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

(upbeat music) >> Hey everyone. Welcome back to "The Cube"'s live coverage of "Women in Data Science 2023". As every year we are here live at Stanford University, profiling some amazing women and men in the fields of data science. I have my co-host for this segment is Hannah Freitag. Hannah is from Stanford's Data Journalism program, really interesting, check it out. We're very pleased to welcome our first guest of the day fresh from the keynote stage, Gayatree Ganu, the VP of Data Science at Meta. Gayatree, It's great to have you on the program. >> Likewise, Thank you for having me. >> So you have a PhD in Computer Science. You shared some really cool stuff. Everyone knows Facebook, everyone uses it. I think my mom might be one of the biggest users (Gayatree laughs) and she's probably watching right now. People don't realize there's so much data behind that and data that drives decisions that we engage with. But talk to me a little bit about you first, PhD in Computer Science, were you always, were you like a STEM kid? Little Gayatree, little STEM, >> Yeah, I was a STEM kid. I grew up in Mumbai, India. My parents are actually pharmacists, so they were not like math or stats or anything like that, but I was always a STEM kid. I don't know, I think it, I think I was in sixth grade when we got our first personal computer and I obviously used it as a Pacman playing machine. >> Oh, that's okay. (all laugh) >> But I was so good at, and I, I honestly believe I think being good at games kind of got me more familiar and comfortable with computers. Yeah. I think I always liked computers, I, yeah. >> And so now you lead, I'm looking at my notes here, the Engagement Ecosystem and Monetization Data Science teams at Facebook, Meta. Talk about those, what are the missions of those teams and how does it impact the everyday user? >> Yeah, so the engagement is basically users coming back to our platform more, there's, no better way for users to tell us that they are finding value on the things that we are doing on Facebook, Instagram, WhatsApp, all the other products than coming back to our platform more. So the Engagement Ecosystem team is looking at trends, looking at where there are needs, looking at how users are changing their behaviors, and you know, helping build strategy for the long term, using that data knowledge. Monetization is very different. You know, obviously the top, top apex goal is have a sustainable business so that we can continue building products for our users. And so, but you know, I said this in my keynote today, it's not about making money, our mission statement is not, you know, maximize as much money as you can make. It's about building a meaningful connection between businesses, customers, users, and, you know especially in these last two or three funky, post-pandemic years, it's been such a big, an important thing to do for small businesses all over all, all around the world for users to find like goods and services and products that they care about and that they can connect to. So, you know, there is truly an connection between my engagement world and the monetization world. And you know, it's not very clear always till you go in to, like, you peel the layers. Everything we do in the ads world is also always first with users as our, you know, guiding principle. >> Yeah, you mentioned how you supported especially small businesses also during the pandemic. You touched a bit upon it in the keynote speech. Can you tell our audience what were like special or certain specific programs you implemented to support especially small businesses during these times? >> Yeah, so there are 200 million businesses on our platform. A lot of them small businesses, 10 million of them run ads. So there is a large number of like businesses on our platform who, you know use the power of social media to connect to the customers that matter to them, to like you, you know use the free products that we built. In the post-pandemic years, we built a lot of stuff very quickly when Covid first hit for business to get the word out, right? Like, they had to announce when special shopping hours existed for at-risk populations, or when certain goods and services were available versus not. We had grants, there's $100 million grant that we gave out to small businesses. Users could show sort of, you know show their support with a bunch of campaigns that we ran, and of course we continue running ads. Our ads are very effective, I guess, and, you know getting a very reliable connection with from the customer to the business. And so, you know, we've run all these studies. We support, I talked about two examples today. One of them is the largest black-owned, woman black-owned wine company, and how they needed to move to an online program and, you know, we gave them a grant, and supported them through their ads campaign and, you know, they saw 60% lift in purchases, or something like that. So, a lot of good stories, small stories, you know, on a scale of 200 million, that really sort of made me feel proud about the work we do. And you know, now more than ever before, I think people can connect so directly with businesses. You can WhatsApp them, I come from India, every business is on WhatsApp. And you can, you know, WhatsApp them, you can send them Facebook messages, and you can build this like direct connection with things that matter to you. >> We have this expectation that we can be connected anywhere. I was just at Mobile World Congress for MWC last week, where, obviously talking about connectivity. We want to be able to do any transaction, whether it's post on Facebook or call an Uber, or watch on Netflix if you're on the road, we expect that we're going to be connected. >> Yeah. >> And what we, I think a lot of us don't realize I mean, those of us in tech do, but how much data science is a facilitator of all of those interactions. >> Yeah! >> As we, Gayatree, as we talk about, like, any business, whether it is the black women-owned wine business, >> Yeah. >> great business, or a a grocer or a car dealer, everybody has to become data-driven. >> Yes. >> Because the consumer has the expectation. >> Yes. >> Talk about data science as a facilitator of just pretty much everything we are doing and conducting in our daily lives. >> Yeah, I think that's a great question. I think data science as a field wasn't really defined like maybe 15 years ago, right? So this is all in our lifetimes that we are seeing this. Even in data science today, People come from so many different backgrounds and bring their own expertise here. And I think we, you know, this conference, all of us get to define what that means and how we can bring data to do good in the world. Everything you do, as you said, there is a lot of data. Facebook has a lot of data, Meta has a lot of data, and how do we responsibly use this data? How do we use this data to make sure that we're, you know representing all diversity? You know, minorities? Like machine learning algorithms don't do well with small data, they do well with big data, but the small data matters. And how do you like, you know, bring that into algorithms? Yeah, so everything we do at Meta is very, very data-driven. I feel proud about that, to be honest, because while data gets a bad rap sometimes, having no data and making decisions in the blind is just the absolute worst thing you can do. And so, you know, we, the job as a data scientist at Facebook is to make sure that we use this data, use this responsibly, make sure that we are representing every aspect of the, you know, 3 billion users who come to our platform. Yeah, data serves all the products that we build here. >> The responsibility factor is, is huge. You know, we can't talk about AI without talking about ethics. One of the things that I was talking with Hannah and our other co-host, Tracy, about during our opening is something I just learned over the weekend. And that is that the CTO of ChatGPT is a woman. (Gayatree laughs) I didn't know that. And I thought, why isn't she getting more awareness? There's a lot of conversations with their CEO. >> Yeah. >> Everyone's using it, playing around with it. I actually asked it yesterday, "What's hot in Data Science?" (all laugh) I was like, should I have asked that to let itself in, what's hot? (Gayatree laughs) But it, I thought that was phenomenal, and we need to be talking about this more. >> Yeah. >> This is something that they're likening to the launch of the iPhone, which has transformed our lives. >> I know, it is. >> ChatGPT, and its chief technologist is a female, how great is that? >> And I don't know whether you, I don't know the stats around this, but I think CTO is even less, it's even more rare to have a woman there, like you have women CEOs because I mean, we are building upon years and years of women not choosing technical fields and not choosing STEM, and it's going to take some time, but yeah, yeah, she's a woman. Isn't it amazing? It's wonderful. >> Yes, there was a great, there's a great "Fast Company" article on her that I was looking at yesterday and I just thought, we need to do what we can to help spread, Mira Murati is her name, because what she's doing is, one of the biggest technological breakthroughs we may ever see in our lifetime. It gives me goosebumps just thinking about it. (Gayatree laughs) I also wanted to share some stats, oh, sorry, go ahead, Hannah. >> Yeah, I was going to follow up on the thing that you mentioned that we had many years with like not enough women choosing a career path in STEM and that we have to overcome this trend. What are some, like what is some advice you have like as the Vice-President Data Science? Like what can we do to make this feel more, you know, approachable and >> Yeah. >> accessible for women? >> Yeah, I, there's so much that we have done already and you know, want to continue, keep doing. Of course conferences like these were, you know and I think there are high school students here there are students from my Alma Mater's undergrad year. It's amazing to like get all these women together to get them to see what success could look like. >> Yeah. >> What being a woman leader in this space could look like. So that's, you know, that's one, at Meta I lead recruiting at Meta and we've done a bunch to sort of open up the thinking around data science and technical jobs for women. Simple things like what you write in your job description. I don't know whether you know this, or this is a story you've heard before, when you see, when you have a job description and there are like 10 things that you need to, you know be good at to apply to this job, a woman sees those 10 and says, okay, I don't meet the qualifications of one of them and she doesn't apply. And a man sees one that he meets the qualifications to and he applies. And so, you know, there's small things you can do, and just how you write your job description, what goals you set for diversity and inclusion for your own organization. We have goals, Facebook's always been pretty up there in like, you know, speaking out for diversity and Sheryl Sandberg has been our Chief Business Officer for a very long time and she's been, like, amazing at like pushing from more women. So yeah, every step of the way, I think, we made a lot of progress, to be honest. I do think women choose STEM fields a lot more than they did. When I did my Computer Science I was often one of one or two women in the Computer Science class. It takes some time to, for it to percolate all the way to like having more CTOs and CEOs, >> Yeah. >> but it's going to happen in our lifetime, and you know, three of us know this, women are going to rule the world, and it (laughs) >> Drop the mic, girl! >> And it's going to happen in our lifetime, so I'm excited about it. >> And we have responsibility in helping make that happen. You know, I'm curious, you were in STEM, you talked about Computer Science, being one of the only females. One of the things that the nadb.org data from 2022 showed, some good numbers, the number of women in technical roles is now 27.6%, I believe, so up from 25, it's up in '22, which is good, more hiring of women. >> Yeah. >> One of the biggest challenges is attrition. What keeps you motivated? >> Yeah. >> To stay what, where you are doing what you're doing, managing a family and helping to drive these experiences at Facebook that we all expect are just going to happen? >> Yeah, two things come to mind. It does take a village. You do need people around you. You know, I'm grateful for my husband. You talked about managing a family, I did the very Indian thing and my parents live with us, and they help take care of the kids. >> Right! (laughs) >> (laughs) My kids are young, six and four, and I definitely needed help over the last few years. It takes mentors, it takes other people that you look up to, who've gone through all of those same challenges and can, you know, advise you to sort of continue working in the field. I remember when my kid was born when he was six months old, I was considering quitting. And my husband's like, to be a good role model for your children, you need to continue working. Like, just being a mother is not enough. And so, you know, so that's one. You know, the village that you build around you your supporters, your mentors who keep encouraging you. Sheryl Sandberg said this to me in my second month at Facebook. She said that women drop out of technical fields, they become managers, they become sort of administrative more, in their nature of their work, and her advice was, "Don't do that, Don't stop the technical". And I think that's the other thing I'd say to a lot of women. Technical stuff is hard, but you know, keeping up with that and keeping sort of on top of it actually does help you in the long run. And it's definitely helped me in my career at Facebook. >> I think one of the things, and Hannah and I and Tracy talked about this in the open, and I think you'll agree with us, is the whole saying of you can't be what you can't see, and I like to way, "Well, you can be what you can see". That visibility, the great thing that WiDS did, of having you on the stage as a speaker this morning so people can understand, everyone, like I said, everyone knows Meta, >> Yeah. >> everyone uses Facebook. And so it's important to bring that connection, >> Yeah. >> of how data is driving the experiences, the fact that it's User First, but we need to be able to see women in positions, >> Yes. >> like you, especially with Sheryl stepping down moving on to something else, or people that are like YouTube influencers, that have no idea that the head of YouTube for a very long time, Susan Wojcicki is a woman. >> (laughs) Yes. Who pioneered streaming, and I mean how often do you are you on YouTube every day? >> Yep, every day. >> But we have to be able to see and and raise the profile of these women and learn from them and be inspired, >> Absolutely. >> to keep going and going. I like what I do, I'm making a difference here. >> Yeah, yeah, absolutely. >> And I can be the, the sponsor or the mentor for somebody down the road. >> Absolutely. >> Yeah, and then referring back to what we talked in the beginning, show that data science is so diverse and it doesn't mean if you're like in IT, you're like sitting in your dark room, >> Right. (laughs) >> coding all day, but you know, >> (laughs) Right! >> to show the different facets of this job and >> Right! >> make this appealing to women, >> Yeah. for sure. >> And I said this in my keynote too, you know, one of the things that helped me most is complimenting the data and the techniques and the algorithms with how you work with people, and you know, empathy and alignment building and leadership, strategic thinking. And I think honestly, I think women do a lot of this stuff really well. We know how to work with people and so, you know, I've seen this at Meta for sure, like, you know, all of these skills soft skills, as we call them, go a long way, and like, you know, doing the right things and having a lasting impact. And like I said, women are going to rule the world, you know, in our lifetimes. (laughs) >> Oh, I can't, I can't wait to see that happen. There's some interesting female candidates that are already throwing their hats in the ring for the next presidential election. >> Yes. >> So we'll have to see where that goes. But some of the things that are so interesting to me, here we are in California and Palo Alto, technically Stanford is its own zip code, I believe. And we're in California, we're freaking out because we've gotten so much rain, it's absolutely unprecedented. We need it, we had a massive drought, an extreme drought, technically, for many years. I've got friends that live up in Tahoe, I've been getting pictures this morning of windows that are >> (laughs) that are covered? >> Yes, actually, yes. (Gayatree laughs) That, where windows like second-story windows are covered in snow. >> Yeah. >> Climate change. >> Climate change. >> There's so much that data science is doing to power and power our understanding of climate change whether it's that, or police violence. >> Yeah. (all talk together) >> We had talk today on that it was amazing. >> Yes. So I want more people to know what data science is really facilitating, that impacts all of us, whether you're in a technical role or not. >> And data wins arguments. >> Yes, I love that! >> I said this is my slide today, like, you know, there's always going to be doubters and naysayers and I mean, but there's hard evidence, there's hard data like, yeah. In all of these fields, I mean the data that climate change, the data science that we have done in the environmental and climate change areas and medical, and you know, medicine professions just so much, so much more opportunity, and like, how much we can learn more about the world. >> Yeah. >> Yeah, it's a pretty exciting time to be a data scientist. >> I feel like, we're just scratching the surface. >> Yeah. >> With the potential and the global impact that we can make with data science. Gayatree, it's been so great having you on theCUBE, thank you. >> Right, >> Thank you so much, Gayatree. >> So much, I love, >> Thank you. >> I'm going to take Data WiD's arguments into my personal life. (Gayatree laughs) I was actually just, just a quick anecdote, funny story. I was listening to the radio this morning and there was a commercial from an insurance company and I guess the joke is, it's an argument between two spouses, and the the voiceover comes in and says, "Let's watch a replay". I'm like, if only they, then they got the data that helped the woman win the argument. (laughs) >> (laughs) I will warn you it doesn't always help with arguments I have with my husband. (laughs) >> Okay, I'm going to keep it in the middle of my mind. >> Yes! >> Gayatree, thank you so much. >> Thank you so much, >> for sharing, >> Thank you both for the opportunity. >> And being a great female that we can look up to, we really appreciate your insights >> Oh, likewise. >> and your time. >> Thank you. >> All right, for our guest, for Hannah Freitag, I'm Lisa Martin, live at Stanford University covering "Women in Data Science '23". Stick around, our next guest joins us in just a minute. (upbeat music) I have been in the software and technology industry for over 12 years now, so I've had the opportunity as a marketer to really understand and interact with customers across the entire buyer's journey. Hi, I'm Lisa Martin and I'm a host of theCUBE. (upbeat music) Being a host on theCUBE has been a dream of mine for the last few years. I had the opportunity to meet Jeff and Dave and John at EMC World a few years ago and got the courage up to say, "Hey, I'm really interested in this. I love talking with customers, gimme a shot, let me come into the studio and do an interview and see if we can work together". I think where I really impact theCUBE is being a female in technology. We interview a lot of females in tech, we do a lot of women in technology events and one of the things I.

(intro music) >> Narrator: "theCUBE's" live coverage is made possible by funding from Dell Technologies, creating technologies that drive human progress. (gentle music) >> Hey everyone, welcome back to "theCUBE," the leader in live and emerging tech coverage. As you well know, we are live at MWC23 in Barcelona, Spain. Lisa Martin with Dave Nicholson. Day three of our coverage, as you know, 'cause you've been watching the first two days. A lot of conversations about ecosystem, a lot about disruption in the telco industry. We're going to be talking about Open RAN. You've heard some of those great conversations, the complexities, the opportunities. Two guests join Dave and me. Abdullah Abuzaid, Technical Product Manager at Dell, and Gil Hellmann, VP Telecom Solutions Engineering and Architecture at Wind River. Welcome to the program guys. >> Thank you. >> Nice to be here. >> Let's talk a little bit about Dell and Wind River. We'll each ask you both the same question, and talk to us about how you're working together to really address the complexities that organizations are having when they're considering moving from a closed environment to an open environment. >> Definitely. Thank you for hosting us. By end of the day, the relationship between Dell and Wind River is not a new. We've been collaborating in the open ecosystem for long a time enough. And that's one of the, our partnership is a result of this collaboration where we've been trying to make more efficient operation in the ecosystem. The open environment ecosystem, it has the plus and a concern. The plus of simplicity, choice of multiple vendors, and then the concern of complexity managing these vendors. Especially if we look at examples for the Open RAN ecosystem, dealing with multiple vendors, trying to align them. It bring a lot of operational complexity and TCO challenges for our customers, from this outcome where we build our partnership with Wind River in order to help our customer to simplify, or run deployment, operation, and lifecycle management and sustain it. >> And who are the customers, by the way? >> Mainly the CSP customers who are targeting Open RAN and Virtual RAN deployments. That digital transformation moving towards unified cloud environment, or a seamless cloud experience from Core to RAN, these are the customers we are working with them. >> You'll give us your perspective, your thoughts on the partnership, and the capabilities that you're enabling, the CSPs with that. >> Sure. It's actually started last year here in Barcelona, when we set together, and started to look at the, you know, the industry, the adoption of Open RAN, and the challenges. And Open RAN brings a lot of possibilities and benefit, but it does bring a lot of challenges of reintegrating what you desegregate. In the past, you purchase everything from one vendor, they provide the whole solution. Now you open it, you have different layers. So if you're looking at Open RAN, you have, I like to look at it as three major layers, the management, application, and the infrastructure. And we're starting to look what are the challenges. And the challenges of integration, of complexity, knowledge that operator has with cloud infrastructure. And this is where we basically, Dell and Winder River set together and say, "How can we ease this? "How we can make it simpler?" And we decided to partner and bring a joint infrastructure solution to market, that's not only integrated at a lab at the factory level, but it basically comes with complete lifecycle management from the day zero deployment, through the day two operation, everything done through location, through Dell supported, working out of the box. So basically taking this whole infrastructure layer integration pain out, de-risking everything, and then continuing from there to work with the ecosystem vendor to reintegrate, validate the application, on top of this infrastructure. >> So what is the, what is the Wind River secret sauce in this, in this mix, for folks who aren't familiar with what Wind River does? >> Yes, absolutely. So Wind River, for many, many don't know, we're in business since 1981. So over 40 years. We specialize high performance, high reliability infrastructure. We touch every aspect of your day and your life. From the airplane that you fly, the cars, the medical equipment. And if we go into the telco, most of the telco equipment that it's not virtualized, not throughout the fight today, using our operating system. So from all the leading equipment manufacturers and even the smaller one. And as the world started to go into desegregation in cloud, Wind River started to look at this and say, "Okay, everything is evolving. Instead of a device that included the application, the hardware, everything fused together, it's now being decomposed. So instead of providing the operating environment to develop and deploy the application to the device manufacturer, now we're providing it basically to build the cloud. So to oversimplify, I call it a cloud OS, okay. It's a lot more than OS, it's an operating environment. But we took basically our experience, the same experience that, you know, we used in all those years with the telco equipment manufacturer, and brought it into the cloud. So we're basically providing solution to build an on-premises scalable cloud from the core all the way to the far edge, that doesn't compromise reliability, doesn't compromise performance, and address all the telco needs. >> So I, Abdullah, maybe you can a answer this. >> Yeah. >> What is the, what does the go-to-market motion look like, considering that you have two separate companies that can address customers directly, separately. What does that, what does that look like if you're approaching a possible customer who is, who's knocking on the door? >> How does that work? >> Exactly. And this effort is a Dell turnkey sales service offering, or solution offering to our customers. Where Dell, in collaboration with Wind River, we proactively validate, integrate, and productize the solution as engineered system, knock door on our customer who are trying to transform to Open RAN or open ecosystem. We can help you to go through that seamless experience, by pre-validating with whatever workload you want to introduce, enable zero touch provisioning, and during the day one deployment, and ensure we have sustainable lifecycle management throughout the lifecycle of the product in, in operate, in operational network, as well as having a unified single call of support from Dell side. >> Okay. So I was just going to ask you about support. So I'm a CSP, I have the solution, I go to Dell for support. >> Exactly. >> Okay. So start with Dell, and level one, level two. And if there are complex issues related to the cloud core itself, then Wind River will be on our back supporting us. >> Talk a little bit about a cust, a CSP example that is, is using the technology, and some of the outcomes that they're able to achieve. I'd love to get both of your perspectives on that. >> Vodafone is a great example. We're here in Barcelona. Vodafone is the first ora network in Europe, and it's using our joint solution. >> What are some of the, the outcomes that it's helping them to achieve? >> Faster time to market. As you see, they already started to deploy the ORAN in commercial network, and very successful in the trials that they did last year. We're also not stopping there. We're evolving, working with them together to improve like stuff around energy efficiency. So continue to optimize. So the outcome, it's just simplifying it, and you know, ready to go. Using experience that we have, Wind River is powering the first basically virtualized RAN 5G network in the world. This is with Verizon. We're at the very large scale. We started this deployment in late '20 and '19, the first site. And then through 2020 to 2022, we basically rolled in large scale. We have a lot of experience learning from it, which what we brought into the table when we partnered with Dell. A lot of experience from how you deploy at scale. Many sites from a central location, updates, upgrade. So the whole day two operation, and this is coming to bearing the solution that basically Vodafone is deploying now, and which allowed them... If I, if I look at my engagement with Verizon, started years before we started. And it took quite some time until we got stuff running. And if you look at the Vodafone time schedule, was significantly compressed compared to the Verizon first deployment. And I can tell you that there are other service providers that were announced here by KDI, for example. It's another one moving even faster. So it's accelerating the whole movement to Ora. >> We've heard a lot of acceleration talk this week. I'd love to get your perspective, Abdullah, talking about, you know, you, you just mentioned two huge names in Telco, Vodafone and Verizon. >> Yep. >> Talk a little bit about Dell's commitment to helping telecommunications companies really advance, accelerate innovation so that all of us on the other end have this thing that just works wherever we are 24 by 7. >> Not exactly. And this, we go back to the challenges in Open ecosystem. Managing multiple vendors at the same time, is a challenge for our customers. And that's why we are trying to simplify their life cycle by have, by being a trusted partner, working with our customer through all the journey. We started with Dish in their 5G deployment. Also with Vodafone. We're finding the right partners working with them proactively before getting into, in front of the customer to, we've done our homework, we are ready to simplify the process for you to go for it. If you look at the RAN in particular, we are talking with the 5g. We have ran the simplification, but they still have on the other side, limited resources and skillset can support it. So, bringing a pro, ahead of time engineer system, with a zero touch of provisioning enablement, and sustainable life cycle management, it lead to the faster time to market deployment, TCO savings, improved margins for our customers, and faster business revenue for their end users. >> Solid outcomes. >> And, and what you just just described, justifies the pain associated with disaggregating and reintegrating, which is the way that Gill referenced it, which I think is great because you're not, you're not, you're not re-aggregating, (laughs) you're reintegrating, and you're creating something that's better. >> Exactly. >> Moving forward. Otherwise, why would you do it? >> Exactly. And if you look at it, the player in the ecosystem, you have the vendors, you have the service integrators, you have the automation enablers, but kind of they are talking in silos. Everyone, this is my raci, this is what I'm responsible for. I, I'm not able, I don't want to get into something else while we are going the extra mile by working proactively in that ecosystem to... Let's bring brains together, find out what's one plus one can bring three for our customers, so we make it end-to-end seamless experience, not only on the technical part, but also on the business aspect side of it. >> So, so the partnership, it's about reducing the pen. I will say eliminating it. So this is the, the core of it. And you mentioned getting better coverage for your phone. I do want to point out that the phones are great, but if you look at the premises of a 5G network, it's to enable a lot more things that will touch your life that are beyond the consumer and the phone. Stuff like connected vehicles. So for example, something as simple as collision avoidance, the ability for the car that goes in front of you to be able to see what's happening and broadcast this information to the car behind that have no ability to see it. And basically affect our life in a way that makes our driving safer. And for this, you need a ultra low, reliable low latency communication. You need a 5G network. >> I'm glad you brought that up, because you know, we think about, "Well we just have to be connected all the time." But those are some of the emerging technologies that are going to be potentially lifesaving, and, and really life transforming that you guys are helping to enable. So, really great stuff there, but so much promise coming down the road. What's next for Dell and Wind River? And, and when you're in conversations with prospective CSP's, what is the superpower that you deliver together? I'd love to get both of your perspectives. >> So, if you look at it, number one, customers look at it, last savings and their day-to-day operation. In 5G nature, we are talking the introduction of ORAN. This is still picking up. But there is a mutualization and densification of ORAN. And this is where we're talking on monetizing my deployment. Then the third phase, we're talking sustainability and advanced service introduction. Where I want to move not only ORAN, I want to bring the edge at the same side, I want to define the advanced use cases of edge, where it enables me with this pre-work being done to deliver more services and better SLA services. By end of the day, 5G as a girl mentioned earlier, is not about a good better phone coverage, or a better speed robot, but what customized SLA's I can deliver. So it enables me to deliver different business streams to my end users. >> Yeah. >> So yeah. I will say there are two pens. One, it's the technology side. So for an example, energy efficiency. It's a very big pin point. And sustainability. So we work a lot around this, and basically to advance this. So if you look at the integrated solution today, it's very highly optimized for resource consumption. But to be able to more dynamically be able to change your power profile without compromising the SLA. So this is one side. The other side, it's about all those applications that will come to the 5G network to make our life better. It's about integrating, validating, certifying those applications. So, it's not just easy to deploy an ORAN network, but it's easy to deploy those applications. >> I'd be curious to get your perspective on the question of ROI in this, in this space. Specifically with the sort of the macro headwinds (clears throat) the economies of the world are facing right now, if you accept that. What does the ROI timeline look like when you're talking about moving towards ORAN, adopting VRAN, an amazing, you know, a plethora of new services that can be delivered, but will these operators have the appetite to take that, make that investment and take on that risk based upon the ROI time horizon? Any thoughts on that? >> Yeah. So if you look at the early days or ORAN introduction in particular, most of the entrepreneurs of ORAN and Virtual RAN ran into the challenges of not only the complexity of open ecosystem, but the integration, is like the redos of the work. And that's where we are trying to address it via pre-engineered system or building an engineer system proactively before getting it to the customers. Per our result or outcomes we get, we are talking about 30 to 50% savings on the optics. We are talking 110 ROI for our customers, simply because we are reducing the redos, the time spent to discover and explore. Because we've done that rework ahead of time, we found the optimization issues. Just for example, any customer can buy the same components from any multiple vendors, but how I can bring them together and give, deliver for me the best performance that I can fully utilize, that's, that's where it brings the value for our customer, and accelerate the deployment and the operation of the network. >> Do you have anything to add before we close in the next 30 seconds? >> Yeah. Yeah. (laughs) >> Absolutely. I would say, we start to see the data coming from two years of operation at scale. And the data supports performance. It's the same or better than traditional system. And the cost of operation, it's as good or better than traditional. Unfortunately, I can't provide more specific data. But the point is, when something is unknown in the beginning, of course you're more afraid, you take more conservative approach. Now the data starts to flow. And from here, the intention needs to go even better. So more efficiency, so cost less than traditional system, both to operate as well as to build up. But it's definitely the data that we have today says, the, ORAN system is at part, at the minimum. >> So, definite ROI there. Guys, thank you so much for joining Dave and me talking about how you're helping organizations not just address the complexities of moving from close to open, but to your point, eliminating them. We appreciate your time and, and your insights. >> Thank you. >> All right. For our guests and for Dave Nicholson, I'm Lisa Martin. You're watching "theCUBE," the leader in live and emerging tech coverage. Live from MWC23. We'll be back after a short break. (outro music)

(gentle music) >> Announcer: "theCube's" live coverage is made possible by funding from Dell Technologies, creating technologies that drive human progress. (upbeat music) (logo whooshing) >> Hey, everyone, welcome back to "theCube's" coverage of day one, MWC23 live from Barcelona, Lisa Martin here with Dave Vellante. Dave, we've got some great conversations so far This is the biggest, most packed show I've been to in years. About 80,000 people here so far. >> Yeah, down from its peak of 108, but still pretty good. You know, a lot of folks from China come to this show, but with the COVID situation in China, that's impacted the attendance, but still quite amazing. >> Amazing for sure. We're going to be talking about trends and mobility, and all sorts of great things. We have a couple of guests joining us for the first time on "theCUBE." Please welcome Dr. Srinivas Mukkamala or Sri, chief product officer at Ivanti. And Dave Shepherd, VP Ivanti. Guys, welcome to "theCUBE." Great to have you here. >> Thank you. >> So, day one of the conference, Sri, we'll go to you first. Talk about some of the trends that you're seeing in mobility. Obviously, the conference renamed from Mobile World Congress to MWC mobility being part of it, but what are some of the big trends? >> It's interesting, right? I mean, I was catching up with Dave. The first thing is from the keynotes, it took 45 minutes to talk about security. I mean, it's quite interesting when you look at the shore floor. We're talking about Edge, we're talking about 5G, the whole evolution. And there's also the concept of are we going into the Cloud? Are we coming back from the Cloud, back to the Edge? They're really two different things. Edge is all decentralized while you recompute. And one thing I observed here is they're talking about near real-time reality. When you look at automobiles, when you look at medical, when you look at robotics, you can't have things processed in the Cloud. It'll be too late. Because you got to make millisecond-based stations. That's a big trend for me. When I look at staff... Okay, the compute it takes to process in the Cloud versus what needs to happen on-prem, on device, is going to revolutionize the way we think about mobility. >> Revolutionize. David, what are some of the things that you're saying? Do you concur? >> Yeah, 100%. I mean, look, just reading some of the press recently, they're predicting 22 billion IoT devices by 2024. Everything Sri just talked about there. It's growing exponentially. You know, problems we have today are a snapshot. We're probably in the slowest place we are today. Everything's just going to get faster and faster and faster. So it's a, yeah, 100% concur with that. >> You know, Sri, on your point, so Jose Maria Alvarez, the CEO of Telefonica, said there are three pillars of the future of telco, low latency, programmable networks, and Cloud and Edge. So, as to your point, Cloud and low latency haven't gone hand in hand. But the Cloud guys are saying, "All right, we're going to bring the Cloud to the Edge." That's sort of an interesting dynamic. We're going to bypass them. We heard somebody, another speaker say, "You know, Cloud can't do it alone." You know? (chuckles) And so, it's like these worlds need each other in a way, don't they? >> Definitely right. So that's a fantastic way to look at it. The Cloud guys can say, "We're going to come closer to where the computer is." And if you really take a look at it with data localization, where are we going to put the Cloud in, right? I mean, so the data sovereignty becomes a very interesting thing. The localization becomes a very interesting thing. And when it comes to security, it gets completely different. I mean, we talked about moving everything to a centralized compute, really have massive processing, and give you the addition back wherever you are. Whereas when you're localized, I have to process everything within the local environment. So there's already a conflict right there. How are we going to address that? >> Yeah. So another statement, I think, it was the CEO of Ericsson, he was kind of talking about how the OTT guys have heard, "We can't let that happen again. And we're going to find new ways to charge for the network." Basically, he's talking about monetizing the API access. But I'm interested in what you're hearing from customers, right? 'Cause our mindset is, what value you're going to give to customers that they're going to pay for, versus, "I got this data I'm going to charge developers for." But what are you hearing from customers? >> It's amazing, Dave, the way you're looking at it, right? So if we take a look at what we were used to perpetual, and we said we're going to move to a subscription, right? I mean, everybody talks about subscription economy. Telcos on the other hand, had subscription economy for a long time, right? They were always based on usage, right? It's a usage economy. But today, we are basically realizing on compute. We haven't even started charging for compute. If you go to AWS, go to Azure, go to GCP, they still don't quite charge you for actual compute, right? It's kind of, they're still leaning on it. So think about API-based, we're going to break the bank. What people don't realize is, we do millions of API calls for any high transaction environment. A consumer can't afford that. What people don't realize is... I don't know how you're going to monetize. Even if you charge a cent a call, that is still going to be hundreds and thousands of dollars a day. And that's where, if you look at what you call low-code no-code motion? You see a plethora of companies being built on that. They're saying, "Hey, you don't have to write code. I'll give you authentication as a service. What that means is, Every single time you call my API to authenticate a user, I'm going to charge you." So just imagine how many times we authenticate on a single day. You're talking a few dozen times. And if I have to pay every single time I authenticate... >> Real friction in the marketplace, David. >> Yeah, and I tell you what. It's a big topic, right? And it's a topic that we haven't had to deal with at the Edge before, and we hear it probably daily really, complexity. The complexity's growing all the time. That means that we need to start to get insight, visibility. You know? I think a part of... Something that came out of the EU actually this week, stated, you know, there's a cyber attack every 11 seconds. That's fast, right? 2016, that was 40 seconds. So actually that speed I talked about earlier, everything Sri says that's coming down to the Edge, we want to embrace the Edge and that is the way we're going to move. But customers are mindful of the complexity that's involved in that. And that, you know, lens thought to how are we going to deal with those complexities. >> I was just going to ask you, how are you planning to deal with those complexities? You mentioned one ransomware attack every 11 seconds. That's down considerably from just a few years ago. Ransomware is a household word. It's no longer, "Are we going to get attacked?" It's when, it's to what extent, it's how much. So how is Ivanti helping customers deal with some of the complexities, and the changes in the security landscape? >> Yeah. Shall I start on that one first? Yeah, look, we want to give all our customers and perspective customers full visibility of their environment. You know, devices that are attached to the environment. Where are they? What are they doing? How often are we going to look for those devices? Not only when we find those devices. What applications are they running? Are those applications secure? How are we going to manage those applications moving forward? And overall, wrapping it round, what kind of service are we going to do? What processes are we going to put in place? To Sri's point, the low-code no-code angle. How do we build processes that protect our organization? But probably a point where I'll pass to Sri in a moment is how do we add a level of automation to that? How do we add a level of intelligence that doesn't always require a human to be fixing or remediating a problem? >> To Sri, you mentioned... You're right, the keynote, it took 45 minutes before it even mentioned security. And I suppose it's because they've historically, had this hardened stack. Everything's controlled and it's a safe environment. And now that's changing. So what would you add? >> You know, great point, right? If you look at telcos, they're used to a perimeter-based network. >> Yep. >> I mean, that's what we are. Boxed, we knew our perimeter. Today, our perimeter is extended to our home, everywhere work, right? >> Yeah- >> We don't have a definition of a perimeter. Your browser is the new perimeter. And a good example, segueing to that, what we have seen is horizontal-based security. What we haven't seen is verticalization, especially in mobile. We haven't seen vertical mobile security solutions, right? Yes, you hear a little bit about automobile, you hear a little bit about healthcare, but what we haven't seen is, what about food sector? What about the frontline in food? What about supply chain? What security are we really doing? And I'll give you a simple example. You brought up ransomware. Last night, Dole was attacked with ransomware. We have seen the beef producer colonial pipeline. Now, if we have seen agritech being hit, what does it mean? We are starting to hit humanity. If you can't really put food on the table, you're starting to really disrupt the supply chain, right? In a massive way. So you got to start thinking about that. Why is Dole related to mobility? Think about that. They don't carry service and computers. What they carry is mobile devices. that's where the supply chain works. And then that's where you have to start thinking about it. And the evolution of ransomware, rather than a single-trick pony, you see them using multiple vulnerabilities. And Pegasus was the best example. Spyware across all politicians, right? And CEOs. It is six or seven vulnerabilities put together that actually was constructed to do an attack. >> Yeah. How does AI kind of change this? Where does it fit in? The attackers are going to have AI, but we could use AI to defend. But attackers are always ahead, right? (chuckles) So what's your... Do you have a point of view on that? 'Cause everybody's crazy about ChatGPT, right? The banks have all banned it. Certain universities in the United States have banned it. Another one's forcing his students to learn how to use ChatGPT to prompt it. It's all over the place. You have a point of view on this? >> So definitely, Dave, it's a great point. First, we all have to have our own generative AI. I mean, I look at it as your digital assistant, right? So when you had calculators, you can't function without a calculator today. It's not harmful. It's not going to take you away from doing multiplication, right? So we'll still teach arithmetic in school. You'll still use your calculator. So to me, AI will become an integral part. That's one beautiful thing I've seen on the short floor. Every little thing there is a AI-based solution I've seen, right? So ChatGPT is well played from multiple perspective. I would rather up level it and say, generated AI is the way to go. So there are three things. There is human intense triaging, where humans keep doing easy work, minimal work. You can use ML and AI to do that. There is human designing that you need to do. That's when you need to use AI. >> But, I would say this, in the Enterprise, that the quality of the AI has to be better than what we've seen so far out of ChatGPT, even though I love ChatGPT, it's amazing. But what we've seen from being... It's got to be... Is it true that... Don't you think it has to be cleaner, more accurate? It can't make up stuff. If I'm going to be automating my network with AI. >> I'll answer that question. It comes down to three fundamentals. The reason ChatGPT is giving addresses, it's not trained on the latest data. So for any AI and ML method, you got to look at three things. It's your data, it's your domain expertise, who is training it, and your data model. In ChatGPT, it's older data, it's biased to the people that trained it, right? >> Mm-hmm. >> And then, the data model is it's going to spit out what it's trained on. That's a precursor of any GPT, right? It's pre-trained transformation. >> So if we narrow that, right? Train it better for the specific use case, that AI has huge potential. >> You flip that to what the Enterprise customers talk about to us is, insight is invaluable. >> Right. >> But then too much insight too quickly all the time means we go remediation crazy. So we haven't got enough humans to be fixing all the problems. Sri's point with the ChatGPT data, some of that data we are looking at there could be old. So we're trying to triage something that may still be an issue, but it might have been superseded by something else as well. So that's my overriding when I'm talking to customers and we talk ChatGPT, it's in the news all the time. It's very topical. >> It's fun. >> It is. I even said to my 13-year-old son yesterday, your homework's out a date. 'Cause I knew he was doing some summary stuff on ChatGPT. So a little wind up that's out of date just to make that emphasis around the model. And that's where we, with our Neurons platform Ivanti, that's what we want to give the customers all the time, which is the real-time snapshot. So they can make a priority or a decision based on what that information is telling them. >> And we've kind of learned, I think, over the last couple of years, that access to real-time data, real-time AI, is no longer nice to have. It's a massive competitive advantage for organizations, but it's going to enable the on-demand, everything that we expect in our consumer lives, in our business lives. This is going to be table stakes for organizations, I think, in every industry going forward. >> Yeah. >> But assumes 5G, right? Is going to actually happen and somebody's going to- >> Going to absolutely. >> Somebody's going to make some money off it at some point. When are they going to make money off of 5G, do you think? (all laughing) >> No. And then you asked a very good question, Dave. I want to answer that question. Will bad guys use AI? >> Yeah. Yeah. >> Offensive AI is a very big thing. We have to pay attention to it. It's got to create an asymmetric war. If you look at the president of the United States, he said, "If somebody's going to attack us on cyber, we are going to retaliate." For the first time, US is willing to launch a cyber war. What that really means is, we're going to use AI for offensive reasons as well. And we as citizens have to pay attention to that. And that's where I'm worried about, right? AI bias, whether it's data, or domain expertise, or algorithmic bias, is going to be a big thing. And offensive AI is something everybody have to pay attention to. >> To your point, Sri, earlier about critical infrastructure getting hacked, I had this conversation with Dr. Robert Gates several years ago, and I said, "Yeah, but don't we have the best offensive, you know, technology in cyber?" And he said, "Yeah, but we got the most to lose too." >> Yeah, 100%. >> We're the wealthiest nation of the United States. The wealthiest is. So you got to be careful. But to your point, the president of the United States saying, "We'll retaliate," right? Not necessarily start the war, but who started it? >> But that's the thing, right? Attribution is the hardest part. And then you talked about a very interesting thing, rich nations, right? There's emerging nations. There are nations left behind. One thing I've seen on the show floor today is, digital inequality. Digital poverty is a big thing. While we have this amazing technology, 90% of the world doesn't have access to this. >> Right. >> What we have done is we have created an inequality across, and especially in mobility and cyber, if this technology doesn't reach to the last mile, which is emerging nations, I think we are creating a crater back again and putting societies a few miles back. >> And at much greater risk. >> 100%, right? >> Yeah. >> Because those are the guys. In cyber, all you need is a laptop and a brain to attack. >> Yeah. Yeah. >> If I don't have it, that's where the civil war is going to start again. >> Yeah. What are some of the things in our last minute or so, guys, David, we'll start with you and then Sri go to you, that you're looking forward to at this MWC? The theme is velocity. We're talking about so much transformation and evolution in the telecom industry. What are you excited to hear and learn in the next couple of days? >> Just getting a complete picture. One is actually being out after the last couple of years, so you learn a lot. But just walking around and seeing, from my perspective, some vendor names that I haven't seen before, but seeing what they're doing and bringing to the market. But I think goes back to the point made earlier around APIs and integration. Everybody's talking about how can we kind of do this together in a way. So integrations, those smart things is what I'm kind of looking for as well, and how we plug into that as well. >> Excellent, and Sri? >> So for us, there is a lot to offer, right? So while I'm enjoying what I'm seeing here, I'm seeing at an opportunity. We have an amazing portfolio of what we can do. We are into mobile device management. We are the last (indistinct) company. When people find problems, somebody has to go remediators. We are the world's largest patch management company. And what I'm finding is, yes, all these people are embedding software, pumping it like nobody's business. As you find one ability, somebody has to go fix them, and we want to be the (indistinct) company. We had the last smile. And I find an amazing opportunity, not only we can do device management, but do mobile threat defense and give them a risk prioritization on what needs to be remediated, and manage all that in our ITSM. So I look at this as an amazing, amazing opportunity. >> Right. >> Which is exponential than what I've seen before. >> So last question then. Speaking of opportunities, Sri, for you, what are some of the things that customers can go to? Obviously, you guys talk to customers all the time. In terms of learning what Ivanti is going to enable them to do, to take advantage of these opportunities. Any webinars, any events coming up that we want people to know about? >> Absolutely, ivanti.com is the best place to go because we keep everything there. Of course, "theCUBE" interview. >> Of course. >> You should definitely watch that. (all laughing) No. So we have quite a few industry events we do. And especially there's a lot of learning. And we just raised the ransomware report that actually talks about ransomware from a global index perspective. So one thing what we have done is, rather than just looking at vulnerabilities, we showed them the weaknesses that led to the vulnerabilities, and how attackers are using them. And we even talked about DHS, how behind they are in disseminating the information and how it's actually being used by nation states. >> Wow. >> And we did cover mobility as a part of that as well. So there's a quite a bit we did in our report and it actually came out very well. >> I have to check that out. Ransomware is such a fascinating topic. Guys, thank you so much for joining Dave and me on the program today, sharing what's going on at Ivanti, the changes that you're seeing in mobile, and the opportunities that are there for your customers. We appreciate your time. >> Thank you >> Thank you. >> Yes. Thanks, guys. >> Thanks, guys. >> For our guests and for Dave Vellante, I'm Lisa Martin. You're watching "theCUBE" live from MWC23 in Barcelona. As you know, "theCUBE" is the leader in live tech coverage. Dave and I will be right back with our next guest. (gentle upbeat music)

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

(upbeat music playing) >> Narrator: theCUBE presents Ignite 22, brought to you by Palo Alto Networks. >> Hey guys, girls, welcome back. It's theCUBE Live in Las Vegas at the MGM Grand for Palo Alto Networks Ignite 22. Lisa Martin here with Dave Vellante. Dave, We've had some great conversations. This is day one of two days of cube coverage. We're talking with Palo Alto executives, their partner network, their customers, going to be learning a lot about what they've been doing to really be that golden nugget. >> Yeah. We've talked, Lisa, about how Palo Alto Networks is affecting a TAM expansion strategy through acquisitions and integration and company CDW, that I remember, you know, been around a long time. I remember back in the Comdex days talk about transformation of a company. Really excited to have them on. >> We're going to talk about that. Stephanie Hagopian is here, the VP of Security at CDW. >> Stephanie, >> Hey it's great to have you on the program. >> It's so nice to be here. Thank you. >> So lots going on. CDW has made several acquisitions in the past couple of quarters alone as it relates to security. Talk to us about what's going on. >> Yes. So we are way more than the computer warehouse that you used to know. The computer catalog days, we've moved beyond that. We've made a lot of strategic acquisitions in the past several quarters. The reason for that is we're trying to change our image and our brand and how, more importantly, we engage with our customers in security. We used to traditionally be, you know, kind of at the end of the procurement cycle with our customers, and we want to be an advisor. We want to really sell solutions and help influence the outcomes that our clients are trying to achieve when it comes to, not just security, but also risk, governance, threatened vulnerability management, how are they dealing with major issues around zero trust and building a zero trust framework for a company. >> Lisa: And I imagine these acquisitions, that really from a catalyst perspective was really driven >> Yeah. by the customers and what they were >> absolutely wanting to see and feel and hear and be able to do. >> Absolutely. So the acquisitions have given us over 400 delivery resources, consultants, advisors people who can actually engage with our clients who have real life experience, have worked with global organizations, some of the biggest companies in the world in order to solve their problems. And using that experience to be able to to really create higher value, you know as we interact and engage. >> Dave: You were telling us, Stephanie, that you actually came into CDW through an acquisition. >> I did. >> And I think if you go back 10 years ago when the cloud was just sort of hitting its steep steep ramp, and it looked, it was pretty obvious. And at the same time you had what we affectionately called you know, box sellers. And it was very clear that if they didn't transform their businesses and you know, the, they a lot of 'em were small, regional companies. They had the owners had big houses and big boats but the companies were going to go away if they didn't transform. So it's interesting to me that you've chosen security and governance in some of the really most difficult areas to as part of that transformation. Where did that come from, from your perspective and you know, why security and why such challenging areas? >> Well, I've been part of security in the security industry for over 20 years, and I've loved the fact it is challenging. It's what, it's what makes us so important and critical to our clients. Security's not an easy problem to solve. And it, it's because the landscape keeps changing. The advent of cloud and now hybrid infrastructure creates endless challenges for our customers. Threat actors change. We have insider threats, we have external threats. There's all sorts of risk when you talk about third parties and how third parties interact with organizations. We have supply chain management. And now that we've moved into this hybrid work environment of virtual, not virtual. You know, we have people kind of engaging within organizations in different ways. There's just a lot of risk associated with that. It's not easy and you have to engage with stakeholders across the entire organization. You have to understand how legal thinks of this and compliance and HR. It's not just an IT issue, it's a business issue. And we understand that and it's just, it's so interesting for us to engage with our customers on critical initiatives and security is at the top of the list. It's not just a, a CISO or even a CIO problem anymore. Boards care about this, >> Lisa: Right? >> We make or break companies with cybersecurity and risk strategies. That's why it's so critical. So we consider ourselves to be a high priority for every single organization, big or small. >> Lisa: From a security perspective, what's the common denominator among industries that you're seeing? >> Oh, I mean, we see, in terms of common denominator, I think every single organization's contending with ransomware. >> Ah >> That's probably number one. Breaches. You know, how do you prevent bad actors from doing something, you know, that's threatening to information sensitive data, especially consumer data. Third party risk is a big topic, and how to secure hybrid cloud infrastructures which is a key part of, you know, Palo's strategy as well. And we realize that. >> Why do they buy from CDW? Pitch me. I'm a customer, what can you do for me? >> Yeah. Because we want to partner. So we, we provide true advisory and consulting services to our customers. We aren't there just to make a sale and walk away. We want long-term commitments and long-term partnerships with our customer base. We're there to, to give them outcomes, right? And to align to their priorities and their challenges. It's, it's not a one and done for us. This is about a long-term partnership and that's what makes us so different. And we're now through the acquisition strategies. We're the largest security integrator in North America in terms of our revenue and our size just our sheer size and capability and the amount of full-time employees we have dedicated to this part of our business. So they know they can trust us and that we can scale. >> Dave: Do you? Is is it a, a teach me how to fish strategy? Or is it also if >> Yeah, >> if you want to have, if I, if I as a customer want to have you continue to manage or at least provide some kind of managed services, where's the the line? >> Stephanie: Yeah. So we are incredibly unique in the way we've built out our security practice in that we, we do both. And we want our clients to understand that there are going to be elements of what they do that they want to keep in house from a security perspective. That is why, and it also came from an acquisition, we have a workforce development team for security. We actually are a Palo authorized training partner. And we're incredibly proud of that fact because we don't just want to configure technology. We want to enable our customers to enhance and maintain their investments with Palo and with all technologies, with all of security. At the same time, we know they can't do everything in-house, and it just might make more sense to do manage through us. So we have end-to-end managed capabilities as well and we continue to enhance that part of our business. >> So a lot, a lot of opportunities for customers there. Talk a little bit about the Palo Alto Network's extension of the value prop that you just talked about. >> Oh yes. We love, you know, Palo is taking a platform approach and really focusing on helping customers rationalize their IT infrastructure around security. We're doing the same exact thing and focusing on zero trust is huge. We're, we're having those conversations with our customers as well. We want them to take their Palo investment and try to create a platform approach because there's simplicity and cost savings in that. The security conversations becoming a CFO conversation, right? We love rationalizing those technology investments in a way that makes sense. And we're right in line with Palo in that we want to provide those capabilities end to end and we want to ensure they integrate and use that all of the capabilities within your platform to the extent of that investment, right? We want them to use everything and not just parts of the technology or just do a partial deployment. We want them to use everything that it functionally is available to them through that investment. >> Dakesh, in his keynote this morning, said the answer is not just more people. I know there's this, this, this gap between the number of required number of cyber professionals that we need and >> Stephanie: Oh yeah. >> And how many employees we have, et cetera, et cetera. However, you just can't get there overnight. So that's where service providers, you know, come in. >> Stephanie: It's huge. >> I saw a stat recently, I think it said 50% of organizations in North America don't have a SOC. >> That's true. >> Okay. So they, they need managed services. So, >> Stephanie: They do. >> What are you seeing with some of the small and mid-size companies >> Stephanie: Managed >> and, and and how does, how is that, how is that going? We're entering a new era with, >> Stephanie: Yeah with, you know, cloud can can be a, a great help and and reduce the IT load internally. >> Yeah. >> Dave: What, what's the dynamic like in the customer base? >> Smaller customers especially they just can't attract the cyber talent. It's a high demand field because there just aren't many people who have that capability, right? For us, providing managed a managed SOC is huge. One of our key acquisitions, Sirius, was our largest acquisition recently, brought us a 24 7 managed SOC capability. And that's exactly what our mid-size customers want and demand and what they need, and it's more cost effective. And now they don't have to worry about being a security business. That's not what they are. They need to run their businesses and that's what we provide through managed capabilities especially for that customer base in particular. >> Lisa: And and >> Dave: How about the really small customers, right? Who, who, you know, they're in some ways the most vulnerable. >> Yeah >> Right? >> In many ways >> They don't have the budgets they're kind of working hand to mouth. How, how do you help them? >> Stephanie: Yeah. Yeah. So we, we provide cost effective managed capabilities. So there's managed for enterprise, there's managed for mid-market, but then for small medium businesses they want something that is at the right price point. And that's what we're doing actually in co-development with Palos. That's why we're expanding, not just our professional services capabilities with the Palo platform, but also providing managed support for every aspect of the platform so that customers don't need to invest in full-time employees to do that. They can, they have a predictable cost model that's affordable, that they can leverage over time. So we're very intent on making sure we're fulfilling that not just for our big customers but also for SMB and our, and small businesses as well. >> So you really have that whole suite taken care of >> The whole suite, yeah. I want to talk about some of the the large enterprises for a second. I saw a survey recently that, you know, you talked about security is a board level conversation. It is. >> Stephanie: Very much so. >> We talk about that all the time, CFO conversation but the survey that I saw recently was that there's not there's lack of alignment on boards with the executive suite where security is concerned. Are you seeing that and how can CDW and the Palo Alto partnership help gain that important alignment? >> Stephanie: Yeah So we, we face this all the time. What's on the CISO whiteboard might not be on the CFO's whiteboard or the, the board's whiteboard right? We love, and this is the whole part of our strategy and our strategy partnering with Palo, is that we want to engage further up on the, on the cycle. The, you know, we don't want to to talk to them at the end of the purchasing cycle because we're not providing value. >> Lisa: Yeah. >> We want to help advise them and build the business case. And by them, I mean our CISOs are, you know the heads of network security. You know, their are various stakeholders that we want to engage with to help them build the business case and the justification so that they are speaking the same language as the board member, the CFO. And we do that in many ways. I think the biggest is that we've we've built a global security strategy office that encompasses practitioners. So these are former CISOs, CIOs CTOs who have sat in their shoes and done what they've done. And we bring that experience to bear, coincidentally but not so coincidentally, Palo has the same capability. So Palo's also has a team of field CISOs and former practitioners. So we're partnering together to make sure that we're enabling our customers in, in providing the right value statements and the the right ROI within the the board meetings so that they get that investment right. And they're able to do what they need to do to secure the infrastructure. >> Dave: I mean, historically the business case has been we're going to help you not get breached, and you're going to reduce your, your, your loss >> Stephanie: (indistinct) still relevant. >> And, and I'm, and it's still very relevant. Is there any sort of on the other side of the algebra algebraic equation where actually having this kind of security practice can actually drive productivity >> Absolutely. >> Or or even drive revenue and can you talk about that part of the equation? >> Stephanie: Yeah, security as an industry, we're we've gotten a lot smarter. We understand it's not just about the compliance aspect or the data privacy aspect. It's very important to your point, you know breach prevention is certainly, you know, a a great justification. It's also about automation. So you think of SOAR, right? Providing automation and visibility and dashboard views into who's doing what actually really reduces administrative overhead. We, you know, we want to re-allow our clients to repurpose individuals because there are a finite amount of people in the security industry to focus on higher value tasks. So we're enabling just a lot of cost savings through that. Self-service is a big piece of this. You know, when you think about security we bring along a lot of automation, self-service automation of business logic, and business process. There's a huge value in cost savings attached to that. So that's huge. That's a huge part of the security conversation. >> I was reading, you talked about the cybersecurity skills gap and I was reading some interesting numbers that there's 26 million developers in the world less than 3 million cybersecurity professionals. >> Stephanie: Yeah. >> Talk to us about one of your favorite customer stories where you think CDW and Palo really nailed it in terms of helping organization drive that value the top line value, the bottom line value while enabling them with your expertise. >> Oh my gosh, I don't even want to focus on one because since we became a Palo authorized training partner we have worked with over a hundred clients. We just started this this year and we've helped over a hundred clients and thousands of people get enabled on on Palo firewall configuration and training and development. So we've co, we've partnered together as and we've impacted over a hundred organizations this year in making sure their people are enabled and they're, they're going from that I'm a developer generic to I'm a security professional. So we're helping to close that cybersecurity workforce gap. And we're just so excited at the scale we've been able to do that in such a short amount of time that, I mean, if you think about next year and the year following I mean it's going to be thousands of different clients. But you think about each client, we're impact we're, we're holding classes with 30 plus people. So we've already impacted thousands of people which is amazing. >> Right? So the idea to scale the program in in calendar year 2023 >> Absolutely. We're going to, we, we tried it. This was a trial run and it was amazingly successful trial run. So we're incredibly excited to scale this even more and continue to provide, you know, that element, that workforce development element, that training element for the entire Palo's stack, not just elements of it. >> Lisa: Excellent. Stephanie, thank you so much for joining us on the program. >> Stephanie: Thank you. >> Sharing what CDW and Palo Alto Networks are doing together. The what's in it for me from a customer perspective, big impact there. We appreciate your insights. >> Thank you so much. >> Dave: Great to have you >> Lisa: Our pleasure. >> It's great to have, great to be here. >> Yeah. For our guest and for Dave Vellante, I'm Lisa Martin. You're watching theCUBE, the leader in live and emerging tech coverage.

(upbeat music) >> We're back at SC22 SuperComputing Conference in Dallas. My name's Paul Gillan, my co-host, John Furrier, SiliconANGLE founder. And huge exhibit floor here. So much activity, so much going on in HPC, and much of it around the chips from AMD, which has been on a roll lately. And in partnership with Dell, our guests are Brian Payne, Dell Technologies, VP of Product Management for ISG mid-range technical solutions, and Raghu Nambiar, corporate vice president of data system, data center ecosystem, and application engineering, that's quite a mouthful, at AMD, And gentlemen, welcome. Thank you. >> Thanks for having us. >> This has been an evolving relationship between you two companies, obviously a growing one, and something Dell was part of the big general rollout, AMD's new chip set last week. Talk about how that relationship has evolved over the last five years. >> Yeah, sure. Well, so it goes back to the advent of the EPIC architecture. So we were there from the beginning, partnering well before the launch five years ago, thinking about, "Hey how can we come up with a way to solve customer problems? address workloads in unique ways?" And that was kind of the origin of the relationship. We came out with some really disruptive and capable platforms. And then it continues, it's continued till then, all the way to the launch of last week, where we've introduced four of the most capable platforms we've ever had in the PowerEdge portfolio. >> Yeah, I'm really excited about the partnership with the Dell. As Brian said, we have been partnering very closely for last five years since we introduced the first generation of EPIC. So we collaborate on, you know, system design, validation, performance benchmarks, and more importantly on software optimizations and solutions to offer out of the box experience to our customers. Whether it is HPC or databases, big data analytics or AI. >> You know, you guys have been on theCUBE, you guys are veterans 2012, 2014 back in the day. So much has changed over the years. Raghu, you were on the founding chair of the TPC for AI. We've talked about the different iterations of power service. So much has changed. Why the focus on these workloads now? What's the inflection point that we're seeing here at SuperComputing? It feels like we've been in this, you know run the ball, get, gain a yard, move the chains, you know, but we feel, I feel like there's a moment where the there's going to be an unleashing of innovation around new use cases. Where's the workloads? Why the performance? What are some of those use cases right now that are front and center? >> Yeah, I mean if you look at today, the enterprise ecosystem has become extremely complex, okay? People are running traditional workloads like Relational Database Management Systems, also new generation of workloads with the AI and HPC and actually like AI actually HPC augmented with some of the AI technologies. So what customers are looking for is, as I said, out of the box experience, or time to value is extremely critical. Unlike in the past, you know, people, the customers don't have the time and resources to run months long of POCs, okay? So that's one idea that we are focusing, you know, working closely with Dell to give out of the box experience. Again, you know, the enterprise applicate ecosystem is, you know, really becoming complex and the, you know, as you mentioned, some of the industry standard benchmark is designed to give the fair comparison of performance, and price performance for the, our end customers. And you know, Brian and my team has been working closely to demonstrate our joint capabilities in the AI space with, in a set of TPCx-AI benchmark cards last week it was the major highlight of our launch last week. >> Brian, you got showing the demo in the booth at Dell here. Not demo, the product, it's available. What are you seeing for your use cases that customers are kind of rallying around now, and what are they doubling down on. >> Yeah, you know, I, so Raghu I think teed it up well. The really data is the currency of business and all organizations today. And that's what's pushing people to figure out, hey, both traditional workloads as well as new workloads. So we've got in the traditional workload space, you still have ERP systems like SAP, et cetera, and we've announced world records there, a hundred plus percent improvements in our single socket system, 70% and dual. We actually posted a 40% advantage over the best Genoa result just this week. So, I mean, we're excited about that in the traditional space. But what's exciting, like why are we here? Why, why are people thinking about HPC and AI? It's about how do we make use of that data, that data being the currency and how do we push in that space? So Raghu mentioned the TPC AI benchmark. We launched, or we announced in collaboration you talk about how do we work together, nine world records in that space. In one case it's a 3x improvement over prior generations. So the workloads that people care about is like how can I process this data more effectively? How can I store it and secure it more effectively? And ultimately, how do I make decisions about where we're going, whether it's a scientific breakthrough, or a commercial application. That's what's really driving the use cases and the demand from our customers today. >> I think one of the interesting trends we've seen over the last couple of years is a resurgence in interest in task specific hardware around AI. In fact venture capital companies invested a $1.8 billion last year in AI hardware startups. I wonder, and these companies are not doing CPUs necessarily, or GPUs, they're doing accelerators, FPGAs, ASICs. But you have to be looking at that activity and what these companies are doing. What are you taking away from that? How does that affect your own product development plans? Both on the chip side and on the system side? >> I think the future of computing is going to be heterogeneous. Okay. I mean a CPU solving certain type of problems like general purpose computing databases big data analytics, GPU solving, you know, problems in AI and visualization and DPUs and FPGA's accelerators solving you know, offloading, you know, some of the tasks from the CPU and providing realtime performance. And of course, you know, the, the software optimizes are going to be critical to stitch everything together, whether it is HPC or AI or other workloads. You know, again, as I said, heterogeneous computing is going to be the future. >> And, and for us as a platform provider, the heterogeneous, you know, solutions mean we have to design systems that are capable of supporting that. So if as you think about the compute power whether it's a GPU or a CPU, continuing to push the envelope in terms of, you know, to do the computations, power consumption, things like that. How do we design a system that can be, you know, incredibly efficient, and also be able to support the scaling, you know, to solve those complex problems. So that gets into challenges around, you know, both liquid cooling, but also making the most out of air cooling. And so we're seeing not only are we we driving up you know, the capability of these systems, we're actually improving the energy efficiency. And those, the most recent systems that we launched around the CPU, which is still kind of at the heart of everything today, you know, are seeing 50% improvement, you know, gen to gen in terms of performance per watt capabilities. So it's, it's about like how do we package these systems in effective ways and make sure that our customers can get, you know, the advertised benefits, so to speak, of the new chip technologies. >> Yeah. To add to that, you know, performance, scalability total cost of ownership, these are the key considerations, but now energy efficiency has become more important than ever, you know, our commitment to sustainability. This is one of the thing that we have demonstrated last week was with our new generation of EPIC Genoa based systems, we can do a one five to one consolidation, significantly reducing the energy requirement. >> Power's huge costs are going up. It's a global issue. >> Raghu: Yeah, it is. >> How do you squeeze more performance too out of it at the same time, I mean, smaller, faster, cheaper. Paul, you wrote a story about, you know, this weekend about hardware and AI making hardware so much more important. You got more power requirements, you got the sustainability, but you need more horsepower, more compute. What's different in the architecture if you guys could share like today versus years ago, what's different in as these generations step function value increases? >> So one of the major drivers from the processor perspective is if you look at the latest generation of processors, the five nanometer technology, bringing efficiency and density. So we are able to pack 96 processor cores, you know, in a two socket system, we are talking about 196 processor cores. And of course, you know, other enhancements like IPC uplift, bringing DDR5 to the market PC (indistinct) for the market, offering overall, you know, performance uplift of more than 2.5x for certain workloads. And of course, you know, significantly reducing the power footprint. >> Also, I was just going to cut, I mean, architecturally speaking, you know, then how do we take the 96 cores and surround it, deliver a balanced ecosystem to make sure that we can get the, the IO out of the system, and make sure we've got the right data storage. So I mean, you'll see 60% improvements and total storage in the system. I think in 2012 we're talking about 10 gig ethernet. Well, you know, now we're on to 100 and 400 on the forefront. So it's like how do we keep up with this increased power, by having, or computing capabilities both offload and core computing and make sure we've got a system that can deliver the desired (indistinct). >> So the little things like the bus, the PCI cards, the NICs, the connectors have to be rethought through. Is that what you're getting at? >> Yeah, absolutely. >> Paul: And the GPUs, which are huge power consumers. >> Yeah, absolutely. So I mean, cooling, we introduce, and we call it smart cooling is a part of our latest generation of servers. I mean, the thermal design inside of a server is a is a complex, you know, complex system, right? And doing that efficiently because of course fans consume power. So I mean, yeah, those are the kind of considerations that we have to put through to make sure that you're not either throttling performance because you don't have you know, keeping the chips at the right temperature. And, and you know, ultimately when you do that, you're hurting the productivity of the investment. So I mean, it's, it's our responsibility to put our thoughts and deliver those systems that are (indistinct) >> You mention data too, if you bring in the data, one of the big discussions going into the big Amazon show coming up, re:Invent is egress costs. Right, So now you've got compute and how you design data latency you know, processing. It's not just contained in a machine. You got to think about outside that machine talking to other machines. Is there an intelligent (chuckles) network developing? I mean, what's the future look like? >> Well, I mean, this is a, is an area that, that's, you know, it's fun and, you know, Dell's in a unique position to work on this problem, right? We have 70% of the mission housed, 70% of the mission critical data that exists in the world. How do we bring that closer to compute? How do we deliver system level solutions? So server compute, so recently we announced innovations around NVMe over Fabrics. So now you've got the NVMe technology and the SAN. How do we connect that more efficiently across the servers? Those are the kinds, and then guide our customers to make use of that. Those are the kinds of challenges that we're trying to unlock the value of the data by making sure we're (indistinct). >> There are a lot of lessons learned from, you know, classic HPC and some of the, you know big data analytics. Like, you know, Hadoops of the world, you know, you know distributor processing for crunching a large amount of amount of data. >> With the growth of the cloud, you see, you know, some pundits saying that data centers will become obsolete in five years, and everything's going to move to the cloud. Obviously data center market that's still growing, and is projected to continue to grow. But what's the argument for captive hardware, for owning a data center these days when the cloud offers such convenience and allegedly cost benefit? >> I would say the reality is that we're, and I think the industry at large has acknowledged this, that we're living in a multicloud world and multicloud methods are going to be necessary to you know, to solve problems and compete. And so, I mean, you know, in some cases, whether it's security or latency, you know, there's a push to have things in your own data center. And then of course growth at the edge, right? I mean, that's, that's really turning, you know, things on their head, if you will, getting data closer to where it's being generated. And so I would say we're going to live in this edge cloud, you know, and core data center environment with multi, you know, different cloud providers providing solutions and services where it makes sense, and it's incumbent on us to figure out how do we stitch together that data platform, that data layer, and help customers, you know, synthesize this data to, to generate, you know, the results they need. >> You know, one of the things I want to get into on the cloud you mentioned that Paul, is that we see the rise of graph databases. And so is that on the radar for the AI? Because a lot of more graph data is being brought in, the database market's incredibly robust. It's one of the key areas that people want performance out of. And as cloud native becomes the modern application development, a lot more infrastructure as code's happening, which means that the internet and the networks and the process should be programmable. So graph database has been one of those things. Have you guys done any work there? What's some data there you can share on that? >> Yeah, actually, you know, we have worked closely with a company called TigerGraph, there in the graph database space. And we have done a couple of case studies, one on the healthcare side, and the other one on the financial side for fraud detection. Yeah, I think they have a, this is an emerging area, and we are able to demonstrate industry leading performance for graph databases. Very excited about it. >> Yeah, it's interesting. It brings up the vertical versus horizontal applications. Where is the AI HPC kind of shining? Is it like horizontal and vertical solutions or what's, what's your vision there. >> Yeah, well, I mean, so this is a case where I'm also a user. So I own our analytics platform internally. We actually, we have a chat box for our product development organization to figure out, hey, what trends are going on with the systems that we sell, whether it's how they're being consumed or what we've sold. And we actually use graph database technology in order to power that chat box. So I'm actually in a position where I'm like, I want to get these new systems into our environment so we can deliver. >> Paul: Graphs under underlie most machine learning models. >> Yeah, Yeah. >> So we could talk about, so much to talk about in this space, so little time. And unfortunately we're out of that. So fascinating discussion. Brian Payne, Dell Technologies, Raghu Nambiar, AMD. Congratulations on the successful launch of your new chip set and the growth of, in your relationship over these past years. Thanks so much for being with us here on theCUBE. >> Super. >> Thank you much. >> It's great to be back. >> We'll be right back from SuperComputing 22 in Dallas. (upbeat music)

(upbeat music) >> Hello everyone, welcome to this CUBE Showcase, accelerating business transformation with VMware Cloud on AWS. It's a solution innovation conversation with two great guests, Fred Wurden, VP of Commercial Services at AWS and Narayan Bharadwaj, who's the VP and General Manager of Cloud Solutions at VMware. Gentlemen, thanks for joining me on the showcase. >> Great to be here. >> Great. Thanks for having us on. It's a great topic. >> We've been covering this VMware cloud on AWS since the launch going back and it's been amazing to watch the evolution from people saying, Oh, it's the worst thing I've ever seen. What's this mean? And the press were not really on board with the vision, but as it played out as you guys had announced together, it did work out great for VMware. It did work out great for AWS and it continues two years later and I want to just get an update from you guys on where you guys see this has been going. I'll see multiple years. Where is the evolution of the solution as we are right now coming off VMware explorer just recently and going in to re:Invent, which is only a couple weeks away Feels like tomorrow. But as we prepare, a lot going on. Where are we with the evolution of the solution? >> I mean, first thing I want to say is October 2016 was a seminal moment in the history of IT. When Pat Gelsinger and Andy Jassy came together to announce this. And I think John, you were there at the time I was there. It was a great, great moment. We launched the solution in 2017 year after that at VMworld, back when we called it VMworld. I think we have gone from strength to strength. One of the things that has really mattered to us is we've learned from AWS also in the processes, this notion of working backwards. So we really, really focused on customer feedback as we built a service offering now five years old. Pretty remarkable journey. In the first years we tried to get across all the regions, that was a big focus because there was so much demand for it. In the second year, we started going really on enterprise great features. We invented this pretty awesome feature called Stretched Clusters, where you could stretch a vSphere cluster using vSAN and NSX-T across to AZs in the same region. Pretty phenomenal four nines of availability that applications started to get with that particular feature. And we kept moving forward, all kinds of integration with AWS Direct Connect, Transit Gateways with our own advanced networking capabilities. Along the way, Disaster Recovery, we punched out two new services just focused on that. And then more recently we launched our Outposts partnership. We were up on stage at re:Invent, again, with Pat and Andy announcing AWS Outposts and the VMware flavor of that, VMware Cloud and AWS Outposts. I think it's been significant growth in our federal sector as well with our federal and high certification more recently. So all in all, we are super excited. We're five years old. The customer momentum is really, really strong and we are scaling the service massively across all geos and industries. >> That's great, great update. And I think one of the things that you mentioned was how the advantages you guys got from that relationship. And this has been the theme for AWS, man, since I can remember from day one, Fred. You guys do the heavy lifting as you always say for the customers. Here, VMware comes on board. Takes advantage of the AWS and just doesn't miss a beat. Continues to move their workloads that everyone's using, vSphere, and these are big workloads on AWS. What's the AWS perspective on this? How do you see it? >> Yeah, it's pretty fascinating to watch how fast customers can actually transform and move when you take the skill set that they're familiar with and the advanced capabilities that they've been using on-prem and then overlay it on top of the AWS infrastructure that's evolving quickly and building out new hardware and new instances we'll talk about. But that combined experience between both of us on a jointly engineered solution to bring the best security and the best features that really matter for those workloads drive a lot of efficiency and speed for the customers. So it's been well received and the partnership is stronger than ever from an engineering standpoint, from a business standpoint. And obviously it's been very interesting to look at just how we stay day one in terms of looking at new features and work and responding to what customers want. So pretty excited about just seeing the transformation and the speed that which customers can move to while at VMC. >> That's a great value proposition. We've been talking about that in context to anyone building on top of the cloud. They can have their own supercloud, as we call it, if you take advantage of all the CapEx and investment Amazon's made and AWS has made and continues to make in performance IaaS and PaaS, all great stuff. I have to ask you guys both as you guys see this going to the next level, what are some of the differentiations you see around the service compared to other options in the market? What makes it different? What's the combination? You mentioned jointly engineered. What are some of the key differentiators of the service compared to others? >> Yeah. I think one of the key things Fred talked about is this jointly engineered notion. Right from day one we were the early adopters of the AWS Nitro platform. The reinvention of EC2 back five years ago. And so we have been having a very, very strong engineering partnership at that level. I think from a VMware customer standpoint, you get the full software-defined data center, compute storage networking on EC2, bare metal across all regions. You can scale that elastically up and down. It's pretty phenomenal just having that consistency globally on AWS EC2 global regions. Now the other thing that's a real differentiator for us, what customers tell us about is this whole notion of a managed service. And this was somewhat new to VMware. But we took away the pain of this undifferentiated heavy lifting where customers had to provision rack stack hardware, configure the software on top, and then upgrade the software and the security patches on top. So we took away all of that pain as customers transitioned to VMware cloud in AWS. In fact, my favorite story from last year when we were all going through the Log4j debacle. Industry was just going through that. Favorite proof point from customers was before they could even race this issue to us, we sent them a notification saying, we already patched all of your systems, no action from you. The customers were super thrilled. I mean, these are large banks. Many other customers around the world were super thrilled they had to take no action, but a pretty incredible industry challenge that we were all facing. >> Narayan, that's a great point. The whole managed service piece brings up the security. You kind of teasing at it, but there's always vulnerabilities that emerge when you are doing complex logic. And as you grow your solutions, there's more bits. Fred, we were commenting before we came on camera more bits than ever before and at the physics layer too, as well as the software. So you never know when there's going to be a zero-day vulnerability out there. It happens. We saw one with Fortinet this week. This came out of the woodwork. But moving fast on those patches, it's huge. This brings up the whole support angle. I wanted to ask you about how you guys are doing that as well, because to me, we see the value when we talk to customers on theCUBE about this. It was a real easy understanding of what the cloud means to them with VMware now with the AWS. But the question that comes up that we want to get more clarity on is how do you guys handle support together? >> Well, what's interesting about this is that it's done mutually. We have dedicated support teams on both sides that work together pretty seamlessly to make sure that whether there's a issue at any layer, including all the way up into the app layer, as you think about some of the other workloads like SAP, we'll go end-to-end and make sure that we support the customer regardless of where the particular issue might be for them. And on top of that, we look at where we're improving reliability in as a first order of principle between both companies. So from availability and reliability standpoint, it's top of mind and no matter where the particular item might land, we're going to go help the customer resolve that. It works really well. >> On the VMware side, what's been the feedback there? What are some of the updates? >> Yeah, I think, look, I mean, VMware owns and operates the service, but we work phenomenal backend relationship with AWS. Customers call VMware for the service or any issues. And then we have a awesome relationship with AWS on the backend for support issues or any hardware issues. The key management that we jointly do. All of the hard problems that customers don't have to worry about. I think on the front end, we also have a really good group of solution architects across the companies that help to really explain the solution, do complex things like cloud migration, which is much, much easier with the VMware Cloud in AWS. We're presenting that easy button to the public cloud in many ways. And so we have a whole technical audience across the two companies that are working with customers every single day. >> You had mentioned, I've got list here of some of the innovations. You mentioned the stretch clustering, getting the geos working, advanced network, Disaster Recovery, FedRAMP, public sector certifications, Outposts. All good, you guys are checking the boxes every year. You got a good accomplishments list there on the VMware AWS side here in this relationship. The question that I'm interested in is what's next? What recent innovations are you doing? Are you making investments in? What's on the list this year? What items will be next year? How do you see the new things, the list of accomplishments? People want to know what's next. They don't want to see stagnant growth here. They want to see more action as cloud continues to scale and modern applications cloud native. You're seeing more and more containers, more and more CI/CD pipelining with modern apps, put more pressure on the system. What's new? What's the new innovations? >> Absolutely. And I think as a five year old service offering, innovation is top of mind for us every single day. So just to call out a few recent innovations that we announced in San Francisco at VMware Explore. First of all, our new platform i4i.metal. It's isolate based. It's pretty awesome. It's the latest and greatest, all the speeds and feeds that we would expect from VMware and AWS at this point in our relationship. We announced two different storage options. This notion of working from customer feedback, allowing customers even more price reductions, really take off that storage and park it externally and separate that from compute. So two different storage offerings there. One is with AWS FSx with NetApp ONTAP, which brings in our NetApp partnership as well into the equation and really get that NetApp based really excited about this offering as well. And the second storage offering called VMware Cloud Flex Storage. VMware's own managed storage offering. Beyond that, we have done a lot of other innovations as well. I really wanted to talk about VMware Cloud Flex Compute where previously customers could only scale by hosts and a host is 36 to 48 cores, give or take. But with VMware Cloud Flex Compute, we are now allowing this notion of a resource defined compute model where customers can just get exactly the vCPU memory and storage that maps to the applications, however small they might be. So this notion of granularity is really a big innovation that we are launching in the market this year. And then last but not least, top of ransomware. Of course it's a hot topic in the industry. We are seeing many, many customers ask for this. We are happy to announce a new ransomware recovery with our VMware Cloud DR solution. A lot of innovation there and the way we are able to do machine learning and make sure the workloads that are covered from snapshots and backups are actually safe to use. So there's a lot of differentiation on that front as well. A lot of networking innovations with Project Northstar. Our ability to have layer four through layer seven, new SaaS services in that area as well. Keep in mind that the service already supports managed Kubernetes for containers. It's built in to the same clusters that have virtual machines. And so this notion of a single service with a great TCO for VMs and containers is sort at the heart of our (faintly speaking). >> The networking side certainly is a hot area to keep innovating on. Every year it's the same, same conversation, get better faster, networking more options there. The Flex Compute is interesting. If you don't mind me getting a quick clarification, could you explain the resource-defined versus hardware-defined? Because this is what we had saw at Explore coming out, that notion of resource-defined versus hardware-defined. What does that mean? >> Yeah, I mean I think we have been super successful in this hardware-defined notion. We we're scaling by the hardware unit that we present as software-defined data centers. And so that's been super successful. But customers wanted more, especially customers in different parts of the world wanted to start even smaller and grow even more incrementally. Lower the cost even more. And so this is the part where resource-defined starts to be very, very interesting as a way to think about, here's my bag of resources exactly based on what the customers request before fiber machines, five containers. It's size exactly for that. And then as utilization grows, we elastically behind the scenes, we're able to grow it through policies. So that's a whole different dimension. That's a whole different service offering that adds value and customers are comfortable. They can go from one to the other. They can go back to that host based model if they so choose to. And there's a jump off point across these two different economic models. >> It's cloud flexibility right there. I like the name. Fred, let's get into some of the examples of customers, if you don't mind, let's get into some of the, we have some time. I want to unpack a little bit of what's going on with the customer deployments. One of the things we've heard again on theCUBE is from customers is they like the clarity of the relationship, they love the cloud positioning of it. And then what happens is they lift and shift the workloads and it's like feels great. It's just like we're running VMware on AWS and then they start consuming higher level services. That adoption next level happens and because it's in the cloud. So can you guys take us through some recent examples of customer wins or deployments where they're using VMware cloud on AWS on getting started and then how do they progress once they're there? How does it evolve? Can you just walk us through a couple use cases? >> Sure. Well, there's a couple. One, it's pretty interesting that like you said, as there's more and more bits, you need better and better hardware and networking. And we're super excited about the i4 and the capabilities there in terms of doubling and or tripling what we're doing around lower variability on latency and just improving all the speeds. But what customers are doing with it, like the college in New Jersey, they're accelerating their deployment on onboarding over like 7,400 students over a six to eight month period. And they've really realized a ton of savings. But what's interesting is where and how they can actually grow onto additional native services too. So connectivity to any other services is available as they start to move and migrate into this. The options there obviously are tied to all the innovation that we have across any services, whether it's containerized and with what they're doing with Tanzu or with any other container and or services within AWS. So there's some pretty interesting scenarios where that data and or the processing, which is moved quickly with full compliance, whether it's in like healthcare or regulatory business is allowed to then consume and use things, for example, with Textract or any other really cool service that has monthly and quarterly innovations. So there's things that you just could not do before that are coming out and saving customers money and building innovative applications on top of their current app base in a rapid fashion. So pretty excited about it. There's a lot of examples. I think I probably don't have time to go into too many here. But that's actually the best part is listening to customers and seeing how many net new services and new applications are they actually building on top of this platform. >> Narayan, what's your perspective from the VMware side? 'Cause you guys have now a lot of headroom to offer customers with Amazon's higher level services and or whatever's homegrown where it's being rolled out 'cause you now have a lot of hybrid too. So what's your take on what's happening in with customers? >> I mean, it's been phenomenal. The customer adoption of this and banks and many other highly sensitive verticals are running production-grade applications, tier one applications on the service over the last five years. And so I have a couple of really good examples. S&P Global is one of my favorite examples. Large bank, they merge with IHS Markit, big conglomeration now. Both customers were using VMware Cloud and AWS in different ways. And with the use case, one of their use cases was how do I just respond to these global opportunities without having to invest in physical data centers? And then how do I migrate and consolidate all my data centers across the global, which there were many. And so one specific example for this company was how they migrated 1000 workloads to VMware Cloud and AWS in just six weeks. Pretty phenomenal if you think about everything that goes into a cloud migration process, people process technology. And the beauty of the technology going from VMware point A to VMware point B. The lowest cost, lowest risk approach to adopting VMware Cloud and AWS. So that's one of my favorite examples. There are many other examples across other verticals that we continue to see. The good thing is we are seeing rapid expansion across the globe, but constantly entering new markets with a limited number of regions and progressing our roadmap. >> It's great to see. I mean, the data center migrations go from months, many, many months to weeks. It's interesting to see some of those success stories. Congratulations. >> One of the other interesting fascinating benefits is the sustainability improvement in terms of being green. So the efficiency gains that we have both in current generation and new generation processors and everything that we're doing to make sure that when a customer can be elastic, they're also saving power, which is really critical in a lot of regions worldwide at this point in time. They're seeing those benefits. If you're running really inefficiently in your own data center, that is not a great use of power. So the actual calculators and the benefits to these workloads are pretty phenomenal just in being more green, which I like. We just all need to do our part there and this is a big part of it here. >> It's a huge point about the sustainability. Fred, I'm glad you called that out. The other one I would say is supply chain issue is another one. You see that constraints. I can't buy hardware. And the third one is really obvious, but no one really talks about it. It's security. I mean, I remember interviewing Steven Schmidt with that AWS and many years ago, this is like 2013 and at that time people were saying, the cloud's not secure. And he's like, listen, it's more secure in the cloud on-premise. And if you look at the security breaches, it's all about the on-premise data center vulnerabilities, not so much hardware. So there's a lot, the stay current on the isolation there is hard. So I think the security and supply chain, Fred, is another one. Do you agree? >> I absolutely agree. It's hard to manage supply chain nowadays. We put a lot of effort into that and I think we have a great ability to forecast and make sure that we can lean in and have the resources that are available and run them more efficiently. And then like you said on the security point, security is job one. It is the only P1. And if you think of how we build our infrastructure from Nitro all the way up and how we respond and work with our partners and our customers, there's nothing more important. >> And Narayan, your point earlier about the managed service patching and being on top of things is really going to get better. All right, final question. I really want to thank you for your time on this showcase. It's really been a great conversation. Fred, you had made a comment earlier. I want to end with a curve ball and put you eyes on the spot. We're talking about a new modern shift. We're seeing another inflection point. We've been documenting it. It's almost like cloud hitting another inflection point with application and open source growth significantly at the app layer. Continue to put a lot of pressure and innovation in the infrastructure side. So the question is for you guys each to answer is, what's the same and what's different in today's market? So it's like we want more of the same here, but also things have changed radically and better here. What's changed for the better and what's still the same thing hanging around that people are focused on? Can you share your perspective? >> I'll tackle it. Businesses are complex and they're often unique, that's the same. What's changed is how fast you can innovate. The ability to combine managed services and new innovative services and build new applications is so much faster today. Leveraging world class hardware that you don't have to worry about, that's elastic. You could not do that even five, 10 years ago to the degree you can today, especially with innovation. So innovation is accelerating at a rate that most people can't even comprehend and understand the set of services that are available to them. It's really fascinating to see what a one pizza team of engineers can go actually develop in a week. It is phenomenal. So super excited about this space and it's only going to continue to accelerate that. That's my take, Narayan. >> You got a lot of platform to compete on. With Amazon, you got a lot to build on. Narayan, your side. What's your answer to that question? >> I think we are seeing a lot of innovation with new applications that customers are constantly (faintly speaking). I think what we see is this whole notion of how do you go from desktop to production to the secure supply chain and how can we truly build on the agility that developers desire and build all the security and the pipelines to energize that production quickly and efficiently. I think we are seeing, we are at the very start of that sort of journey. Of course, we have invested in Kubernetes, the means to an end, but we're so much more beyond that's happening in industry and I think we're at the very, very beginning of this transformations, enterprise transformation that many of our customers are going through and we are inherently part of it. >> Well, gentlemen, I really appreciate that we're seeing the same thing. It's more the same here on solving these complexities with distractions, whether it's higher level services with large scale infrastructure. At your fingertips, infrastructure as code, infrastructure to be provisioned, serverless, all the good stuff happen and Fred with AWS on your side. And we're seeing customers resonate with this idea of being an operator again, being a cloud operator and developer. So the developer ops is kind of, DevOps is changing too. So all for the better. Thank you for spending the time and we're seeing again that traction with the VMware customer base and AWS getting along great together. So thanks for sharing your perspectives. >> We appreciate it. Thank you so much. >> Thank you John. >> This is theCUBE and AWS VMware showcase accelerating business transformation, VMware Cloud on AWS. Jointly engineered solution bringing innovation to the VMware customer base, going to the cloud and beyond. I'm John Furrier, your host. Thanks for watching. (gentle music)

>> The past 2 1/2 years have seen a dramatic change in the security posture of virtually all organizations. By accelerating the digital business mandate, the isolation economy catalyzed a move toward cloud computing to support remote workers. This we know. This had several ripple effects on CSO and CIO strategies that were highly visible at the Board of Directors' level. Now, the first major change was to recognize that the perimeter had suddenly been vaporized. Protection, as a result, moved away from things like perimeter-based firewalls toward more distributed endpoints, cloud security, and modern identity management. The second major change was a heightened awareness of the realities of ransomware. Ransomware as a service, for example, emerged as a major threat where virtually anyone with access to critical data and criminal intentions could monetize corporate security exposures. The third major change was a much more acute understanding of how data protection needed to become a fundamental component of cybersecurity strategies, and more specifically, CIOs quickly realized that their business resilience strategies were too narrowly DR-focused, that their DR approach was not cost efficient and needed to be modernized, and that new approaches to operational resilience were needed to reflect the architectural and business realities of this new environment. Hello, and welcome to "Why Ransomware isn't Your Only Problem," a service of theCUBE made possible by Druva, and in collaboration with IDC. I'm your host, Dave Vellante, and today, we're presenting a three-part program. We'll start with the data. IDC recently conducted a global survey of 500 business technology practitioners across 20 industries to understand the degree to which organizations are aware of and prepared for the threats they face in today's new world. IDC Research Vice President Phil Goodwin is here to share the highlights of the study and to summarize the findings from a recent research report on the topic. After that, we're going to hear from Curtis Preston, who's the Chief Technical Evangelist at Druva. I've known Curtis for decades. He's one of the world's foremost experts on backup and recovery, specifically, and data protection, generally. Curtis will help us understand how the survey data presented by IDC aligns with the real world findings from the field from his point of view. And he'll discuss why so many organizations have failed to successfully recover from an attack without major pains and big costs, and how to avoid such operational disruptions and disasters. And then finally, we'll hear from the technical experts at Druva, Stephen Manley and Anjan Srinivas. Stephen is a 10-time CUBE alum and Chief Technology Officer at Druva, and Anjan is Vice President and General Manager of Product Management at the company. And these individuals will specifically address how Druva is closing the gaps presented in the IDC survey through their product innovation. But right now I'm going to toss it to Lisa Martin, another one of the hosts for today's program. Lisa, over to you. (upbeat music) >> Bill Goodwin joins me next, the VP of Research at IDC. We're going to be breaking down what's going on in the threat landscape. Phil, welcome to the program. It's great to have you back on theCUBE. >> Hey, Lisa, it's great to be here with you. >> So talk to me about the state of the global IT landscape as we see cyberattacks massively increasing, the threat landscape changing so much. What is IDC seeing? >> You know, you really hit the top topic that we find from IT organizations as well as business organizations. And really, it's that digital resilience, that ransomware that has everybody's attention, and it has the attention, not just of the IT people, but of the business people alike, because it really does have profound effects across the organization. The other thing that we're seeing, Lisa, is really a move towards cloud. And I think part of that is driven by the economics of cloud, which fundamentally changed the way that we can approach disaster recovery, but also has accelerated during the pandemic for all the reasons that people have talked about in terms of work from home and so on. And then really the third thing is the economic uncertainty, and this is relatively new for 2022, but within IDC we've been doing a lot of research around what are those impacts going to be? And what we find people doing is they want greater flexibility, they want more cost certainty, and they really want to be able to leverage those cloud economics to have the scale up or scale down on demand nature of cloud. So those are, in a nutshell, kind of the three things that people are looking at. >> You mentioned ransomware. It's a topic we've been talking about a lot. It's a household word these days. It's now, Phil, no longer if we're going to get attacked, it's when, it's how often, it's the severity. Talk about ransomware as a priority all the way up the stack to the C-suite, and what are they trying to do to become resilient against it? >> Well, what some of the research that we did is we found that about 77% of organizations have digital resilience as a top priority within their organization. And so what you're seeing is organizations trying to leverage things to become more resilient, more digitally resilient, and to be able to really hone in on those kinds of issues that are keeping them awake at night, quite honestly. If you think about digital resilience, it really is foundational to the organization, whether it's through digital transformation or whether it's simply data availability, whatever it might happen to be. Digital resilience is really a large umbrella term that we use to describe that function that is aimed at avoiding data loss, assuring data availability, and helping the organization to extract value from their data. >> And digital resilience, data resilience, as every company these days has to be a data company to be competitive. Digital resilience, data resilience, are you using those terms interchangeably or is data resilience defined as something a little bit different? >> Well, sometimes yeah, we do get caught using them when one is the other. But data resilience is really a part of digital resilience, if you think about the data itself in the context of IT computing. So it really is a subset of that, but it is foundational to IT resilience. You can't have IT resilience without data resilience. So that's where we're coming from on it. >> Inextricably linked, and it's becoming a corporate initiative, but there's some factors that can complicate digital resilience, data resilience for organizations. What are some of those complications that organizations need to be aware of? >> Well, one of the biggest is what you mentioned at the top of the segment, and that is the area of ransomware. The research that we found is about 46% of organizations have been hit within the last three years. You know, it's kind of interesting how it's changed over the years. Originally, being hit by ransomware had a real stigma attached to it. Organizations didn't want to admit it, and they really avoided confronting that. Nowadays, so many people have been hit by it that that stigma has gone. And so really it is becoming more of a community kind of effort as people try to defend against these ransomers. The other thing about it is it's really a lot like Whac-A-Mole, you know. They attack us in one area and we defend against it so they attack us in another area, and we defend against it. And in fact, I had an individual come up to me at a show not long ago and said, "You know, one of these days we're going to get pretty well defended against ransomware and it's going to go away." And I responded I don't think so because we're constantly introducing new systems, new software, and introducing new vulnerabilities. And the fact is ransomware is so profitable, the bad guys aren't going to just fade into the night without giving it a a lot of fight. So I really think that ransomware is one of those things that is here for the long term and something that we have to address and have to get proactive about. >> You mentioned some stats there, and recently IDC and Druva did a white paper together that really revealed some quite shocking results. Talk to me about some of the things. Let's talk a little bit about the demographics of the survey and then talk about what was the biggest finding there, especially where it's concerning ransomware? >> Yeah, this was a worldwide study. It was sponsored by Druva and conducted by IDC as an independent study. And what we did, we surveyed 500, it was a little over 500 different individuals across the globe in North America, select countries in Western Europe, as well as several in Asia Pacific. And we did it across industries there were 20 different industries represented, they're all evenly represented. We had surveys that included IT practitioners, primarily CIOs, CTOs, VP of infrastructure, you know, managers of data centers, things like that. And the biggest finding that we had in this, Lisa, was really finding that there is a huge disconnect, I believe, between how people think they are ready and what the actual results are when they get attacked. Some of the statistics that we learned from this, Lisa, include 83% of organizations believe, or told us that they have a playbook that they have for ransomware. I think 93% said that they have a high degree, or a high or very high degree of confidence in their recovery tools and are fully automated. And yet, when you look at the actual results, you know, I told you a moment ago, 46% have been attacked successfully. I can also tell you that in separate research, fewer than 1/3 of organizations were able to fully recover their data without paying the ransom, and some 2/3 actually had to pay the ransom. And even when they did, they didn't necessarily achieve their full recovery. You know, the bad guys aren't necessarily to be trusted, and so the software that they provide sometimes is fully recovered, sometimes it's not. So you look at that and you go, wow. On the one hand, people think they're really, really prepared, and on the other hand, the results are absolutely horrible. You know, 2/3 of people having to pay the ransom. So you start to ask yourself, well, what's going on there? And I believe that a lot of it comes down to, kind of reminds me of the old quote from Mike Tyson. "Everybody has a plan until they get punched in the mouth." And I think that's kind of what happens with ransomware. You think you know what you're doing. You think you're ready, based on the information you have. And these people are smart people, and they're professionals, but oftentimes, you don't know what you don't know. And like I said, the bad guys are always dreaming up new ways to attack us. And so, I think, for that reason, a lot of these have been successful. So that was kind of the key finding to me and kind of the aha moment really in this whole thing, Lisa. >> That's a massive disconnect with the vast majority saying, "We have a cyber recovery playbook," yet nearly 1/2 being the victims of ransomware in the last three years, and then 1/2 of them experiencing data loss. What is it then that organizations in this situation across any industry can do to truly enable cyber resilience, data resilience? As we said, this is a matter of this is going to happen, just a matter of when and how often. >> It is a matter, yeah, as you said, it's not if, when, or how often, it's really how badly. So I think what organizations are really doing now is starting to turn more to cloud-based services, you know, finding professionals who know what they're doing, who have that breadth of experience and who have seen the kinds of necessary steps that it takes to do a recovery. And the fact of the matter is a disaster recovery and a cyber recovery are really not the same thing. And so organizations need to be able to plan the kinds of recovery associated with cyber recovery in terms of forensics, in terms of scanning, in terms of analysis, and so forth. So they're turning to professionals in the cloud much more, in order to get that breadth of experience, and to take advantage of cloud-based services that are out there. >> Talk to me about some of the key advantages of cloud-based services for data resilience versus traditional legacy on-prem equipment. What are some of the advantages? Why is IDC seeing this big shift to cloud where data resilience is concerned? >> Well, the first and foremost is the economics of it. You know, you can have on-demand resources. In the old days, when we had disaster recoveries where we had two different data centers and a failover and so forth, you know, you had double the infrastructure. If you're financial services, it might even be triple the infrastructure. It was very complicated, very difficult. By going to the cloud, organizations can subscribe to disaster recovery as a service. And increasingly what we see is a new market of cyber recovery as a service. So being able to leverage those resources, to be able to have the forensic analysis available to them, to be able to have the other resources available that are on demand, and to have that plan in place to have those resources in place. I think what happens in a number of situations, Lisa, is that organizations think they're ready, but then all of a sudden they get hit, and all of a sudden they have to engage with outside consultants, or they have to bring in other experts, and that extends the time to recover that they have and it also complicates it. So if they have those resources in place, then they can simply turn them on, engage them, and get that recovery going as quickly as possible. >> So what do you think the big issue here is? Is it that these IPT practitioners, over 500 that you surveyed across 20 industries, this a global survey, do they they not know what they don't know? What's the overlying issue here? >> Yeah, I think that's right. You don't know what you don't know, and until you get into a specific attack, you know, there are so many different ways that organizations can be attacked. And, in fact, from this research that we found is that, in many cases, data exfiltration exceeds data corruption by about 50%. But when you think about that, the issue is, once I have your data, what are you going to do? I mean, there's no amount of recovery that is going to help. So organizations are either faced with paying the ransom to keep the data from perhaps being used on the dark web, or whatever, or simply saying no, and taking their chances. So best practice things like encryption, immutability, things like that that organizations can put into place. Certainly air gaps, having a solid backup foundation to where data is, you have a high recovery, high probability of recovery, things like that. Those are the kinds of things that organizations have to put into place, really as a baseline to assure that they can recover as fast as possible and not lose data in the event of a ransomware attack. >> Given some of the disconnect that you articulated, the stats that show so many think we are prepared, we've got a playbook, yet so many are being attacked, the vulnerabilities as the landscape, threat landscape, just gets more and more amorphous. What do you recommend organizations do? You talked to the IT practitioners, but does this go all the way up to the board level in terms of, hey guys, across every industry, we are vulnerable, this is going to happen. We've got to make sure that we are truly resilient and proactive? >> Yes, and in fact, what we found from this research is in more than 1/2 of cases, the CEO is directly involved in the recovery. So this is very much a C-suite issue. And if you look at the consequences of ransomware, it's not just the ransom, it's the lost productivity, it's the loss of revenue. It's the loss of customer faith and goodwill, and organizations that have been attacked have suffered those consequences, and many of them are permanent. So people at the board level, whether it's the CEO, the CFO, the CIO, the CSO, you know, whoever it is, they're extremely concerned about these. And I can tell you, they are fully engaged in addressing those issues within their organization. >> So all the way at the top, and critically important, business critical for any industry. I imagine some industries may be a little bit more vulnerable than others, financial services, healthcare, education. We've just seen a big attack in Los Angeles County. But in terms of establishing data resilience, you mentioned ransomware isn't going anywhere, it's a big business, it's very profitable. But what is IDC's prediction where ransomware is concerned? Do you think that organizations, if they truly adopt cloud and SaaS-based technologies, can they get to a place where the C-suite doesn't have to be involved to the point where they really actually have a functioning playbook? >> I don't know if we'll ever get to the point where the C-suite is not involved. It's probably very important to have that level of executive sponsorship. But what we are seeing is, in fact, we predict that by 2025, 55% of organizations will have shifted to a cloud-centric strategy for their data resilience. And the reason we say that is, you know, workloads on premises aren't going away. So that's the core. We have an increasing number of workloads in the cloud and at the edge, and that's really where the growth is. So being able to take that cloud-centric model and take advantage of cloud resources like immutable storage, being able to move data from region to region inexpensively and easily, and to be able to take that cloud-centric perspective and apply it on premises as well as in the cloud and at the edge is really where we believe that organizations are shifting their focus. >> Got it, we're just cracking the surface here, Phil. I wish we had more time, but I had a chance to read the Druva-sponsored IDC white paper. Fascinating finds. I encourage all of you to download that, take a read. You're going to learn some very interesting statistics and recommendations for how you can really truly deploy data resilience in your organization. Phil, it's been a pleasure to have you on the program. Thank you for joining me. >> No problem. Thank you, Lisa. >> In a moment, John Furrier will be here with his next guest. For right now, I'm Lisa Martin, and you are watching theCUBE, the leader in live tech coverage. >> We live in a world of infinite data. Sprawling, dispersed, valuable, but also vulnerable. So how do organizations achieve data resiliency when faced with ever expanding workloads, increasing security threats, and intensified regulations? Unfortunately, the answer often boils down to what flavor of complexity do you like best? The common patchwork approaches are expensive, convoluted, and difficult to manage. There's multiple software and hardware vendors to worry about, different deployments for workloads running on-premises or in the cloud. And an inconsistent security framework resulting in enterprises maintaining four to five copies of the same data, increasing costs and risk, building to an incoherent mess of complications. Now, imagine a world free from these complexities. Welcome to the the Druva Data Resiliency Cloud, where full data protection and beautiful simplicity converge. No hardware, no upgrades, no management, just total data resilience. With just a few clicks, you can get started integrating all of your data resiliency workflows in minutes. Through a true cloud experience built on Amazon Web Services, the Druva platform automates and manages critical daily tasks, giving you time to focus on your business. In other words, get simplicity, scalability, and security instantly. With the Druva Data Resiliency Cloud, your data isn't just backed up, it's ready to be used 24/7 to meet compliance needs and to extract critical insights. You can archive data for long-term retention, be protected against device failure and natural disasters, and recover from ransomware lightning fast. Druva is trusted with billions of backups annually by thousands of enterprises, including more than 60 of the Fortune 500, costing up to 50% less than the convoluted hardware, software, and appliance solutions. As data grows and becomes more critical to your business advantage, a data resiliency plan is vital, but it shouldn't be complicated. Druva makes it simple. (upbeat music) (mouse clicks) >> Welcome back, everyone, to theCUBE and the Druva special presentation of "Why Ransomware isn't Your Only Problem." I'm John Furrier, host of theCUBE. We're here with W Curtis Preston, Curtis Preston, as he's known in the industry, Chief Technical Evangelist at Druva. Curtis, great to see you. We're here at "Why Ransomware isn't Your Only Problem." Great to see you, thanks for coming on. >> Happy to be here. >> So we always see each other at events now events are back. So it's great to have you here for this special presentation. The white paper from IDC really talks about this in detail. I'd like to get your thoughts, and I'd like you to reflect on the analysis that we've been covering here in this survey data, how it lines up with the real world that you're seeing out there. >> Yeah, I think it's, the survey results really, I'd like to say, I'd like to say that they surprised me, but unfortunately, they didn't. The data protection world has been this way for a while where there's this difference in belief, or difference between the belief and the reality. And what we see is that there are a number of organizations that have been hit, successfully hit by ransomware, paid the ransom and/or lost data, and yet the same people that were surveyed, they had high degrees of confidence in their backup system. And, you know, I could probably go on for an hour as to the various reasons why that would be the case, but I think that this long running problem that as long as I've been associated with backups, which, you know, has been a while, it's that problem of, you know, nobody wants to be the backup person. And people often just, they don't want to have anything to do with the backup system, and so it sort of exists in this vacuum. And so then management is like, "Oh, the backup system's great," because the backup person often, you know, might say that it's great because maybe it's their job to say so. But the reality has always been very, very different. >> It's funny, you know. "We're good, boss, we got this covered." >> Yeah, it's all good, it's all good. >> And the fingers crossed, right? So again, this is the reality, and as it becomes backup and recovery, which we've talked about many times on theCUBE, certainly we have with you before, but now with ransomware, also, the other thing is people get ransomware hit multiple times. So it's not only like they get hit once, so, you know, this is a constant chasing the tail on some ends, but there are some tools out there, You guys have a solution, and so let's get into that. You know, you have had hands-on backup experience. What are the points that surprise you the most about what's going on in this world and the realities of how people should be going forward? What's your take? >> Well, I would say that the one part in the survey that surprised me the most was people that had a huge, you know, there was a huge percentage of people that said that they had, you know, a ransomware response, you know, and readiness program. And you look at that, and how could you be, you know, that high a percentage of people be comfortable with their ransomware readiness program, which includes a number of things, right? There's the cyberattack aspect of responding to a ransomware attack, and then there's the recovery aspect. And so you believe that your company was ready for that, and then you go, and I think it was 67% of the people in the survey paid the ransom, which as a person who, you know, has spent my entire career trying to help people successfully recover their data, that number, I think, just hurt me the most is that because, you talked about re-infections. The surest way to guarantee that you get re-attacked and reinfected is to pay the ransom. This goes back all the way to ransom since the beginning of time, right? Everyone knows if you pay the blackmail, all you're telling people is that you pay blackmail. >> You're in business, you're a good customer >> Yeah, yeah, exactly. >> for ransomware. >> Yeah, so the fact that, you know, 60, what, 2/3 of the people that were attacked by ransomware paid the ransom. That one statistic just hurt my heart. >> Yeah, and I think this is the reality. I mean, we go back, and even the psychology of the practitioners was, you know, it's super important to get backup and recovery, and that's been around for a long time, but now that's an attack vector, okay? And there's dollars involved, like I said, I'm joking, but there's recurring revenue for the bad guys if they know you're paying up and if you're stupid enough not to change your tooling. So again, it works both ways. So I got to ask you, why do you think so many owners are unable to successfully respond after an attack? Is it because, they know it's coming, I mean, they're not that dumb. I mean, they have to know it's coming. Why aren't they responding successfully to this? >> I think it's a litany of things, starting with that aspect that I mentioned before, that nobody wants to have anything to do with the backup system, right? So nobody wants to be the one to raise their hand because if you're the one that raises their hand, "You know, that's a good idea, Curtis, why don't you look into that?" Nobody wants to be- >> Where's that guy now? He doesn't work here anymore. Yeah, I hear where you coming from. >> Exactly. >> It's psychology (indistinct) >> Yeah, so there's that. But then the second is that because of that, no one's looking at the fact that backups are the attack vector. They become the attack vector. And so because they're the attack vector, they have to be protected as much, if not more than the rest of the environment. The rest of the environment can live off of Active Directory and, you know, and things like Okta, so that you can have SSO and things like that. The backup environment has to be segregated in a very special way. Backups have to be stored completely separate from your environment. The login and authentication and authorization system needs to be completely separate from your typical environment. Why? Because if that production environment is compromised, now knowing that the attacks or that the backup systems are a significant portion of the attack vector, then if the production system is compromised, then the backup system is compromised. So you've got to segregate all of that. And I just don't think that people are thinking about that. You know, and they're using the same backup techniques that they've used for many, many years. >> So what you're saying is that the attack vectors and the attackers are getting smarter. They're saying, "Hey, we'll just take out the backup first so they can't backup. So we got the ransomware." It makes sense. >> Yeah, exactly. The largest ransomware group out there, the Conti ransomware group, they are specifically targeting specific backup vendors. They know how to recognize the backup servers. They know how to recognize where the backups are stored, and they are exfiltrating the backups first, and then deleting them, and then letting you know you have ransom. >> Okay, so you guys have a lot of customers. They all kind of have the same problem. What's the patterns that you're seeing? How are they evolving? What are some of the things that they're implementing? What is the best practice? >> Well, again, you've got to fully segregate that data, and everything about how that data is stored and everything about how that data's created and accessed, there are ways to do that with other, you know, with other commercial products. You can take a standard product and put a number of layers of defense on top of it, or you can switch to the way Druva does things, which is a SaaS offering that stores your data completely in the cloud in our account, right? So your account could be completely compromised. That has nothing to do with our account. It's a completely different authentication and authorization system. You've got multiple layers of defense between your computing environment and where we store your backups. So basically, what you get by default with the way Druva stores your backups is the best you can get after doing many, many layers of defense on the other side and having to do all that work. With us, you just log in and you get all of that. >> I guess, how do you break the laws of physics? I guess that's the question here. >> Well, because that's the other thing is that by storing the data in the cloud, and I've said this a few times, you get to break the laws of physics, and the only way to do that is time travel. (both laughing) So yes, so Druva has time travel. And this is a Curtisism, by the way, I don't think this is our official position, but the idea is that the only way to restore data as fast as possible is to restore it before you actually need it, and that's kind of what I mean by time travel, in that you, basically, you configure your DR, your disaster recovery environment in Druva one time, and then we are pre-restoring your data as often as you tell us to do, to bring your DR environment up to the, you know, the current environment as quickly as we can so that in a disaster recovery scenario, which is part of your ransomware response, right? Again, there are many different parts, but when you get to actually restoring the data, you should be able to just push a button and go. The data should already be restored. And that's the way that you break the laws of physics is you break the laws of time. >> (laughs) Well, all right, everyone wants to know the next question, and this is a real big question is, are you from the future? >> (laughs) Yeah. Very much the future. >> What's it like in the future, backup, recovery? How does it restore? Is it air gapping everything? >> Yeah, well, it's a world where people don't have to worry about their backups. I like to use the phrase get out of the backup business, just get into the restore business. You know, I'm a grandfather now, and I love having a granddaughter, and I often make the joke that if I'd have known how great grandkids were, I would've skipped straight to them, right? Not possible. Just like this. Recoveries are great. Backups are really hard. So in the future, if you use a SaaS data protection system and data resiliency system, you can just do recoveries and not have to worry about backups. >> Yeah, and what's great about your background is you've got a lot of historical perspective. You've seen that, the waves of innovation. Now it really is about the recovery and real time. So a lot of good stuff going on. And got to think automated, things got to be rocking and rolling. >> Absolutely. Yeah. I do remember, again, having worked so hard with many clients over the years, back then, we worked so hard just to get the backup done. There was very little time to work on the recovery. And I really, I kid you not, that our customers don't have to do all of those things that all of our competitors have to do to, you know, to break, to try to break the laws of physics, I've been fighting the laws of physics my entire career, to get the backup done in the first place, then to secure all the data, and to air gap it and make sure that a ransomware attack isn't going to attack it. Our customers get to get straight to a fully automated disaster recovery environment that they get to test as often as possible and they get to do a full test by simply pressing a single button. And you know, I wish everybody had that ability. >> Yeah, I mean, security's a big part of it. Data's in the middle of it all. This is now mainstream, front lines, great stuff. Curtis, great to have you on, bring that perspective, and thanks for the insight. Really appreciate it. >> Always happy to talk about my favorite subject. >> All right, we'll be back in a moment. We'll have Stephen Manley, the CTO, and Anjan Srinivas, the GM and VP of Product Management will join me. You're watching theCUBE, the leader in high tech enterprise coverage. >> Ransomware is top of mind for everyone. Attacks are becoming more frequent and more sophisticated. It's a problem you can't solve alone anymore. Ransomware is built to exploit weaknesses in your backup solution, destroying data, and your last line of defense. With many vendors, it can take a lot of effort and configuration to ensure your backup environment is secure. Criminals also know that it's easy to fall behind on best practices like vulnerability scans, patches, and updates. In fact, 42% of vulnerabilities are exploited after a patch has been released. After an attack, recovery can be a long and manual process that still may not restore clean or complete data. The good news is that you can keep your data safe and recover faster with the Druva Data Resiliency Cloud on your side. The Druva platform functions completely in the cloud with no hardware, software, operating system, or complex configurations, which means there are none of the weaknesses that ransomware commonly uses to attack backups. Our software as a service model delivers 24/7/365 fully managed security operations for your backup environment. We handle all the vulnerability scans, patches, and upgrades for you. Druva also makes zero trust security easy with built-in multifactor authentication, single sign-on, and role-based access controls. In the event of an attack, Druva helps you stop the spread of ransomware and quickly understand what went wrong with built-in access insights and anomaly detection. Then you can use industry first tools and services to automate the recovery of clean, unencrypted data from the entire timeframe of the attack. Cyberattacks are a major threat, but you can make protection and recovery easy with Druva. (electronic music) (upbeat music) (mouse clicks) >> Welcome back, everyone, to theCUBE's special presentation with Druva on "Why Ransomware isn't Your Only Problem." I'm John Furrier, host of theCUBE. Our next guests are Stephen Manley, Chief Technology Officer of Druva, and Anjan Srinivas, who is the General Manager and Vice President of Product Management at Druva. Gentlemen, you got the keys to the kingdom, the technology, ransomware, data resilience. This is the topic. The IDC white paper that you guys put together with IDC really kind of nails it out. I want to get into it right away. Welcome to this segment. I really appreciate it. Thanks for coming on. >> Great to be here, John. >> So what's your thoughts on the survey's conclusion? Obviously, the resilience is huge. Ransomware continues to thunder away at businesses and causes a lot of problems, disruption. I mean, it's endless ransomware problems. What's your thoughts on the conclusion? >> So I'll say the thing that pops out to me is, on the one hand, everybody who sees the survey and reads it is going to say, "Well, that's obvious." Of course, ransomware continues to be a problem. Cyber resilience is an issue that's plaguing everybody. But I think when you dig deeper and there's a lot of subtleties to look into, but one of the things that I hear on a daily basis from the customers is, it's because the problem keeps evolving. It's not as if the threat was a static thing to just be solved and you're done. Because the threat keeps evolving, it remains top of mind for everybody because it's so hard to keep up with what's happening in terms of the attacks. >> And I think the other important thing to note, John, is that people are grappling with this ransomware attack all of a sudden where they were still grappling with a lot of legacy in their own environment. So they were not prepared for the advanced techniques that these ransomware attackers were bringing to market. It's almost like these ransomware attackers had a huge leg up in terms of technology that they had in their favor while keeping the lights on was keeping IT away from all the tooling that they needed to do. A lot of people are even still wondering, when that happens next time, what do I even do? So clearly not very surprising. Clearly, I think it's here to stay, and I think as long as people don't retool for a modern era of data management, this is going to to stay this way. >> Yeah, I hear this all the time in our CUBE conversations with practitioners. It's kind of like the security pro, give me more tools, I'll buy anything that comes in the market, I'm desperate. There's definitely attention, but it doesn't seem like people are satisfied with the tooling that they have. Can you guys share kind of your insights into what's going on in the product side? Because, you know, people claim that they have tools at crime points of recovery opportunities, but they can't get there. So it seems to be that there's a confidence problem here in the market. How do you guys see that? 'cause I think this is where the rubber meets the road with ransomware 'cause it is a moving train, it's always changing, but it doesn't seem there's confidence. Can you guys talk about that? What's your reaction? >> Yeah, let me jump in first, and Stephen can add to it. What happens is, I think this is a panic buying and they have accumulated this tooling now just because somebody said they could solve your problem, but they haven't had a chance to take a real look from a ground up perspective to see where are the bottlenecks? Where are the vulnerabilities? And which tooling set needs to lie where? Where does the logic need to reside? And what, in Druva, we are watching people do and people do it successfully, is that as they have adopted Druva technology, which is ground up built for the cloud, and really built in a way which is, you know, driven at a data insight level where we have people even monitoring our service for anomalies and activities that are suspicious. We know where we need to play a role in really kind of mitigating this ransomware, and then there's a whole plethora of ecosystem players that kind of combine to really finish the story, so to say, right? So I think this has been a panic buying situation. This is like, "Get me any help you can give me." And I think as this settles down and people really understand that longer term as they really build out a true defense mechanism, they need to think really ground up. They will start to really see the value of technologies like Druva, and try to identify the right set of ecosystem to really bring together to solve it meaningfully. >> Yes, Stephen? >> I was going to say, I mean, one of the the really interesting things in the survey for me, and for a moment, a little more than a moment, it made me think was that the large number of respondents who said, "I've got a really efficient, well-run back environment," who, then, on basically the next question said, "And I have no confidence that I can recover from a ransomware attack." And you scratch your head and you think, "Well, if your backup environment is so good, why do you have such low confidence?" And I think that's the moment when we dug deeper and we realized, if you've got a traditional architecture, and let's face it, the disk-based architecture's been around for almost two decades now, in terms of disk-based backup, you can have that tuned to the hilt. That can be running as efficiently as you want it, but it was built before the ransomware attacks, before all these cyber issues, you know, really start hitting companies. And so I have this really well-run traditional backup environment that is not at all built for these modern threat vectors. And so that's really why customers are saying, "I'm doing the best I can," but as Anjan pointed out, the architecture, the tooling isn't there to support what problems I need to solve today. >> Yeah, great point. >> And so, yeah. >> Well, that's a great point. Before we get into the customer side I want to get to in second, you know, I interviewed Jaspreet, the founder and CEO many years ago, even before the pandemic, and you mentioned modern. You guys have always had the cloud with Druva. This is huge. Now that you're past the pandemic, what is that modern cloud edge that you guys have? 'Cause that's a great point. A lot of stuff was built kind of backup and recovery bolted on, not really kind of designed into the current state of the infrastructure and the cloud native application modern environment we're seeing right now. It's a huge issue. >> I think, to me there's three things that come up over and over and over again as we talk to people in terms of, you know, being built in cloud, being cloud native, why is it an advantage? The first one is security and ransomware. And we can go deeper, but the most obvious one that always comes up is every single backup you do with Druva is air gapped, offsite, managed under a separate administrative domain so that you're not retrofitting any sort of air gap network and buying another appliance or setting up your own cloud environment to manage this. Every backup is ransomware protected, guaranteed. The second advantage is the scalability. And you know, this certainly plays into account as your business grows, or, in some cases, as you shrink or repurpose workloads, you're only paying for what you use. But it also plays a big role, again, when you start thinking of ransomware recoveries because we can scale your recovery in cloud, on premises as much or as little as you want. And then I think the third one is we're seeing, basically, things evolving, new workloads, data sprawl, new threat vectors. And one of the nice parts of being a SaaS service in the cloud is we're able to roll out new functionality every two weeks and there's no upgrade cycle, there's no waiting. The customer doesn't have to say, "Wow, I needed six months in the lab before I upgrade it and it's an 18-month, 24-month cycle before the functionality releases. You're getting it every two weeks, and it's backed by Druva to make sure it works. >> Anjan, you know, you got the product side, you know, it's a challenging job 'cause you have so many customers asking for things, probably on the roadmap, you probably can go an hour for that one, but I want to get your thoughts on what you're hearing and seeing from customers. We just reviewed the IDC with Phil. How are you guys responding to your customer's needs? Because it seems that it's highly accelerated, probably on the feature requests, but also structurally as ransomware continues to evolve. What are you hearing? What's the key customer need? How are you guys responding? >> Yeah, actually, I have two things that I hear very clearly when I talk to customers. One, I think, after listening to their security problems and their vulnerability challenges, because we see customers and help customers who are getting challenged by ransomware on a weekly basis. And what I find that this problem is not just a technology problem, it's an operating model problem. So in order to really secure themselves, they need a security operating model and a lot of them haven't figured out that security operating model in totality. Now where we come in, as Druva, is that we are providing them the cloud operating model and a data protection operating model, combined with a data insights operating model which all fit into their overall security operating model that they are really owning and they need to manage and operate, because this is not just about a piece of technology. On top of that, I think our customers are getting challenged by all the same challenges of not just spending time on keeping the lights on, but innovating faster with less. And that has been this age old problem, do more with less. But in this whole, they're like trying to innovate in the middle of the war, so to say. The war is happening, they're getting attacked, but there's also net new shadow IT challenges that's forcing them to make sure that they can manage all the new applications that are getting developed in the cloud. There is thousands of SaaS applications that they're consuming, not knowing which data is critical to their success and which ones to protect and govern and secure. So all of these things are coming at them at 100 miles per hour, while they're just trying to live one day at a time. And unless they really develop this overall security operating model, helped by cloud native technologies like Druva that really providing them a true cloud native model of really giving like a touchless and an invisible protection infrastructure. Not just beyond backups, beyond just the data protection that we all know of into this mindset of kind of being able to look at where each of those functionalities need to lie. That's where I think they're grappling with. Now Druva is clearly helping them with keep up to pace with the public cloud innovations that they need to do and how to protect data. We just launched our EC2 offering to protect EC2 virtual machines back in AWS, and we are going to be continuing to evolve that to further the many services that public cloud software 'cause our customers are really kind of consuming them at breakneck speed. >> So new workloads, new security capabilities. Love that. Good call out there. Stephen, there's still the issue of the disruption side of it. You guys have a guarantee. There's a cost of ownership as you get more tools. Can you talk about that angle of it? You got new workloads, you got the new security needs, what's the disruption impact? 'Cause you want to avoid that. How much is it going to cost you? And you guys have this guarantee, can you explain that? >> Yeah, absolutely. So Druva launched our $10 million data resiliency guarantee. And for us, there were really two key parts to this. The first obviously is $10 million means that, you know, again, we're willing to put our money where our mouth is, and that's a big deal, right? That we're willing to back this with the guarantee. But then the second part, and this is the part that I think reflects that sort of model that Anjan was talking about. We sort of look at this and we say the goal of Druva is to do the job of protecting and securing your data for you so that you, as a customer, don't have to do it anymore. And so the guarantee actually protects you against multiple types of risks, all with SLAs. So everything from your data's going to be recoverable in the case of a ransomware attack. Okay, that's good. Of course, for it to be recoverable, we're also guaranteeing your backup success rate. We're also guaranteeing the availability of the service. We're guaranteeing that the data that we're storing for you can't be compromised or leaked externally, and we're guaranteeing the long-term durability of the data so that if you backup with us today and you need to recover 30 years from now, that data's going to be recovered. So we wanted to really attack the end-to-end risks that affect our customers. Cybersecurity is a big deal, but it is not the only problem out there, and the only way for this to work is to have a service that can provide you SLAs across all of the risks, because that means, as a SaaS vendor, we're doing the job for you so you're buying results as opposed to technology. >> That's great. Great point. Ransomware isn't the only problem. That's the title of this presentation, but it's a big one. (laughs) People are concerned about it, so great stuff. In the last five minutes, guys, if you don't mind, I'd love to have you share what's on the horizon for Druva? You mentioned the new workloads, Anjan. You mentioned this new security. You're going to shift left. DevOps is now the developer model. They're running IT. Get data and security teams now stepping in and trying to be as high velocity as possible for the developers and enterprises. What's on the horizon for Druva? What trends is the company watching, and how are you guys putting that together to stay ahead in the marketplace and the competition? >> Yeah, I think, listening to our customers, what we realize is they need help with the public cloud, number one. I think that's a big wave of consumption. People are consolidating their data centers, moving to the public cloud. They need help in expanding data protection, which becomes the basis of a lot of the security operating model that I talked about. They need that first, from Druva, before they can start to get into much more advanced level of insights and analytics around that data to protect themselves and secure themselves and do interesting things with that data. So we are expanding our coverage on multiple fronts there. The second key thing is to really bring together a very insightful presentation layer, which, I think, is very unique to Druva because only we can look at multiple tenants, multiple customers because we are a SaaS vendor, and look at insights and give them best practices and guidances and analytics that nobody else can give. There's no silo anymore because we are able to take a good big vision view and now help our customers with insights that otherwise that information map is completely missing. So we are able to guide them down a path where they can optimize which workloads need what kind of protection, and then how to secure them. So that is the second level of insights and analytics that we are building. And there's a whole plethora of security offerings that we are going to build, all the way from a feature level where we have things like (audio distorts) that's already available to our customers today to prevent any anomalous behavior and attacks that would delete their backups and then they still have a way to recover from it, but also things to curate and get back to that point in time where it is safe to recover and help them with a sandbox which they can recover confidently knowing it's not going to jeopardize them again and reinfect the whole environment again. So there's a whole bunch of things coming, but the key themes are public cloud, data insights, and security, and that's where my focus is, to go and get those features delivered, and Stephen can add a few more things around services that Stephen is looking to build and launch. >> Sure, so, yeah, so John, I think one of the other areas that we see just an enormous groundswell of interest. So public cloud is important, but there are more and more organizations that are running hundreds, if not thousands of SaaS applications, and a lot of those SaaS applications have data. So there's the obvious things, like Microsoft 365, Google Workspace, but we're also seeing a lot of interest in protecting Salesforce because, if you think about it, if someone you know deletes some really important records in Salesforce, that's actually kind of the record of your business. And so, we're looking at more and more SaaS application protection, and really getting deep in that application awareness. It's not just about backup and recovery when you look at something like a Salesforce, or something like Microsoft 365. You do want to look into sandboxing, you want to look into long-term archival, because this is the new record of the business. What used to be in your on-premises databases, that all lives in cloud and SaaS applications now. So that's a really big area of investment for us. The second one, just to echo what Anjan said is, one of the great things of being a SaaS provider is I have metadata that spans across thousands of customers and tens of billions of backups a year. I'm tracking all sorts of interesting information that is going to enable us to do things like make backups more autonomous so that customers, again, I want to do the job for them. We'll do all the tuning, we'll do all the management for them to be able to better detect ransomware attacks, better respond to ransomware attacks, because we're seeing across the globe. And then, of course, being able to give them more insight into what's happening in their data environment so they can get a better security posture before any attack happens. Because, let's face it, if you can set your data up more cleanly, you're going to be a lot less worried and a lot less exposed when that attack happens. So we want to be able to, again, cover those SaaS applications in addition to the public cloud, and then we want to be able to use our metadata and use our analytics and use this massive pipeline we've got to deliver value to our customers. Not just charts and graphs, but actual services that enable them to focus their attention on other parts of the business. >> That's great stuff. >> And remember, John, I think all this while keeping things really easy to consume, consumer grade UI, APIs, and then really the power of SaaS as a service, simplicity to kind of continue on, amongst kind of keeping these complex technologies together. >> Anjan, that's a great callout. I was going to mention ease of use and self-service. Big part of the developer and IT experience. Expected. It's the table stakes. Love the analytic angle, I think that brings the scale to the table, and faster time to value to get to learn best practices. But at the end of the day, automation, cross-cloud protection and security to protect and recover. This is huge, and this is a big part of not only just protecting against ransomware and other things, but really being fast and being agile. So really appreciate the insights. Thanks for sharing on this segment, really under the hood and really kind of the value of the product. Thanks for coming on, appreciate it. >> Thank you very much. >> Okay, there it is. You have the experts talk about under the hood, the product, the value, the future of what's going on with Druva, and the future of cloud native protecting and recovering. This is what it's all about. It's not just ransomware they have to worry about. In a moment, Dave Vellante will give you some closing thoughts on the subject here. You're watching theCUBE, the leader in high tech enterprise coverage. >> As organizations migrate their business processes to multi-cloud environments, they still face numerous threats and risks of data loss. With a growing number of cloud platforms and fragmented applications, it leads to an increase in data silos, sprawl, and management complexity. As workloads become more diverse, it's challenging to effectively manage data growth, infrastructure, and resource costs across multiple cloud deployments. Using numerous backup vendor solutions for multiple cloud platforms can lead to management complexity. More importantly, the lack of centralized visibility and control can leave you exposed to security vulnerabilities, including ransomware that can cripple your business. The Druva Data Resiliency Cloud is the only 100% SaaS data resiliency platform that provides centralized, secure, air gapped, and immutable backup and recovery. 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(upbeat music) >> One of the big takeaways from today's program is that in the scramble to keep business flowing over the past 2+ years, a lot of good technology practices have been put into place, but there's much more work to be done, specifically, because the frequency of attacks is on the rise and the severity of lost, stolen, or inaccessible data is so much higher today, business resilience must be designed into architectures and solutions from the start. It cannot be an afterthought. Well, actually it can be, but you won't be happy with the results. Now, part of the answer is finding the right partners, of course, but it also means taking a system's view of your business, understanding the vulnerabilities and deploying solutions that can balance cost efficiency with appropriately high levels of protection, flexibility, and speed slash accuracy of recovery. Here we hope you found today's program useful and informative. Remember, this session is available on demand in both its full format and the individual guest segments. All you got to do is go to thecube.net, and you'll see all the content, or you can go to druva.com. There are tons of resources available, including analyst reports, customer stories. There's this cool TCO calculator. You can find out what pricing looks like and lots more. Thanks for watching "Why Ransomware isn't Your Only Problem," made possible by Druva, in collaboration with IDC and presented by theCUBE, your leader in enterprise and emerging tech coverage. (upbeat music)

>>Hey everyone. Welcome back to Miami, Miami Beach. Specifically, not a bad location to have a conference. Lisa Martin here with the Cube live at IFS Unleashed. We're gonna be having a great conversation next about Ization moments of Service Rules. Royces here, as is the C of IFS for aerospace and defense. Scott Camani. Nick Ward joins us as well, the VP of Digital Systems at Roll Royce. Guys, excited to have you on the program and welcome back. >>Thank you very much. Nice to be back. It's >>Been three years since the last IFS show. I love How's Scott? I was talking with Darren Roots earlier today and I said, Well, didn't it used to be IFS world? And he said, Yes. And I said, I love the name. I would love to, to unpack that with your cheek marketing officer because it, there's a lot of, of, of power behind Unleash. A lot of companies do such and such world or accelerate, but we're talking about unleashing the power of the technology to help customers deliver those moments of service. Yes. Love it. So Scott, start us off here. Talk about ization. That's a relatively new term to me. Sure. Help me understand what it means, because IFS is a pioneer in this sense. >>We are. So one of the things that IFS is always trying to do is to try to find a way to help our customers to realize a moment of service. And that moment of service is really when they found the ability to delight their customers. And when we look at the way in which we're trying to drive those business outcomes for our customers, ization seems to be at the core of it. So whether it's the ability for a company to use a product, a service, or an outcome, they're driving ization in a way where they're shaping their business. They're orchestrating their customers and their people and their assets behind a val value chain that helps them to provide a delightful experience for their customers. And with IFS being focused on Lifecycle asset management, we no longer have customers that have to choose from best of suite or best of breed. They can actually have both with ifs. And that's something we're really excited to provide to our customers and more excited for our customers to realize that value with their customers, their partners. Along the way. >>You, you mentioned customer delight and it's a term that we, we all use it, right? But there's so much power and, and capabilities and metrics behind that phrase, customer delight, which will unpack Nick bringing you into the conversation. Talk to us a little bit about what your role is at Rolls Royce. My first thought when I saw you was, oh, the fancy cars, but we're talking about aerospace and the fence, so give us a little bit of a history. >>Okay. So yes, we don't make cars is the first point. So we are, we are power, we do power as a service. So we are most well known, I guess for large aircraft airliners. You know, if you've, if you've flown here to Miami, there's probably a 50 50 chance you've flown on a Rod Roy powered aircraft. Our market segment is what we call wide bodied aircraft where you go on, there's two aisles. So the larger section of the market, and we, we provide power, so we provide the engines, but more importantly, we've been a ization company, a service company for at least two decades. We, we have a, a service relationship we call total care. And the whole idea of total care is, yes, I have my engine, it's on my aircraft, but I take care of it. I make sure it's available to fly when you need to fly it. And all of the things that have to come together to make that happen, it's a service company. >>Service company. Talk to me a little bit about, and I wanna get got your perspective as well, but the relationship that Roll Royce and IFS have this is a little bit unique. >>Well, I can start, but I I think Nick's gonna be better served to tell us about that as our customer. Nick and I actually started this journey about four years ago, and what we did was, is we were working closely with our perspective customer Rolls-Royce identified what they were looking for as a desired business outcome. And then we found a way through the technology and the software that we provide to all of our enterprise customers globally to find a solution that actually helped to provide a, an outcome not only to Rolls-Royce, but also to our collective downstream customers, commercial operators around the globe. So that's where we started the journey and we're continuing our discussions around other solutions, but that's how we started and it's been an incredible partnership. We're so happy and proud to have Nick as a customer and a advocate of all things ifs and I'll let him kind of continue from his point of view how he sees the partnership in the relationship. >>No, thank you Scott. I think we've, we've always, we've valued the kind of relationship that we have because I think IFS has always got Rolls Royce in terms of strategic direction. What do we try to do? I said, we're a service company. You know, we, we are, we have to have a service relationship with our, our customers, our airlines. To have a service relationship, you have to be able to connect to your service customer. And ifs is a big part of how we connect for data. That's how do we understand what the airline is doing with the engines, but it's also how we return data back into the airline. So we are, we're get a very close integrated relation between us, our airlines, through a bridge that, that ifs create through the maintenance product. Got it. So it works really well. >>I I think I'd make one other point. One of the things that we've always focused on is quantifiable business value. The only way a partnership like this could possibly work is if we have a desired business outcome, but if we're providing value, So the value work that we did in conjunction with Rolls Royce and really identifying that helped to support the business case that allowed this partnership to really begin and flourish. So I I, I'd be remiss if I didn't mention that business value element that's really core to everything we do and all the, the conversations that Nick and I have. >>Well, it's all about outcomes. Absolutely. It's all about outcomes. It >>Is, it has to be about, it's about moments of service, right? That's why we're here, right? So perhaps a moment of service for Robs Royce is every time you're a passenger, you're going through the terminal. You expect your aircraft to be there, ready, waiting for you to get on and depart on time. And our moment of service is every aircraft takes off on time, every time we live. When we die by the quality of that statement, how well we live up to that statement, I think I checked this morning, there's something alike, 600 aircraft in the sky right now with Rolls Royce power carrying passengers. All of those passengers have relied on that moment. Service happening regularly like clockwork. Every single time you don't get any forgiveness for a delay, you get very little forgiveness for a cancellation that has to happen. And then so many things have to come together for that to happen. >>Those 600 aircraft, that's maybe 200,000 people right now in the sky, Wow. Those 200,000 people are trying to connect, They're trying to connect with friends, they're trying to connect with loved ones, family, colleagues, whatever the purpose is of that trip. It's really important to them. And we just have to make sure that that happens for us. We've had something like a million flights so far this year, 300 million people relying on that moment of so is happening. So I really resonate with, with the language that Scott users about the importance of sort of that focal point on when does it all come together? It comes together when as a passenger, I get on the plane and it goes and I get no issues. >>Right. Well people don't tolerate fragmented experiences anymore. No, no. I think one of the things that was in short supply during the pandemic was patience and tolerance. Sure. Not sure how much of that's gonna come back, right? But those integrated connected experiences, as you described so eloquently, Nick, those are table stakes for the customers, but also the brands behind them because of customers are unhappy, the churn rates go way up. And you see that reflected in obviously the success of the business and what you guys are doing together is seems to be quite powerful. Now then when you were on the cube with us three years ago in Boston at IFS back then you first introduced the intelligent engine and the Blue Data thread. Let's talk about the intelligent engine. Just give our audience a refresher of what that actually entails. >>So perhaps if we just step one one step back for that, just to understand how this fits in. So Roro is a service organization. We talked about that. What that means is we take a lot of the, the risk and the uncertainty away from our airline customers on the availability, the costs and maintenance effort associated with having a, having a chat engine. These are incredibly complicated and complex and sophisticated pieces of equipment. The most expensive, most sophisticated pieces of an aircraft. Managing that is, is difficult. And every airline does not want to have to focus on that. They wanna focus on being able to get the passenger on the air after, fly it, look after the airframe. So our role in that is to take that risk away, is to manage those engines, look after their health, look after their life, make sure they're available to fly whenever they need to fly. >>So for us to understand that, we then have to have data, we have to understand the state of every engine, where it is, the health of the engine, the life of that engine, what do we need to do next to that engine? And we can't do that unless we have data and that data flows into a digital platform. The intelligent engine, which is our cloud based ai, big data, all of the iot, all of the big buzzwords are there, right? So the data flows into that, that lets us run the models. It lets us understand, I can see something maybe it's a, it's a small issue, but if I leave it alone, it become a bigger issue. And maybe that will cause disruption further down the line. So we need to understand that we need to preempt it. So preemptive predictive maintenance is a, is a big part of the intelligent engine, but it's more than just that. >>It's also, we can understand how that engine is being flown. We can understand is it having a really intense flight? Is it having a more benign, gentle flight? Wow. That change time after the flight, typically after the flight. But what that means is we can then understand, actually we can keep that engine on the wing longer then you might otherwise have to do, If you have no data, you have to be conservative, safety rules, everything. Sure. So data allows you to say, actually I'm being overly conservative in this space. I can get more flying bios, flying hours from my product by extending the interval between maintenance and the intelligent engine has a large part to play in us justifying that we're able to do that. And then the final part that it does is eventually the engine is gonna have to come off from maintenance. >>These things fly 5 million miles between overhauls. You imagine you try to do that in your family car. It's, it doesn't happen. It's incredibly sophisticated thing can fly 5 million miles and then we take it off for a major overhaul. But there are thousands of these engines in the fleet. We have to understand which engine is going to come off when for what reason, and prepare our maintenance network to then receive the engine and deal with it and get it back to the customer. So the intelligent engine has a massive part to play in understanding the maintenance demand that the flying fleet is then creating. >>Wow, that's fascinating. And so you talked about that three years ago. What's next for that? I imagine there's only more evolution that's gonna happen. >>It keeps growing. It keeps growing. It's driven by the data. The more data we have, the more that we can do with that. I think as well that, you know, one of the big places that we've we've gone is you can do as much predictive analytics as you, like, there's a lot of people we'll talk about doing predictive analytics, but if you don't do the hard yards of turning predictive analytics into outcome Yeah. Then what did you get? You, you got a bit of smart advice. So we, we take that maintenance demand, we then have to understand how that drives the orchestration and the management of all the parts, the people, the work scope definition, the allocating an engine into a maintenance slot, exactly when it's gonna go. And what are we gonna do to, how do we control and manage our inventory to make sure that engine is gonna go through. >>How do we then actually execute the work inside our, our our overall shops? How do we get that engine back and and integrate our logistics process. So the intelligent engine is, if you like, the shiny front end of a process, it's all the buzzwords, but actually the hard yards behind the scene is just as if not more important to get right. And again, this is why I really like the moment of service concept. Because without that, the moment of service doesn't happen. The engine's not there, the part wasn't there. The field service maintenance guy wasn't there to go fix it. >>And brands are affected >>An, an aircraft on the ground earns no revenue for anybody. No. It's, it's a cost. It's it's a big sink of cost. It >>Is, it is. Absolutely. >>And you're helping aircraft only earn engines only earn when they fly. Yeah, >>Yeah. Absolutely. And what a fascinating, the intelligent engine. Scott, talk a little bit about, we talking about power, we can't not talk about sustainability. Yes, I understand that IFS has a new inaugural awards program that Rolls Roys was a recipient of the Change for Good sustainability awards. Congratulations. Thank you very much. And to Scott, talk to me a little bit about the Change for Good program sustainability program. What types of organizations across the industries of expertise are you looking for and why does Rules ROY really highlight what a winner embodies? >>So since Darren has joined IFS as the ceo, he's had a lot of intentional areas that we focused on. And sustainability has been one that's at the top of the list. IFS has a US ambassador Lewis Pew, who's our Chief Sustainability officer, and he helps us to provide worldwide coverage of the efforts around sustainability. So it's not just about ifss ability to become a more sustainable organization, but it's the solutions that IFS is putting together in the five verticals that we focus on that can help those organizations achieve a level of sustainability for their, for their downstream customers, their partners, and for their enterprises themselves. So when we look at, you know, the social ability for us to be more conscientious about leaving the world a better place or trying to do our best to leave the world not as bad as we came into it, sustainability is a real focus for us. And, you know, the way in which we can support an organization like Rolls Royce and Nickel obviously share those areas of focus from Rolls Royce. It's a perfect fit. And congratulations again for the award. Thank you. We're, we're, we're so excited to, to have shared that with you. We have some other customers that have achieved it across different categories, but it's an area of current and continuous focus for ifs. >>Nick, talk to us, take us out here as our last question is the, the focus on sustainability at Rolls Royce. Talk to us a little bit about that and what some of the major efforts are that you've got underway. >>I think, you know, very similar as, as, as Scott taught there, the focus within Rolls Royce as a strategic group level is really high aviation particularly, I mean we're a, we're an engineering company. We're a power company. Power inherently consumes natural resources. It tends to generate climate affecting outcomes. But at the same time, we are an innovative organization and if anybody's gonna help solve climate challenges, it's gonna be organizations like Rolls Royce who are able to bring different technologies into the market. So we have a responsibility to manage and, and optimize the behavior of our, our existing product suite. But we also have a, a vested interest in trying to move aviation on into the next, the next phase. We talk about sustainable aviation. Aviation has to earn the right to exist. People have choices. We've come out of covid, people are used to doing zoom and not flying. >>People are used to doing things when they don't necessarily get on an aircraft and do something. The aviation business always has to earn the right from the public to exist. And increasingly people will make choices about how they fly when they fly, how far they fly based on the sustainability footprint. So it's really important to us to help both our customers operate the aircraft in as sustainable and climate friendly way as we can. It's really important to find those, those balance points between the cost of an operation and it's the impact of an operation. If you go all over and say, I am going to be net, well, not even net to, but zero carbon by almost inference, that means I'm not gonna operate. You have to operate to get to an outcome. But how do I do that? Why I manage my cost, I manage the, the profitability, the organization doing it, right? >>So it has to be financially sustainable, it has to be sustainable for the people operating within it. It has to be sustainable for the planet, right? So we do that in lots of different ways in small places and, and in big places. So small things we do is we help the operator understand if you change your flight profile, you'll generate fewer emissions. You may avoid controls if you flying a different way, maybe you create trails, you'll lose, you'll lose less fuel while you're doing that. So it's cost effective for you. There was always a balance point there between the wear and tear on the engine versus the, the, the environmental impact. And you find that optimum place. One of the first things we started doing with, with Scott is we have a, a way that we life our engine components. And one of the very simple outcomes of that is using that data, the blue data for connection to the customer. >>If we can see, effectively see inside the engine about how well it's wearing and we can extend those maintenance intervals as we talked about, what that eventually does is it reduces the need to take the engine off, ship it around the world. Probably on a great big 7, 4 7 or maybe year or two ago on an Anson off four big engines flying a long distance trek, shipping our engine to an overhaul facility. We're avoiding something like 200 of those shop visit overhauls a year. So every year that's 200 flights there and back again, which don't happen, right? Collectively that's around about 15,000 automobile equivalent emissions just don't happen. So simple things we can do just starts to have accumulative effect, >>Right? Simple things that you're doing that, that have a huge impact. We could talk for so much longer on stability, I'm sure we're out of time, but I can see why Roll Royce was, was the winner of the Inocular award. Congratulations. Well deserved. Well >>Deserved. I well >>Deserved. So interesting to hear about the intelligent engine. So you're gonna have to come back. Hopefully we'll be here next year and we can hear more of the evolution. Cuz I have a feeling there's never a dual moment in what you're doing. >>It's never a dull moment. There's never an end point. >>No. >>Okay, >>Going Scott, Nick, thank you so much for joining me on the program today. Thank you, Lisa. It's great to have you talk through what's going on at ifx and the partnership with Rolls Royce. We >>Appreciate, and again, Nick, Nick, thank you for your continued support in the partnership. >>I thank you, Scott. We appreciate it. Likewise, thank >>You. Kudos all around. All right, for my guests, I'm Lisa Martin, you're watching a Cube live from Miami. We're at IFS unleashed. We'll be back shortly after a break with our next guests. So stick around.

foreign greetings from San Francisco thecube is live this is our second day of wall-to-wall coverage of VMware Explorer 2022. Lisa Martin and Dave Nicholson here we're going to be talking with some ladies from Rackspace next please welcome Adriana Bustamante VP of strategic alliances and Hannah Deuce director of strategic alliances from Rackspace it's great to have you on the program thank you so much for having us good afternoon good morning is it lunchtime already almost almost yes and it's great to be back in person we were just talking about the keynote yesterday that we were in and it was standing room only people are ready to be back they're ready to be hearing from VMware it's ecosystem its Partners it's Community yes talk to us Adriana about what Rackspace is doing with Dell and VMware particularly in the healthcare space sure no so for us Partnerships are a big foundation to how we operate as a company and um and I have the privilege of doing it for over over 16 years so we've been looking after the dell and VMware part partnership ourselves personally for the last three years but they've been long-standing partners for for us and and how do we go and drive more meaningful joint Solutions together so Rackspace you know been around since since 98 we've seen such an evolution of coming becoming more of this multi-cloud transformation agile Global partner and we have a lot of customers that fall in lots of different verticals from retail to public sector into Healthcare but we started noticing and what we're trying trying to drive as a company is how do we drive more specialized Solutions and because of the pandemic and because of post-pandemic and everyone really trying to to figure out what the new normal is addressing different clients we saw that need increasing and we wanted to Rally together with our most strategic alliances to do more Hannah talk about obviously the the pandemic created such problems for every industry but but Healthcare being front and center it still is talk about some of the challenges that Healthcare organizations are coming to Rackspace going help yeah common theme that we've heard from some of our large providers Healthcare Providers has been helped me do more with less which we're all trying to do as we navigate The New Normal but in that space we found the opportunity to really leverage some of our expertise long-term expertise and that the talent and the resource pool that we had to really help in a some of the challenges that are being faced at a resource shortage Talent shortage and so Rackspace is able to Leverage What what we've done for many many years and really tailor it to the outcomes that Health Care Providers are needing nowadays that more with less Mantra runs across the gamut but a lot of it's been helped me modernize helped me get to that next phase I can't I can't I don't have the resources to DIY it myself anymore I need to figure out a more robust business continuity program and so helping with business continuity Dr you know third copies of just all all this data that's growing so it's not just covered pandemic driven but it's that's definitely driving the the need and the requirement to modernize so much quicker it's interesting that you mentioned rackspace's history and expertise in doing things and moving that forward and leveraging that pivoting focusing on specific environments to create something net new we've seen a lot of that here if you go back 10 years I don't know if that's the perfect date to go back to but if you go back 10 years ago you think about VMware where would we have expected VMware to be in this era of cloud we may have thought of things very very differently differently Rackspace a Pioneer in creating off-premises hey we will do this for you didn't even really call it Cloud at the time right but it was Cloud yeah and so the ability for entities like Rackspace like VMware we had a NetApp talking to us about stuff they're doing in the cloud 10 years ago if you I would say no they'd be they'll be gone they'll be gone so it's really really cool to see Rackspace making this transition and uh you know being aware of everything that's going on and focusing on the best value proposition moving forward I mean am I am I you know do I sound like somebody who would who would fit into the Rackspace culture right now or do I not get it yes you sound like a rocker we'll make you an honorary record that's what we call a Rackspace employees yes you know what we've noticed too and is budgets are moving those decision makers are moving so again 10 years ago just like you said you would be talking to sometimes a completely different Persona than we do than we do today and we've seen a shift more towards that business value we have a really unique ability to bring business and Technical conversations together I did a lot of work in the past of working with a lot of CMO and and digital transformation companies and so helping bring it and business seeing the same and how healthcare because budgets are living in different places and even across the board with Rackspace people are trying to drive more business outcomes business driven Solutions so the technical becomes the back end and really the ingredients to make all of that all of that happen and that's what we're helping to solve and it's a lot it's very fast paced everyone wants to be agile now and so they're leaning on us more and more to drive more services so if you've seen Rackspace evolve we're driving more of that advisement and those transformation service type discussions where where our original history was DNA was very much always embedded in driving a great experience now they're just wanting more from us more services help us how help us figure out the how Adriana comment on the outcomes that you're helping Healthcare organizations achieve as as we as we it's such a relatable tangible topic Healthcare is Right everybody's everybody's got somebody who's sick or you've been sick or whatnot what are some of those outcomes that we can ex that customers can expect to achieve with Rackspace and VMware oh great great question so very much I can't mentioned earlier it's how do I modernize how do I optimize how do I take the biggest advantage of the budgets and the landscape that I have I want to get to the Cloud we need to help our patients and get access to that data is this ready to go into the cloud is this not ready to go into the cloud you know how do we how do we help make sure we're taking care of our patients we're keeping things secure and accessible you know what else do you think is coming up yeah and one specific one uh sequencing genetic sequencing and so we've had this come up from a few different types of providers whether it's medical devices that they may provide to their end clients and an outcome that they're looking for is how do we get how do we leverage um here's rip here's what we do but now we have so many more people we need to give this access to we need them to be able to have access to the sequencing that all of this is doing all of these different entities are doing and the outcome that they're trying to get to to is more collaboration so so that way we can speed up in the face of a pandemic we can speed up those resolutions we could speed up to you know whether it's a vaccine needed or something that's going to address the next thing that might be coming you know um so that's a specific one I've heard that from a handful of different different um clients that that we work with and so trying to give them a Consolidated not trying to we are able to deliver them a Consolidated place that their application and tooling can run in and then all of these other entities can safely and securely access this data to do what they're going to do in their own spaces and then hopefully it helps the betterment of of of us globally like as humans in the healthcare space we all benefit from this so leveraging the technology to really drive a valuable outcome helps us all so so and by the way I like trying to because it conveys the proper level of humility that we all need to bring to this because it's complicated and anybody who looks you in the eye it pretends like they know exactly how to do it you need to run from those people no it is and and look that's where our partners become so significant we we know we're Best in Class for specific things but we rely on our Partnerships with Dell and VMware to bring their expertise to bring their tried and true technology to help us all together collectively deliver something good technology for good technology for good it is inherently good and it's nice when it's used for goodness it's nice when it's yeah yeah talk about security for a second you know we've seen the threat landscape change dramatically obviously nobody wants to be the next breach ransomware becoming a household term it's now a matter of when we get a head not F where has security gone in terms of conversations with customers going help us ensure that what we're doing is delivering data access to the right folks that need it at the right time in real time in a secure fashion no uh that's another good question in hot and burning so you know I think if we think about past conversations it was that nice Insurance offering that seemed like it came at a high cost if you really need it I've never been breached before um I'll get it when I when I need it but exactly to your point it's the win and not the if so what we're finding and also working with a nice ecosystem of Partners as well from anywhere from Akamai to cloudflare to BT it's how do we help ensure that there is the security as Hannah mentioned that we're delivering the right data access to the right people and permissions you know we're able to help meet multitude of compliance and regulations obviously health care and other regulated space as well we look to make sure that from our side of the house from the infrastructure that we have the right building blocks to help them Reach those compliance needs obviously it's a mutual partnership in maintaining that compliance and that we're able to provide guidance and best practices on to make sure that the data is living in a secure place that the people that need access to it get it when they when they need it and monitor those permissions and back to your complexity comment so more and more complex as we are a global global provider so when you start to talk to our teams in the UK and our our you know clients there specializing um kind of that Sovereign Cloud mentality of hey we need to have um we need to have a cloud that is built for the specific needs that reside within Healthcare by region so it's not just even I mean you know we're we're homegrown out of San Antonio Texas so like we know the U.S and have spent time here but we've been Global for many years so we just get down into the into the nitty-gritty to customize what's needed within each region well Hannah is that part of the Rackspace value proposition at large moving forward because frankly look if I if I want if I want something generic I can I can swipe credit card and and fire up some Services sure um moving forward this is something that is going to more characterize the Rackspace experience and I and I understand that the hesitancy to say hey it's complicated it's like I don't want to hear that I want to hear that it's easy it's like well okay we'll make it easy for you yes but it's still complicated is that okay that's the honest that's that's the honest yeah that's why you need help right that's why we need to talk about that because people people have a legitimate question why Rackspace yep and we don't I don't want to put you on the spot but no yeah but why why Rackspace you've talked a little bit about it already but kind of encapsulate it oh gosh so good good question why Rackspace it's because you can stand up [Laughter] well you can you do it there's many different options out there um and if I had a PowerPoint slide I'd show you this like lovely web of options of directions that you could go and what is Rackspace value it's that we come in and simplify it because we've had experience with this this same use case whatever somebody is bringing forward to us is typically something we've dealt with at numerous times and so we're repeating and speeding up the ability to simplify the complex and to deliver something more simplified well it may be complex within us and we're like working to get it done the outcome that we're delivering is is faster it's less expensive than dedicating all the resources yourself to do it and go invest in all of that that we've already built up and then we're able to deliver it in a more simplified manner it's like the duck analogy the feet below the water yes exactly and a lot of expertise as well yes a lot talk a little bit about the solution that that Dell VMware Rackspace are delivering to customers sure so when we think about um Healthcare clouds or Cloud specific to the healthcare industry you know there's some major players within that space that you think epic we'll just use them as an example this can play out with others but we are building out a custom or we have a custom clouds able to host epic and then provide services up through the Epic help application through partnership so that is broadening the the market for us in the sense that we can tailor what the what that end and with that healthcare provider needs uh do they do they have the expertise to manage the application okay you do that and then we will build out a custom fit Cloud for that application oh and you need all the adjacent things that come with it too so then we have reference architecture you know built out already to to tailor to whatever all those other 40 80 90 hundreds of applications that need to come with that and then and then you start to think about Imaging platforms so we have Imaging platforms available for those specific needs whether it's MRIs and things like that and then the long-term retention that's needed with that so all of these pieces that build out a healthcare ecosystem and those needs we've built those we've built those out and provide those two to our clients yesterday VMware was talking about Cloud chaos yes and and it's true you talk about the complexity and Dave talks about it too like acknowledging yes this is a very complex thing to do yeah there's just so many moving parts so many Dynamics so many people involved or lack thereof people they they then talked about kind of this this the goal of getting customers from cloud chaos to Cloud smart how does that message resonate with Rackspace and how are you helping customers get from simplifying the chaos to eventually get to that cloud smart goal so a lot of it I I believe is with the power of our alliances and I was talking about this earlier we really believe in creating those powerful ecosystems and Jay McBain former for Forester analyst talks about you know the people are going to come ahead really are serve as that orchestration layer of bringing everybody together so if you look at all of that cloud chaos and all of the different logos and the webs and which decisions to make you know the ones that can help simplify that bring it all together like we're going to need a little bit of this like baking a cake in some ways we're going to need a little bit of sugar we'll need this technology this technology and whoever is able to put it together in a clean and seamless way and as Hannah said you know we have specific use cases in different verticals Healthcare specifically and talking from the Imaging and the Epic helping them get hospitals and different you know smaller clinics get to the edge so we have all of the building blocks to get them what they need and we can't do that without Partners but we help simplify those outcomes for those customers yep so there's where they're Cloud smart so then they're like I want I want to be agile I want to work on my cost I want to be able to leverage a multi-cloud fashion because some things may may inherently need to be on Azure some things we inherently need to be on VMware how do we make them feel like they still have that modernized platform and Technology but still give the secure and access that they need right yeah we like to think of it as are you multi-cloud by accident or multi-cloud by Design and help you get to that multi-cloud by Design and leveraging the right yeah the right tools the right places and Dell was talking about that just that at Dell Technologies world just a couple months ago that most most organizations are multi-cloud by default not designed are you seeing any customers that are are able or how are you able to help customers go from that we're here by default for whatever reason acquisition growth.oit line of business and go from that default to a more strategic multi-cloud approach yes it takes planning and commitment you know you really need the business leaders and the technical leaders bought in and saying this is what I'm gonna do because it is a journey because exactly right M A is like inherited four different tools you have databases that kind of look similar but they're a little bit different but they serve four different things so at Rackspace we're able to help assess and we sit down with their teams we have very amazing rock star expertise that will come in and sit with the customers and say what are we trying to drive for it let's get a good assessment of the landscape and let's figure out what are you trying to get towards in your journey and looking at what's the best fit for that application from where it is now to where it is where it wants to be because we saw a lot of customers move to the cloud very quickly you know they went Cloud native very fast some of it made sense retailers who had the spikiness that completely made sense we had some customers though that we've seen move certain workloads they've been in the public Cloud now for a couple years but it was a static website it doesn't make as much sense anymore for certain things so we're able to help navigate all of those choices for them so it's interesting you just you just said something sort of offhand about having experts having them come in so if I am a customer and I have some outcome I want to achieve yes the people that I'm going to be talking to from Rackspace or from Rackspace and the people from Rackspace who are going to be working with the actual people who are deploying infrastructure are also Rackspace people so the interesting contrast there between other circumstances oftentimes is you may have a Global Systems integrator with smart people representing what a cloud provider is doing the perception if they try to make people perceive that okay everybody is working in lockstep but often there are disconnects between what the real capabilities are and what's being advertised so is that I mean I I know it's like a leading question it's like softball get your bats out but I mean isn't that an advantage you've got a single you know the saying used to be uh one throat to show now it's one back to pack because it's kind of Contour friendly yeah yeah but talk about that is that a real Advantage it does it really helps us because again this is our our this is our expertise this is where we where we live we're really close to the infrastructure we're great at the advisement on it we can help with those ongoing and day two management and Opera in operations and what it feels like to grow and scale so we lay this out cleanly and and clearly as possible if this is where we're really good we can we can help you in these areas but we do work with system integrators as well and part of our partner Community because they're working on sometimes the bigger overall Transformations and then we're staying look we understand this multi-cloud but it helps us because in the end we're doing that end to end for for them customer knows this is Rackspace and on hand and we we really strive to be very transparent in what it is that we want to drive and outcomes so sometimes at the time where it's like we're gonna talk about a certain new technology Dell might bring some of their Architects to the table we will say here is Dell with us we're doing that actively in the healthcare space today and it's all coming together but you know at the end of the day this is what Rackspace is going to drive and deliver from an end to end and we tap those people when needed so you don't have to worry about picking up the phone to call Dell or VMware so if I had worded the hard-hitting journalist question the right way it would have elicited the same responses that yeah yeah it drives accountability at the end of the day because what we advised on what we said now we got to go deliver yeah and it's it's all the same the same organization driving accountability so from a customer perspective they're engaging Rackspace who will then bring in dell and VMware as needed as we find the solution exactly we have all of the certification I mean the team the team is great on getting all of the certs because we're getting to handling all of the level one level two level three business they know who to call they have their dedicated account teams they have engagement managers that help them Drive what those bigger conversations are and they don't have to worry about the experts because we either have it on hand or we'll pull them in as needed if it's the bat phone we need to call awesome ladies thank you so much for joining Dave and me today talking about what Rackspace is up to in the partner ecosystem space and specifically what you're doing to help Healthcare organizations transform and modernize we appreciate your insights and your thoughts yeah thank you for having us thank you pleasure for our guests and Dave Nicholson I'm Lisa Martin you're watching thecube live from VMware Explorer 2022 we'll be back after a short break foreign [Music]

>>Hey everyone. Welcome back to the Cube's day one coverage of VMware Explorer, 2022 live from San Francisco. I'm Lisa Martin, and I'm basically sitting with the cloud. I got a power panel here with me. You are not gonna wanna miss the segment, please. Welcome, nor Barage I probably did. I do. Okay on that. Great, thank you. VP and GM of cloud solutions at VMware. Thanks for joining us. Field brother tune is back our alumni VP solutions and alliances at NetApp bill. Great to see you in person. Thank you. And Steve Jones, GM SAP, and VMware cloud at Amazon. Welcome guys. Thank you. Pleasure. So we got VMware, NetApp and Amazon. I was telling Phil before we went live, I was snooping around on the NetApp website the other day. And I saw a tagline that said two is the company three is a cloud, but I get to sit with the cloud. This is fantastic. Nora, talk to us about the big news that came out just about 24 hours ago. These three powerhouse, we >>Were super excited. We are celebrating five years of VMware cloud this week. And with three powerhouses here, we're announcing the general availability of VMware cloud and AWS with NetApp on tap. We have AWS FSX. And so this solution is now generally available across all global regions. We are super excited with all our joint customers and partners to bring this to the market. >>So Steve, give us your perspective as AWS as the biggest hyperscaler. Talk about the importance of the partnership and the longstanding partnerships that you've had with both NetApp and VMware. >>Yeah, you bet. So first all, maybe I'll start with Ryan and VMware. So we've had a very long standing partnership with VMware for over five years now. One thing that we've heard consistently from customers is they, they want help in reducing the heavy lifting or the, the friction that typically comes with cloud adoption. And VMware's been right in the trenches with us and helping with that over the years with the VMware cloud on AWS offering. And, and now that we've got NetApp, right, the FSX on tap solution, a managed storage solution that is, is been known and trusted in the on-premises world. Now available since September on AWS, but now available for use with VMware cloud is just amazing for customers who are looking for that agility, >>Right? Phil talk about NetApp has done a phenomenal job in its own digital transformation journey. Talk about that as an enabler for what you announced yesterday and the, and the capabilities that NetApp is able to bring to its customers with VMware and with AWS. >>Yeah. You know, it started, it's interesting because we NetApp's always been a company that works very closely with our partners. VMware has been a huge partner of ours since gosh, 2005 probably, or sometime like that. I started working with Amazon back in about 20 13, 20 14, when we first took on tap and brought it to the Amazon platform in the marketplace ahead of what's. Now FSX ends like a dream to bring a fully managed ONAP onto the world's biggest cloud. So that work you you're really looking at about. I mean, it depends how you look at it, 15 years of work. And then as Ryan was saying that VMware was working in parallel with us on being a first party service on Amazon, we came together and, or Ryan and I came together and VMware and NetApp came together about probably about two years ago now with this vision of what we're announcing today and to have so to have GA of this combination for meaning global availability, anybody can try it today. It's just an amazing day. It's really a great day. >>Yeah. It's unbelievable how we have sort of partnered together and hard engineering problems to create a very simple outcome for customers and partners. One of the things, you know, VMware cloud is a very successful service offering with a lot of great consumption and different verticals. Things like cloud migration, you know, transforming your entire, you know, data center and moving to the cloud. Things like, you know, modernizing our apps, disaster recovery now ransomware this week. So really, really exciting uptake and innovation in that whole service. One thing customers always told us that they want more options for storage decouple from compute. And so that really helped customers to lower their total cost of ownership and get to, you know, get even more workloads into VMware cloud. And this partnership really creates that opportunity for us to provide customers with those options. >>Let me give you an example, just I was walking over here just before I walked over here. We were with a customer talking about exactly what Orion's talking about. We were modeling using a TCO calculator that we all put together as well on what we call data intensive workloads, which is in this case, it was a 500 gigabytes per VM. So not a huge amount of data per VM. The, the case study modeled out of 38% cost savings or reduction in total cost, which in the case was like 1.2 million per year of total cost down to 700 million. And just, you could do the, just depends on how many VMs you have and how big odes you have, but that's the kind of cost savings we're talking about. So the, this is a really easy value to talk about. You save a lot of money in it's exactly as nor Ryan said, because we can separate the compute and the storage. Yep. >>Yep. I was just gonna say the reason for that is it used to be with VMware cloud on AWS. If you wanted more storage for your workload, you would have to add another node. So with another node, you would get another compute node. You would get the compute, you'd get the memory and the storage, but now we've actually decoupled the ability to expand the storage footprint from the compute, allowing customers to really expand as their needs grow. And so it's, it's just a lot more flexibility. Yep. That customers had. Yeah. >>Flexibility is key. Every customer needs that they need to be agile. There's always a competitor waiting in the rear view mirror behind any business, waiting to take over. If, if they can't innovate fast enough, if they can't partner with the best of the best to deliver the infrastructure that's needed to enable those business outcomes, I wanna get your perspective, Steve, what are some of the outcomes that when you're talking to customers, you talked about fill the TCO. Those are huge numbers, very compelling. What are some of the other outcomes that customers can expect to achieve from this solution? >>That's a great question. I think customers want the flexibility. We talked about customers absolutely wanna be able to move fast. They're also very demanding customers who have had an experience with solutions like NetApp on tap on premises, right? So they've come to expect enterprise features like thin provisioning, snapshoting cloning, rapid cloning, right? And even replication of data given that customers now can leverage this type of functionality as well through the NetApp solution with VMC, they're getting all those enterprise class features from, from the storage in combination with what they already had with vs a and, and VMC. >>Steve earlier mentioned the word we used, we kind of took it from VMware or from Amazon was friction is so many workloads run in VMware VMs today to be able to just simply pick them up as is move them to Amazon makes cloud adoption. Just, I mean, frictionless is an extreme word, but it's really lowers the friction to cloud adoption. And as Steve said, then you've get all these enterprise features wherever you need to run. >>Just brings speed. >>I was just about to say, it's gotta be the speed. It has to be a huge factor here. Yep, >>Yep. Yeah. >>Sure. One of the things that we've seen with VMware cloud is operational consistency as, as a customer value because when customers are thinking about, you know, complex enterprise apps, moving that to the cloud, they need that operational consistency, which drives down their costs. They don't have to relearn new skills. They're used to VMware, they're used to NetApp. And so this partnership really fosters that operational consistency as a big customer value, and they can reuse those skills and really reapply them in this cloud model. The other thing is the cloud model here is super completely managed. If you think about that, right, customers have to do less VMware, AWS and NetApp is doing more for them. That's true in this model. >>So you're able to really deliver a lot of workforce efficiency, workforce productivity across the stack. >>Absolutely. >>And that's definitely true that it just, as it gets more complex, how do you manage it? Just continue, hear everybody talking about this, right. So when a completely managed service by VMware and Amazon is such a savings in com in management complexity, which then gets back to speed. How do I grow my plant faster? >>I mean, and really at the end of the day, customers are actually able to focus on what differentiate differentiates them, obviously versus the management of the underlying infrastructure and storage and all those, those things that are still critical, but exactly, but >>For, for the customer to be able to have to abstract the underlying underlying technology layer and focus on what differentiates them from the competition. That's like I said, right back here, right. That's especially if there's anything we've learned in the last couple of years, it's that it, that is critical for businesses across every industry, no industry exempt from this. >>None. One other thing, just an example of what you're talking about is we all work a lot on modernization techniques like using Kubernetes and container technologies. So with this, if you think about this, you, this solution, you can move an app as is modernize on the cloud. You can modernize, you can modernize and then move. You can, the flexibility that this enables like. So it's sort of like move to the cloud at your rate is a really big benefit. >>And we've seen so many customer examples of migrating modernize is how we like to summarize it, where customers are, you know, migrating, modernizing at their own pace. Yep. And the good, good thing about the platform and the service is that it is the home for all applications, virtual machines containers with Kubernetes backed by local storage, external storage options. The level of flexibility for all applications is really immense. And that drives down your TCO even more. >>What, from a target customer perspective, Noran, talk about that. Who, who is the target? Obviously I imagine VMware customers, it's NetApp customers, it's AWS, but is there, are there any targets kind of within that, that are really prime candidates for this solution? >>Yeah. A great question. First of all, the, the easy sort of overlap between all of us is our shared customer pool. And so VMware and NetApp have been partners for what, 20 years, something like that. And we have thousands of customers using our joint solutions in the data center. And so that's a very clear target for this solution, as they're considering use cases such as, you know, cloud migration, disaster recovery, virtual desktops, application modernization. So that's a very clear target and we see this day in and day out, obviously there are many other customers that would be interested in this solution, as well as they're considering, you know, AWS and we provide a whole range of consumption options for them. Right. And I think that's one of the, sort of the, the good things about our partnership, including with AWS, where customers can purchase this from VMware can purchase this from AWS and all of these different options, including from our partners really makes it very, very compelling. >>Talk a little bit about from each of your perspectives about the what's in it. For me as a partner of these companies, Steve, we'll start with you. >>I mean, what's in it for me is that it's what my customers have been asking for. And we, we have a long history, I think of providing managed services again, to remove that heavy lifting that customers often just don't want to have to do. Having seen the, the adoption of managed storage offerings, including the, the NetApp solution here and now being able to bring that into the VMware space where they're already using it in an on-premises world, and now they're moving those, those workloads being able to satisfy that need that a customer's asking for is awesome. >>We, every time we're at an AWS event, we are always talking about it's absolute customer obsession, and I know NetApp and VMware well, and know that that is a shared obsession across the three companies. >>Hey, Lisa, let me add one more thing. It's interesting, not everybody sees this, but it's really obvious that the NetApp on-prem installed base with VMware, which is tens of thousands of customers. This is an awesome solution. Not quite as obvious is that every on-prem VMware customer gets that TCO benefit. I mentioned that's not limited to the NetApp on-prem installed base. So we're really excited to be able to expose all the market that hasn't used our products on-prem to this cloud solution. And, and it's really clear customers are adopting the cloud, right? So we're, that's one of the reasons we're so excited about this is it opens up a huge new opportunity to work with new customers for us. Talk >>About those customer conversations, Phil, how, where are they happening at? What level are you talking with customers about migration to cloud? Has it changed in the last couple >>Of years? Oh yeah. You know, I've been working on this for years and a lot of the on-prem conversation, it's been a little bifurcated that on-prem is on-prem and cloud developers or cloud developers. And Amazon's done a huge amount to break that down. VMware getting in the game, a lot of it's networking complexities, those have gone down. A lot of people are cross connected and set up today, which that wasn't so true five years ago. So now it's a lot of conversations about, I hear carbon footprint reduction. I hear data all in around data center reduction. The cloud guys are super efficient operators of data center infrastructure. We were talking about different use cases like disaster recovery. It's it's everybody though. It's small companies, it's big companies. They're all sort of moving into this, it call it at least hybrid world. And that's why when I say we're get really excited about this, because it does get rid of a lot of friction for moving loads in those directions, at the rate, the customer wants to do it. >>And that one last really quick thing is I was using NetApp as an example, we have about 300 enterprise workloads. We wanna move to the cloud two, right? And so they're all running VMware, like most, most of the world. And so this solution is, looks really good to us and we're gonna do the exact, I was just out with our CIO. We're going, looking at those 300, which do we just lift and move? Which do we refactor? And how do we do that? In fact, that Ryan was out to dinner with us last night, talking about >>This it's more and more it's being driven top down. So in the early days, and I've been with Amazon for 10 years now. Yep. Early days, it was kind of developer oriented, often initiated projects. Now it's top level CIOs. Exactly. I >>Are two mandates today talking to customers. >>I think of reinvent as an it conference. Now in the way, some of these top down mandates are driven, but listen, I mean, we got great customer interest. We have been in preview for three to six months now, and we've seen a lot of customers were not able to drag their entire data center workloads because of different reasons of PCO data, intensive workloads, et cetera. And we've seen tremendous amounts of interest from them. And we're also seeing a lot of new customers in the pipeline that want to consider VMware cloud now that we have these great storage options. >>So there's a pretty healthy Tam I'm hearing. >>Absolutely. >>I think so. Yeah. It's interesting. Another, just both like WWT and Presidio, channel partners, big, huge channel partners. It takes no selling to explain. We, we just say, Hey, we're doing this. And they start building services. Presidio is here with us talking about a customer win that they got. So this is it. It's easy for people to see why this is a cool, a cool solution. >>The value prop is there >>Definitely >>There's no having appeal the onion to >>Find it. No, the money savings. It's just in what or Ryan said, a lot of people have seen the, the seen an obstacle of cost. Yeah. So the TCO benefit, I mentioned removes that obstacle. And then that opens the door to all the features Steve was talking about of the advanced storage features and things on the platform. >>So is there a customer that's been in beta on this solution that you can talk about in, in terms of what they were looking for, the challenges that you helped them erase and the outcomes they're achieving? >>Yeah, sure. I can. I can provide one example. A large financial customer was looking at this during the preview phase and you know, for, for, for reasons before that were already a customer, but they were not able to attract a lot of their other workloads from other business units. And with this solution, now the service is a much better candidate for those workloads and those business units that had not considered VMware cloud. So we're really excited to see new workloads coming from that particular customer, given this particular solution and the whole TCO math for them was very, very straightforward and simple. And this became a more attractive option for that particular customer. >>Is there a shadow it elimination factor here in this technology and who you're selling to? >>Not real, I, don't not intent. Wouldn't intentionally. I wouldn't say yeah, not intentionally. I, it was funny with the customers I was thinking is yes. The question, the customers that are in the preview are seeing the benefits that we're talking about. The, one of the reasons we started the project on our side a number of years ago was this very large cement company was looking for carbon CO2 reduction. Part of that was moving disaster recovery to the cloud. There was a lot of friction in the solution prior to this, the, the customers have done some of the things we're talking about, but there's a, it takes a lot of skill. And we were looking at working with that customer going, how could we simplify this? And that was from our point of NetApp's point of view, it, it drove us to VMware and to AWS saying, can't we pull some of the friction of this out. And I think that that's what we've seen in the, in the previews. And it's, that's what I meant. It's so exciting to go from having say, I know we have about 20 previews right now, going to the globe today is the, is the exciting news today. >>And is the solution here in booze that it can be demoed and folks can kind of get their hands on it. >>Yeah. Yeah. They can go to the VMware cloud booth at the expo and they can get their hands on their demo and they can take it for a test drive. >>Excellent. >>You can run TCO calculators and do your own math and see what you're gonna all this, the all that's integrated today. We >>Also have pilots where we can help walk customers through a scenario of their own. >>Yep. Excellent. Is there, is there a, a joint website that you guys have, we should drive folks to? >>Yeah, it's >>Actually talk about the press release. It's >>It's yours. So >>It's it's prominently on our website. Okay. VMware cloud. It is onc.vmware.com where we also have the other, you know, our corporate marketing websites that have this vmware.com is a great starting point. Yeah. And we feature the solution. Prominently customers can get started today and they can even participate in the hands on labs here and take the solution for a test drive. >>All right. Last question, nor Ryan, we'll start with you on this. Here we are. I love the theme of this event, the center of the multicloud universe. Does it not sound like a Marvel movie? I feel like there should be some, is there any superheroes running around? Cause I really feel like there should be, how is this solution an enabler of allowing customers to really extract the most of value from their multi-cloud world that they're living in? >>Yeah. I mean, look, I mean, our mission is to build, run, managed, secure applications in any cloud, right. And regu has been talking about this with the keynote this morning as well. You know, at least with NetApp, we share a very good joint vision of enabling customers to, you know, place applications with really good TCO across clouds. And so it's really good story I feel. And I think this is a really good step in that direction where customers have choice and flexibility in terms of where they put their applications in the TCO value that they get. >>Awesome. Guys, you gotta come back next with a customer would love to dig. Maybe at reinvent sounds, we can dig into more and to see a great story of how a customer came together and is really leveraging that the power that is sitting next to me here. Thank you all so much for joining me and having this great conversation. Congratulations on the announcement and it being GA. >>Thank you. Awesome. >>Thank you. Thanks Lisa. All right. Fun conversation. I told you power panel for my guests. I'm Lisa Martin. You're watching the cube, keep it right here for more live coverage of VMware Explorer, 2022 from downtown San Francisco. We'll be right back with our next guest.

(upbeat music) >> Welcome to this CUBE Power Panel where we're going to talk about application modernization, also success templates, and take a look at some new survey data to see how CIOs are thinking about digital transformation, as we get deeper into the post isolation economy. And with me are three familiar VIP guests to CUBE audiences. Tony Bear, the principal at DB InSight, Doug Henschen, VP and principal analyst at Constellation Research and Sanjeev Mohan principal at SanjMo. Guys, good to see you again, welcome back. >> Thank you. >> Glad to be here. >> Thanks for having us. >> Glad to be here. >> All right, Doug. Let's get started with you. You know, this recent survey, which was commissioned by Couchbase, 650 CIOs and CTOs, and IT practitioners. So obviously very IT heavy. They responded to the following question, "In response to the pandemic, my organization accelerated our application modernization strategy and of course, an overwhelming majority, 94% agreed or strongly agreed." So I'm sure, Doug, that you're not shocked by that, but in the same survey, modernizing existing technologies was second only behind cyber security is the top investment priority this year. Doug, bring us into your world and tell us the trends that you're seeing with the clients and customers you work with in their modernization initiatives. >> Well, the survey, of course, is spot on. You know, any Constellation Research analyst, any systems integrator will tell you that we saw more transformation work in the last two years than in the prior six to eight years. A lot of it was forced, you know, a lot of movement to the cloud, a lot of process improvement, a lot of automation work, but transformational is aspirational and not every company can be a leader. You know, at Constellation, we focus our research on those market leaders and that's only, you know, the top 5% of companies that are really innovating, that are really disrupting their markets and we try to share that with companies that want to be fast followers, that these are the next 20 to 25% of companies that don't want to get left behind, but don't want to hit some of the same roadblocks and you know, pioneering pitfalls that the real leaders are encountering when they're harnessing new technologies. So the rest of the companies, you know, the cautious adopters, the laggards, many of them fall by the wayside, that's certainly what we saw during the pandemic. Who are these leaders? You know, the old saw examples that people saw at the Amazons, the Teslas, the Airbnbs, the Ubers and Lyfts, but new examples are emerging every year. And as a consumer, you immediately recognize these transformed experiences. One of my favorite examples from the pandemic is Rocket Mortgage. No disclaimer required, I don't own stock and you're not client, but when I wanted to take advantage of those record low mortgage interest rates, I called my current bank and some, you know, stall word, very established conventional banks, I'm talking to you Bank of America, City Bank, and they were taking days and weeks to get back to me. Rocket Mortgage had the locked in commitment that day, a very proactive, consistent communications across web, mobile, email, all customer touchpoints. I closed in a matter of weeks an entirely digital seamless process. This is back in the gloves and masks days and the loan officer came parked in our driveway, wiped down an iPad, handed us that iPad, we signed all those documents digitally, completely electronic workflow. The only wet signatures required were those demanded by the state. So it's easy to spot these transformed experiences. You know, Rocket had most of that in place before the pandemic, and that's why they captured 8% of the national mortgage market by 2020 and they're on track to hit 10% here in 2022. >> Yeah, those are great examples. I mean, I'm not a shareholder either, but I am a customer. I even went through the same thing in the pandemic. It was all done in digital it was a piece of cake and I happened to have to do another one with a different firm and stuck with that firm for a variety of reasons and it was night and day. So to your point, it was a forced merge to digital. If you were there beforehand, you had real advantage, it could accelerate your lead during the pandemic. Okay, now Tony bear. Mr. Bear, I understand you're skeptical about all this buzz around digital transformation. So in that same survey, the data shows that the majority of respondents said that their digital initiatives were largely reactive to outside forces, the pandemic compliance changes, et cetera. But at the same time, they indicated that the results while somewhat mixed were generally positive. So why are you skeptical? >> The reason being, and by the way, I have nothing against application modernization. The problem... I think the problem I ever said, it often gets conflated with digital transformation and digital transformation itself has become such a buzzword and so overused that it's really hard, if not impossible to pin down (coughs) what digital transformation actually means. And very often what you'll hear from, let's say a C level, you know, (mumbles) we want to run like Google regardless of whether or not that goal is realistic you know, for that organization (coughs). The thing is that we've been using, you know, businesses have been using digital data since the days of the mainframe, since the... Sorry that data has been digital. What really has changed though, is just the degree of how businesses interact with their customers, their partners, with the whole rest of the ecosystem and how their business... And how in many cases you take look at the auto industry that the nature of the business, you know, is changing. So there is real change of foot, the question is I think we need to get more specific in our goals. And when you look at it, if we can boil it down to a couple, maybe, you know, boil it down like really over simplistically, it's really all about connectedness. No, I'm not saying connectivity 'cause that's more of a physical thing, but connectedness. Being connected to your customer, being connected to your supplier, being connected to the, you know, to the whole landscape, that you operate in. And of course today we have many more channels with which we operate, you know, with customers. And in fact also if you take a look at what's happening in the automotive industry, for instance, I was just reading an interview with Bill Ford, you know, their... Ford is now rapidly ramping up their electric, you know, their electric vehicle strategy. And what they realize is it's not just a change of technology, you know, it is a change in their business, it's a change in terms of the relationship they have with their customer. Their customers have traditionally been automotive dealers who... And the automotive dealers have, you know, traditionally and in many cases by state law now have been the ones who own the relationship with the end customer. But when you go to an electric vehicle, the product becomes a lot more of a software product. And in turn, that means that Ford would have much more direct interaction with its end customers. So that's really what it's all about. It's about, you know, connectedness, it's also about the ability to act, you know, we can say agility, it's about ability not just to react, but to anticipate and act. And so... And of course with all the proliferation, you know, the explosion of data sources and connectivity out there and the cloud, which allows much more, you know, access to compute, it changes the whole nature of the ball game. The fact is that we have to avoid being overwhelmed by this and make our goals more, I guess, tangible, more strictly defined. >> Yeah, now... You know, great points there. And I want to just bring in some survey data, again, two thirds of the respondents said their digital strategies were set by IT and only 26% by the C-suite, 8% by the line of business. Now, this was largely a survey of CIOs and CTOs, but, wow, doesn't seem like the right mix. It's a Doug's point about, you know, leaders in lagers. My guess is that Rocket Mortgage, their digital strategy was led by the chief digital officer potentially. But at the same time, you would think, Tony, that application modernization is a prerequisite for digital transformation. But I want to go to Sanjeev in this war in the survey. And respondents said that on average, they want 58% of their IT spend to be in the public cloud three years down the road. Now, again, this is CIOs and CTOs, but (mumbles), but that's a big number. And there was no ambiguity because the question wasn't worded as cloud, it was worded as public cloud. So Sanjeev, what do you make of that? What's your feeling on cloud as flexible architecture? What does this all mean to you? >> Dave, 58% of IT spend in the cloud is a huge change from today. Today, most estimates, peg cloud IT spend to be somewhere around five to 15%. So what this number tells us is that the cloud journey is still in its early days, so we should buckle up. We ain't seen nothing yet, but let me add some color to this. CIOs and CTOs maybe ramping up their cloud deployment, but they still have a lot of problems to solve. I can tell you from my previous experience, for example, when I was in Gartner, I used to talk to a lot of customers who were in a rush to move into the cloud. So if we were to plot, let's say a maturity model, typically a maturity model in any discipline in IT would have something like crawl, walk, run. So what I was noticing was that these organizations were jumping straight to run because in the pandemic, they were under the gun to quickly deploy into the cloud. So now they're kind of coming back down to, you know, to crawl, walk, run. So basically they did what they had to do under the circumstances, but now they're starting to resolve some of the very, very important issues. For example, security, data privacy, governance, observability, these are all very big ticket items. Another huge problem that nav we are noticing more than we've ever seen, other rising costs. Cloud makes it so easy to onboard new use cases, but it leads to all kinds of unexpected increase in spikes in your operating expenses. So what we are seeing is that organizations are now getting smarter about where the workloads should be deployed. And sometimes it may be in more than one cloud. Multi-cloud is no longer an aspirational thing. So that is a huge trend that we are seeing and that's why you see there's so much increased planning to spend money in public cloud. We do have some issues that we still need to resolve. For example, multi-cloud sounds great, but we still need some sort of single pane of glass, control plane so we can have some fungibility and move workloads around. And some of this may also not be in public cloud, some workloads may actually be done in a more hybrid environment. >> Yeah, definitely. I call it Supercloud. People win sometimes-- >> Supercloud. >> At that term, but it's above multi-cloud, it floats, you know, on topic. But so you clearly identified some potholes. So I want to talk about the evolution of the application experience 'cause there's some potholes there too. 81% of their respondents in that survey said, "Our development teams are embracing the cloud and other technologies faster than the rest of the organization can adopt and manage them." And that was an interesting finding to me because you'd think that infrastructure is code and designing insecurity and containers and Kubernetes would be a great thing for organizations, and it is I'm sure in terms of developer productivity, but what do you make of this? Does the modernization path also have some potholes, Sanjeev? What are those? >> So, first of all, Dave, you mentioned in your previous question, there's no ambiguity, it's a public cloud. This one, I feel it has quite a bit of ambiguity because it talks about cloud and other technologies, that sort of opens up the kimono, it's like that's everything. Also, it says that the rest of the organization is not able to adopt and manage. Adoption is a business function, management is an IT function. So I feed this question is a bit loaded. We know that app modernization is here to stay, developing in the cloud removes a lot of traditional barriers or procuring instantiating infrastructure. In addition, developers today have so many more advanced tools. So they're able to develop the application faster because they have like low-code/no-code options, they have notebooks to write the machine learning code, they have the entire DevOps CI/CD tool chain that makes it easy to version control and push changes. But there are potholes. For example, are developers really interested in fixing data quality problems, all data, privacy, data, access, data governance? How about monitoring? I doubt developers want to get encumbered with all of these operationalization management pieces. Developers are very keen to deliver new functionality. So what we are now seeing is that it is left to the data team to figure out all of these operationalization productionization things that the developers have... You know, are not truly interested in that. So which actually takes me to this topic that, Dave, you've been quite actively covering and we've been talking about, see, the whole data mesh. >> Yeah, I was going to say, it's going to solve all those data quality problems, Sanjeev. You know, I'm a sucker for data mesh. (laughing) >> Yeah, I know, but see, what's going to happen with data mesh is that developers are now going to have more domain resident power to develop these applications. What happens to all of the data curation governance quality that, you know, a central team used to do. So there's a lot of open ended questions that still need to be answered. >> Yeah, That gets automated, Tony, right? With computational governance. So-- >> Of course. >> It's not trivial, it's not trivial, but I'm still an optimist by the end of the decade we'll start to get there. Doug, I want to go to you again and talk about the business case. We all remember, you know, the business case for modernization that is... We remember the Y2K, there was a big it spending binge and this was before the (mumbles) of the enterprise, right? CIOs, they'd be asked to develop new applications and the business maybe helps pay for it or offset the cost with the initial work and deployment then IT got stuck managing the sprawling portfolio for years. And a lot of the apps had limited adoption or only served a few users, so there were big pushes toward rationalizing the portfolio at that time, you know? So do I modernize, they had to make a decision, consolidate, do I sunset? You know, it was all based on value. So what's happening today and how are businesses making the case to modernize, are they going through a similar rationalization exercise, Doug? >> Well, the Y2K era experience that you talked about was back in the days of, you know, throw the requirements over the wall and then we had waterfall development that lasted months in some cases years. We see today's most successful companies building cross functional teams. You know, the C-suite the line of business, the operations, the data and analytics teams, the IT, everybody has a seat at the table to lead innovation and modernization initiatives and they don't start, the most successful companies don't start by talking about technology, they start by envisioning a business outcome by envisioning a transformed customer experience. You hear the example of Amazon writing the press release for the product or service it wants to deliver and then it works backwards to create it. You got to work backwards to determine the tech that will get you there. What's very clear though, is that you can't transform or modernize by lifting and shifting the legacy mess into the cloud. That doesn't give you the seamless processes, that doesn't give you data driven personalization, it doesn't give you a connected and consistent customer experience, whether it's online or mobile, you know, bots, chat, phone, everything that we have today that requires a modern, scalable cloud negative approach and agile deliver iterative experience where you're collaborating with this cross-functional team and course correct, again, making sure you're on track to what's needed. >> Yeah. Now, Tony, both Doug and Sanjeev have been, you know, talking about what I'm going to call this IT and business schism, and we've all done surveys. One of the things I'd love to see Couchbase do in future surveys is not only survey the it heavy, but also survey the business heavy and see what they say about who's leading the digital transformation and who's in charge of the customer experience. Do you have any thoughts on that, Tony? >> Well, there's no question... I mean, it's kind like, you know, the more things change. I mean, we've been talking about that IT and the business has to get together, we talked about this back during, and Doug, you probably remember this, back during the Y2K ERP days, is that you need these cross functional teams, we've been seeing this. I think what's happening today though, is that, you know, back in the Y2K era, we were basically going into like our bedrock systems and having to totally re-engineer them. And today what we're looking at is that, okay, those bedrock systems, the ones that basically are keeping the lights on, okay, those are there, we're not going to mess with that, but on top of that, that's where we're going to innovate. And that gives us a chance to be more, you know, more directed and therefore we can bring these related domains together. I mean, that's why just kind of, you know, talk... Where Sanjeev brought up the term of data mesh, I've been a bit of a cynic about data mesh, but I do think that work and work is where we bring a bunch of these connected teams together, teams that have some sort of shared context, though it's everybody that's... Every team that's working, let's say around the customer, for instance, which could be, you know, in marketing, it could be in sales, order processing in some cases, you know, in logistics and delivery. So I think that's where I think we... You know, there's some hope and the fact is that with all the advanced, you know, basically the low-code/no-code tools, they are ways to bring some of these other players, you know, into the process who previously had to... Were sort of, you know, more at the end of like a, you know, kind of a... Sort of like they throw it over the wall type process. So I do believe, but despite all my cynicism, I do believe there's some hope. >> Thank you. Okay, last question. And maybe all of you could answer this. Maybe, Sanjeev, you can start it off and then Doug and Tony can chime in. In the survey, about a half, nearly half of the 650 respondents said they could tangibly show their organizations improve customer experiences that were realized from digital projects in the last 12 months. Now, again, not surprising, but we've been talking about digital experiences, but there's a long way to go judging from our pandemic customer experiences. And we, again, you know, some were great, some were terrible. And so, you know, and some actually got worse, right? Will that improve? When and how will it improve? Where's 5G and things like that fit in in terms of improving customer outcomes? Maybe, Sanjeev, you could start us off here. And by the way, plug any research that you're working on in this sort of area, please do. >> Thank you, Dave. As a resident optimist on this call, I'll get us started and then I'm sure Doug and Tony will have interesting counterpoints. So I'm a technology fan boy, I have to admit, I am in all of all these new companies and how they have been able to rise up and handle extreme scale. In this time that we are speaking on this show, these food delivery companies would have probably handled tens of thousands of orders in minutes. So these concurrent orders, delivery, customer support, geospatial location intelligence, all of this has really become commonplace now. It used to be that, you know, large companies like Apple would be able to handle all of these supply chain issues, disruptions that we've been facing. But now in my opinion, I think we are seeing this in, Doug mentioned Rocket Mortgage. So we've seen it in FinTech and shopping apps. So we've seen the same scale and it's more than 5G. It includes things like... Even in the public cloud, we have much more efficient, better hardware, which can do like deep learning networks much more efficiently. So machine learning, a lot of natural language programming, being able to handle unstructured data. So in my opinion, it's quite phenomenal to see how technology has actually come to rescue and as, you know, billions of us have gone online over the last two years. >> Yeah, so, Doug, so Sanjeev's point, he's saying, basically, you ain't seen nothing yet. What are your thoughts here, your final thoughts. >> Well, yeah, I mean, there's some incredible technologies coming including 5G, but you know, it's only going to pave the cow path if the underlying app, if the underlying process is clunky. You have to modernize, take advantage of, you know, serverless scalability, autonomous optimization, advanced data science. There's lots of cutting edge capabilities out there today, but you know, lifting and shifting you got to get your hands dirty and actually modernize on that data front. I mentioned my research this year, I'm doing a lot of in depth looks at some of the analytical data platforms. You know, these lake houses we've had some conversations about that and helping companies to harness their data, to have a more personalized and predictive and proactive experience. So, you know, we're talking about the Snowflakes and Databricks and Googles and Teradata and Vertica and Yellowbrick and that's the research I'm focusing on this year. >> Yeah, your point about paving the cow path is right on, especially over the pandemic, a lot of the processes were unknown. But you saw this with RPA, paving the cow path only got you so far. And so, you know, great points there. Tony, you get the last word, bring us home. >> Well, I'll put it this way. I think there's a lot of hope in terms of that the new generation of developers that are coming in are a lot more savvy about things like data. And I think also the new generation of people in the business are realizing that we need to have data as a core competence. So I do have optimism there that the fact is, I think there is a much greater consciousness within both the business side and the technical. In the technology side, the organization of the importance of data and how to approach that. And so I'd like to just end on that note. >> Yeah, excellent. And I think you're right. Putting data at the core is critical data mesh I think very well describes the problem and (mumbles) credit lays out a solution, just the technology's not there yet, nor are the standards. Anyway, I want to thank the panelists here. Amazing. You guys are always so much fun to work with and love to have you back in the future. And thank you for joining today's broadcast brought to you by Couchbase. By the way, check out Couchbase on the road this summer at their application modernization summits, they're making up for two years of shut in and coming to you. So you got to go to couchbase.com/roadshow to find a city near you where you can meet face to face. In a moment. Ravi Mayuram, the chief technology officer of Couchbase will join me. You're watching theCUBE, the leader in high tech enterprise coverage. (bright music)

(upbeat music) >> The ascendancy of cloud and SAS has shown new light on how organizations think about, pay for, and value hardware. Once sought after skills for practitioners with expertise in hardware troubleshooting, configuring ports, tuning storage arrays, and maximizing server utilization has been superseded by demand for cloud architects, DevOps pros, developers with expertise in microservices, container, application development, and like. Even a company like Dell, the largest hardware company in enterprise tech touts that it has more software engineers than those working in hardware. Begs the question, is hardware going the way of Coball? Well, not likely. Software has to run on something, but the labor needed to deploy, and troubleshoot, and manage hardware infrastructure is shifting. At the same time, we've seen the value flow also shifting in hardware. Once a world dominated by X86 processors value is flowing to alternatives like Nvidia and arm based designs. Moreover, other componentry like NICs, accelerators, and storage controllers are becoming more advanced, integrated, and increasingly important. The question is, does it matter? And if so, why does it matter and to whom? What does it mean to customers, workloads, OEMs, and the broader society? Hello and welcome to this week's Wikibon theCUBE Insights powered by ETR. In this breaking analysis, we've organized a special power panel of industry analysts and experts to address the question, does hardware still matter? Allow me to introduce the panel. Bob O'Donnell is president and chief analyst at TECHnalysis Research. Zeus Kerravala is the founder and principal analyst at ZK Research. David Nicholson is a CTO and tech expert. Keith Townson is CEO and founder of CTO Advisor. And Marc Staimer is the chief dragon slayer at Dragon Slayer Consulting and oftentimes a Wikibon contributor. Guys, welcome to theCUBE. Thanks so much for spending some time here. >> Good to be here. >> Thanks. >> Thanks for having us. >> Okay before we get into it, I just want to bring up some data from ETR. This is a survey that ETR does every quarter. It's a survey of about 1200 to 1500 CIOs and IT buyers and I'm showing a subset of the taxonomy here. This XY axis and the vertical axis is something called net score. That's a measure of spending momentum. It's essentially the percentage of customers that are spending more on a particular area than those spending less. You subtract the lesses from the mores and you get a net score. Anything the horizontal axis is pervasion in the data set. Sometimes they call it market share. It's not like IDC market share. It's just the percentage of activity in the data set as a percentage of the total. That red 40% line, anything over that is considered highly elevated. And for the past, I don't know, eight to 12 quarters, the big four have been AI and machine learning, containers, RPA and cloud and cloud of course is very impressive because not only is it elevated in the vertical access, but you know it's very highly pervasive on the horizontal. So what I've done is highlighted in red that historical hardware sector. The server, the storage, the networking, and even PCs despite the work from home are depressed in relative terms. And of course, data center collocation services. Okay so you're seeing obviously hardware is not... People don't have the spending momentum today that they used to. They've got other priorities, et cetera, but I want to start and go kind of around the horn with each of you, what is the number one trend that each of you sees in hardware and why does it matter? Bob O'Donnell, can you please start us off? >> Sure Dave, so look, I mean, hardware is incredibly important and one comment first I'll make on that slide is let's not forget that hardware, even though it may not be growing, the amount of money spent on hardware continues to be very, very high. It's just a little bit more stable. It's not as subject to big jumps as we see certainly in other software areas. But look, the important thing that's happening in hardware is the diversification of the types of chip architectures we're seeing and how and where they're being deployed, right? You refer to this in your opening. We've moved from a world of x86 CPUs from Intel and AMD to things like obviously GPUs, DPUs. We've got VPU for, you know, computer vision processing. We've got AI-dedicated accelerators, we've got all kinds of other network acceleration tools and AI-powered tools. There's an incredible diversification of these chip architectures and that's been happening for a while but now we're seeing them more widely deployed and it's being done that way because workloads are evolving. The kinds of workloads that we're seeing in some of these software areas require different types of compute engines than traditionally we've had. The other thing is (coughs), excuse me, the power requirements based on where geographically that compute happens is also evolving. This whole notion of the edge, which I'm sure we'll get into a little bit more detail later is driven by the fact that where the compute actually sits closer to in theory the edge and where edge devices are, depending on your definition, changes the power requirements. It changes the kind of connectivity that connects the applications to those edge devices and those applications. So all of those things are being impacted by this growing diversity in chip architectures. And that's a very long-term trend that I think we're going to continue to see play out through this decade and well into the 2030s as well. >> Excellent, great, great points. Thank you, Bob. Zeus up next, please. >> Yeah, and I think the other thing when you look at this chart to remember too is, you know, through the pandemic and the work from home period a lot of companies did put their office modernization projects on hold and you heard that echoed, you know, from really all the network manufacturers anyways. They always had projects underway to upgrade networks. They put 'em on hold. Now that people are starting to come back to the office, they're looking at that now. So we might see some change there, but Bob's right. The size of those market are quite a bit different. I think the other big trend here is the hardware companies, at least in the areas that I look at networking are understanding now that it's a combination of hardware and software and silicon that works together that creates that optimum type of performance and experience, right? So some things are best done in silicon. Some like data forwarding and things like that. Historically when you look at the way network devices were built, you did everything in hardware. You configured in hardware, they did all the data for you, and did all the management. And that's been decoupled now. So more and more of the control element has been placed in software. A lot of the high-performance things, encryption, and as I mentioned, data forwarding, packet analysis, stuff like that is still done in hardware, but not everything is done in hardware. And so it's a combination of the two. I think, for the people that work with the equipment as well, there's been more shift to understanding how to work with software. And this is a mistake I think the industry made for a while is we had everybody convinced they had to become a programmer. It's really more a software power user. Can you pull things out of software? Can you through API calls and things like that. But I think the big frame here is, David, it's a combination of hardware, software working together that really make a difference. And you know how much you invest in hardware versus software kind of depends on the performance requirements you have. And I'll talk about that later but that's really the big shift that's happened here. It's the vendors that figured out how to optimize performance by leveraging the best of all of those. >> Excellent. You guys both brought up some really good themes that we can tap into Dave Nicholson, please. >> Yeah, so just kind of picking up where Bob started off. Not only are we seeing the rise of a variety of CPU designs, but I think increasingly the connectivity that's involved from a hardware perspective, from a kind of a server or service design perspective has become increasingly important. I think we'll get a chance to look at this in more depth a little bit later but when you look at what happens on the motherboard, you know we're not in so much a CPU-centric world anymore. Various application environments have various demands and you can meet them by using a variety of components. And it's extremely significant when you start looking down at the component level. It's really important that you optimize around those components. So I guess my summary would be, I think we are moving out of the CPU-centric hardware model into more of a connectivity-centric model. We can talk more about that later. >> Yeah, great. And thank you, David, and Keith Townsend I really interested in your perspectives on this. I mean, for years you worked in a data center surrounded by hardware. Now that we have the software defined data center, please chime in here. >> Well, you know, I'm going to dig deeper into that software-defined data center nature of what's happening with hardware. Hardware is meeting software infrastructure as code is a thing. What does that code look like? We're still trying to figure out but servicing up these capabilities that the previous analysts have brought up, how do I ensure that I can get the level of services needed for the applications that I need? Whether they're legacy, traditional data center, workloads, AI ML, workloads, workloads at the edge. How do I codify that and consume that as a service? And hardware vendors are figuring this out. HPE, the big push into GreenLake as a service. Dale now with Apex taking what we need, these bare bone components, moving it forward with DDR five, six CXL, et cetera, and surfacing that as cold or as services. This is a very tough problem. As we transition from consuming a hardware-based configuration to this infrastructure as cold paradigm shift. >> Yeah, programmable infrastructure, really attacking that sort of labor discussion that we were having earlier, okay. Last but not least Marc Staimer, please. >> Thanks, Dave. My peers raised really good points. I agree with most of them, but I'm going to disagree with the title of this session, which is, does hardware matter? It absolutely matters. You can't run software on the air. You can't run it in an ephemeral cloud, although there's the technical cloud and that's a different issue. The cloud is kind of changed everything. And from a market perspective in the 40 plus years I've been in this business, I've seen this perception that hardware has to go down in price every year. And part of that was driven by Moore's law. And we're coming to, let's say a lag or an end, depending on who you talk to Moore's law. So we're not doubling our transistors every 18 to 24 months in a chip and as a result of that, there's been a higher emphasis on software. From a market perception, there's no penalty. They don't put the same pressure on software from the market to reduce the cost every year that they do on hardware, which kind of bass ackwards when you think about it. Hardware costs are fixed. Software costs tend to be very low. It's kind of a weird thing that we do in the market. And what's changing is we're now starting to treat hardware like software from an OPEX versus CapEx perspective. So yes, hardware matters. And we'll talk about that more in length. >> You know, I want to follow up on that. And I wonder if you guys have a thought on this, Bob O'Donnell, you and I have talked about this a little bit. Marc, you just pointed out that Moore's laws could have waning. Pat Gelsinger recently at their investor meeting said that he promised that Moore's law is alive and well. And the point I made in breaking analysis was okay, great. You know, Pat said, doubling transistors every 18 to 24 months, let's say that Intel can do that. Even though we know it's waning somewhat. Look at the M1 Ultra from Apple (chuckles). In about 15 months increased transistor density on their package by 6X. So to your earlier point, Bob, we have this sort of these alternative processors that are really changing things. And to Dave Nicholson's point, there's a whole lot of supporting components as well. Do you have a comment on that, Bob? >> Yeah, I mean, it's a great point, Dave. And one thing to bear in mind as well, not only are we seeing a diversity of these different chip architectures and different types of components as a number of us have raised the other big point and I think it was Keith that mentioned it. CXL and interconnect on the chip itself is dramatically changing it. And a lot of the more interesting advances that are going to continue to drive Moore's law forward in terms of the way we think about performance, if perhaps not number of transistors per se, is the interconnects that become available. You're seeing the development of chiplets or tiles, people use different names, but the idea is you can have different components being put together eventually in sort of a Lego block style. And what that's also going to allow, not only is that going to give interesting performance possibilities 'cause of the faster interconnect. So you can share, have shared memory between things which for big workloads like AI, huge data sets can make a huge difference in terms of how you talk to memory over a network connection, for example, but not only that you're going to see more diversity in the types of solutions that can be built. So we're going to see even more choices in hardware from a silicon perspective because you'll be able to piece together different elements. And oh, by the way, the other benefit of that is we've reached a point in chip architectures where not everything benefits from being smaller. We've been so focused and so obsessed when it comes to Moore's law, to the size of each individual transistor and yes, for certain architecture types, CPUs and GPUs in particular, that's absolutely true, but we've already hit the point where things like RF for 5g and wifi and other wireless technologies and a whole bunch of other things actually don't get any better with a smaller transistor size. They actually get worse. So the beauty of these chiplet architectures is you could actually combine different chip manufacturing sizes. You know you hear about four nanometer and five nanometer along with 14 nanometer on a single chip, each one optimized for its specific application yet together, they can give you the best of all worlds. And so we're just at the very beginning of that era, which I think is going to drive a ton of innovation. Again, gets back to my comment about different types of devices located geographically different places at the edge, in the data center, you know, in a private cloud versus a public cloud. All of those things are going to be impacted and there'll be a lot more options because of this silicon diversity and this interconnect diversity that we're just starting to see. >> Yeah, David. David Nicholson's got a graphic on that. They're going to show later. Before we do that, I want to introduce some data. I actually want to ask Keith to comment on this before we, you know, go on. This next slide is some data from ETR that shows the percent of customers that cited difficulty procuring hardware. And you can see the red is they had significant issues and it's most pronounced in laptops and networking hardware on the far right-hand side, but virtually all categories, firewalls, peripheral servers, storage are having moderately difficult procurement issues. That's the sort of pinkish or significant challenges. So Keith, I mean, what are you seeing with your customers in the hardware supply chains and bottlenecks? And you know we're seeing it with automobiles and appliances but so it goes beyond IT. The semiconductor, you know, challenges. What's been the impact on the buyer community and society and do you have any sense as to when it will subside? >> You know, I was just asked this question yesterday and I'm feeling the pain. People question, kind of a side project within the CTO advisor, we built a hybrid infrastructure, traditional IT data center that we're walking with the traditional customer and modernizing that data center. So it was, you know, kind of a snapshot of time in 2016, 2017, 10 gigabit, ARISTA switches, some older Dell's 730 XD switches, you know, speeds and feeds. And we said we would modern that with the latest Intel stack and connected to the public cloud and then the pandemic hit and we are experiencing a lot of the same challenges. I thought we'd easily migrate from 10 gig networking to 25 gig networking path that customers are going on. The 10 gig network switches that I bought used are now double the price because you can't get legacy 10 gig network switches because all of the manufacturers are focusing on the more profitable 25 gig for capacity, even the 25 gig switches. And we're focused on networking right now. It's hard to procure. We're talking about nine to 12 months or more lead time. So we're seeing customers adjust by adopting cloud. But if you remember early on in the pandemic, Microsoft Azure kind of gated customers that didn't have a capacity agreement. So customers are keeping an eye on that. There's a desire to abstract away from the underlying vendor to be able to control or provision your IT services in a way that we do with VMware VP or some other virtualization technology where it doesn't matter who can get me the hardware, they can just get me the hardware because it's critically impacting projects and timelines. >> So that's a great setup Zeus for you with Keith mentioned the earlier the software-defined data center with software-defined networking and cloud. Do you see a day where networking hardware is monetized and it's all about the software, or are we there already? >> No, we're not there already. And I don't see that really happening any time in the near future. I do think it's changed though. And just to be clear, I mean, when you look at that data, this is saying customers have had problems procuring the equipment, right? And there's not a network vendor out there. I've talked to Norman Rice at Extreme, and I've talked to the folks at Cisco and ARISTA about this. They all said they could have had blowout quarters had they had the inventory to ship. So it's not like customers aren't buying this anymore. Right? I do think though, when it comes to networking network has certainly changed some because there's a lot more controls as I mentioned before that you can do in software. And I think the customers need to start thinking about the types of hardware they buy and you know, where they're going to use it and, you know, what its purpose is. Because I've talked to customers that have tried to run software and commodity hardware and where the performance requirements are very high and it's bogged down, right? It just doesn't have the horsepower to run it. And, you know, even when you do that, you have to start thinking of the components you use. The NICs you buy. And I've talked to customers that have simply just gone through the process replacing a NIC card and a commodity box and had some performance problems and, you know, things like that. So if agility is more important than performance, then by all means try running software on commodity hardware. I think that works in some cases. If performance though is more important, that's when you need that kind of turnkey hardware system. And I've actually seen more and more customers reverting back to that model. In fact, when you talk to even some startups I think today about when they come to market, they're delivering things more on appliances because that's what customers want. And so there's this kind of app pivot this pendulum of agility and performance. And if performance absolutely matters, that's when you do need to buy these kind of turnkey, prebuilt hardware systems. If agility matters more, that's when you can go more to software, but the underlying hardware still does matter. So I think, you know, will we ever have a day where you can just run it on whatever hardware? Maybe but I'll long be retired by that point. So I don't care. >> Well, you bring up a good point Zeus. And I remember the early days of cloud, the narrative was, oh, the cloud vendors. They don't use EMC storage, they just run on commodity storage. And then of course, low and behold, you know, they've trot out James Hamilton to talk about all the custom hardware that they were building. And you saw Google and Microsoft follow suit. >> Well, (indistinct) been falling for this forever. Right? And I mean, all the way back to the turn of the century, we were calling for the commodity of hardware. And it's never really happened because you can still drive. As long as you can drive innovation into it, customers will always lean towards the innovation cycles 'cause they get more features faster and things. And so the vendors have done a good job of keeping that cycle up but it'll be a long time before. >> Yeah, and that's why you see companies like Pure Storage. A storage company has 69% gross margins. All right. I want to go jump ahead. We're going to bring up the slide four. I want to go back to something that Bob O'Donnell was talking about, the sort of supporting act. The diversity of silicon and we've marched to the cadence of Moore's law for decades. You know, we asked, you know, is Moore's law dead? We say it's moderating. Dave Nicholson. You want to talk about those supporting components. And you shared with us a slide that shift. You call it a shift from a processor-centric world to a connect-centric world. What do you mean by that? And let's bring up slide four and you can talk to that. >> Yeah, yeah. So first, I want to echo this sentiment that the question does hardware matter is sort of the answer is of course it matters. Maybe the real question should be, should you care about it? And the answer to that is it depends who you are. If you're an end user using an application on your mobile device, maybe you don't care how the architecture is put together. You just care that the service is delivered but as you back away from that and you get closer and closer to the source, someone needs to care about the hardware and it should matter. Why? Because essentially what hardware is doing is it's consuming electricity and dollars and the more efficiently you can configure hardware, the more bang you're going to get for your buck. So it's not only a quantitative question in terms of how much can you deliver? But it also ends up being a qualitative change as capabilities allow for things we couldn't do before, because we just didn't have the aggregate horsepower to do it. So this chart actually comes out of some performance tests that were done. So it happens to be Dell servers with Broadcom components. And the point here was to peel back, you know, peel off the top of the server and look at what's in that server, starting with, you know, the PCI interconnect. So PCIE gen three, gen four, moving forward. What are the effects on from an interconnect versus on performance application performance, translating into new orders per minute, processed per dollar, et cetera, et cetera? If you look at the advances in CPU architecture mapped against the advances in interconnect and storage subsystem performance, you can see that CPU architecture is sort of lagging behind in a way. And Bob mentioned this idea of tiling and all of the different ways to get around that. When we do performance testing, we can actually peg CPUs, just running the performance tests without any actual database environments working. So right now we're at this sort of imbalance point where you have to make sure you design things properly to get the most bang per kilowatt hour of power per dollar input. So the key thing here what this is highlighting is just as a very specific example, you take a card that's designed as a gen three PCIE device, and you plug it into a gen four slot. Now the card is the bottleneck. You plug a gen four card into a gen four slot. Now the gen four slot is the bottleneck. So we're constantly chasing these bottlenecks. Someone has to be focused on that from an architectural perspective, it's critically important. So there's no question that it matters. But of course, various people in this food chain won't care where it comes from. I guess a good analogy might be, where does our food come from? If I get a steak, it's a pink thing wrapped in plastic, right? Well, there are a lot of inputs that a lot of people have to care about to get that to me. Do I care about all of those things? No. Are they important? They're critically important. >> So, okay. So all I want to get to the, okay. So what does this all mean to customers? And so what I'm hearing from you is to balance a system it's becoming, you know, more complicated. And I kind of been waiting for this day for a long time, because as we all know the bottleneck was always the spinning disc, the last mechanical. So people who wrote software knew that when they were doing it right, the disc had to go and do stuff. And so they were doing other things in the software. And now with all these new interconnects and flash and things like you could do atomic rights. And so that opens up new software possibilities and combine that with alternative processes. But what's the so what on this to the customer and the application impact? Can anybody address that? >> Yeah, let me address that for a moment. I want to leverage some of the things that Bob said, Keith said, Zeus said, and David said, yeah. So I'm a bit of a contrarian in some of this. For example, on the chip side. As the chips get smaller, 14 nanometer, 10 nanometer, five nanometer, soon three nanometer, we talk about more cores, but the biggest problem on the chip is the interconnect from the chip 'cause the wires get smaller. People don't realize in 2004 the latency on those wires in the chips was 80 picoseconds. Today it's 1300 picoseconds. That's on the chip. This is why they're not getting faster. So we maybe getting a little bit slowing down in Moore's law. But even as we kind of conquer that you still have the interconnect problem and the interconnect problem goes beyond the chip. It goes within the system, composable architectures. It goes to the point where Keith made, ultimately you need a hybrid because what we're seeing, what I'm seeing and I'm talking to customers, the biggest issue they have is moving data. Whether it be in a chip, in a system, in a data center, between data centers, moving data is now the biggest gating item in performance. So if you want to move it from, let's say your transactional database to your machine learning, it's the bottleneck, it's moving the data. And so when you look at it from a distributed environment, now you've got to move the compute to the data. The only way to get around these bottlenecks today is to spend less time in trying to move the data and more time in taking the compute, the software, running on hardware closer to the data. Go ahead. >> So is this what you mean when Nicholson was talking about a shift from a processor centric world to a connectivity centric world? You're talking about moving the bits across all the different components, not having the processor you're saying is essentially becoming the bottleneck or the memory, I guess. >> Well, that's one of them and there's a lot of different bottlenecks, but it's the data movement itself. It's moving away from, wait, why do we need to move the data? Can we move the compute, the processing closer to the data? Because if we keep them separate and this has been a trend now where people are moving processing away from it. It's like the edge. I think it was Zeus or David. You were talking about the edge earlier. As you look at the edge, who defines the edge, right? Is the edge a closet or is it a sensor? If it's a sensor, how do you do AI at the edge? When you don't have enough power, you don't have enough computable. People were inventing chips to do that. To do all that at the edge, to do AI within the sensor, instead of moving the data to a data center or a cloud to do the processing. Because the lag in latency is always limited by speed of light. How fast can you move the electrons? And all this interconnecting, all the processing, and all the improvement we're seeing in the PCIE bus from three, to four, to five, to CXL, to a higher bandwidth on the network. And that's all great but none of that deals with the speed of light latency. And that's an-- Go ahead. >> You know Marc, no, I just want to just because what you're referring to could be looked at at a macro level, which I think is what you're describing. You can also look at it at a more micro level from a systems design perspective, right? I'm going to be the resident knuckle dragging hardware guy on the panel today. But it's exactly right. You moving compute closer to data includes concepts like peripheral cards that have built in intelligence, right? So again, in some of this testing that I'm referring to, we saw dramatic improvements when you basically took the horsepower instead of using the CPU horsepower for the like IO. Now you have essentially offload engines in the form of storage controllers, rate controllers, of course, for ethernet NICs, smart NICs. And so when you can have these sort of offload engines and we've gone through these waves over time. People think, well, wait a minute, raid controller and NVMe? You know, flash storage devices. Does that make sense? It turns out it does. Why? Because you're actually at a micro level doing exactly what you're referring to. You're bringing compute closer to the data. Now, closer to the data meaning closer to the data storage subsystem. It doesn't solve the macro issue that you're referring to but it is important. Again, going back to this idea of system design optimization, always chasing the bottleneck, plugging the holes. Someone needs to do that in this value chain in order to get the best value for every kilowatt hour of power and every dollar. >> Yeah. >> Well this whole drive performance has created some really interesting architectural designs, right? Like Nickelson, the rise of the DPU right? Brings more processing power into systems that already had a lot of processing power. There's also been some really interesting, you know, kind of innovation in the area of systems architecture too. If you look at the way Nvidia goes to market, their drive kit is a prebuilt piece of hardware, you know, optimized for self-driving cars, right? They partnered with Pure Storage and ARISTA to build that AI-ready infrastructure. I remember when I talked to Charlie Giancarlo, the CEO of Pure about when the three companies rolled that out. He said, "Look, if you're going to do AI, "you need good store. "You need fast storage, fast processor and fast network." And so for customers to be able to put that together themselves was very, very difficult. There's a lot of software that needs tuning as well. So the three companies partner together to create a fully integrated turnkey hardware system with a bunch of optimized software that runs on it. And so in that case, in some ways the hardware was leading the software innovation. And so, the variety of different architectures we have today around hardware has really exploded. And I think it, part of the what Bob brought up at the beginning about the different chip design. >> Yeah, Bob talked about that earlier. Bob, I mean, most AI today is modeling, you know, and a lot of that's done in the cloud and it looks from my standpoint anyway that the future is going to be a lot of AI inferencing at the edge. And that's a radically different architecture, Bob, isn't it? >> It is, it's a completely different architecture. And just to follow up on a couple points, excellent conversation guys. Dave talked about system architecture and really this that's what this boils down to, right? But it's looking at architecture at every level. I was talking about the individual different components the new interconnect methods. There's this new thing called UCIE universal connection. I forget what it stands answer for, but it's a mechanism for doing chiplet architectures, but then again, you have to take it up to the system level, 'cause it's all fine and good. If you have this SOC that's tuned and optimized, but it has to talk to the rest of the system. And that's where you see other issues. And you've seen things like CXL and other interconnect standards, you know, and nobody likes to talk about interconnect 'cause it's really wonky and really technical and not that sexy, but at the end of the day it's incredibly important exactly. To the other points that were being raised like mark raised, for example, about getting that compute closer to where the data is and that's where again, a diversity of chip architectures help and exactly to your last comment there Dave, putting that ability in an edge device is really at the cutting edge of what we're seeing on a semiconductor design and the ability to, for example, maybe it's an FPGA, maybe it's a dedicated AI chip. It's another kind of chip architecture that's being created to do that inferencing on the edge. Because again, it's that the cost and the challenges of moving lots of data, whether it be from say a smartphone to a cloud-based application or whether it be from a private network to a cloud or any other kinds of permutations we can think of really matters. And the other thing is we're tackling bigger problems. So architecturally, not even just architecturally within a system, but when we think about DPUs and the sort of the east west data center movement conversation that we hear Nvidia and others talk about, it's about combining multiple sets of these systems to function together more efficiently again with even bigger sets of data. So really is about tackling where the processing is needed, having the interconnect and the ability to get where the data you need to the right place at the right time. And because those needs are diversifying, we're just going to continue to see an explosion of different choices and options, which is going to make hardware even more essential I would argue than it is today. And so I think what we're going to see not only does hardware matter, it's going to matter even more in the future than it does now. >> Great, yeah. Great discussion, guys. I want to bring Keith back into the conversation here. Keith, if your main expertise in tech is provisioning LUNs, you probably you want to look for another job. So maybe clearly hardware matters, but with software defined everything, do people with hardware expertise matter outside of for instance, component manufacturers or cloud companies? I mean, VMware certainly changed the dynamic in servers. Dell just spun off its most profitable asset and VMware. So it obviously thinks hardware can stand alone. How does an enterprise architect view the shift to software defined hyperscale cloud and how do you see the shifting demand for skills in enterprise IT? >> So I love the question and I'll take a different view of it. If you're a data analyst and your primary value add is that you do ETL transformation, talk to a CDO, a chief data officer over midsize bank a little bit ago. He said 80% of his data scientists' time is done on ETL. Super not value ad. He wants his data scientists to do data science work. Chances are if your only value is that you do LUN provisioning, then you probably don't have a job now. The technologies have gotten much more intelligent. As infrastructure pros, we want to give infrastructure pros the opportunities to shine and I think the software defined nature and the automation that we're seeing vendors undertake, whether it's Dell, HP, Lenovo take your pick that Pure Storage, NetApp that are doing the automation and the ML needed so that these practitioners don't spend 80% of their time doing LUN provisioning and focusing on their true expertise, which is ensuring that data is stored. Data is retrievable, data's protected, et cetera. I think the shift is to focus on that part of the job that you're ensuring no matter where the data's at, because as my data is spread across the enterprise hybrid different types, you know, Dave, you talk about the super cloud a lot. If my data is in the super cloud, protecting that data and securing that data becomes much more complicated when than when it was me just procuring or provisioning LUNs. So when you say, where should the shift be, or look be, you know, focusing on the real value, which is making sure that customers can access data, can recover data, can get data at performance levels that they need within the price point. They need to get at those datasets and where they need it. We talked a lot about where they need out. One last point about this interconnecting. I have this vision and I think we all do of composable infrastructure. This idea that scaled out does not solve every problem. The cloud can give me infinite scale out. Sometimes I just need a single OS with 64 terabytes of RAM and 204 GPUs or GPU instances that single OS does not exist today. And the opportunity is to create composable infrastructure so that we solve a lot of these problems that just simply don't scale out. >> You know, wow. So many interesting points there. I had just interviewed Zhamak Dehghani, who's the founder of Data Mesh last week. And she made a really interesting point. She said, "Think about, we have separate stacks. "We have an application stack and we have "a data pipeline stack and the transaction systems, "the transaction database, we extract data from that," to your point, "We ETL it in, you know, it takes forever. "And then we have this separate sort of data stack." If we're going to inject more intelligence and data and AI into applications, those two stacks, her contention is they have to come together. And when you think about, you know, super cloud bringing compute to data, that was what Haduck was supposed to be. It ended up all sort of going into a central location, but it's almost a rhetorical question. I mean, it seems that that necessitates new thinking around hardware architectures as it kind of everything's the edge. And the other point is to your point, Keith, it's really hard to secure that. So when you can think about offloads, right, you've heard the stats, you know, Nvidia talks about it. Broadcom talks about it that, you know, that 30%, 25 to 30% of the CPU cycles are wasted on doing things like storage offloads, or networking or security. It seems like maybe Zeus you have a comment on this. It seems like new architectures need to come other to support, you know, all of that stuff that Keith and I just dispute. >> Yeah, and by the way, I do want to Keith, the question you just asked. Keith, it's the point I made at the beginning too about engineers do need to be more software-centric, right? They do need to have better software skills. In fact, I remember talking to Cisco about this last year when they surveyed their engineer base, only about a third of 'em had ever made an API call, which you know that that kind of shows this big skillset change, you know, that has to come. But on the point of architectures, I think the big change here is edge because it brings in distributed compute models. Historically, when you think about compute, even with multi-cloud, we never really had multi-cloud. We'd use multiple centralized clouds, but compute was always centralized, right? It was in a branch office, in a data center, in a cloud. With edge what we creates is the rise of distributed computing where we'll have an application that actually accesses different resources and at different edge locations. And I think Marc, you were talking about this, like the edge could be in your IoT device. It could be your campus edge. It could be cellular edge, it could be your car, right? And so we need to start thinkin' about how our applications interact with all those different parts of that edge ecosystem, you know, to create a single experience. The consumer apps, a lot of consumer apps largely works that way. If you think of like app like Uber, right? It pulls in information from all kinds of different edge application, edge services. And, you know, it creates pretty cool experience. We're just starting to get to that point in the business world now. There's a lot of security implications and things like that, but I do think it drives more architectural decisions to be made about how I deploy what data where and where I do my processing, where I do my AI and things like that. It actually makes the world more complicated. In some ways we can do so much more with it, but I think it does drive us more towards turnkey systems, at least initially in order to, you know, ensure performance and security. >> Right. Marc, I wanted to go to you. You had indicated to me that you wanted to chat about this a little bit. You've written quite a bit about the integration of hardware and software. You know, we've watched Oracle's move from, you know, buying Sun and then basically using that in a highly differentiated approach. Engineered systems. What's your take on all that? I know you also have some thoughts on the shift from CapEx to OPEX chime in on that. >> Sure. When you look at it, there are advantages to having one vendor who has the software and hardware. They can synergistically make them work together that you can't do in a commodity basis. If you own the software and somebody else has the hardware, I'll give you an example would be Oracle. As you talked about with their exit data platform, they literally are leveraging microcode in the Intel chips. And now in AMD chips and all the way down to Optane, they make basically AMD database servers work with Optane memory PMM in their storage systems, not MVME, SSD PMM. I'm talking about the cards itself. So there are advantages you can take advantage of if you own the stack, as you were putting out earlier, Dave, of both the software and the hardware. Okay, that's great. But on the other side of that, that tends to give you better performance, but it tends to cost a little more. On the commodity side it costs less but you get less performance. What Zeus had said earlier, it depends where you're running your application. How much performance do you need? What kind of performance do you need? One of the things about moving to the edge and I'll get to the OPEX CapEx in a second. One of the issues about moving to the edge is what kind of processing do you need? If you're running in a CCTV camera on top of a traffic light, how much power do you have? How much cooling do you have that you can run this? And more importantly, do you have to take the data you're getting and move it somewhere else and get processed and the information is sent back? I mean, there are companies out there like Brain Chip that have developed AI chips that can run on the sensor without a CPU. Without any additional memory. So, I mean, there's innovation going on to deal with this question of data movement. There's companies out there like Tachyon that are combining GPUs, CPUs, and DPUs in a single chip. Think of it as super composable architecture. They're looking at being able to do more in less. On the OPEX and CapEx issue. >> Hold that thought, hold that thought on the OPEX CapEx, 'cause we're running out of time and maybe you can wrap on that. I just wanted to pick up on something you said about the integrated hardware software. I mean, other than the fact that, you know, Michael Dell unlocked whatever $40 billion for himself and Silverlake, I was always a fan of a spin in with VMware basically become the Oracle of hardware. Now I know it would've been a nightmare for the ecosystem and culturally, they probably would've had a VMware brain drain, but what does anybody have any thoughts on that as a sort of a thought exercise? I was always a fan of that on paper. >> I got to eat a little crow. I did not like the Dale VMware acquisition for the industry in general. And I think it hurt the industry in general, HPE, Cisco walked away a little bit from that VMware relationship. But when I talked to customers, they loved it. You know, I got to be honest. They absolutely loved the integration. The VxRail, VxRack solution exploded. Nutanix became kind of a afterthought when it came to competing. So that spin in, when we talk about the ability to innovate and the ability to create solutions that you just simply can't create because you don't have the full stack. Dell was well positioned to do that with a potential span in of VMware. >> Yeah, we're going to be-- Go ahead please. >> Yeah, in fact, I think you're right, Keith, it was terrible for the industry. Great for Dell. And I remember talking to Chad Sakac when he was running, you know, VCE, which became Rack and Rail, their ability to stay in lockstep with what VMware was doing. What was the number one workload running on hyperconverged forever? It was VMware. So their ability to remain in lockstep with VMware gave them a huge competitive advantage. And Dell came out of nowhere in, you know, the hyper-converged market and just started taking share because of that relationship. So, you know, this sort I guess it's, you know, from a Dell perspective I thought it gave them a pretty big advantage that they didn't really exploit across their other properties, right? Networking and service and things like they could have given the dominance that VMware had. From an industry perspective though, I do think it's better to have them be coupled. So. >> I agree. I mean, they could. I think they could have dominated in super cloud and maybe they would become the next Oracle where everybody hates 'em, but they kick ass. But guys. We got to wrap up here. And so what I'm going to ask you is I'm going to go and reverse the order this time, you know, big takeaways from this conversation today, which guys by the way, I can't thank you enough phenomenal insights, but big takeaways, any final thoughts, any research that you're working on that you want highlight or you know, what you look for in the future? Try to keep it brief. We'll go in reverse order. Maybe Marc, you could start us off please. >> Sure, on the research front, I'm working on a total cost of ownership of an integrated database analytics machine learning versus separate services. On the other aspect that I would wanted to chat about real quickly, OPEX versus CapEx, the cloud changed the market perception of hardware in the sense that you can use hardware or buy hardware like you do software. As you use it, pay for what you use in arrears. The good thing about that is you're only paying for what you use, period. You're not for what you don't use. I mean, it's compute time, everything else. The bad side about that is you have no predictability in your bill. It's elastic, but every user I've talked to says every month it's different. And from a budgeting perspective, it's very hard to set up your budget year to year and it's causing a lot of nightmares. So it's just something to be aware of. From a CapEx perspective, you have no more CapEx if you're using that kind of base system but you lose a certain amount of control as well. So ultimately that's some of the issues. But my biggest point, my biggest takeaway from this is the biggest issue right now that everybody I talk to in some shape or form it comes down to data movement whether it be ETLs that you talked about Keith or other aspects moving it between hybrid locations, moving it within a system, moving it within a chip. All those are key issues. >> Great, thank you. Okay, CTO advisor, give us your final thoughts. >> All right. Really, really great commentary. Again, I'm going to point back to us taking the walk that our customers are taking, which is trying to do this conversion of all primary data center to a hybrid of which I have this hard earned philosophy that enterprise IT is additive. When we add a service, we rarely subtract a service. So the landscape and service area what we support has to grow. So our research focuses on taking that walk. We are taking a monolithic application, decomposing that to containers, and putting that in a public cloud, and connecting that back private data center and telling that story and walking that walk with our customers. This has been a super enlightening panel. >> Yeah, thank you. Real, real different world coming. David Nicholson, please. >> You know, it really hearkens back to the beginning of the conversation. You talked about momentum in the direction of cloud. I'm sort of spending my time under the hood, getting grease under my fingernails, focusing on where still the lions share of spend will be in coming years, which is OnPrem. And then of course, obviously data center infrastructure for cloud but really diving under the covers and helping folks understand the ramifications of movement between generations of CPU architecture. I know we all know Sapphire Rapids pushed into the future. When's the next Intel release coming? Who knows? We think, you know, in 2023. There have been a lot of people standing by from a practitioner's standpoint asking, well, what do I do between now and then? Does it make sense to upgrade bits and pieces of hardware or go from a last generation to a current generation when we know the next generation is coming? And so I've been very, very focused on looking at how these connectivity components like rate controllers and NICs. I know it's not as sexy as talking about cloud but just how these opponents completely change the game and actually can justify movement from say a 14th-generation architecture to a 15th-generation architecture today, even though gen 16 is coming, let's say 12 months from now. So that's where I am. Keep my phone number in the Rolodex. I literally reference Rolodex intentionally because like I said, I'm in there under the hood and it's not as sexy. But yeah, so that's what I'm focused on Dave. >> Well, you know, to paraphrase it, maybe derivative paraphrase of, you know, Larry Ellison's rant on what is cloud? It's operating systems and databases, et cetera. Rate controllers and NICs live inside of clouds. All right. You know, one of the reasons I love working with you guys is 'cause have such a wide observation space and Zeus Kerravala you, of all people, you know you have your fingers in a lot of pies. So give us your final thoughts. >> Yeah, I'm not a propeller heady as my chip counterparts here. (all laugh) So, you know, I look at the world a little differently and a lot of my research I'm doing now is the impact that distributed computing has on customer employee experiences, right? You talk to every business and how the experiences they deliver to their customers is really differentiating how they go to market. And so they're looking at these different ways of feeding up data and analytics and things like that in different places. And I think this is going to have a really profound impact on enterprise IT architecture. We're putting more data, more compute in more places all the way down to like little micro edges and retailers and things like that. And so we need the variety. Historically, if you think back to when I was in IT you know, pre-Y2K, we didn't have a lot of choice in things, right? We had a server that was rack mount or standup, right? And there wasn't a whole lot of, you know, differences in choice. But today we can deploy, you know, these really high-performance compute systems on little blades inside servers or inside, you know, autonomous vehicles and things. I think the world from here gets... You know, just the choice of what we have and the way hardware and software works together is really going to, I think, change the world the way we do things. We're already seeing that, like I said, in the consumer world, right? There's so many things you can do from, you know, smart home perspective, you know, natural language processing, stuff like that. And it's starting to hit businesses now. So just wait and watch the next five years. >> Yeah, totally. The computing power at the edge is just going to be mind blowing. >> It's unbelievable what you can do at the edge. >> Yeah, yeah. Hey Z, I just want to say that we know you're not a propeller head and I for one would like to thank you for having your master's thesis hanging on the wall behind you 'cause we know that you studied basket weaving. >> I was actually a physics math major, so. >> Good man. Another math major. All right, Bob O'Donnell, you're going to bring us home. I mean, we've seen the importance of semiconductors and silicon in our everyday lives, but your last thoughts please. >> Sure and just to clarify, by the way I was a great books major and this was actually for my final paper. And so I was like philosophy and all that kind of stuff and literature but I still somehow got into tech. Look, it's been a great conversation and I want to pick up a little bit on a comment Zeus made, which is this it's the combination of the hardware and the software and coming together and the manner with which that needs to happen, I think is critically important. And the other thing is because of the diversity of the chip architectures and all those different pieces and elements, it's going to be how software tools evolve to adapt to that new world. So I look at things like what Intel's trying to do with oneAPI. You know, what Nvidia has done with CUDA. What other platform companies are trying to create tools that allow them to leverage the hardware, but also embrace the variety of hardware that is there. And so as those software development environments and software development tools evolve to take advantage of these new capabilities, that's going to open up a lot of interesting opportunities that can leverage all these new chip architectures. That can leverage all these new interconnects. That can leverage all these new system architectures and figure out ways to make that all happen, I think is going to be critically important. And then finally, I'll mention the research I'm actually currently working on is on private 5g and how companies are thinking about deploying private 5g and the potential for edge applications for that. So I'm doing a survey of several hundred us companies as we speak and really looking forward to getting that done in the next couple of weeks. >> Yeah, look forward to that. Guys, again, thank you so much. Outstanding conversation. Anybody going to be at Dell tech world in a couple of weeks? Bob's going to be there. Dave Nicholson. Well drinks on me and guys I really can't thank you enough for the insights and your participation today. Really appreciate it. Okay, and thank you for watching this special power panel episode of theCube Insights powered by ETR. Remember we publish each week on Siliconangle.com and wikibon.com. All these episodes they're available as podcasts. DM me or any of these guys. I'm at DVellante. You can email me at David.Vellante@siliconangle.com. Check out etr.ai for all the data. This is Dave Vellante. We'll see you next time. (upbeat music)

(gentle melody) >> Welcome back to theCUBE's live coverage of AWS Summit in San Francisco, California. Events are back. AWS Summit in New York City this summer, theCUBE will be there as well. Check us out there. I'm glad to have events back. It's great to have of everyone here. I'm John Furrier, host of theCUBE. Dr. Matt Wood is with me, CUBE alumni, now VP of Business Analytics Division of AWS. Matt, great to see you. >> Thank you, John. It's great to be here. I appreciate it. >> I always call you Dr. Matt Wood because Andy Jackson always says, "Dr. Matt, we would introduce you on the arena." (Matt laughs) >> Matt: The one and only. >> The one and only, Dr. Matt Wood. >> In joke, I love it. (laughs) >> Andy style. (Matt laughs) I think you had walk up music too. >> Yes, we all have our own personalized walk up music. >> So talk about your new role, not a new role, but you're running the analytics business for AWS. What does that consist of right now? >> Sure. So I work. I've got what I consider to be one of the best jobs in the world. I get to work with our customers and the teams at AWS to build the analytics services that millions of our customers use to slice dice, pivot, better understand their data, look at how they can use that data for reporting, looking backwards. And also look at how they can use that data looking forward, so predictive analytics and machine learning. So whether it is slicing and dicing in the lower level of Hadoop and the big data engines, or whether you're doing ETL with Glue, or whether you're visualizing the data in QuickSight or building your models in SageMaker. I got my fingers in a lot of pies. >> One of the benefits of having CUBE coverage with AWS since 2013 is watching the progression. You were on theCUBE that first year we were at Reinvent in 2013, and look at how machine learning just exploded onto the scene. You were involved in that from day one. It's still day one, as you guys say. What's the big thing now? Look at just what happened. Machine learning comes in and then a slew of services come in. You've got SageMaker, became a hot seller right out of the gate. The database stuff was kicking butt. So all this is now booming. That was a real generational change over for database. What's the perspective? What's your perspective on that's evolved? >> I think it's a really good point. I totally agree. I think for machine learning, there's sort of a Renaissance in machine learning and the application of machine learning. Machine learning as a technology has been around for 50 years, let's say. But to do machine learning right, you need like a lot of data. The data needs to be high quality. You need a lot of compute to be able to train those models and you have to be able to evaluate what those models mean as you apply them to real world problems. And so the cloud really removed a lot of the constraints. Finally, customers had all of the data that they needed. We gave them services to be able to label that data in a high quality way. There's all the compute you need to be able to train the models. And so where you go? And so the cloud really enabled this Renaissance with machine learning. And we're seeing honestly a similar Renaissance with data and analytics. If you look back five to ten years, analytics was something you did in batch, your data warehouse ran an analysis to do reconciliation at the end of the month, and that was it. (John laughs) And so that's when you needed it. But today, if your Redshift cluster isn't available, Uber drivers don't turn up, DoorDash deliveries don't get made. Analytics is now central to virtually every business, and it is central to virtually every business's digital transformation. And being able to take that data from a variety of sources, be able to query it with high performance, to be able to actually then start to augment that data with real information, which usually comes from technical experts and domain experts to form wisdom and information from raw data. That's kind of what most organizations are trying to do when they kind of go through this analytics journey. >> It's interesting. Dave Velanta and I always talk on theCUBE about the future. And you look back, the things we're talking about six years ago are actually happening now. And it's not hyped up statement to say digital transformation is actually happening now. And there's also times when we bang our fists on the table saying, say, "I really think this is so important." And David says, "John, you're going to die on that hill." (Matt laughs) And so I'm excited that this year, for the first time, I didn't die on that hill. I've been saying- >> Do all right. >> Data as code is the next infrastructure as code. And Dave's like, "What do you mean by that?" We're talking about how data gets... And it's happening. So we just had an event on our AWS startups.com site, a showcase for startups, and the theme was data as code. And interesting new trends emerging really clearly, the role of a data engineer, right? Like an SRE, what an SRE did for cloud, you have a new data engineering role because of the developer onboarding is massively increasing, exponentially, new developers. Data science scientists are growing, but the pipelining and managing and engineering as a system, almost like an operating system. >> Kind of as a discipline. >> So what's your reaction to that about this data engineer, data as code? Because if you have horizontally scalable data, you've got to be open, that's hard (laughs), okay? And you got to silo the data that needs to be siloed for compliance and reason. So that's a big policy around that. So what's your reaction to data's code and the data engineering phenomenon? >> It's a really good point. I think with any technology project inside of an organization, success with analytics or machine learning, it's kind of 50% technology and then 50% cultural. And you have often domain experts. Those could be physicians or drug design experts, or they could be financial experts or whoever they might be, got deep domain expertise, and then you've got technical implementation teams. And there's kind of a natural, often repulsive force. I don't mean that rudely, but they just don't talk the same language. And so the more complex a domain and the more complex the technology, the stronger their repulsive force. And it can become very difficult for domain experts to work closely with the technical experts to be able to actually get business decisions made. And so what data engineering does and data engineering is, in some cases a team, or it can be a role that you play. It's really allowing those two disciplines to speak the same language. You can think of it as plumbing, but I think of it as like a bridge. It's a bridge between the technical implementation and the domain experts, and that requires a very disparate range of skills. You've got to understand about statistics, you've got to understand about the implementation, you got to understand about the data, you got to understand about the domain. And if you can put all of that together, that data engineering discipline can be incredibly transformative for an organization because it builds the bridge between those two groups. >> I was advising some young computer science students at the sophomore, junior level just a couple of weeks ago, and I told them I would ask someone at Amazon this question. So I'll ask you, >> Matt: Okay. since you've been in the middle of it for years, they were asking me, and I was trying to mentor them on how do you become a data engineer, from a practical standpoint? Courseware, projects to work on, how to think, not just coding Python, because everyone's coding in Python, but what else can they do? So I was trying to help them. I didn't really know the answer myself. I was just trying to kind of help figure it out with them. So what is the answer, in your opinion, or the thoughts around advice to young students who want to be data engineers? Because data scientists is pretty clear on what that is. You use tools, you make visualizations, you manage data, you get answers and insights and then apply that to the business. That's an application. That's not the standing up a stack or managing the infrastructure. So what does that coding look like? What would your advice be to folks getting into a data engineering role? >> Yeah, I think if you believe this, what I said earlier about 50% technology, 50 % culture, the number one technology to learn as a data engineer is the tools in the cloud which allow you to aggregate data from virtually any source into something which is incrementally more valuable for the organization. That's really what data engineering is all about. It's about taking from multiple sources. Some people call them silos, but silos indicates that the storage is kind of fungible or undifferentiated. That's really not the case. Success requires you to have really purpose built, well crafted, high performance, low cost engines for all of your data. So understanding those tools and understanding how to use them, that's probably the most important technical piece. Python and programming and statistics go along with that, I think. And then the most important cultural part, I think is... It's just curiosity. You want to be able to, as a data engineer, you want to have a natural curiosity that drives you to seek the truth inside an organization, seek the truth of a particular problem, and to be able to engage because probably you're going to some choice as you go through your career about which domain you end up in. Maybe you're really passionate about healthcare, or you're really just passionate about transportation or media, whatever it might be. And you can allow that to drive a certain amount of curiosity. But within those roles, the domains are so broad you kind of got to allow your curiosity to develop and lead you to ask the right questions and engage in the right way with your teams, because you can have all the technical skills in the world. But if you're not able to help the team's truth seek through that curiosity, you simply won't be successful. >> We just had a guest, 20 year old founder, Johnny Dallas who was 16 when he worked at Amazon. Youngest engineer- >> Johnny Dallas is a great name, by the way. (both chuckle) >> It's his real name. It sounds like a football player. >> That's awesome. >> Rock star. Johnny CUBE, it's me. But he's young and he was saying... His advice was just do projects. >> Matt: And get hands on. Yeah. >> And I was saying, hey, I came from the old days where you get to stand stuff up and you hugged on for the assets because you didn't want to kill the project because you spent all this money. And he's like, yeah, with cloud you can shut it down. If you do a project that's not working and you get bad data no one's adopting it or you don't like it anymore, you shut it down, just something else. >> Yeah, totally. >> Instantly abandon it and move on to something new. That's a progression. >> Totally! The blast radius of decisions is just way reduced. We talk a lot about in the old world, trying to find the resources and get the funding is like, all right, I want to try out this kind of random idea that could be a big deal for the organization. I need $50 million and a new data center. You're not going to get anywhere. >> And you do a proposal, working backwards, documents all kinds of stuff. >> All that sort of stuff. >> Jump your hoops. >> So all of that is gone. But we sometimes forget that a big part of that is just the prototyping and the experimentation and the limited blast radius in terms of cost, and honestly, the most important thing is time, just being able to jump in there, fingers on keyboards, just try this stuff out. And that's why at AWS, we have... Part of the reason we have so many services, because we want, when you get into AWS, we want the whole toolbox to be available to every developer. And so as your ideas develop, you may want to jump from data that you have that's already in a database to doing realtime data. And then you have the tools there. And when you want to get into real time data, you don't just have kinesis, you have real time analytics, and you can run SQL against that data. The capabilities and the breadth really matter when it comes to prototyping. >> That's the culture piece, because what was once a dysfunctional behavior. I'm going to go off the reservation and try something behind my boss' back, now is a side hustle or fun project. So for fun, you can just code something. >> Yeah, totally. I remember my first Hadoop projects. I found almost literally a decommissioned set of servers in the data center that no one was using. They were super old. They're about to be literally turned off. And I managed to convince the team to leave them on for me for another month. And I installed Hadoop on them and got them going. That just seems crazy to me now that I had to go and convince anybody not to turn these servers off. But what it was like when you- >> That's when you came up with Elastic MapReduce because you said this is too hard, we got to make it easier. >> Basically yes. (John laughs) I was installing Hadoop version Beta 9.9 or whatever. It was like, this is really hard. >> We got to make it simpler. All right, good stuff. I love the walk down memory Lane. And also your advice. Great stuff. I think culture is huge. That's why I like Adam's keynote at Reinvent, Adam Selipsky talk about Pathfinders and trailblazers, because that's a blast radius impact when you can actually have innovation organically just come from anywhere. That's totally cool. >> Matt: Totally cool. >> All right, let's get into the product. Serverless has been hot. We hear a lot of EKS is hot. Containers are booming. Kubernetes is getting adopted, still a lot of work to do there. Cloud native developers are booming. Serverless, Lambda. How does that impact the analytics piece? Can you share the hot products around how that translates? >> Absolutely, yeah. >> Aurora, SageMaker. >> Yeah, I think it's... If you look at kind of the evolution and what customers are asking for, they don't just want low cost. They don't just want this broad set of services. They don't just want those services to have deep capabilities. They want those services to have as low an operating cost over time as possible. So we kind of really got it down. We got built a lot of muscle, a lot of services about getting up and running and experimenting and prototyping and turning things off and turning them on and turning them off. And that's all great. But actually, you really only in most projects start something once and then stop something once, and maybe there's an hour in between or maybe there's a year. But the real expense in terms of time and operations and complexity is sometimes in that running cost. And so we've heard very loudly and clearly from customers that running cost is just undifferentiated to them. And they want to spend more time on their work. And in analytics, that is slicing the data, pivoting the data, combining the data, labeling the data, training their models, running inference against their models, and less time doing the operational pieces. >> Is that why the service focuses there? >> Yeah, absolutely. It dramatically reduces the skill required to run these workloads of any scale. And it dramatically reduces the undifferentiated heavy lifting because you get to focus more of the time that you would have spent on the operations on the actual work that you want to get done. And so if you look at something just like Redshift Serverless, that we launched a Reinvent, we have a lot of customers that want to run the cluster, and they want to get into the weeds where there is benefit. We have a lot of customers that say there's no benefit for me, I just want to do the analytics. So you run the operational piece, you're the experts. We run 60 million instant startups every single day. We do this a lot. >> John: Exactly. We understand the operations- >> I just want the answers. Come on. >> So just give me the answers or just give me the notebook or just give me the inference prediction. Today, for example, we announced Serverless Inference. So now once you've trained your machine learning model, just run a few lines of code or you just click a few buttons and then you got an inference endpoint that you do not have to manage. And whether you're doing one query against that end point per hour or you're doing 10 million, we'll just scale it on the back end. I know we got not a lot of time left, but I want to get your reaction on this. One of the things about the data lakes not being data swamps has been, from what I've been reporting and hearing from customers, is that they want to retrain their machine learning algorithm. They need that data, they need the real time data, and they need the time series data. Even though the time has passed, they got to store in the data lake. So now the data lake's main function is being reusing the data to actually retrain. It works properly. So a lot of post mortems turn into actually business improvements to make the machine learnings smarter, faster. Do you see that same way? Do you see it the same way? >> Yeah, I think it's really interesting >> Or is that just... >> No, I think it's totally interesting because it's convenient to kind of think of analytics as a very clear progression from point A to point B. But really, you're navigating terrain for which you do not have a map, and you need a lot of help to navigate that terrain. And so having these services in place, not having to run the operations of those services, being able to have those services be secure and well governed. And we added PII detection today. It's something you can do automatically, to be able to use any unstructured data, run queries against that unstructured data. So today we added text queries. So you can just say, well, you can scan a badge, for example, and say, well, what's the name on this badge? And you don't have to identify where it is. We'll do all of that work for you. It's more like a branch than it is just a normal A to B path, a linear path. And that includes loops backwards. And sometimes you've got to get the results and use those to make improvements further upstream. And sometimes you've got to use those... And when you're downstream, it will be like, "Ah, I remember that." And you come back and bring it all together. >> Awesome. >> So it's a wonderful world for sure. >> Dr. Matt, we're here in theCUBE. Just take the last word and give the update while you're here what's the big news happening that you're announcing here at Summit in San Francisco, California, and update on the business analytics group. >> Yeah, we did a lot of announcements in the keynote. I encourage everyone to take a look at, that this morning with Swami. One of the ones I'm most excited about is the opportunity to be able to take dashboards, visualizations. We're all used to using these things. We see them in our business intelligence tools, all over the place. However, what we've heard from customers is like, yes, I want those analytics, I want that visualization, I want it to be up to date, but I don't actually want to have to go from my tools where I'm actually doing my work to another separate tool to be able to look at that information. And so today we announced 1-click public embedding for QuickSight dashboard. So today you can literally as easily as embedding a YouTube video, you can take a dashboard that you've built inside QuickSight, cut and paste the HTML, paste it into your application and that's it. That's what you have to do. It takes seconds. >> And it gets updated in real time. >> Updated in real time. It's interactive. You can do everything that you would normally do. You can brand it, there's no power by QuickSight button or anything like that. You can change the colors, fit in perfectly with your application. So that's an incredibly powerful way of being able to take an analytics capability that today sits inside its own little fiefdom and put it just everywhere. Very transformative. >> Awesome. And the business is going well. You got the Serverless detail win for you there. Good stuff. Dr. Matt Wood, thank you for coming on theCUBE. >> Anytime. Thank you. >> Okay, this is theCUBE's coverage of AWS Summit 2022 in San Francisco, California. I'm John Furrier, host of theCUBE. Stay with us for more coverage of day two after this short break. (gentle music)

>>Hello, everyone. Welcome to the cubes presentation of the 80 minutes startup showcase. Season two, episode two, the theme is data as code, the future of analytics. I'm John furry, your host. We had a great day lineup for you. Fast growing startups, great lineup of companies, founders, and stories around data as code. And we're going to kick it off here with our opening keynote with Rahul Pathak VP of analytics at AWS cube alumni. Right? We'll thank you for coming on and being the opening keynote for this awesome event. >>Yeah. And it's great to see you, and it's great to be part of this event, uh, excited to, um, to help showcase some of the great innovation that startups are doing on top of AWS. >>Yeah. We last spoke at AWS reinvent and, uh, a lot's happened there, service loss of serverless as the center of the, of the action, but all these start-ups rock set Dremio Cribble monks next Liccardo, a HANA imply all doing great stuff. Data as code has a lot of traction. So a lot of still momentum going on in the marketplace. Uh, pretty exciting. >>No, it's, uh, it's awesome. I mean, I think there's so much innovation happening and you know, the, the wonderful part of working with data is that the demand for services and products that help customers drive insight from data is just skyrocketing and has no sign of no sign of slowing down. And so it's a great time to be in the data business. >>It's interesting to see the theme of the show getting traction, because you start to see data being treated almost like how developers write software, taking things out of branches, working on them, putting them back in, uh, machine learnings, uh, getting iterated on you, seeing more models, being trained differently with better insights, action ones that all kind of like working like code. And this is a whole nother way. People are reinventing their businesses. This has been a big, huge wave. What's your reaction to that? >>Uh, I think it's spot on, I mean, I think the idea of data's code and bringing some of the repeatability of processes from software development into how people built it, applications is absolutely fundamental and especially so in machine learning where you need to think about the explainability of a model, what version of the world was it trained on? When you build a better model, you need to be able to explain and reproduce it. So I think your insights are spot on and these ideas are showing up in all stages of the data work flow from ingestion to analytics to I'm out >>This next way is about modernization and going to the next level with cloud-scale. Uh, thank you so much for coming on and being the keynote presenter here for this great event. Um, I'll let you take it away. Reinventing businesses, uh, with ads analytics, right? We'll take it away. >>Okay, perfect. Well, folks, we're going to talk about, uh, um, reinventing your business with, uh, data. And if you think about it, the first wave of reinvention was really driven by the cloud. As customers were able to really transform how they thought about technology and that's well on her way. Although if you stop and think about it, I think we're only about five to 10% of the way done in terms of it span being on the cloud. So lots of work to do there, but we're seeing another wave of reinvention, which is companies reinventing their businesses with data and really using data to transform what they're doing to look for new opportunities and look for ways to operate more efficiently. And I think the past couple of years of the pandemic, it really only accelerated that trend. And so what we're seeing is, uh, you know, it's really about the survival of the most informed folks for the best data are able to react more quickly to what's happening. >>Uh, we've seen customers being able to scale up if they're in, say the delivery business or scale down, if they were in the travel business at the beginning of all of this, and then using data to be able to find new opportunities and new ways to serve customers. And so it's really foundational and we're seeing this across the board. And so, um, you know, it's great to see the innovation that's happening to help customers make sense of all of this. And our customers are really looking at ways to put data to work. It's about making better decisions, finding new efficiencies and really finding new opportunities to succeed and scale. And, um, you know, when it comes to, uh, good examples of this FINRA is a great one. You may not have heard of them, but that the U S equities regulators, all trading that happens in equities, they keep track of they're look at about 250 billion records per day. >>Uh, the examiner, I was only EMR, which is our spark and Hadoop service, and they're processing 20 terabytes of data running across tens of thousands of nodes. And they're looking for fraud and bad actors in the market. So, um, you know, huge, uh, transformation journey for FINRA over the years of customer I've gotten to work with personally since really 2013 onward. So it's been amazing to see their journey, uh, Pinterest, not a great customer. I'm sure everyone's familiar with, but, um, you know, they're about visual search and discovery and commerce, and, um, they're able to scale their daily lot searches, um, really a factor of three X or more, uh, drive down their costs. And they're using the Amazon Opus search service. And really what we're trying to do at AWS is give our customers the most comprehensive set of services for the end-to-end journey around, uh, data from ingestion to analytics and machine learning. And we will want to provide a comprehensive set of capabilities for ingestion, cataloging analytics, and then machine learning. And all of these are things that our partners and the startups that are run on us have available to them to build on as they build and deliver value for their customers. >>And, you know, the way we think about this is we want customers to be able to modernize what they're doing and their infrastructure. And we provide services for that. It's about unifying data, wherever it lives, connecting it. So the customers can build a complete picture of their customers and business. And then it's about innovation and really using machine learning to bring all of this unified data, to bear on driving new innovation and new opportunities for customers. And what we're trying to do AWS is really provide a scalable and secure cloud platform that customers and partners can build on a unifying is about connecting data. And it's also about providing well-governed access to data. So one of the big trends that we see is customers looking for the ability to make self-service data available to that customer there and use. And the key to that is good foundational governance. >>Once you can define good access controls, you then are more comfortable setting data free. And, um, uh, the other part of it is, uh, data lakes play a huge role because you need to be able to think about structured and unstructured data. In fact, about 80% of the data being generated today, uh, is unstructured. And you want to be able to connect data that's in data lakes with data that's in purpose-built data stores, whether that's databases on AWS databases, outside SAS products, uh, as well as things like data warehouses and machine learning systems, but really connecting data as key. Uh, and then, uh, innovation, uh, how can we bring to bear? And we imagine all processes with new technologies like AI and machine learning, and AI is also key to unlocking a lot of the value that's in unstructured data. If you can figure out what's in an imagine the sentiment of audio and do that in real-time that lets you then personalize and dynamically tailor experiences, all of which are super important to getting an edge, um, in, uh, in the modern marketplace. And so at AWS, we, when we think about connecting the dots across sources of data, allowing customers to use data, lakes, databases, analytics, and machine learning, we want to provide a common catalog and governance and then use these to help drive new experiences for customers and their apps and their devices. And then this, you know, in an ideal world, we'll create a closed loop. So you create a new experience. You observe our customers interact with it, that generates more data, which is a data source that feeds into the system. >>And, uh, you know, on AWS, uh, thinking about a modern data strategy, uh, really at the core is a data lakes built on us three. And I'll talk more about that in a second. Then you've got services like Athena included, lake formation for managing that data, cataloging it and querying it in place. And then you have the ability to use the right tool for the right job. And so we're big believers in purpose-built services for data because that's where you can avoid compromising on performance functionality or scale. Uh, and then as I mentioned, unification and inter interconnecting, all of that data. So if you need to move data between these systems, uh, there's well-trodden pathways that allow you to do that, and then features built into services that enable that. >>And, um, you know, some of the core ideas that guide the work that we do, um, scalable data lakes at key, um, and you know, this is really about providing arbitrarily scalable high throughput systems. It's about open format data for future-proofing. Uh, then we talk about purpose-built systems at the best possible functionality, performance, and cost. Uh, and then from a serverless perspective, this has been another big trend for us. We announced a bunch of serverless services and reinvented the goal here is to really take away the need to manage infrastructure from customers. They can really focus about driving differentiated business value, integrated governance, and then machine learning pervasively, um, not just as an end product for data scientists, but also machine learning built into data, warehouses, visualization and a database. >>And so it's scalable data lakes. Uh, data three is really the foundation for this. One of our, um, original services that AWS really the backbone of so much of what we do, uh, really unmatched your ability, availability, and scale, a huge portfolio of analytics services, uh, both that we offer, but also that our partners and customers offer and really arbitrary skin. We've got individual customers and estimator in the expert range, many in the hundreds of petabytes. And that's just growing. You know, as I mentioned, we see roughly a 10 X increase in data volume every five years. So that's a exponential increase in data volumes, Uh, from a purpose-built perspective, it's the right tool for the right job, the red shift and data warehousing Athena for querying all your data. Uh, EMR is our managed sparking to do, uh, open search for log analytics and search, and then Kinesis and Amex care for CAFCA and streaming. And that's been another big trend is, uh, real time. Data has been exploding and customers wanting to make sense of that data in real time, uh, is another big deal. >>Uh, some examples of how we're able to achieve differentiated performance and purpose-built systems. So with Redshift, um, using managed storage and it's led us and since types, uh, the three X better price performance, and what's out there available to all our customers and partners in EMR, uh, with things like spark, we're able to deliver two X performance of open source with a hundred percent compatibility, uh, almost three X and Presto, uh, with on two, which is our, um, uh, new Silicon chips on AWS, better price performance, about 10 to 12% better price performance, and 20% lower costs. And then, uh, all compatible source. So drop your jobs, then have them run faster and cheaper. And that translates to customer benefits for better margins for partners, uh, from a serverless perspective, this is about simplifying operations, reducing total cost of ownership and freeing customers from the need to think about capacity management. If we invent, we, uh, announced serverless redshifts EMR, uh, serverless, uh, Kinesis and Kafka, um, and these are all game changes for customers in terms of freeing our customers and partners from having to think about infrastructure and allowing them to focus on data. >>And, um, you know, when it comes to several assumptions in analytics, we've really got a very full and complete set. So, uh, whether that's around data warehousing, big data processing streaming, or cataloging or governance or visualization, we want all of our customers to have an option to run something struggles as well as if they have specialized needs, uh, uh, instances are available as well. And so, uh, really providing a comprehensive deployment model, uh, based on the customer's use cases, uh, from a governance perspective, uh, you know, like information is about easy build and management of data lakes. Uh, and this is what enables data sharing and self service. And, um, you know, with you get very granular access controls. So rule level security, uh, simple data sharing, and you can tag data. So you can tag a group of analysts in the year when you can say those only have access to the new data that's been tagged with the new tags, and it allows you to very, scaleably provide different secure views onto the same data without having to make multiple copies, another big win for customers and partners, uh, support transactions on data lakes. >>So updates and deletes. And time-travel, uh, you know, John talked about data as code and with time travel, you can look at, um, querying on different versions of data. So that's, uh, a big enabler for those types of strategies. And with blue, you're able to connect data in multiple places. So, uh, whether that's accessing data on premises in other SAS providers or, uh, clouds, uh, as well as data that's on AWS and all of this is, uh, serverless and interconnected. And, um, and really it's about plugging all of your data into the AWS ecosystem and into our partner ecosystem. So this API is all available for integration as well, but then from an AML perspective, what we're really trying to do is bring machine learning closer to data. And so with our databases and warehouses and lakes and BI tools, um, you know, we've infused machine learning throughout our, by, um, the state of the art machine running that we offer through SageMaker. >>And so you've got a ML in Aurora and Neptune for broths. Uh, you can train machine learning models from SQL, directly from Redshift and a female. You can use free inference, and then QuickSight has built in forecasting built in natural language, querying all powered by machine learning, same with anomaly detection. And here are the ideas, you know, how can we up our systems get smarter at the surface, the right insights for our customers so that they don't have to always rely on smart people asking the right questions, um, and you know, uh, really it's about bringing data back together and making it available for innovation. And, uh, thank you very much. I appreciate your attention. >>Okay. Well done reinventing the business with AWS analytics rural. That was great. Thanks for walking through that. That was awesome. I have to ask you some questions on the end-to-end view of the data. That seems to be a theme serverless, uh, in there, uh, Mel integration. Um, but then you also mentioned picking the right tool for the job. So then you've got like all these things moving on, simplify it for me right now. So from a business standpoint, how do they modernize? What's the steps that the clients are taking with analytics, what's the best practice? How do they, what's the what's the high order bit here? >>Uh, so the basic hierarchy is, you know, historically legacy systems are rigid and inflexible, and they weren't really designed for the scale of modern data or the variety of it. And so what customers are finding is they're moving to the cloud. They're moving from legacy systems with punitive licensing into more flexible, more systems. And that allows them to really think about building a decoupled, scalable future proof architecture. And so you've got the ability to combine data lakes and databases and data warehouses and connect them using common KPIs and common data protection. And that sets you up to deal with arbitrary scale and arbitrary types. And it allows you to evolve as the future changes since it makes it easy to add in a new type of engine, as we invent a better one a few years from now. Uh, and then, uh, once you've kind of got your data in a cloud and interconnected in this way, you can now build complete pictures of what's going on. You can understand all your touch points with customers. You can understand your complete supply chain, and once you can build that complete picture of your business, you can start to use analytics and machine learning to find new opportunities. So, uh, think about modernizing, moving to the cloud, setting up for the future, connecting data end to end, and then figuring out how to use that to your advantage. >>I know as you mentioned, modern data strategy gives you the best of both worlds. And you've mentioned, um, briefly, I want to get a little bit more, uh, insight from you on this. You mentioned open, open formats. One of the themes that's come out of some of the interviews, these companies we're going to be hearing from today is open source. The role opens playing. Um, how do you see that integrating in? Because again, this is just like software, right? Open, uh, open source software, open source data. It seems to be a trend. What does open look like to you? How do you see that progressing? >>Uh, it's a great question. Uh, open operates on multiple dimensions, John, as you point out, there's open data formats. These are things like JSI and our care for analytics. This allows multiple engines tend to operate on data and it'll, it, it creates option value for customers. If you're going to data in an open format, you can use it with multiple technologies and that'll be future-proofed. You don't have to migrate your data. Now, if you're thinking about using a different technology. So that's one piece now that sort of software, um, also, um, really a big enabler for innovation and for customers. And you've got things like squat arc and Presto, which are popular. And I know some of the startups, um, you know, that we're talking about as part of the showcase and use these technologies, and this allows for really the world to contribute, to innovating and these engines and moving them forward together. And we're big believers in that we've got open source services. We contribute to open-source, we support open source projects, and that's another big part of what we do. And then there's open API is things like SQL or Python. Uh, again, uh, common ways of interacting with data that are broadly adopted. And this one, again, create standardization. It makes it easier for customers to inter-operate and be flexible. And so open is really present all the way through. And it's a big part, I think, of, uh, the present and the future. >>Yeah. It's going to be fun to watch and see how that grows. It seems to be a lot of traction there. I want to ask you about, um, the other comment I thought was cool. You had the architectural slides out there. One was data lakes built on S3, and you had a theme, the glue in lake formation kind of around S3. And then you had the constellation of, you know, Kinesis SageMaker and other things around it. And you said, you know, pick the tool for the right job. And then you had the other slide on the analytics at the center and you had Redshift and all the other, other, other services around it around serverless. So one was more about the data lake with Athena glue and lake formation. The other one's about serverless. Explain that a little bit more for me, because I'm trying to understand where that fits. I get the data lake piece. Okay. Athena glue and lake formation enables it, and then you can pick and choose what you need on the serverless side. What does analytics in the center mean? >>So the idea there is that really, we wanted to talk about the fact that if you zoom into the analytics use case within analytics, everything that we offer, uh, has a serverless option for our customers. So, um, you could look at the bucket of analytics across things like Redshift or EMR or Athena, or, um, glue and league permission. You have the option to use instances or containers, but also to just not worry about infrastructure and just think declaratively about the data that you want to. >>Oh, so basically you're saying the analytics is going serverless everywhere. Talking about volumes, you mentioned 10 X volumes. Um, what are other stats? Can you share in terms of volumes? What are people seeing velocity I've seen data warehouses can't move as fast as what we're seeing in the cloud with some of your customers and how they're using data. How does the volume and velocity community have any kind of other kind of insights into those numbers? >>Yeah, I mean, I think from a stats perspective, um, you know, take Redshift, for example, customers are processing. So reading and writing, um, multiple exabytes of data there across from each shift. And, uh, you know, one of the things that we've seen in, uh, as time has progressed as, as data volumes have gone up and did a tapes have exploded, uh, you've seen data warehouses get more flexible. So we've added things like the ability to put semi-structured data and arbitrary, nested data into Redshift. Uh, we've also seen the seamless integration of data warehouses and data lakes. So, um, actually Redshift was one of the first to enable a straightforward acquiring of data. That's sitting in locally and drives as well as feed and that's managed on a stream and, uh, you know, those trends will continue. I think you'll kind of continue to see this, um, need to query data wherever it lives and, um, and, uh, allow, uh, leaks and warehouses and purpose-built stores to interconnect. >>You know, one of the things I liked about your presentation was, you know, kind of had the theme of, you know, modernize, unify, innovate, um, and we've been covering a lot of companies that have been, I won't say stumbling, but like getting to the future, some go faster than others, but they all kind of get stuck in an area that seems to be the same spot. It's the silos, breaking down the silos and get in the data lakes and kind of blending that purpose built data store. And they get stuck there because they're so used to silos and their teams, and that's kind of holding back the machine learning side of it because the machine learning can't do its job if they don't have access to all the data. And that's where we're seeing machine learning kind of being this new iterative model where the models are coming in faster. And so the silo brake busting is an issue. So what's your take on this part of the equation? >>Uh, so there's a few things I plan it. So you're absolutely right. I think that transition from some old data to interconnected data is always straightforward and it operates on a number of levels. You want to have the right technology. So, um, you know, we enable things like queries that can span multiple stores. You want to have good governance, you can connect across multiple ones. Uh, then you need to be able to get data in and out of these things and blue plays that role. So there's that interconnection on the technical side, but the other piece is also, um, you know, you want to think through, um, organizationally, how do you organize, how do you define it once data when they share it? And one of the asylees for enabling that sharing and, um, think about, um, some of the processes that need to get put in place and create the right incentives in your company to enable that data sharing. And then the foundational piece is good guardrails. You know, it's, uh, it can be scary to open data up. And, uh, the key to that is to put good governance in place where you can ensure that data can be shared and distributed while remaining protected and adhering to the privacy and compliance and security regulations that you have for that. And once you can assert that level of protection, then you can set that data free. And that's when, uh, customers really start to see the benefits of connecting all of it together, >>Right? And then we have a batch of startups here on this episode that are doing a lot of different things. Uh, some have, you know, new lake new lakes are forming observability lakes. You have CQL innovation on the front end data, tiering innovation at the data tier side, just a ton of innovation around this new data as code. How do you see as executive at AWS? You're enabling all this, um, where's the action going? Where are the white spaces? Where are the opportunities as this architecture continues to grow, um, and get traction because of the relevance of machine learning and AI and the apps are embedding data in there now as code where's the opportunities for these startups and how can they continue to grow? >>Yeah, the, I mean, the opportunity is it's amazing, John, you know, we talked a little bit about this at the beginning, but the, there is no slow down insight for the volume of data that we're generating pretty much everything that we have, whether it's a watch or a phone or the systems that we interact with are generating data and, uh, you know, customers, uh, you know, we talk a lot about the things that'll stay the same over time. And so, you know, the data volumes will continue to go up. Customers are gonna want to keep analyzing that data to make sense of it. They're going to want to be able to do it faster and more cheaply than they were yesterday. And then we're going to want to be able to make decisions and innovate, uh, in a shorter cycle and run more experiments than they were able to do. >>And so I think as long as, and they're always going to want this data to be secure and well-protected, and so I think as long as we, and the startups that we work with can continue to push on making these things better. Can I deal with more data? Can I deal with it more cheaply? Can I make it easier to get insight? And can I maintain a super high bar in security investments in these areas will just be off. Um, because, uh, the demand side of this equation is just in a great place, given what we're seeing in terms of theater and the architect for forum. >>I also love your comment about, uh, ML integration being the last leg of the equation here or less likely the journey, but you've got that enablement of the AIP solves a lot of problems. People can see benefits from good machine learning and AI is creating opportunities. Um, and also you also have mentioned the end to end with security piece. So data and security are kind of going hand in hand these days, not just the governments and the compliance stuff we're talking about security. So machine learning integration kind of connects all of this. Um, what's it all mean for the customers, >>For customers. That means that with machine learning and really enabling themselves to use machine learning, to make sense of data, they're able to find patterns that can represent new opportunities, um, quicker than ever before. And they're able to do it, uh, dynamically. So, you know, in a prior version of the world, we'd have little bit of systems and they would be relatively rigid and then we'd have to improve them. Um, with machine learning, this can be dynamic and near real time and you can customize them. So, uh, that just represents an opportunity to deepen relationships with customers and create more value and to find more efficiency in how businesses are run. So that piece is there. Um, and you know, your ideas around, uh, data's code really come into play because machine learning needs to be repeatable and explainable. And that means versioning, uh, keeping track of everything that you've done from a code and data and learning and training perspective >>And data sets are updating the machine learning. You got data sets growing, they become code modules that can be reused and, uh, interrogated, um, security okay. Is a big as a big theme data, really important security is seen as one of our top use cases. Certainly now in this day and age, we're getting a lot of, a lot of breaches and hacks coming in, being defended. It brings up the open, brings up the data as code security is a good proxy for kind of where this is going. What's your what's take on that and your reaction to that. >>So I'm, I'm security. You can, we can never invest enough. And I think one of the things that we, um, you know, guide us in AWS is security, availability, durability sort of jobs, you know, 1, 2, 3, and, um, and it operates at multiple levels. You need to protect data and rest with encryption, good key management and good practices though. You need to protect data on the wire. You need to have a good sense of what data is allowed to be seen by whom. And then you need to keep track of who did what and be able to verify and come back and prove that, uh, you know, uh, only the things that were allowed to happen actually happened. And you can actually then use machine learning on top of all of this apparatus to say, uh, you know, can I detect things that are happening that shouldn't be happening in near real time so they could put a stop to them. So I don't think any of us can ever invest enough in securing and protecting my data and our systems, and it is really fundamental or adding customer trust and it's just good business. So I think it is absolutely crucial. And we think about it all the time and are always looking for ways to raise >>Well, I really appreciate you taking the time to give the keynote final word here for the folks watching a lot of these startups that are presenting, they're doing well. Business wise, they're being used by large enterprises and people buying their products and using their services for customers are implementing more and more of the hot startups products they're relevant. What's your advice to the customer out there as they go on this journey, this new data as code this new future of analytics, what's your recommendation. >>So for customers who are out there, uh, recommend you take a look at, um, what, uh, the startups on AWS are building. I think there's tremendous innovation and energy, uh, and, um, there's really great technology being built on top of a rock solid platform. And so I encourage customers thinking about it to lean forward, to think about new technology and to embrace, uh, move to the cloud suite, modernized, you know, build a single picture of our data and, and figure out how to innovate and when >>Well, thanks for coming on. Appreciate your keynote. Thanks for the insight. And thanks for the conversation. Let's hand it off to the show. Let the show begin. >>Thank you, John pleasure, as always.