >>So we have plenty of data. So we have, uh, we have over a hundred data sets, uh, petabytes and petabytes of data all free. You don't even need an AWS account to access the data and take it out if you want to. Uh, but I, I would say a few things that are exciting that are happening at Mars. One is that we are actually got integrated into ADX. So the AWS that exchange and what that means is that now you can find the open data, free data from a STI in the same searching capability and service as the paid data, right. License data. So hopefully we'll make it easier if I, if you wanna play with data, we have actually something great. We just announced a hackathon this week, uh, in partnership with UNESCO, uh, focus on sustainable development goals, uh, a hundred K in prices and, uh, so much data <laugh> you >>Too years, they get the world is your oyster to go check that out at URL at website, I'll see it's on Amazon. It use our website or a project that can join, or how do people get in touch with you? >>Yeah. So, uh, Amazon SDI, like for Amazon sustainability, that initiative, so Amazon sdi.com and you'll find, um, all the data, a lot of examples of customer stories that are using the data for impactful solutions, um, and much more >>So, and these are, there's a, there's a, a new kind of hustle going out there, seeing entrepreneurs do this. And very successfully, they pick a narrow domain and they, they own it. Something really obscure that could be off the big player's reservation. Mm-hmm <affirmative> and they just become fluent in the data. And it's a big white space for them, right. This market opportunities. And at the minimum you're playing with data. So this is becoming kind of like a long tail domain expertise, data opportunity. Yeah, absolutely. This really hot. So yes. Yeah. Go play around with the data, check it outs for good cause too. And it's free. >>It's all free. >>Almost free. It's not always free. Is it >>Always free? Well, if you, a friend of mine said is only free if your time is worth nothing. <laugh>. Yeah, >>Exactly. Well, Anna, great to have you on the cube. Thanks for sharing the stories. Sustainability is super important. Thanks for coming on. Thank you for the opportunity. Okay. Cube coverage here in Las Vegas. I'm Sean. Furier, we've be back with more day one. After this short break.