(upbeat music) >> Welcome back to The Cubes coverage of WIDS 2023 the eighth Annual Women in Data Science Conference which is held at Stanford University. I'm your host, Lisa Martin. I'm really excited to be having some great co-hosts today. I've got Hannah Freytag with me, who is a data journalism master student at Stanford. We have yet another inspiring woman in technology to bring to you today. Kelly Hoang joins us, data scientist at Gilead. It's so great to have you, Kelly. >> Hi, thank you for having me today. I'm super excited to be here and share my journey with you guys. >> Let's talk about that journey. You recently got your PhD in information sciences, congratulations. >> Thank you. Yes, I just graduated, I completed my PhD in information sciences from University of Illinois Urbana-Champaign. And right now I moved to Bay Area and started my career as a data scientist at Gilead. >> And you're in better climate. Well, we do get snow here. >> Kelly: That's true. >> We proved that the last... And data science can show us all the climate change that's going on here. >> That's true. That's the topic of the data fund this year, right? To understand the changes in the climate. >> Yeah. Talk a little bit about your background. You were mentioning before we went live that you come from a whole family of STEM students. So you had that kind of in your DNA. >> Well, I consider myself maybe I was a lucky case. I did grew up in a family in the STEM environment. My dad actually was a professor in computer science. So I remember when I was at a very young age, I already see like datas, all of these computer science concepts. So grew up to be a data scientist is always something like in my mind. >> You aspired to be. >> Yes. >> I love that. >> So I consider myself in a lucky place in that way. But also, like during this journey to become a data scientist you need to navigate yourself too, right? Like you have this roots, like this foundation but then you still need to kind of like figure out yourself what is it? Is it really the career that you want to pursue? But I'm happy that I'm end up here today and where I am right now. >> Oh, we're happy to have you. >> Yeah. So you' re with Gilead now after you're completing your PhD. And were you always interested in the intersection of data science and health, or is that something you explored throughout your studies? >> Oh, that's an excellent question. So I did have background in computer science but I only really get into biomedical domain when I did my PhD at school. So my research during my PhD was natural language processing, NLP and machine learning and their applications in biomedical domains. And then when I graduated, I got my first job in Gilead Science. Is super, super close and super relevant to what my research at school. And at Gilead, I am working in the advanced analytics department, and our focus is to bring artificial intelligence and machine learning into supporting clinical decision making. And really the ultimate goal is how to use AI to accelerate the precision medicine. So yes, it's something very like... I'm very lucky to get the first job that which is very close to my research at school. >> That's outstanding. You know, when we talk about AI, we can't not talk about ethics, bias. >> Kelly: Right. >> We know there's (crosstalk) Yes. >> Kelly: In healthcare. >> Exactly. Exactly. Equities in healthcare, equities in so many things. Talk a little bit about what excites you about AI, what you're doing at Gilead to really influence... I mean this, we're talking about something that's influencing life and death situations. >> Kelly: Right. >> How are you using AI in a way that is really maximizing the opportunities that AI can bring and maximizing the value in the data, but helping to dial down some of the challenges that come with AI? >> Yep. So as you may know already with the digitalization of medical records, this is nowaday, we have a tremendous opportunities to fulfill the dream of precision medicine. And what I mean by precision medicines, means now the treatments for people can be really tailored to individual patients depending on their own like characteristic or demographic or whatever. And nature language processing and machine learning, and AI in general really play a key role in that innovation, right? Because like there's a vast amount of information of patients and patient journeys or patient treatment is conducted and recorded in text. So that's why our group was established. Actually our department, advanced analytic department in Gilead is pretty new. We established our department last year. >> Oh wow. >> But really our mission is to bring AI into this field because we see the opportunity now. We have a vast amount of data about patient about their treatments, how we can mine these data how we can understand and tailor the treatment to individuals. And give everyone better care. >> I love that you brought up precision medicine. You know, I always think, if I kind of abstract everything, technology, data, connectivity, we have this expectation in our consumer lives. We can get anything we want. Not only can we get anything we want but we expect whoever we're engaging with, whether it's Amazon or Uber or Netflix to know enough about me to get me that precise next step. I don't think about precision medicine but you bring up such a great point. We expect these tailored experiences in our personal lives. Why not expect that in medicine as well? And have a tailored treatment plan based on whatever you have, based on data, your genetics, and being able to use NLP, machine learning and AI to drive that is really exciting. >> Yeah. You recap it very well, but then you also bring up a good point about the challenges to bring AI into this field right? Definitely this is an emerging field, but also very challenging because we talk about human health. We are doing the work that have direct impact to human health. So everything need to be... Whatever model, machine learning model that you are building, developing you need to be precise. It need to be evaluated properly before like using as a product, apply into the real practice. So it's not like recommendation systems for shopping or anything like that. We're talking about our actual health. So yes, it's challenging that way. >> Yeah. With that, you already answered one of the next questions I had because like medical data and health data is very sensitive. And how you at Gilead, you know, try to protect this data to protect like the human beings, you know, who are the data in the end. >> The security aspect is critical. You bring up a great point about sensitive data. We think of healthcare as sensitive data. Or PII if you're doing a bank transaction. We have to be so careful with that. Where is security, data security, in your everyday work practices within data science? Is it... I imagine it's a fundamental piece. >> Yes, for sure. We at Gilead, for sure, in data science organization we have like intensive trainings for employees about data privacy and security, how you use the data. But then also at the same time, when we work directly with dataset, it's not that we have like direct information about patient at like very granular level. Everything is need to be kind of like anonymized at some points to protect patient privacy. So we do have rules, policies to follow to put that in place in our organization. >> Very much needed. So some of the conversations we heard, were you able to hear the keynote this morning? >> Yes. I did. I attended. Like I listened to all of them. >> Isn't it fantastic? >> Yes, yes. Especially hearing these women from different backgrounds, at different level of their professional life, sharing their journeys. It's really inspiring. >> And Hannah, and I've been talking about, a lot of those journeys look like this. >> I know >> You just kind of go... It's very... Yours is linear, but you're kind of the exception. >> Yeah, this is why I consider my case as I was lucky to grow up in STEM environment. But then again, back to my point at the beginning, sometimes you need to navigate yourself too. Like I did mention about, I did my pa... Sorry, my bachelor degree in Vietnam, in STEM and in computer science. And that time, there's only five girls in a class of 100 students. So I was not the smartest person in the room. And I kept my minority in that areas, right? So at some point I asked myself like, "Huh, I don't know. Is this really my careers." It seems that others, like male people or students, they did better than me. But then you kind of like, I always have this passion of datas. So you just like navigate yourself, keep pushing yourself over those journey. And like being where I am right now. >> And look what you've accomplished. >> Thank you. >> Yeah. That's very inspiring. And yeah, you mentioned how you were in the classroom and you were only one of the few women in the room. And what inspired or motivated you to keep going, even though sometimes you were at these points where you're like, "Okay, is this the right thing?" "Is this the right thing for me?" What motivated you to keep going? >> Well, I think personally for me, as a data scientist or for woman working in data science in general, I always try to find a good story from data. Like it's not, when you have a data set, well it's important for you to come up with methodologies, what are you going to do with the dataset? But I think it's even more important to kind of like getting the context of the dataset. Like think about it like what is the story behind this dataset? What is the thing that you can get out of it and what is the meaning behind? How can we use it to help use it in a useful way. To have in some certain use case. So I always have that like curiosity and encouragement in myself. Like every time someone handed me a data set, I always think about that. So it's helped me to like build up this kind of like passion for me. And then yeah. And then become a data scientist. >> So you had that internal drive. I think it's in your DNA as well. When you were one of five. You were 5% women in your computer science undergrad in Vietnam. Yet as Hannah was asking you, you found a lot of motivation from within. You embrace that, which is so key. When we look at some of the statistics, speaking of data, of women in technical roles. We've seen it hover around 25% the last few years, probably five to 10. I was reading some data from anitab.org over the weekend, and it shows that it's now, in 2022, the number of women in technical roles rose slightly, but it rose, 27.6%. So we're seeing the needle move slowly. But one of the challenges that still remains is attrition. Women who are leaving the role. You've got your PhD. You have a 10 month old, you've got more than one child. What would you advise to women who might be at that crossroads of not knowing should I continue my career in climbing the ladder, or do I just go be with my family or do something else? What's your advice to them in terms of staying the path? >> I think it's really down to that you need to follow your passion. Like in any kind of job, not only like in data science right? If you want to be a baker, or you want to be a chef, or you want to be a software engineer. It's really like you need to ask yourself is it something that you're really passionate about? Because if you really passionate about something, regardless how difficult it is, like regardless like you have so many kids to take care of, you have the whole family to take care of. You have this and that. You still can find your time to spend on it. So it's really like let yourself drive your own passion. Drive the way where you leading to. I guess that's my advice. >> Kind of like following your own North Star, right? Is what you're suggesting. >> Yeah. >> What role have mentors played in your career path, to where you are now? Have you had mentors on the way or people who inspired you? >> Well, I did. I certainly met quite a lot of women who inspired me during my journey. But right now, at this moment, one person, particular person that I just popped into my mind is my current manager. She's also data scientist. She's originally from Caribbean and then came to the US, did her PhDs too, and now led a group, all women. So believe it or not, I am in a group of all women working in data science. So she's really like someone inspire me a lot, like someone I look up to in this career. >> I love that. You went from being one of five females in a class of 100, to now having a PhD in information sciences, and being on an all female data science team. That's pretty cool. >> It's great. Yeah, it's great. And then you see how fascinating that, how things shift right? And now today we are here in a conference that all are women in data science. >> Yeah. >> It's extraordinary. >> So this year we're fortunate to have WIDS coincide this year with the actual International Women's Day, March 8th which is so exciting. Which is always around this time of year, but it's great to have it on the day. The theme of this International Women's Day this year is embrace equity. When you think of that theme, and your career path, and what you're doing now, and who inspires you, how can companies like Gilead benefit from embracing equity? What are your thoughts on that as a theme? >> So I feel like I'm very lucky to get my first job at Gilead. Not only because the work that we are doing here very close to my research at school, but also because of the working environment at Gilead. Inclusion actually is one of the five core values of Gilead. >> Nice. >> So by that, we means we try to create and creating a working environment that all of the differences are valued. Like regardless your background, your gender. So at Gilead, we have women at Gilead which is a global network of female employees, that help us to strengthen our inclusion culture, and also to influence our voices into the company cultural company policy and practice. So yeah, I'm very lucky to work in the environment nowadays. >> It's impressive to not only hear that you're on an all female data science team, but what Gilead is doing and the actions they're taking. It's one thing, we've talked about this Hannah, for companies, and regardless of industry, to say we're going to have 50% women in our workforce by 2030, 2035, 2040. It's a whole other ballgame for companies like Gilead to actually be putting pen to paper. To actually be creating a strategy that they're executing on. That's awesome. And it must feel good to be a part of a company who's really adapting its culture to be more inclusive, because there's so much value that comes from inclusivity, thought diversity, that ultimately will help Gilead produce better products and services. >> Yeah. Yes. Yeah. Actually this here is the first year Gilead is a sponsor of the WIDS Conference. And we are so excited to establish this relationship, and looking forward to like having more collaboration with WIDS in the future. >> Excellent. Kelly we've had such a pleasure having you on the program. Thank you for sharing your linear path. You are definitely a unicorn. We appreciate your insights and your advice to those who might be navigating similar situations. Thank you for being on theCUBE today. >> Thank you so much for having me. >> Oh, it was our pleasure. For our guests, and Hannah Freytag this is Lisa Martin from theCUBE. Coming to you from WIDS 2023, the eighth annual conference. Stick around. Our final guest joins us in just a minute.

>>Hey everyone, welcome to the Cube's coverage of AWS Reinvent 2022. Lisa Martin here with you with Subaru ier, one of our alumni who's now the CEO of Aerospike. Sabu. Great to have you on the program. Thank you for joining us. >>Great as always, to be on the cube. Luisa, good to meet you. >>So, you know, every company these days has got to be a data company, whether it's a retailer, a manufacturer, a grocer, a automotive company. But for a lot of companies, data is underutilized, yet a huge asset that is value added. Why do you think companies are struggling so much to make data a value added asset? >>Well, you know, we, we see this across the board when I talk to customers and prospects. There's a desire from the business and from it actually to leverage data to really fuel newer applications, newer services, newer business lines, if you will, for companies. I think the struggle is one, I think one the, you know, the plethora of data that is created, you know, surveys say that over the next three years data is gonna be, you know, by 2025, around 175 zetabytes, right? A hundred and zetabytes of data is gonna be created. And that's really a, a, a growth of north of 30% year over year. But the more important, and the interesting thing is the real time component of that data is actually growing at, you know, 35% cagr. And what enterprises desire is decisions that are made in real time or near real time. >>And a lot of the challenges that do exist today is that either the infrastructure that enterprises have in place was never built to actually manipulate data in real time. The second is really the ability to actually put something in place which can handle spikes yet be cost efficient if you'll, so you can build for really peak loads, but then it's very expensive to operate that particular service at normal loads. So how do you build something which actually works for you, for both you, both users, so to speak? And the last point that we see out there is even if you're able to, you know, bring all that data, you don't have the processing capability to run through that data. So as a result, most enterprises struggle with one, capturing the data, you know, making decisions from it in real time and really operating it at the cost point that they need to operate it at. >>You know, you bring up a great point with respect to real time data access. And I think one of the things that we've learned the last couple of years is that access to real time data, it's not a nice to have anymore. It's business critical for organizations in any industry. Talk about that as one of the challenges that organizations are facing. >>Yeah. When, when, when we started Aerospike, right when the company started, it started with the premise that data is gonna grow, number one, exponentially. Two, when applications open up to the internet, there's gonna be a flood of users and demands on those applications. And that was true primarily when we started the company in the ad tech vertical. So ad tech was the first vertical where there was a lot of data both on the supply side and the demand side from an inventory of ads that were available. And on the other hand, they had like microseconds or milliseconds in which they could make a decision on which ad to put in front of you and I so that we would click or engage with that particular ad. But over the last three to five years, what we've seen is as digitization has actually permeated every industry out there, the need to harness data in real time is pretty much present in every industry. >>Whether that's retail, whether that's financial services, telecommunications, e-commerce, gaming and entertainment. Every industry has a desire. One, the innovative companies, the small companies rather, are innovating at a pace and standing up new businesses to compete with the larger companies in each of these verticals. And the larger companies don't wanna be left behind. So they're standing up their own competing services or getting into new lines of business that really harness and are driven by real time data. So this compelling pressures, one, the customer exp you know, customer experience is paramount and we as customers expect answers in, you know, an instant in real time. And on the other hand, the way they make decisions is based on a large data set because you know, larger data sets actually propel better decisions. So there's competing pressures here, which essentially drive the need. One from a business perspective, two from a customer perspective to harness all of this data in real time. So that's what's driving an inces need to actually make decisions in real or near real time. >>You know, I think one of the things that's been in short supply over the last couple of years is patients we do expect as consumers, whether we're in our business lives, our personal lives that we're going to be getting, be given information and data that's relevant, it's personal to help us make those real time decisions. So having access to real time data is really business critical for organizations across any industries. Talk about some of the main capabilities that modern data applications and data platforms need to have. What are some of the key capabilities of a modern data platform that need to be delivered to meet demanding customer expectations? >>So, you know, going back to your initial question Lisa, around why is data really a high value but underutilized or underleveraged asset? One of the reasons we see is a lot of the data platforms that, you know, some of these applications were built on have been then around for a decade plus and they were never built for the needs of today, which is really driving a lot of data and driving insight in real time from a lot of data. So there are four major capabilities that we see that are essential ingredients of any modern data platform. One is really the ability to, you know, operate at unlimited scale. So what we mean by that is really the ability to scale from gigabytes to even petabytes without any degradation in performance or latency or throughput. The second is really, you know, predictable performance. So can you actually deliver predictable performance as your data size grows or your throughput grows or your concurrent user on that application of service grows? >>It's really easy to build an application that operates at low scale or low throughput or low concurrency, but performance usually starts degrading as you start scaling one of these attributes. The third thing is the ability to operate and always on globally resilient application. And that requires a, a really robust data platform that can be up on a five, nine basis globally, can support global distribution because a lot of these applications have global users. And the last point is, goes back to my first answer, which is, can you operate all of this at a cost point? Which is not prohibitive, but it makes sense from a TCO perspective. Cuz a lot of times what we see is people make choices of data platforms and as ironically their service or applications become more successful and more users join their journey, the revenue starts going up, the user base starts going up, but the cost basis starts crossing over the revenue and they're losing money on the service, ironically, as the service becomes more popular. So really unlimited scale, predictable performance always on, on a globally resilient basis and low tco. These are the four essential capabilities of any modern data platform. >>So then talk to me with those as the four main core functionalities of a modern data platform. How does aerospace deliver that? >>So we were built, as I said, from the from day one to operate at unlimited scale and deliver predictable performance. And then over the years as we work with customers, we build this incredible high availability capability which helps us deliver the always on, you know, operations. So we have customers who are, who have been on the platform 10 years with no downtime for example, right? So we are talking about an amazing continuum of high availability that we provide for customers who operate these, you know, globally resilient services. The key to our innovation here is what we call the hybrid memory architecture. So, you know, going a little bit technically deep here, essentially what we built out in our architecture is the ability on each node or each server to treat a bank of SSDs or solid state devices as essentially extended memory. So you're getting memory performance, but you're accessing these SSDs, you're not paying memory prices, but you're getting memory performance as a result of that. >>You can attach a lot more data to each node or each server in your distributed cluster. And when you kind of scale that across basically a distributed cluster you can do with aerospike, the same things at 60 to 80% lower server count and as a result 60 to 80% lower TCO compared to some of the other options that are available in the market. Then basically, as I said, that's the key kind of starting point to the innovation. We layer around capabilities like, you know, replication change, data notification, you know, synchronous and asynchronous replication. The ability to actually stretch a single cluster across multiple regions. So for example, if you're operating a global service, you can have a single aerospace cluster with one node in San Francisco, one northern New York, another one in London. And this would be basically seamlessly operating. So that, you know, this is strongly consistent. >>Very few no SQL data platforms are strongly consistent or if they are strongly consistent, they will actually suffer performance degradation. And what strongly consistent means is, you know, all your data is always available, it's guaranteed to be available, there is no data lost anytime. So in this configuration that I talked about, if the node in London goes down, your application still continues to operate, right? Your users see no kind of downtime and you know, when London comes up, it rejoins the cluster and everything is back to kind of the way it was before, you know, London left the cluster so to speak. So the op, the ability to do this globally resilient, highly available kind of model is really, really powerful. A lot of our customers actually use that kind of a scenario and we offer other deployment scenarios from a higher availability perspective. So everything starts with HMA or hybrid memory architecture and then we start building out a lot of these other capabilities around the platform. >>And then over the years, what our customers have guided us to do is as they're putting together a modern kind of data infrastructure, we don't live in a silo. So aerospace gets deployed with other technologies like streaming technologies or analytics technologies. So we built connectors into Kafka, pulsar, so that as you're ingesting data from a variety of data sources, you can ingest them at very high ingest speeds and store them persistently into Aerospike. Once the data is in Aerospike, you can actually run spark jobs across that data in a, in a multithreaded parallel fashion to get really insight from that data at really high, high throughput and high speed, >>High throughput, high speed, incredibly important, especially as today's landscape is increasingly distributed. Data centers, multiple public clouds, edge IOT devices, the workforce embracing more and more hybrid these days. How are you ex helping customers to extract more value from data while also lowering costs? Go into some customer examples cause I know you have some great ones. >>Yeah, you know, I think we have, we have built an amazing set of customers and customers actually use us for some really mission critical applications. So, you know, before I get into specific customer examples, let me talk to you about some of kind of the use cases which we see out there. We see a lot of aerospace being used in fraud detection. We see us being used in recommendations and since we use get used in customer data profiles or customer profiles, customer 360 stores, you know, multiplayer gaming and entertainment, these are kind of the repeated use case digital payments. We power most of the digital payment systems across the globe. Specific example from a, from a specific example perspective, the first one I would love to talk about is PayPal. So if you use PayPal today, then you know when you actually paying somebody your transaction is, you know, being sent through aero spike to really decide whether this is a fraudulent transaction or not. >>And when you do that, you know, you and I as a customer not gonna wait around for 10 seconds for PayPal to say yay or me, we expect, you know, the decision to be made in an instant. So we are powering that fraud detection engine at PayPal for every transaction that goes through PayPal before us, you know, PayPal was missing out on about 2% of their SLAs, which was essentially millions of dollars, which they were losing because, you know, they were letting transactions go through and taking the risk that it, it's not a fraudulent transaction with the aerospace. They can now actually get a much better sla and the data set on which they compute the fraud score has gone up by, you know, several factors. So by 30 x if you will. So not only has the data size that is powering the fraud engine actually grown up 30 x with Aerospike. Yeah. But they're actually making decisions in an instant for, you know, 99.95% of their transactions. So that's, >>And that's what we expect as consumers, right? We want to know that there's fraud detection on the swipe regardless of who we're interacting with. >>Yes. And so that's a, that's a really powerful use case and you know, it's, it's a great customer, great customer success story. The other one I would talk about is really Wayfair, right? From retail and you know, from e-commerce. So everybody knows Wayfair global leader in really, you know, online home furnishings and they use us to power their recommendations engine and you know, it's basically if you're purchasing this, people who bought this but also bought these five other things, so on and so forth, they have actually seen the card size at checkout go by up to 30% as a result of actually powering their recommendations in G by through Aerospike. And they, they were able to do this by reducing the server count by nine x. So on one ninth of the servers that were there before aerospace, they're now powering their recommendation engine and seeing card size checkout go up by 30%. Really, really powerful in terms of the business outcome and what we are able to, you know, drive at Wayfair >>Hugely powerful as a business outcome. And that's also what the consumer wants. The consumer is expecting these days to have a very personalized, relevant experience that's gonna show me if I bought this, show me something else that's related to that. We have this expectation that needs to be really fueled by technology. >>Exactly. And you know, another great example you asked about, you know, customer stories, Adobe, who doesn't know Adobe, you know, they, they're on a, they're on a mission to deliver the best customer experience that they can and they're talking about, you know, great customer 360 experience at scale and they're modernizing their entire edge compute infrastructure to support this. With Aerospike going to Aerospike, basically what they have seen is their throughput go up by 70%, their cost has been reduced by three x. So essentially doing it at one third of the cost while their annual data growth continues at, you know, about north of 30%. So not only is their data growing, they're able to actually reduce their cost to actually deliver this great customer experience by one third to one third and continue to deliver great customer 360 experience at scale. Really, really powerful example of how you deliver Customer 360 in a world which is dynamic and you know, on a dataset which is constantly growing at north, north of 30% in this case. >>Those are three great examples, PayPal, Wayfair, Adobe talking about, especially with Wayfair when you talk about increasing their cart checkout sizes, but also with Adobe increasing throughput by over 70%. I'm looking at my notes here. While data is growing at 32%, that's something that every organization has to contend with data growth is continuing to scale and scale and scale. >>Yep. I, I'll give you a fun one here. So, you know, you may not have heard about this company, it's called Dream 11 and it's a company based out of India, but it's a very, you know, it's a fun story because it's the world's largest fantasy sports platform and you know, India is a nation which is cricket crazy. So you know, when, when they have their premier league going on, you know, there's millions of users logged onto the dream alone platform building their fantasy lead teams and you know, playing on that particular platform, it has a hundred million users, a hundred million plus users on the platform, 5.5 million concurrent users and they have been growing at 30%. So they are considered a, an amazing success story in, in terms of what they have accomplished and the way they have architected their platform to operate at scale. And all of that is really powered by aerospace where think about that they are able to deliver all of this and support a hundred million users, 5.5 million concurrent users all with you know, 99 plus percent of their transactions completing in less than one millisecond. Just incredible success story. Not a brand that is you know, world renowned but at least you know from a what we see out there, it's an amazing success story of operating at scale. >>Amazing success story, huge business outcomes. Last question for you as we're almost out of time is talk a little bit about Aerospike aws, the partnership GRAVITON two better together. What are you guys doing together there? >>Great partnership. AWS has multiple layers in terms of partnerships. So you know, we engage with AWS at the executive level. They plan out, really roll out of new instances in partnership with us, making sure that, you know, those instance types work well for us. And then we just released support for Aerospike on the graviton platform and we just announced a benchmark of Aerospike running on graviton on aws. And what we see out there is with the benchmark, a 1.6 x improvement in price performance and you know, about 18% increase in throughput while maintaining a 27% reduction in cost, you know, on graviton. So this is an amazing story from a price performance perspective, performance per wat for greater energy efficiencies, which basically a lot of our customers are starting to kind of talk to us about leveraging this to further meet their sustainability target. So great story from Aero Aerospike and aws, not just from a partnership perspective on a technology and an executive level, but also in terms of what joint outcomes we are able to deliver for our customers. >>And it sounds like a great sustainability story. I wish we had more time so we would talk about this, but thank you so much for talking about the main capabilities of a modern data platform, what's needed, why, and how you guys are delivering that. We appreciate your insights and appreciate your time. >>Thank you very much. I mean, if, if folks are at reinvent next week or this week, come on and see us at our booth. We are in the data analytics pavilion. You can find us pretty easily. Would love to talk to you. >>Perfect. We'll send them there. So Ira, thank you so much for joining me on the program today. We appreciate your insights. >>Thank you Lisa. >>I'm Lisa Martin. You're watching The Cubes coverage of AWS Reinvent 2022. Thanks for watching.

>>Hello everyone. Welcome to the Cubes Live here in Dallas, Texas. I'm John Ferer, host of the Cube, Three days of wall to wall coverage. Of course, we've got the three fabulous guests here, myself, Savannah, Peterson. S look wonderful. >>Thank you. Jong on. I, I feel lucky to play the part here with my 10 gallon hat. >>Dave Nicholson, who's the analyst uncovering all the Dell Supercomputing, hpe all the technology is changing the game. Dave, you look great. Thanks for coming on. >>Thanks, John. I appreciate >>It. All right, so, so, so you look good. So we're in Dallas, Texas is a trade show conference. I don't know what you'd call this these days, but thousands of booths are here. What's the take here? Why supercomputing 22? What's the big deal? >>Well, the big deal is dramatic incremental progress in terms of supercomputing capability. So what this conference represents is the leading edge in what it can deliver to the world. We're talking about scale that is impossible to comprehend with the human brain, but you can toss out facts and figures like performance measured in ex flops, millions of CPU cores working together, thousands of kilowatts of power required to power these systems. And I think what makes this, what makes this show unique is that it's not just a bunch of vendors, but it's academia. It's PhD candidates coming and looking for companies that they might work with. So it's a very, very different vibe here. >>Savannah, we were talking last night before we were setting up our agenda for it to drill down on this week. And you know, you were, by the way, that looks great. I mean, I wish I had one. >>We'll get you one by the end of the show, >>John. Don't worry. You know, Texas is always big in Texas and that's the, the thing here, but Supercomputing seems like that had a lull for a while. Yeah, it seems like it's gonna explode and you get a chance to review the papers, take a look at it. You, you're a, I won't say closet hardware nerd, but that's your roots. >>Yeah, yeah. Very openly hardware nerd. And, and I'm excited because I, we saw a lot of hype around quantum and around AI five, 10 years ago, but we weren't seeing the application at scale and we also weren't seeing, quite frankly, the hardware wasn't ready to power these types of endeavors at scale. Whereas now, you know, we've got, we've got air cooling, we've got liquid cooling, we've got multiple GPU's. Dell was just showing me all eight of theirs that they put in their beautiful million dollar piece of equipment, which is extremely impressive for folks to run complex calculations. And, but what I'm excited about with all the, I love when we fuse business and academia together, I think that that doesn't happen very often. I've been impressed. I mean, when I walked in today, right away, I'm sure y'all can't see this at home just yet, but we'll try and give you a feel over the course of the next few days. This conference is huge. This >>Is, yeah, it is >>Way bigger than I was expecting, You know, a lot larger than where we just were in Detroit. And, and I love it because we've got the people that are literally inventing the calculations that will determine a lot of our future from sequencing our genome to powering our weather forecasting, as well as all of the companies that create the hardware and the software that's gonna actually support that. Those algorithms and >>Those, and, and the science and the engineering involved has just been going on since 1988. This conference, this trade show going on since 1988, which is, it, it passes the test of time and now the future with all the new use cases emerging from the compute and supercomputing architectures out there, it's from cradle to grave. If you're, if you're in this business, you, you're in school all the way through the industry, it doesn't seem to stop that, that university student side of it. I mean that whole student section here. So you don't see that very often in some of these tech shows, like from students to boardroom. >>Yeah. I actually brought the super computer from 1988 with me in my pocket. And I'm not sure that I'm even joking. I this may have as much processing power, certainly as much storage with one terabyte on board. I sprung for the one terabyte folks. But it is mind boggling the amount of compute power we're, we're talking about. When you dig below the surface, which we'll be doing in the coming days, you see things like leaping from P C I E, you know, gen four to gen five, and the increase that that gives us in, in terms of capabilities for plugging into the motherboard and accessing the CPU complex and on and on and on. But, but you know, something Savannah alluded to, we're talking about the leading edge of what is possible from a humanity perspective. 1%. And, and so I'd like to get into, you know, as we're we're talking to some of the experts that we'll get a chance to talk to, I'd like to get their view on what the future holds and whether we can simply grow through quantitative increases in compute power, or if the real promise is out there in the land of quantum computing, are we all sort of hanging our hats, our large 10 gallon hats? >>If that's yes. Our hats, if we're hanging our hats on that, that that's when truly we'll be able to tease insight out of chaos. I'd like to hear from some of the real experts on that subject. >>I'm glad you brought that up, cuz I'm personally pretty pumped about quantum computing, but I've seen it sit in this hype stage for quite a while and I'm ready for the application. So I'm curious to hear >>What our experts, That's an awesome, that would be, I think that would be an awesome bumper sticker. Frankly. Savannah, I'm pumped, I'm pumped about quantum computing. Who is this person? Who is this person? >>I wanna see it first. Did someone show me it? >>Yeah, yeah. 400 qubits I think was the latest IBM announcement, which, which means something. I'll pretend like I completely understand what it means. >>Tell us what that means, David. >>Well, well, so, so Savannah, let me man explain it to you. Yeah, >>Let's >>Hear it. So, so it's basically, it's, you know, in conventional computing you can either, you can either be on or off zero or one in quantum computing, you can be both, neither or all of the above. That's, that's, that's, that's the depth to which I can go. I >>Like that. That was actually a succinct, as humanly possible >>Really sounds like a Ponzi scheme to me. I, I'm not sure if I, >>Well, let's get into some of the thoughts that you guys have on some of the papers. We saw Savannah and Dave, your perspective on this whole next level kind of expansion with supercomputing and super cloud and super apps will do for this next gen. What use cases are kind of shining out of this, because, you know, it used to be you were limited by how much gear you had stacked up, how big the server could be, the supercomputer. Now you've got large scale cloud computing, you got the ability to have different subsystems like advances in networking. So you're seeing a new architectural, almost bigger. Super computing isn't just a machine, it's a collection of machines, It's a collection of Yeah. Of other stuff. What's your thoughts on these, this architecture and then the use cases that are gonna emerge that were not getable before? >>So in the past, you, you talk about, you know, 1988 and, and you know, let's say a decade ago, the race was to assemble enough compute power to be able to do things quickly enough to be practical. So we knew that if we applied software to hardware, we could get an answer to a problem because we were asking very, very specific questions. And how quickly we got the answer would determine whether it was practical to pursue it or not. So if something took a day instead of a month, okay, fantastic. But now we've reached this critical mass. You could argue when that happened, but definitely I think we're there where things like artificial intelligence and machine learning are the core of what we're doing. We're not just simply asking systems to deliver defined answers. We're asking them to learn from their experiences, starts getting a little spooky, and we're asking them to tease insights out in a way that we haven't figured out. >>So we're saying give us the insight. We're not telling the system specifically how to give us that insight. So I think that's, that's the fundamental difference that's the frontier, is, you know, you're gonna hear a lot about AI and ml and then if you retreat back a bit from Supercomputing, you're in the realm of high performance computing, which is sort of junior version of supercomputing. It's instead of the billion dollar system, it's the system that, you know, schlubs like, like, like, like Facebook or AWS might be able to afford, you know, maybe a hundred million dollars for a system casual, just, just sort of casual kind of thing next to the coffee table in the living room. But I think that's really gonna be the talk. So that's a huge tent when you talk about AI and ml. Yeah, >>I I, I totally agree. We're having some of the conversations that we've had for a long time about AI and bias. I saw a lot of the papers were looking at that. I think that's what's gonna be really interesting to me, what's most exciting about this is how are we pulling together all of this on a global scale. So I'm excited to see how supercomputing impacts climate change, our ability to monitor environmental conditions around the globe and different governments and bodies can all combine. And all of this information can be going into a central brain and learning from it and figuring out how we can make the world a better place. We're learning about the body. There's a lot of people doing molecular biology and sequencing of the genome here. We've got, there's, there's, It's just, it's very, I I don't think a lot of people realize that supercomputing pretty much touches every aspect of our >>Lives. I mean, we've had it, we've had it for a while. I think cloud computing took a lot of the attention, given that that brought in massive capabilities, a lot of agility. And I think what's interesting here at this show, if you look at, you know, what's going on from the guess, like I said, from the dorm room to the boardroom, everyone's here, but you look at what's actually going on above the hardware, CNCF is here. They have a booth, the whole cloud native software business. It's gonna be interesting to see how the software business takes advantage of totally. How these architectures, because let's face it, I've never heard a developer pointer say, I wanna run on slower hardware. So no one wants that. So now if you abstract away the hardware, as we know with, with cloud computing and DevOps cloud on premises and Edge, David, this is like, this is again, nirvana for the industry because you want, it's an exciting thing, the fastest possible compute system for the software. >>Yeah, yeah. >>I I, at the end of the day, that's what we're talking >>About. So I asked, I asked the, the gift question to my Wharton students this morning on a call, and I, you know, I asked specifically if, if I could give you something that was the result of super computing's amazing nature, what would it be? Would it be personalized therapeutics in healthcare? Would it be something related to climate? Being able to figure out exactly what we can do. There's a whole range of possibilities. And what's interesting is >>What were some of the answers? >>So, so, so a lot of the answers, a lot of the answers came down to, to two categories and it was really, it was healthcare and climate. Yeah. A lot of, a lot of understanding and of course, and of course a lot of jokes about how eventually supercomputers will determine that. The problem is people, >>It's people. Yeah, no. So I knew you were headed there, >>But >>Don't people just want custom jeans? Yeah. >>Or, well, so one of the, one of the good ones though was, >>Was also that >>While we're >>Here, a person from a company who shall not be named said, oh, advertising, it was the, it was the what if you could predict with a high degree of certainty that when you sent someone an email saying, Hey, do you wanna buy this? They would say, Well, yeah, I do. Dramatically lowering the cost of acquisition for an individual customer as an example. Those are the kinds of breakthroughs that will transform how we live. Because all of a sudden, industries are completely disrupted, disrupted, not necessarily directly related to supercomputing, but you think about automating the entire fleet of, of, of trucks in, in North America. What does that do to people who currently drive those trucks? Yeah, so there are, there are societal questions at hand that I don't necessarily know the academics are, are, are considering when they're thinking what's possible. >>Well, I think, I think the point about the ad thing brings up the whole cultural shift that's going on from the old generation of, Hey, let's use our best minds in the industry to figure out how to place an ad at the right place in the right pixel, at the right time. Versus solving real problems like climate change our, you know, culture and society and get us getting along as a country and world water sustainability fires in California. Yeah, I mean, come on. >>There's a lot. So I, I gotta say, I was curious when you were playing with your pocket computer there and talking about the terabyte that you have inside. So back in 1988 when Supercomputing started, the first show was in Orlando. It was actually the same four days that we're here right now. I was born in 1988 if we're just talking about how great 1988 is. And so I guess I, >>I was born, So were we Savannah? So were we >>The era of, I think I was in third grade at that time. >>We won't tell, we won't say what you told me earlier about 1988 for you. But that said, so 1988 was when Steve Jobs released the next computer. He was out of Apple at that time. Yeah, that's right. >>Eight >>Megabytes of Ram. >>It's called the Cube. I think >>It's respectable. That's all it was called. It was, it was, it was, it was the cube, which is pretty, pretty exciting. But when we were looking at, yeah, on the supercomputing side, your phone would've been about, is a capable, >>So where will we be in 20 years? It's amazing >>What we gonna, >>Will our holograms be here instead of us physically sitting, sitting at the table? I don't know. >>Well, it's gonna be very interesting to see how the global ecosystem evolves. It used to be very nationalistic culture with computing. I think, I think we're gonna see global, you know, flattening of culture relative to computing. I think space will be a, a massive hopeful, massive discussion. I think software and automation will be at levels we don't even see. So I think software, to me, I'm looking at, that's the enablement of this supercomputing show. In terms of the next five years, what are they gonna do to enable more faster intelligent horsepower? And, and what does that look like? Is it, it used to be simple processor, more processors, more threads, multicores, and then stuff around it. I think this is where I think it's gonna shift to more network computing, network processing, edge latency, physics is involved. I mean, every, everything you can squeeze out of the physics will be Yeah. Interesting to watch. Well, when >>We, when we, when we peel back the cover on the actual pieces of hardware that are driving this revolution, parallelizing, you know, of workloads is critical to this. It's what super computing consists of. There's no such thing as a supercomputer sitting by itself on a table. Even the million dollar system from Dell, which is crazy when you hear Dell and million dollar system. >>And it's still there too, >>Right? Just, just hanging out. Yeah. But, but it's all about the interconnect. When you want to take advantage of parallel processing, you have to have software that can leverage all of the resources and connectivity becomes increasingly important. I think that's gonna be a thread that we're gonna see throughout the next few days with the, with the, you know, the motherboards, for lack of a lack of a better term, allowing faster access to memory, faster access to cpu, gpu, dpu, networking, storage devices, plugging in those all work together. But increasingly it's that connectivity layer that's critically important. Questions of InfiniBand versus ethernet. Our DMA over converged ethernet as an example, a lot of these architectural decisions are gonna be based on power cooling, dead city. So lot of details behind the scenes to make the magic happen. I >>Think the power is gonna be, you know, thinking 20 years out, hopefully everything here is powered sustainably 20 years from now because power pull, I mean these, the more exciting things going on in your supercomputer. The power suck is massive. That when we were talking to Dell, they were saying that's one of the biggest problems, >>Concerns, that's gonna their customers and that's gonna play into sustainability. So a lot of great guests, we got folks from Dell and the industry, a lot of the manufacturers, a lot of the hardware software experts gonna come on and share what's going on. You know, we did a, we did a post why hardware matters a few months ago, Dave. Everyone's like, well it does now more than ever. So we're gonna get into it here at Supercomputing 22, where the hardware matters. Faster power, as we say for the applications. Mr. Cube, moving back with more live coverage. Stay with us back.

>>Hey everyone. Welcome to the Cube's Special Program series. Women of the Cloud Drops You by aws. I'm your host for the series, Lisa Martin. Very pleased to welcome Elle Mans to the program VP of North America Cloud platforms at Converge Technology Solutions. Rochelle, great to have you on the program. Thank you for your time today. >>Thank you, Lisa. Excited to be here. >>Tell me a little bit about you, a little bit about your role so the audience gets that understanding. >>Sure. So my role here is to help our customers migrate to public cloud or, or adopt public cloud as part as their overall digital transformation strategy. I've been in this role a little over two years supporting our, our customers and, and our organization as, as a whole. My background in technology, I've actually been a, a woman in technology since 1989. I'm one of those rare breeds that from a very, very young age, I knew I loved computers and, and always wanted something, something to do with it. The last 10 years of, of my career really has been working with clients and, and companies in the, in the industry with disruptive technologies, adopting new and and emerging technologies and, and cloud has been my focus for, for the last two years. >>But you're an og it sounds like when it comes >>To >>Tech, that's outstanding. >>It's surprises a lot of folks, >>Doesn't it? Yeah. Yes. Sometimes it surprises me as well, like how long I've been doing something, and I'm sure the same for you, but you have such wisdom and such experience that I would love to be able to share with the audience. Talk a little bit about some of your recommendations. Are they tactical, they strategic for those in the audience watching who really want to grow their careers and tech and climb that ladder? >>Yeah, I, I think, you know, our younger generations right now have, have, I think, a little bit of an easier path to, to take than, than some of us have with the amount of information that's out there, the access to, to information and the opportunity. I think one of the biggest recommendations that, that I can put out there is to always continue learning and find a mentor. Find a sponsor. You know, I, with being a female in tech, there weren't that many when I started out in the industry. And it's just, I get amazed every time I meet another, another female. And whether she's been in the industry for, you know, 20 years or two or five years, it's just exciting to see and listen to the stories of other people's paths and their journey. So mentor and, and your tribe, you definitely need your tribe. >>Absolutely. You know, something I didn't understand until a few years ago was the difference between a mentor and a sponsor. And it's so incredibly important to understand differences between the two, how they can help you lev get leverage in the career path that you're on, but, but people need to know you. You have a network, it's there. You might not think you do, but it is there. And think about those who are mentors, those that can be sponsors to help elevate you along your journey. >>Yeah, it's, it's amazing. I, I think about, I have three, three really good friends that we've grown up in the industry together, but the, sometimes even having those three really good friends, we went through many things by ourselves that we didn't have to, as you mentioned it, it, it, it took me longer than, than than I should to understand that I have someone that we can lean on sometimes just having those conversations and saying, Is this what I should do? Is this something or did did that just happen to me? You know, and having those that, that mentor and, and that partnership with someone that they may be in your organization, they may be outside of your organization, but definitely that you can have those candid conversations about what your growth or goal, what you'd like to strive for. You know, especially if it's something that may on the surface appear to be out of, out of reach. You know, if you have, have someone that is maybe not as invested in what you're trying to achieve, but can look at you and have that objective conversation, I think makes, makes all the difference and makes all the difference in the world. >>It does. And it's, it's a little bit about vulnerability, about raising your hand, saying, Hey, I'm very interested in this. I may not meet every single written criteria in the job description, but I have an interest and a passion. Can you help me navigate the, the path to, in order to get there? It's part of, it's just really raising your hand. >>It's, that's such a, such a great point, Lisa, because in some ways we can't be vulnerable because we are underrepresented as, as women in technology, but at the same time, we have to have that ability to have those same conversations that, you know, I don't know everything. Can I do this? What do I need to learn? So it, it really is finding that that balance and when you have a mentor that can help you in that area, that's the way you can show that vulnerability without, without looking like you don't have strength. >>Right. There's a balance there for sure. Speaking of that, vulnerability, diversity, we talk a lot about diversity when it comes to technology. There's a lot of strides being made. There's also some challenges, there's some gaps. What are some of the things that you see from your lens, from your seat with respect to diversity and some of the challenges that are still out there? >>Yeah, I, I look at companies like AWS with much respect on where, you know, their diversity and inclusion goals. It's not just a checkbox. You can actually see that when it is part of the culture, the room looks diverse. There are so many companies that have have the diversity and and inclusion goals, but when you go into the room or you, you're sitting in a meeting or you have a board, it is, it's, it's still, it's, it's still not seeing yourself in that, in that room. I go to a lot of conferences, attend, attend a lot of meetings, and it, and it's still surprising to see, you know, the lack of minority representation, leadership and the lack of women in, in, in leadership. So while there's been amazing strides that we've seen happen, you know, particularly, like I said, with companies like aws, we've got a long way to go. >>And I think you mentioned the difference between a mentorship and, and sponsorship. That's one thing within these organizations, particularly in leadership, there, there needs to be that sponsorship of, of the individuals in your organization that can help change what the landscape looks like at the top through your leadership. You'd be surprised how how problems are solved differently. Problems can be solved more quickly and talk about innovation when you've got more a diverse lens. There's more ways to innovate if you've got different people bringing different perspectives to the, to the conversation. So looking forward to seeing that continuing changing of, of the landscape. When I look inside the room and, and I count, >>I do the same thing and there's so much value in thought diversity for organizations and that data clearly speaks for us stuff. We, we can't have a tech conversation without talking about data, but data demonstrate that for organizations that have diversity emails, for example, in the C-suite, those organizations are more profitable. So bringing in different tracks of thought, different perspectives, the thought diversity, diversity and gender diversity and other things is so valuable. It's invaluable to organizations in every industry. >>Yeah, it's, it's invaluable. And it, and it's funny because our industry tech right now, I mean data is, you know, it's the, it's the new water, it's the, the gold mine. It's the asset. And it's, it's funny that in this area that the data is, is almost ignored. It's, it's, the data proves itself. So it doesn't have to be a checkbox for these, you know, diversity inclusion goals because the data's there to, to prove that we're all here to be profitable, follow that data. >>Exactly. And sometimes it seems so simple. Follow the data and we, we think the same recommendation holds true to, to any industry that any company and any industry that needs to be a data company to be able to deliver what the demanding consumers want, follow the data, it won't leave you astray. So I wanna get though back to talking about you and some of the impact that you've been able to have in your career. Talk a little bit about some of the specific success stories of problems that you've helped solve related to cloud computing. >>Yeah, I, this last, I'd say 16 to 18 months for us as an organization has been amazing for me as well as my team. Some of our, you know, the majority of our success, we couldn't be, I couldn't be here having this conversation without my team. And for, for us as a, as an organization where our heritage is legacy data center, and we've got customers that we've had a 10, 15, 20 year selling relationship with that now via our acquisition strategy and growth strategy, we're going to them in saying, let us help you with your cloud journey. And it's something that they haven't known our, our organization for in the past. And so when we go in there and, and meet with CIOs and CEOs and ask for them to trust us to take them on this cloud journey, and many of our clients are, are what you term greenfield, that they've got very little activity in public cloud. >>And so it's a, it's a disruption, it's an internal disruption that can be a very emotional journey that has to start with trust because you transform so much of the business. And so each and every of our wins, particularly when we have, when we have wins with brands that are recognizable, particularly when we have wins against competitors that have been in the cloud space, and that's all they do. For me, I take that as, as a personal stamp of endorsement because we've, we've shown and demonstrated to those clients that we're the right ones to, to take 'em on that journey. And we've created that, we've created that, that trust. So for me, we've had some incredible wins with our clients and those conversations can get tough sometimes we're in, we're in the middle of a migration and the operational change that'll happen. And sometimes there's tough conversations to say, you know, you think your organization is here, it's not, it's here. And we're not calling that out to say, you haven't done something, we're calling that out so that your journey ends where you'd like it to be, where we've all agreed for it to to be. And so when we, you know, have that final party or have, you know, that final sign off at the end of the project, that that's, that's a personal personal win for, for me, I, I, I enjoy solving problems and, and, and taking customers on those journeys, >>Solving problems and, and helping customers navigate the journey, whether it's the journey to cloud, the journey to digital, the journey to being more competitive than their competitors is, is just that, it's a journey. It's a multi-phased multi-step process. And to your point, underpinning that has to be trust between the organization and the people that are working to get them successfully on that journey. >>It does, and it's, it's funny, some of the, some of the conversations we're, we're starting out. Our, our approach, our team is very prescriptive and we'll get a lot of customers that just wanna go, go, go. And it's, it's, I'm, I'm road racing as, as my hobby. And so the old adage, sometimes you've gotta go slow to go fast and we, we talk to our customers and there's a lot of interviewing and they just wanna deliver. They just wanna jump in. And we're, we're like, it, it is, we know this may feel like we're going slow, but if we can really truly understand what that business outcome looks like, if we can uncover how you can leverage your investment and your, your movement to cloud, many, many customers are looking at it from a total cost of owner ownership. Can I, can I get outta the data center? >>If just that moving out of the data center, if we do those interviews with your different teams, and then we can understand an area where we can improve a customer experience, you know, make an offering that's been a, a cost center for you, a profit center for you. Those are things that we're looking for. So we really get to know our client's business. So it's not just about the technology or the destination, it's, it's what do you do when you get there? And so having those deep conversations with, with our, with our clients is, is the approach that we like to take. >>It's really about, to your point, it's about technology, but also processes and people, we can't forget the people part of this. Talk to me a little bit from the people perspective about how you see cloud evolving in the industry. Where are people involved and what are some of the things that you're excited about in terms of the evolution of your role? >>Yeah, In, in some ways for both our, our team internally and when we're working with clients, people in operations tend to be the things that are minimized. It, it tends to focus a lot on the technology, and we like to tell folks, you have to operate in the cloud and operating requires people in process. And so the, the people we know individuals with cloud skills are very much high in demand. And so how do you attract those skills? How do you retain those skills or how do you upskill the individuals in your organization? There's so much opportunity to bring people along. We go back to one of your earlier questions and, and you know, what's the evolution or roles that people, people can look at in, in the cloud, individuals that are in organizations right now where there hasn't been much public cloud adoption, taking those initiatives. >>Going back to another comment of learning, AWS provides so much free training and so much opportunity for individuals to upskill themselves to have growth in, in technology. And cloud is an area, you know, we're going through a recession. Cloud is an area that is still going to be one of the, the, the places that organizations look for answers to say, how do we drive innovation, right? How do we, how do we advance what we're doing from a, a profitability standpoint? And can we leverage, leverage cloud to cloud to do that? So upscaling and investing in yourself in those areas is, is, there's a great opportunity for that. >>There's a huge opportunity in upscaling and investing in ways to improve your own skills. My last question for you is, if we think back the last few years, talk about some of the changes in tech innovation in the workforce that you've seen and what are some of the things that you think are on the horizon? >>Yeah, so there, there's still a great opportunity to, to exploit cloud and in general, I mean, we see so many companies, software companies looking at sas, business models, subscription models. That's still changing. If we think about cloud economics and, and how we, how, how we purchase today. There's still an evolution there. But I think for me, being a, a self, self-proclaimed tech nerd, everything that's happening with AI and ML from an advanced analytics standpoint, the good and the bad. I mean, I think we've gotta look at the, the, the social responsibility behind this. When you talk about models and, and models themselves being diverse. If, if there isn't diverse background building those miles, the, the intentional bias gets built into, into some of those. But then I look at the, the advancements, I mean, it's exciting. We're working with, with, with one of our clients where autonomous taxis is, is something that they're trying to bring to market. >>You know, these are things that we saw in cartoons growing up that are reality and becoming reality in this day and age. So, you know, that's through AI and machine learning and just, you know, all of the new services that, you know, companies like AWS continue to bring out so that people can be innovative and, and and develop. But it's just, that's the, it's, it's exciting for me to, to see that across the board. So transportation from AI and ml, what we saw, what came out from, you know, covid and testing and the data and, and just the advancements of, of that. So there's, there's so many different ways to apply, apply that technology. >>There is the horizon I think is clearly bright. And thank you so much Rochelle, for sharing what you've done, your experiences, how you're helping to make that horizon even brighter. We appreciate your insights, we appreciate your time. Thank you for joining us in the program today. Thank you Lisa for Rochelle Mans. I'm Lisa Martin. You're watching The Cubes coverage of the special program series Women of the Cloud, brought to you by aws. Thanks for watching.

>>Hey everyone, welcome to this Cube's special program series Women of the Cloud, brought to you by aws. I'm your host for the series, Lisa Martin. Very pleased to be joined by Patty Jordan, the VP of enabling processes and technology at Optimus. My next guest, Patty, welcome to the program. >>Hi Lisa. Thank you for having me. >>Tell me a little bit about yourself, a little bit about your role so the audience gets that understanding of exactly who you are. >>Sure thing. Hi, my name is Patty Jordan. As we mentioned, I am originally from Cameroon, Central Africa, but I was raised in the DC area. I'm called and what you call a bank brat. My father worked for an international organization, the the World Bank. Lived in, like I said, grew up in dc, moved to Austin, Texas about seven years ago. Been with Optum for the last nine years of my working career. And I've had multiple roles, but currently my role as is with the enabling technologies and processes, which means that I manage teams that support the platform of a lot of analytics products in Optum. >>Got it. All right. Bank Brett, that's a new one to me. I hadn't heard that. I love that you're a bank, Brit and proud of it. I can tell. Talk to me a little bit about your, the career path that you have navigated and what are some of your sort of tactical and also strategic recommendations for the audiences looking to grow their career in tech? >>So the interesting thing is, I did not start in tech. My background is as an economist. I have a bachelor's of economics from the women, from the College of Women, Mary. I also have a financial master's in public policy from American University. However, I did take some IT classes and as a kid I'm probably dating myself a little bit, but I programmed in dos, so I, I was always excited by it and I had internships as a programmer that helped me pay for my master's degree in when I graduated. I just felt like I was having fun and I was getting paid very well and I was able to pay off my graduate schools. So I just stayed with tech. >>Love that. But it sounds like you had that interest from when you were quite young and as a lot of us and end up in tech, we didn't start there originally. There's a lot of zigzaggy paths to get there. Sounds like you had that as well. What are some of your recommendations for people, either those that are in tech now or aren't who want to get into it and really expand and climb that ladder? >>So definitely, so one of the things to understand is tech could be many different things. Like one of the things could be programming, which I started doing and now dislike intensely. And then another thing could be like being in the business analyst in tech, getting the business requirements versus product management or even, you know, management. And what I would encourage people to do is really focus on what you feel happy doing, which for me is problem solving and collaborating and getting the right people together to solve very complex problems. And if you focus on that then you'll find your, your the role for you even in tech. >>I love that problem solving is such an important skill to be able to have and to cultivate regardless of the industry that you're in. But I'd love to know a little bit more about some of the successes that you've had helping organizations really navigate their cloud journeys, their migration to cloud as we've seen the last couple of years, a massive acceleration to the cloud that was really born outta the pandemic. Talk to me about some of the successes that you've been able to achieve. >>So the first, I guess most obvious thing is understanding the technology. What do you have at your disposal? What do you need for your team to succeed in the cloud or even OnPrem? But what I've learned most in the last four to five years with the projects that I work on, whether it was migrating from a host data center to one that we owned ourselves or migrating from that data center to AWS recently was you really need to get the business organization engaged. And that's not just getting the sponsorship and getting them this to write that check, but really helping them understand how this journey to the cloud is a combined journey between both organizations, right? And they will be able to be more successful as well with us going to the cloud with improved processing with revenue protection because we, there's more tools available with revenue expansion because now we can now expand faster address client needs faster. And you know, so there's various different aspects of going to cloud that are more than just we're using the coolest technology. >>You're a problem solver, has there. And one of the challenges with organizations and from a cloud migration standpoint that we often talk about is it's a cultural migration as well, which is really challenging to do for any type of organization regardless of industry. Do you have a favorite example where as a, as the problem solver, you came in and really helped the organization, the business side understand, be able to transform their cultural direction, understand why cloud migration can be such a facilitator of the business from the top line in a bottom line perspective. >>So from a bottom line perspective, I think the hardest thing for them to understand or what does not compute for them is you can't give them a set. This is what you're gonna cost in the cloud, right? Because the benefit of being in the cloud is being able to scale shrink, et cetera. So that's one hurdle that we're still fighting to be a hundred percent candid. But from a a top line perspective, what's what's been great is we've been able to ramp up more clients with the same, right? So we haven't had to go out and procure more servers, more storage, hire more staff because we're in the cloud and we've actually been able to scale our teams as well because we incorporated the DevOps functions and we do not need a team to manage a data center anymore. So that they absolutely understood, you know, savings ratified, but really just how do we get to market faster? How do we get to revenue faster and how do we get more revenue with the same pool of resources is something that they've really, really resonated with. >>Well, you're starting to speak their language so that to your point that resonates well, but there's so much productivity improvements, efficiencies to be gained by leveraging cloud computing that that really hit the bottom line of an organization that businesses, if you put it in the right way. And it sounds like as the problem solver you have, they understand the immense value and competitive advantage that cloud can bring to their organization and become sort of a ah, the blinders are off. I get it. >>Exactly. Exactly. You're just not trying to, to play with the latest toys, you are actually solving a business problem even before it happens. >>And that's the key solving business problems before they happen. Being able to predict and forecast is huge for businesses, especially as we've seen the last couple of years. Everybody racing to digital, to to pivot, to survive Now to be competitive. If they don't do that and embrace that emerging technology suite, there's a competitor that's right back here that if they're more culturally willing and able to, to be more agile, they're gonna take the place of a competing organization. So yeah, so it absolutely is a huge differentiator for organizations. And it sounds like you've had some great successes there in helping organizations really navigate the challenges, the cultural challenges, but the benefits of cloud computing. Yes. I do wanna talk to you a little bit about in your expertise, diversity is something that is talked about in every industry. We talk about it in tech all the time, there's still challenges there. What are, what's, what are your thoughts on diversity? What are you seeing and what are some of those challenges that are still sitting on the table? >>So I guess the first thing I would say is there's multiple facets to diversity, right? The first one we always lean to is gender and race, but there's also diversity of thought. And being in the healthcare industry is very important for us to have a diversity of thought and experiences so that we can target a lot of these health equity issues that are, you know, that, that are ongoing. So that's one thing that we've, we've been trying to do is making sure that I don't just have people that think like me on the team. And typically that also means not having people that look like me. So making sure that we have the right pipelines to hire for partnering with our, with some of our vendors. AWS for example, is a good one where they had avenues and they had non-profits that they worked with and they connected us with some of our staff augmentation people also did the same thing, really just expanding the scope of where we're looking for talent and, and that helps also bring that diversity of thought and the diversity of gender race into the, into the full >>It is. And it and, and there's also, there's so much data if we follow the data and of course in tech we're all about data. Every company these days, regardless of industry needs to be a data company. If we follow the data, we can see that organizations with, for example, females within the C-suite are far more profitable than those organizations that don't have that even that element of diversity. So the data is demonstrating there's tremendous business value, tremendous competitive advantage, faster time to market, more products and services that can be delivered if there is thought diversity among the entire organization, not just the C-suite. >>Exactly. And and since we have an impact on what is being delivered as an engineering organization, we also need that in engineering, right? One of the things that's very keen right now is machine language and ai. If we don't have the right models for example, then we either introduced bias or perpetuate by it. So we definitely need people on our teams as well that understand how these technologies work, how we can leverage 'em on our data sets so that we could run counter to this bias >>And countering that bias is incredibly important. Machine learning ai, so driven by data, the volumes of data, but the data needs to be as clean and and non-biased as possible. And that's a big challenge for organizations to undertake. Is there advice that you have for those folks watching who might be, I, I don't see me in this organization, I don't feel represented. How can I change that? >>Well, one would be to speak up, right? Even if you don't see you apply for the job, right? And one of the things that we're trying to address even in the DEI space is making sure that our job descriptions are not introducing any biases so that people will eliminate themselves immediately, right? But really just if you have the skill set and you feel like you can ramp up to the talent, then just apply for the job. Talk to somebody. You do have a network whether you realize it or not. So leverage that network. But really like there's this expression that my kid taught me saying, you miss a hundred percent of the shots you don't take, right? So if you don't try, you're not gonna make it by default. If you do try, there's a chance to make it right. At the very least, you build a connection with someone who can potentially help you down the line. >>That is one of my absolute favorite sayings. You miss a hundred percent of the shots that you don't take. So encouraging people to raise their hand there, there are stats, data, speaking of data we've been talking about that, that demonstrate that women are far less likely to apply for jobs like on LinkedIn for example, unless they need 100% of the job requirements, which we all know are quite stringent and not necessary in a lot of cases. So I love your advice of just try raise your hand, ask the question. All the can say is no. And at the end of the day, what is that? It's a word but can also be directional and and really guiding for people on their journey to wherever that, if it's an engineering, cloud, engineering, DevOps, whatever happen that happens to be, raise your hand the question. And to your point, you have a network, it is there, open that up. There's so much potential for people that just raise, I think that's to raise their hand and ask the question. >>And the corollary to that though is I would also encourage people who are in leader leadership roles to be strong allies, right? Like we need to be aware of what biases we might be introducing or candidates that we might be leaving on the table because we're being too stringent because we're not expanding our, our our search, right? So definitely that's something that I've started doing about five, six years old shortly after I moved to Austin, which I kind of beat myself up about not having done before, is really contributing to that community, helping out, being a mentor, being a coach, being a guide. Sometimes it's just reviewing somebody's resume. Other times it's talking to 'em about a role that I have and helping them map their current state to that role. But really just being an ally to everyone and anyone who wants to come into this space. >>I love that. I, and I have a feeling, Patty, that you're a great mentor and ally for those in your organization across organizations and those out there that may not know yet. Patty can be an ally for me. I'd love to get your take in our final minutes on a couple things. One, the, what's next in cloud from your perspective, the things that you've seen, what you've been able to achieve, and how do you see your role evolving in the industry at Optum? >>So what's next in cloud, and we've talked about that a lot, is data. How do we manage all this data? How do we catalog this data, how to reuse this data, how to reshift this data? We have data in various different environments. We're a multi-cloud company. So how do we make sure that we don't have the same data everywhere? Or even if we do, how do we reconcile that? So data, data, data, right? And from data, get to information so that we can monetize it and we can share it. So that's the, that's for me is really next step. I mean we, we know the applications that we can build, we know the analytics that we can build, but if we don't have the right data, we're limiting ourselves. So that's definitely one aspect that I know that we wanna drive. And as far as my role, I was fortunate enough to be provided with the leadership of development of a platform for analytics, which yes, involves data. >>So I'm very excited about this, right? Cuz that's, that's next level for me. I've been typically in roles that protect revenue in the DevOps and operations role. And now I'm in a revenue generating role and it has a shift in mindset. But I, I really appreciate it and I'm really taking everything I've learned up to now as a DevOps team. I knew when the bad things came. So now I'm trying to prevent, prevent my team from pushing bad things down the pipe, right? So I'm just really excited about what's, what's, what's to come because there's so many opportunities for improving the products that we build. And I'm so excited to be part of this platform. >>There are the, the horizon of opportunities is really endless, which is exciting. And to your point about data, like I mentioned, for every company, whether it's your grocery store, a retailer, the postal service has to become a data driven company. Cuz as consumers we expect that we bring that into our business lives and we expect to be able to transact in business as easily as we do on the consumer side. And that all requires organizations to not just have access to data, but to be able to build the right data infrastructure, toing insights to act on that, to feed the AI and ML models so that products services can get better, more personalized and meet the demands of the ever demanding consumer, which I know I, one of them. I wanna ask you one more final question and that is, what do you think some of the biggest challenges have been with, with respect to tech innovation in the workforce over the past five years? What are some of those things that, that you've seen that you think we're on the right track moving forward to eliminate some of these? >>That is a good question. I think one of the biggest challenges for me has been not to remain in the status quo, right? Like not to do something because it's what we've been doing, but being in the cloud allows us with so many opportunities where we can fail fast. That let's give it a shot, let's do a quick sprint, let's figure out whether it is a possibility or not. Eliminate it if it's not, and then keep moving, right? Like we don't have the same development methodology before that we had to do three months, five months, six months. You can iterate in two week chunks, get it done, confirm your, your statement or not, or negate it, but at the very least have an answer, right? So that for me is the biggest challenge. We're aware of the thinking we're just not doing. So it'd be very exciting when we, when we pivot from that and really start innovating because we have the time >>Innovating because we have the time, as I mentioned, you know, with the demand of consumers, whether it's consumer in, in on the personal side, business side, those demands are there. But the, the exciting thing is to your point, the innovations are there. The capabilities are there, the data is there. We have a lot of what we need to be able to take advantage of that. So it's gonna be exciting to see what happens over the next few years. Patty, it's been such a pleasure having you on the cube today. Thank you so much for joining. You are clearly a, a leader in terms of women in the cloud. We appreciate what you're doing, your insights, your recommendations, and your insights as to what you see in the future. You've been a great guest. Thank you so much for joining me today. >>Thank you for having me Lisa. >>My pleasure For Patty Jordan, I'm Lisa Martin. You're watching The Cubes coverage of Women of the Cloud, brought to you by aws, a special program series. We thank you so much for watching. Take care.

(bright upbeat music) >> Greetings, brilliant community and thank you so much for tuning in to theCUBE here for the last three days where we've been live from Detroit, Michigan. I've had the pleasure of spending this week with Lisa Martin and John Furrier. Thank you both so much for hanging out, for inviting me into the CUBE family. It's our first show together, it's been wonderful. >> Thank you. >> You nailed it. >> Oh thanks, sweetheart. >> Great job. Great job team, well done. Free wall to wall coverage, it's what we do. We stay till everyone else-- >> Savannah: 100 percent. >> Everyone else leaves, till they pull the plug. >> Lisa: Till they turn the lights out. We're still there. >> Literally. >> Literally last night. >> Still broadcasting. >> Whatever takes to get the stories and get 'em out there at scale. >> Yeah. >> Great time. >> 33. 33 different segments too. Very impressive. John, I'm curious, you're a trend watcher and you've been at every single KubeCon. >> Yep. >> What are the trends this year? Give us the breakdown. >> I think CNCF does this, it's a hard job to balance all the stakeholders. So one, congratulations to the CNCF for another great KubeCon and CloudNativeCon. It is really hard to balance bringing in the experts who, as time goes by, seven years we've been all of, as you said, you get experts, you get seniority, and people who can be mentors, 60% new people. You have vendors who are sponsoring and there's always people complaining and bitching and moaning. They want this, they want that. It's always hard and they always do a good job of balancing it. We're lucky that we get to scale the stories with CUBE and that's been great. We had some great stories here, but it's a great community and again, they're inclusive. As I've said before, we've talked about it. This year though is an inflection point in my opinion, because you're seeing the developer ecosystem growing so fast. It's global. You're seeing events pop up, you're seeing derivative events. CNCF is at the center point and they have to maintain the culture of developer experts, maintainers, while balancing the newbies. And that's going to be >> Savannah: Mm-hmm. really hard. And they've done a great job. We had a great conversation with them. So great job. And I think it's going to continue. I think the attendance metric is a little bit of a false positive. There's a lot of online people who didn't come to Detroit this year. And I think maybe the combination of the venue, the city, or just Covid preferences may not look good on paper, on the numbers 'cause it's not a major step up in attendance. It's still bigger, but the community, I think, is going to continue to grow. I'm bullish on it. >> Yeah, I mean at least we did see double the number of people that we had in Los Angeles. Very curious. I think Amsterdam, where we'll be next with CNCF in the spring, in April. I think that's actually going to be a better pulse check. We'll be in Europe, we'll see what's going on. >> John: Totally. >> I mean, who doesn't like Amsterdam in the springtime? Lisa, what have been some of your observations? >> Oh, so many observations. The evolution of the conference, the hallway track conversations really shifting towards adjusting to the enterprise. The enterprise momentum that we saw here as well. We had on the show, Ford. >> Savannah: Yes. We had MassMutual, we had ING, that was today. Home Depot is here. We are seeing all these big companies that we know and love, become software companies right before our eyes. >> Yeah. Well, and I think we forget that software powers our entire world. And so of course they're going to have to be here. So much running on Kubernetes. It's on-prem, it's at the edge, it's everywhere. It's exciting. Woo, I'm excited. John, what do you think is the number one story? This is your question. I love asking you this question. What is the number one story out KubeCon? >> Well, I think the top story is a combination of two things. One is the evolution of Cloud Native. We're starting to see web assembly. That's a big hyped up area. It got a lot of attention. >> Savannah: Yeah. That's kind of teething out the future. >> Savannah: Rightfully so. The future of this kind of lightweight. You got the heavy duty VMs, you got Kubernetes and containers, and now this web assembly, shows a trajectory of apps, server-like environment. And then the big story is security. Software supply chain is, to me, was the number one consistent theme. At almost all the interviews, in the containers, and the workflows, >> Savannah: Very hot. software supply chain is real. The CD Foundation mentioned >> Savannah: Mm-hmm. >> they had 16,000 vulnerabilities identified in their code base. They were going to automate that. So again, >> Savannah: That was wild. >> That's the top story. The growth of open source exposes potential vulnerabilities with security. So software supply chain gets my vote. >> Did you hear anything that surprised you? You guys did this great preview of what you thought we were going to hear and see and feel and touch at KubeCon, CloudNativeCon 2022. You talked about, for example, the, you know, healthcare financial services being early adopters of this. Anything surprise either one of you in terms of what you predicted versus what we saw? Savannah, let's start with you. >> You know what really surprised me, and this is ironic, so I'm a community gal by trade. But I was really just impressed by the energy that everyone brought here and the desire to help. The thing about the open source community that always strikes me is, I mean 187 different countries participating. You've got, I believe it's something like 175,000 people contributing to the 140 projects plus that CNCF is working on. But that culture of collaboration extends far beyond just the CNCF projects. Everyone here is keen to help each other. We had the conversation just before about the teaching and the learnings that are going on here. They brought in Detroit's students to come and learn, which is just the most heartwarming story out of this entire thing. And I think it's just the authenticity of everyone in this community and their passion. Even though I know it's here, it still surprises me to see it in the flesh. Especially in a place like Detroit. >> It's nice. >> Yeah. >> It's so nice to see it. And you bring up a good point. It's very authentic. >> Savannah: It's super authentic. >> I mean, what surprised me is one, the Wasm, or web assembly. I didn't see that coming at the scale of the conversation. It sucked a lot of options out of the room in my opinion, still hyped up. But this looks like it's got a good trajectory. I like that. The other thing that surprised me that was a learning was my interview with Solo.io, Idit, and Brian Gracely, because he's a CUBE alumni and former host of theCUBE, and analyst at Wikibon, was how their go-to-market was an example of a modern company in Covid with a clean sheet of paper and smart people, they're just doing things different. They're in Slack with their customers. And I walked away with, "Wow that's like a playbook that's not, was never, in the go-to-market VC-backed company playbook." I thought that was, for me, a personal walk away saying that's important. I like how they did that. And there's a lot of companies I think could learn from that. Especially as the recession comes where partnering with customers has always been a top priority. And how they did that was very clever, very effective, very efficient. So I walked away with that saying, "I think that's going to be a standard." So that was a pleasant surprise. >> That was a great surprise. Also, that's a female-founded company, which is obviously not super common. And the growth that they've experienced, to your point, really being catalyzed by Covid, is incredibly impressive. I mean they have some massive brand name customers, Amex, BMW for example. >> Savannah: Yeah. >> Great point. >> And I interviewed her years ago and I remember saying to myself, "Wow, she's impressive." I liked her. She's a player. A player for sure. And she's got confidence. Even on the interview she said, "We're just better, we have better product." And I just like the point of view. Very customer-focused but confident. And I just took, that's again, a great company. And again, I'm not surprised that Brian Gracely left Red Hat to go work there. So yeah, great, great call there. And of course other things that weren't surprising that I predicted, Red Hat continued to invest. They continue to bring people on theCUBE, they support theCUBE but more importantly they have a good strategy. They're in that multicloud positioning. They're going to have an opportunity to get a bite at the apple. And I what I call the supercloud. As enterprises try to go and be mainstream, Cloud Native, they're going to need some help. And Red Hat is always has the large enterprise customers. >> Savannah: What surprised you, Lisa? >> Oh my gosh, so many things. I think some of the memorable conversations that we had. I love talking with some of the enterprises that we mentioned, ING Bank for example. You know, or institutions that have been around for 100 plus years. >> Savannah: Oh, yeah. To see not only how much they've innovated and stayed relevant to meet the demands of the consumer, which are only increasing, but they're doing so while fostering a culture of innovation and a culture that allows these technology leaders to really grow within the organization. That was a really refreshing conversation that I think we had. 'Cause you can kind of >> Savannah: Absolutely. think about these old stodgy companies. Nah, of course they're going to digitize. >> Thinking about working for the bank, I think it's boring. >> Right? >> Yeah. And they were talking about, in fact, those great t-shirts that they had on, >> Yeah, yeah, yeah, yeah. were all about getting more people to understand how fun it is to work in tech for ING Bank in different industries. You don't just have to work for the big tech companies to be doing really cool stuff in technology. >> What I really liked about this show is we had two female hosts. >> Savannah: Yeah. >> How about that? Come on. >> Hey, well done, well done on your recruitment there, champ. >> Yes, thank you boss. (John laughs) >> And not to mention we have a really all-star production team. I do just want to give them a little shout out. To all the wonderful folks behind the lines here. (people clapping) >> John: Brendan. Good job. >> Yeah. Without Brendan, Anderson, Noah, and Andrew, we would be-- >> Of course Frank Faye holding it back there too. >> Yeah, >> Of course, Frank. >> I mean, without the business development wheels on the ship we'd really be in an unfortunate spot. I almost just swore on television. We're not going to do that. >> It's okay. No one's regulating. >> Yeah. (all laugh) >> Elon Musk just took over Twitter. >> It was a close call. >> That's right! >> It's going to be a hellscape. >> Yeah, I mean it's, shit's on fire. So we'll just see what happens next. I do, I really want to talk about this because I think it's really special. It's an ethos and some magic has happened here. Let's talk about Detroit. Let's talk about what it means to be here. We saw so many, and I can't stress this enough, but I think it really matters. There was a commitment to celebrating place here. Lisa, did you notice this too? >> Absolutely. And it surprised me because we just don't see that at conferences. >> Yeah. We're so used to going to the same places. >> Right. >> Vegas. Vegas, Vegas. More Vegas. >> Your tone-- >> San Francisco >> (both laugh) sums up my feelings. Yes. >> Right? >> Yeah. And, well, it's almost robotic but, and the fact that we're like, oh Detroit, really? But there was so much love for this city and recognizing and supporting its residents that we just don't see at conferences. You uncovered a lot of that with your swag-savvy segments, >> Savannah: Yeah. >> And you got more of that to talk about today. >> Don't worry, it's coming. Yeah. (laughs) >> What about you? Have you enjoyed Detroit? I know you hadn't been here in a long time, when we did our intro session. >> I think it's a bold move for the CNCF to come here and celebrate. What they did, from teaching the kids in the city some tech, they had a session. I thought that was good. >> Savannah: Loved that. I think it was a risky move because a lot of people, like, weren't sure if they were going to fly to Detroit. So some say it might impact the attendance. I thought they did a good job. Their theme, Road Ahead. Nice tie in. >> Savannah: Yeah. And so I think I enjoyed Detroit. The weather was great. It didn't rain. Nice breeze outside. >> Yeah. >> The weather was great, the restaurants are phenomenal. So Detroit's a good city. I missed some hockey games. I'd love to see the Red Wings play. Missed that game. But we always come back. >> I think it's really special. I mean, every time I talked to a company about their swag, that had sourced it locally, there was a real reason for this story. I mean even with Kasten in that last segment when I noticed that they had done Carhartt beanies, Carhartt being a Michigan company. They said, "I'm so glad you noticed. That's why we did it." And I think that type of, the community commitment to place, it all comes back to community. One of the bigger themes of the show. But that passion and that support, we need more of that. >> Lisa: Yeah. >> And the thing about the guests we've had this past three days have been phenomenal. We had a diverse set of companies, individuals come on theCUBE, you know, from Scott Johnston at Docker. A really one on one. We had a great intense conversation. >> Savannah: Great way to kick it off. >> We shared a lot of inside baseball, about Docker, super important company. You know, impressed with companies like Platform9 it's been around since the OpenStack days who are now in a relevant position. Rafi Systems, hot startup, they don't have a lot of resources, a lot of guerilla marketing going on. So I love to see the mix of startups really contributing. The big players are here. So it's a real great mix of companies. And I thought the interviews were phenomenal, like you said, Ford. We had, Kubia launched on theCUBE. >> Savannah: Yes. >> That's-- >> We snooped the location for KubeCon North America. >> You did? >> Chicago, everyone. In case you missed it, Bianca was nice enough to share that with us. >> We had Sarbjeet Johal, CUBE analyst came on, Keith Townsend, yesterday with you guys. >> We had like analyst speed dating last night. (all laugh) >> How'd that go? (laughs) >> It was actually great. One of the things that they-- >> Did they hug and kiss at the end? >> Here's the funny thing is that they were debating the size of the CNC app. One thinks it's too big, one thinks it's too small. And I thought, is John Goldilocks? (John laughs) >> Savannah: Yeah. >> What is John going to think about that? >> Well I loved that segment. I thought, 'cause Keith and Sarbjeet argue with each other on Twitter all the time. And I heard Keith say before, he went, "Yeah let's have it out on theCUBE." So that was fun to watch. >> Thank you for creating this forum for us to have that kind of discourse. >> Lisa: Yes, thank you. >> Well, it wouldn't be possible without the sponsors. Want to thank the CNCF. >> Absolutely. >> And all the ecosystem partners and sponsors that make theCUBE possible. We love doing this. We love getting the stories. No story's too small for theCUBE. We'll go with it. Do whatever it takes. And if it wasn't for the sponsors, the community wouldn't get all the great knowledge. So, and thank you guys. >> Hey. Yeah, we're, we're happy to be here. Speaking of sponsors and vendors, should we talk a little swag? >> Yeah. >> What do you guys think? All right. Okay. So now this is becoming a tradition on theCUBE so I'm very delighted, the savvy swag segment. I do think it's interesting though. I mean, it's not, this isn't just me shouting out folks and showing off t-shirts and socks. It's about standing out from the noise. There's a lot of players in this space. We got a lot of CNCF projects and one of the ways to catch the attention of people walking the show floor is to have interesting swag. So we looked for the most unique swag on Wednesday and I hadn't found this yet, but I do just want to bring it up. Oops, I think I might have just dropped it. This is cute. Is, most random swag of the entire show goes to this toothbrush. I don't really have more in terms of the pitch there because this is just random. (Lisa laughs) >> But so, everyone needs that. >> John: So what's their tagline? >> And you forget these. >> Yeah, so the idea was to brush your cloud bills. So I think they're reducing the cost of-- >> Kind of a hygiene angle. >> Yeah, yeah. Very much a hygiene angle, which I found a little ironic in this crowd to be completely honest with you. >> John: Don't leave the lights on theCUBE. That's what they say. >> Yeah. >> I mean we are theCUBE so it would be unjust of me not to show you a Rubik's cube. This is actually one of those speed cubes. I'm not going to be able to solve this for you with one hand on camera, but apparently someone did it in 17 seconds at the booth. Knowing this audience, not surprising to me at all. Today we are, and yesterday, was the t-shirt contest. Best t-shirt contest. Today we really dove into the socks. So this is, I noticed this trend at KubeCon in Los Angeles last year. Lots of different socks, clouds obviously a theme for the cloud. I'm just going to lay these out. Lots of gamers in the house. Not surprising. Here on this one. >> John: Level up. >> Got to level up. I love these 'cause they say, "It's not a bug." And anyone who's coded has obviously had to deal with that. We've got, so Star Wars is a huge theme here. There's Lego sets. >> John: I think it's Star Trek. But. >> That's Star Trek? >> John: That's okay. >> Could be both. (Lisa laughs) >> John: Nevermind, I don't want to. >> You can flex your nerd and geek with us anytime you want, John. I don't mind getting corrected. I'm all about, I'm all about the truth. >> Star Trek. Star Wars. Okay, we're all the same. Okay, go ahead. >> Yeah, no, no, this is great. Slim.ai was nice enough to host us for dinner on Tuesday night. These are their lovely cloud socks. You can see Cloud Native, obviously Cloud Native Foundation, cloud socks, whole theme here. But if we're going to narrow it down to some champions, I love these little bee elephants from Raft. And when I went up to these guys, I actually probably would've called these my personal winner. They said, again, so community focused and humble here at CNCF, they said that Wiz was actually the champion according to the community. These unicorn socks are pretty excellent. And I have to say the branding is flawless. So we'll go ahead and give Wiz the win on the best sock contest. >> John: For the win. >> Yeah, Wiz for the win. However, the thing that I am probably going to use the most is this really dope Detroit snapback from Kasten. So I'm going to be rocking this from now on for the rest of the segment as well. And I feel great about this snapback. >> Looks great. Looks good on you. >> Yeah. >> Thanks John. (John laughs) >> So what are we expecting between now and KubeCon in Amsterdam? >> Well, I think it's going to be great to see how they, the European side, it's a chill show. It's great. Brings in the European audience from the global perspective. I always love the EU shows because one, it's a great destination. Amsterdam's going to be a great location. >> Savannah: I'm pumped. >> The American crowd loves going over there. All the event cities that they choose are always awesome. I missed Valencia cause I got Covid. I'm really bummed about that. But I love the European shows. It's just a little bit, it's high intensity, but it's the European chill. They got a little bit more of that siesta vibe going on. >> Yeah. >> And it's just awesome. >> Yeah, >> And I think that the mojo that carried throughout this week, it's really challenging to not only have a show that's five days, >> but to go through all week, >> Savannah: Seriously. >> to a Friday at 4:00 PM Eastern Time, and still have the people here, the energy and all the collaboration. >> Savannah: Yeah. >> The conversations that are still happening. I think we're going to see a lot more innovation come spring 2023. >> Savannah: Mm-hmm. >> Yeah. >> So should we do a bet, somebody's got to buy dinner? Who, well, I guess the folks who lose this will buy dinner for the other one. How many attendees do you think we'll see in Amsterdam? So we had 4,000, >> Oh, I'm going to lose this one. >> roughly in Los Angeles. Priyanka was nice enough to share with us, there was 8,000 here in Detroit. And I'm talking in person, we're not going to meddle this with the online. >> 6500. >> Lisa: I was going to say six, six K. >> I'm going 12,000. >> Ooh! >> I'm going to go ahead and go big I'm going to go opposite Price Is Right. >> One dollar. >> Yeah. (all laugh) That's exactly where I was driving with it. I'm going, I'm going absolutely all in. I think the momentum here is building. I think if we look at the numbers from-- >> John: You could go Family Feud >> Yeah, yeah, exactly. And they mentioned that they had 11,000 people who have taken their Kubernetes course in that first year. If that's a benchmark and an indicator, we've got the veteran players here. But I do think that, I personally think that the hype of Kubernetes has actually preceded adoption. If you look at the data and now we're finally tipping over. I think the last two years we were on the fringe and right now we're there. It's great. (voice blares loudly on loudspeaker) >> Well, on that note (all laugh) On that note, actually, on that note, as we are talking, so I got to give cred to my cohosts. We deal with a lot of background noise here on theCUBE. It is a live show floor. There's literally someone on an e-scooter behind me. There's been Pong going on in the background. The sound will haunt the three of us for the rest of our lives, as well as the production crew. (Lisa laughs) And, and just as we're sitting here doing this segment last night, they turned the lights off on us, today they're letting everyone know that the event is over. So on that note, I just want to say, Lisa, thank you so much. Such a warm welcome to the team. >> Thank you. >> John, what would we do without you? >> You did an amazing job. First CUBE, three days. It's a big show. You got staying power, I got to say. >> Lisa: Absolutely. >> Look at that. Not bad. >> You said it on camera now. >> Not bad. >> So you all are stuck with me. (all laugh) >> A plus. Great job to the team. Again, we do so much flow here. Brandon, Team, Andrew, Noah, Anderson, Frank. >> They're doing our hair, they're touching up makeup. They're helping me clean my teeth, staying hydrated. >> We look good because of you. >> And the guests. Thanks for coming on and spending time with us. And of course the sponsors, again, we can't do it without the sponsors. If you're watching this and you're a sponsor, support theCUBE, it helps people get what they need. And also we're do a lot more segments around community and a lot more educational stuff. >> Savannah: Yeah. So we're going to do a lot more in the EU and beyond. So thank you. >> Yeah, thank you. And thank you to everyone. Thank you to the community, thank you to theCUBE community and thank you for tuning in, making it possible for us to have somebody to talk to on the other side of the camera. My name is Savannah Peterson for the last time in Detroit, Michigan. Thanks for tuning into theCUBE. >> Okay, we're done. (bright upbeat music)

>>Good morning and welcome back to the Cube where we are excited to be broadcasting live all week from Detroit to Michigan at Cuban slash cloud Native con. Depending on who you're asking, Lisa, it's day two things are buzzing. How are you feeling? >>Good, excited. Ready for day two, ready to have more great conversations to see how this community is expanding, how it's evolving, and how it's really supporting it itself. >>Yeah, Yeah. This is a very supportive community. Something we talked a lot about. And speaking of community, we've got some very bold and brave folks over here. We've got this CTO and the head of product from Storm Forge, and they are on a mission to automate Kubernetes. Now automatic and Kubernetes are not words that go in the same sentence very often, so please welcome Patrick and Yasmin. Thank you both for being here. Hello. How you doing? >>Thanks for having us. >>Thanks for having us. >>Talk about what you guys are doing. Cause as you said, Kubernetes auto spelling is anything but auto. >>Yeah. >>The, what are some of the challenges? How do you help >>Eliminate this? Yeah, so the mission at Storm Forge is primarily automatic resource configuration and optimization essentially. So we started as a machine learning company first. And it's kind of an interesting story cuz we're one of those startups that has pivoted a few times. And so we were running our machine learning workloads. Most >>Have, I think, >>Right? Yeah. Yeah. We were, we started out running our machine learning workloads and moving them into Kubernetes. And then we weren't quite sure how to correctly adjust and size our containers. And so our ML team, we've got three PhDs and applied mathematics. They said, Well, hang on, we could write an algorithm for that. And so they did. And then, Oh, I love this. Yeah. And then we said, Well holy cow, that's actually really useful. I wonder if other people would like that. And that's kind of where we got our start. >>You solved your own problem and then you built a business >>Around it. Yeah, exactly. >>That is fantastic. Is, is that driving product development at Storm Forge still? That kind of attitude? >>I mean that kind of attitude definitely drives product development, but we're, you know, balancing that with what the users are, the challenges that they have, especially at large scale. We deal with a lot of large enterprises and for us as a startup, we can relate to the problems that come with Kubernetes when you're trying to scale it. But when you're talking about the scale of some of these larger enterprises, it's just a different mentality. So we're trying to balance that of how we take that input into how we build our product. Talk >>About that, like the, the end user input and how you're taking that in, because of course it's only going to be a, you know, more of a symbiotic relationship when that customer feedback is taken and >>Acted on. Yeah, totally. And for us, because we use machine learning, it's a lot of building confidence with our users. So making sure that they understand how we look at the data, how we come up with the recommendations, and actually deploy those changes in their environment. There's a lot of trust that needs to be built there. So being able to go back to our users and say, Okay, we're presenting you this type of data, give us your feedback and building it alongside them has helped a lot in these >>Relationships. Absolutely. You said the word trust, and that's something that we talk about at every >>Show. I was gonna jump on that too. It's >>Not, Yeah, it's not a buzzword. It's not, It shouldn't be. Yeah. It really should be, I wanna say lived and breathed, but that's probably grammatically incorrect. >>We're not a gram show. It's okay darling. Yeah, thank >>You. It should be truly embodied. >>Yeah. And I, I think it's, it's not even unique to just what we do, but across tech in general, right? Like when I talk about SRE and building SRE teams, one of the things I mentioned is you have to build that trust first. And with machine learning, I think it can be really difficult too for a couple different reasons. Like one, it tends to be a black box if it's actually true machine learning. Totally. Which ours is. But the other piece that we run into. Yeah. And the other piece we run into though is, is what I was an executive at United Health Group before I joined Storm Forge. And I would get companies that would come to me and try to sell me machine learning and I would kind of look at it and say, Well no, that's just a basic decision tree. Or like, that's a super basic whole winter forecast, right? Like that's not actually machine learning. And that's one of the things that we actually find ourselves kind of battling a little bit when we talk about what we do in building that trust. >>Talk a little bit about the latest release as you guys had a very active September. Here we are. And towards the, I think end of October. Yeah. What are some of the, the new things that have come out? New integrations, new partnerships. Give us a scoop on that. >>Yeah, well I guess I'll start and then I'll probably hand it over to you. But like the, the big thing for us is we talked about automating Kubernetes in the very beginning, right? Like Kubernetes has got a vpa it's >>A wild sentence anyway. Yeah, yeah. >>It it >>Has. We're not gonna get over at the whole show. Yeah. >>It as a VPA built in, it has an HPA built in and, and when you look at the data and even when you read the documentation from Google, it explicitly says never the two should meet. Right. Because you'll end up thrashing and they'll fight each other. Well the big release we just announced is with our machine learning, we can now do both. And so we vertically scale your pods to the correct up. Yeah. >>Follow status. I love that. >>Yeah, we can, we can scale your pods to the correct size and still allow you to enable the HPA and we'll make recommendations for your scaling points and your thresholds on the HPA as well so that they can work together to really truly maximize your efficiency that without sacrificing your performance and your reliability of the applications that you're running. That >>Sounds like a massive differentiator for >>Storm launch, which I would say it is. Yeah. I think as far as I know, we're the first in the industry that can do this. Yeah. >>And >>From very singularity vibes too. You know, the machines are learning, teaching themselves and doing it all automatically. Yep. Gets me very >>Excited. >>Yeah, absolutely. And from a customer demand perspective, what's the feedback been? Yeah, it's been a few >>Weeks. Yeah, it's been really great actually. And a lot of why we went down this path was user driven because they're doing horizontal scale and they want to be able to vertically size as they're scaling. So if you put yourself in the shoes of someone that's configuring Kubernetes, you're usually guessing on what you're setting your CPU requests and limits do. But horizontal scale makes sense. You're either adding more things or removing more things. And so once they actually are scaled out as a large environment and they have to rethink, how am I gonna resize this now? It's just not possible. It's so many thousands of settings across all the different environments and you're only thinking about CPU memory, You're not thinking about a lot of things. It's just, but once you scale that out, it's a big challenge. So they came to us and said, Okay, you're doing, cuz we were doing vertical scaling before and now we enable vertical and horizontal. And so they came to us and said, I love what you're doing about right sizing, but we wanna be able to do this while also horizontally scaling. And so the way that our software works is we give you the recommendations for what the setting should be and then allow Kubernetes to continue to add and remove replicas as needed. So it's not like we're going in and making changes to Kubernetes, but we make changes to the configuration settings so that it's the most optimal from a resource perspective. >>Efficiency has been a real big theme of the show. Yeah. And it's clear that that's a focus for you. Everyone here wants to do more faster Of course. And innovation, that's the thing to do that sometimes we need partners. You just announced an integration with Datadog. Tell us about that. Yeah, >>Absolutely. Yeah. So the way our platform works is we need data of course, right? So they're, they're a great partner for us and we use them both as an input and an output. So we pull in metrics from Datadog to provide recommendations and we'll actually display all those within the Datadog portal. Cause we have a lot of users that are like, Look, Datadog's my single pane of glass and I hate using that word, but they get all their insights there. They can see their recommendations and then actually go deploy those. Whether they wanna automatically have the recommendations deployed or go in and actually push a button. >>So give me an example of a customer that is using the, the new release and some of the business outcomes they're achieving. I imagine one of the things that you're enabling is just closing that ES skills gap. But from a business level perspective, how are they gaining like competitive advantages to be able to get products to market faster, for example? >>Yeah, so one of the customers that was actually part of our press release and launch and spoke about us at a webinar, they are a SaaS product and deal with really bursty workloads. And so their cloud costs have been growing 40% year over year. And their platform engineering team is basically enabled to provide the automation for developers and in their environment, but also to reduce those costs. So they want to, it's that trade off of resiliency and cost performance. And so they came to us and said, Look, we know we're over provisioned, but we don't know how to tackle that problem without throwing tons of humans at the problem. And so we worked with them and just on a single app found 60% savings and we're working now to kind of deploy that across their entire production workload. But that allows them to then go back and get more out of the, the budget that they already have and they can kind of reallocate that in other areas, >>Right? So there can be chop line and bottom >>Line impact. Yeah. And I, I think there's some really direct impact to the carbon emissions of an organization as well. That's a good point. When you can reduce your compute consumption by 60%. >>I love this. We haven't talked about this at all during the show. Yeah. And I'm really glad that you brought this up. All of the things that power this use energy. Yeah. >>What is it like seven to 8% of all electricity in the world is consumed by data centers. Like it's crazy. Yeah. Yeah. And so like that's wild. Yeah. Yeah. So being able to make a reduction in impact there too, especially with organizations that are trying to sign green pledges and everything else. >>It's hard. Yeah. ESG initiatives are huge. >>Absolut, >>It's >>A whole lot. A lot of companies have ESG initiatives where they can't even go out and do an RFP with a business, Right. If they don't have an actual active starting, impactful ESG program. Yes. Yeah. >>And the RFPs that we have to fill out, we have to tell them how they'll help. >>Yeah. Yes. It's so, yeah, I mean I was really struck when I looked on your website and I saw 54% average cost reduction for Yeah. For your cloud operations. I hadn't even thought about it from a power perspective. Yeah. I mean, imagine if we cut that to 3% of the world's power grid. That is just, that is very compelling. Speaking of compelling and exciting future things, talk to us about what's next? What's got you pumped for 2023 and and what lies >>Ahead? Oh man. Well that seems like a product conversation for sure. >>Well, we're super excited about extending what we do to other platforms, other metrics. So we optimize a lot right now around CPU and memory, but we can also give people insights into, you know, limiting kills, limiting CPU throttling, so extending the metrics. And when you look at hba and horizontal scale today, most of it is done with cpu, but there are some organizations out there that are scaling on custom metrics. So being able to take in more data to provide more recommendations and kind of extend what we can do from an optimization standpoint. >>That's, yeah, that's cool. And what house you most excited on the show floor? Anything? Anything that you've seen? Any keynotes? >>There's, Well, I haven't had a lot of time to go to the keynotes unfortunately, but it's, >>Well, I'm shock you've been busy or something, right? Much your time here. >>I can't imagine why. But no, there's, it's really interesting to see all the vendors that are popping up around Kubernetes focus specifically with security is always something that's really interesting to me. And automating CICD and how they continue to dive into that automation devs, SEC ops continues to be a big thing for a lot of organizations. Yeah. Yeah. >>I I do, I think it's interesting when we marry, Were you guys here last year? >>I was not here. >>No. So at, at the smaller version of this in Los Angeles. Yeah. I, I was really struck because there was still a conversation of whether or not we were all in on Kubernetes as, as kind of a community and a society this year. And I'm curious if you feel this way too. Everyone feels committed. Yeah. Yeah. I I I feel like there's no question that Kubernetes is the tool that we are gonna be using. >>Yeah. I I think so. And I think a lot of that is actually being unlocked by some of these vendors that are being partners and helping people get the most outta Kubernetes, you know, especially at the larger enterprise organizations. Like they want to do it, but the skills gap is a very real problem. Right. And so figuring out, like Jasmine talked about figuring out how do we, you know, optimize or set up the correct settings without throwing thousands of humans at it. Never mind the fact you'll never find a thousand people that wanna do that all day every day. >>I was gonna, It's a fold endeavor for those >>People study, right? Yeah. And, and being able to close some of those gaps, whether it's optimization, security, DevOps, C I C D. As we get more of those partners like I just talked about on the floor, then you see more and more enterprises being more open to leaning into Kubernetes a little bit. >>Yeah. Yeah. We've seen, we've had some great conversations the last day and, and today as well with organizations that are history companies like Ford Motor Companies for >>Example. Yeah. Right. >>Just right behind us. One of their EVs and, and it's, they're becoming technology companies that happen to do cars or home >>Here. I had a nice job with 'em this morning. Yes. With that storyline, honestly. >>Yes. That when we now have such a different lens into these organizations, how they're using technologies, advanced technologies, Kubernetes, et cetera, to really become data companies. Yeah. Because they have to be, well the consumers on the other end expect a Home Depot or a Ford or whomever or your bank Yeah. To know who you are. I want the information right here whenever I need it so I can do the transaction I need and I want you to also deliver me information that is relevant to me. Yeah. Because there, there's no patience anymore. Yeah. >>And we partner with a lot of big FinTech companies and it's, it's very much that. It's like how do we continue to optimize? But then as they look at transitioning off of older organizations and capabilities, whether that's, they have a physical data center that's racked to the gills and they can't do anything about that, so they wanna move to cloud or they're just dipping their toe into even private cloud with Kubernetes in their own instances. A lot of it is how do we do this right? Like how do we lean in and, Yeah. >>Yeah. Well I think you said it really well that the debate seems to be over in terms of do we go in on Kubernetes? That that was a theme that I think we felt that yesterday, even on on day one of the keynotes. The community seems to be just craving more. I think that was another thing that we felt yesterday was all of the contributors and the collaborators, people want to be able to help drive this community forward because it's, it's a flywheel of symbiosis for all of the vendors here. The maintainers and, and really businesses in any industry can benefit. >>Yeah. It's super validating. I mean if you just look at the floor, there's like 20 different booths that talk about cost reporting for Kubernetes. So not only have people moved, but now they're dealing with those challenges at scale. And I think for us it's very validating because there's so many vendors that are looking into the reporting of this and showing you the problem that you have. And then where we can help is, okay, now you know, you have a problem, here's how we can fix it for you. >>Yeah. Yeah. That, that sort of dealing with challenges at scale that you set, I think that's also what we're hearing. Yeah. And seeing and feeling on the show floor. >>Yeah, absolutely. >>What can folks see and, and touch and feel in your booth? >>We have some demos there you can play around with the product. We're giving away a Lego set so we've let >>Gotta gets >>Are right now we're gonna have to get some Lego, We do a swag segment at the end of the day every day. Now we've >>Some cool socks. >>Yep. Socks are hot. Let's, let's actually talk about scale internally as our closing question. What's going on at Storm Forge? If someone's watching right now, they're excited. Are you hiring? We are hiring. Yeah. How can they stalk you? What's the >>School? Absolutely. So you can check us out on Storm forge.io. We're certainly hiring across the engineering organization. We're hiring across the UX a product organization. We're dealing, like I said, we've got some really big customers that we're, we're working through with some really fun challenges. And we're looking to continue to build on what we do and do new innovative things like especially cuz like I said, we are a machine learning organization first. And so for me it's like how do I collect all the data that I can and then let's find out what's interesting in there that we can help people with. Whether that's cpu, memory, custom metrics, like as said, preventing kills, driving availability, reliability, What can we do to, to kind of make a little bit more transparent the stuff that's going on underneath the covers in Kubernetes for the decision makers in these organizations. >>Yes. Transparency is a goal of >>Many. >>Yeah, absolutely. Well, and you mentioned fun. If this conversation is any representation, it would be very fun to be working on both of your teams. We, we have a lot of fun Ya. Patrick, thank you so much for joining. Thanks for having us, Lisa, As usual, thanks for being here with me. My pleasure. And thank you to all of you for turning into the Cubes live show from Detroit. My name's Savannah Peterson and we'll be back in a few.

>>Hello and welcome back to the live coverage of the Cube here. Live in Detroit, Michigan for Cub Con, our seventh year covering all seven years. The cube has been here. M John Fur, host of the Cube, co-founder of the Cube. I'm here with Lisa Mart, my co-host, and our new host, Savannah Peterson. Great to see you guys. We're wrapping up day one of three days of coverage, and our guest analyst is Sario Wall, who's the cube analyst who's gonna give us his report. He's been out all day, ear to the ground in the sessions, peeking in, sneaking in, crashing him, getting all the data. Great to see you, Sarvi. Lisa Savannah, let's wrap this puppy up. >>I am so excited to be here. My first coupon with the cube and being here with you and Lisa has just been a treat. I can't wait to hear what you have to say in on the report side. And I mean, I have just been reflecting, it was last year's coupon that brought me to you, so I feel so lucky. So much can change in a year, folks. You never know where you're be. Wherever you're sitting today, you could be living your dreams in just a few >>Months. Lisa, so much has changed. I mean, just look at the past this year. Events we're back in person. Yeah. Yep. This is a big team here. They're still wearing masks, although we can take 'em off with a cube. But mask requirement. Tech has changed. Conversations are upleveling, skill gaps still there. So much has changed. >>So much has changed. There's so much evolution and so much innovation that we've also seen. You know, we started out the keynote this morning, standing room. Only thousands of people are here. Even though there's a mass requirement, the community that is CNCF Co Con is stronger than I, stronger than I saw it last year. This is only my second co con. But the collaboration, what they've done, their devotion to the maintainers, their devotion to really finding mentors for mentees was really a strong message this morning. And we heard a >>Lot of that today. And it's going beyond Kubernetes, even though it's called co con. I also call it cloud native con, which I think we'll probably end up being the name because at the end of day, the cloud native scaling, you're starting to see the pressure points. You're start to see where things are breaking, where automation's coming in, breaking in a good way. And we're gonna break it all down Again. So much going on again, I've overs gonna be in charge. Digital is transformation. If you take it to its conclusion, then you will see that the developers are running the business. It isn't a department, it's not serving the business, it is the business. If that's the case, everything has to change. And we're, we're happy to have Sarib here with us Cube analysts on the badge. I saw that with the press pass. Well, >>Thank you. Thanks for getting me that badge. So I'm here with you guys and >>Well, you got a rapport. Let's get into it. You, I >>Know. Let's hear what you gotta say. I'm excited. >>Yeah. Went around, actually attend some sessions and, and with the analysts were sitting in, in the media slash press, and I spoke to some people at their booth and the, there are a few, few patterns, you know, which are, some are the exaggeration of existing patterns or some are kind of new patterns emerging. So things are getting complex in open source. The lawn more projects, right. They have, the CNCF has graduated some projects even after graduation, they're, they're exploring, right? Kubernetes is one of those projects which has graduated. And on that front, just a side note, the new projects where, which are entering the cncf, they're the, we, we gotta see that process and the three stages and all that stuff. I tweeted all day long, if you wanna know what it is, you can look at my tweets. But when I will look, actually write right on that actually after, after the show ends, what, what I saw there, these new projects need to be curated properly. >>I think they need to be weed. There's a lot of noise in these projects. There's a lot of overlap. So the, the work is cut out for CNCF folks, by the way. They're sort of managerial committee or whatever you call that. The, the people who are leading it, they're try, I think they're doing their best and they're doing a good job of that. And another thing actually, I really liked in the morning's keynote was that lot of women on the stage and minorities represented. I loved it, to be honest with you. So believe me, I'm a minority even though I'm Indian, but from India, I'm a minority. So people who have Punjab either know that I'm a minority, so I, I understand their pain and how hard it is to, to break through the ceiling and all that. So I love that part as well. Yeah, the >>Activity is clear. Yeah. From day one. It's in the, it's in the dna. I mean, they'll reject anything that the opposite >>Representation too. I mean, it's not just that everyone's invited, it's they're celebrated and that's a very big difference. Yeah. It's, you see conferences offer discounts for women for tickets or minorities, but you don't necessarily see them put them running where their mouth is actually recruit the right women to be on stage. Right. Something you know a little bit about John >>Diversity brings better outcomes, better product perspectives. The product is better with all the perspectives involved. Percent, it might go a little slower, maybe a little debates, but it's all good. I mean, it's, to me, the better product comes when everyone's in. >>I hope you didn't just imply that women would make society. So >>I think John men, like slower means a slower, >>More diversity, more debate, >>The worst. Bringing the diversity into picture >>Wine. That's, that's how good groups, which is, which is >>Great. I mean, yeah, yeah, >>Yeah, yeah. I, I take that mulligan back and say, hey, you knows >>That's >>Just, it's gonna go so much faster and better and cheaper, but that not diversity. Absolutely. >>Yes. Well, you make better products faster because you have a variety >>Of perspectives. The bigger the group, there's more debate. More debate is key. But the key to success is aligning and committing. Absolutely. Once you have that, and that's what open sources has been about for. Oh God, yeah. Generations >>Has been a huge theme in the >>Show generations. All right, so, so, >>So you have to add another, like another important, so observation if you will, is that the security is, is paramount right. Requirement, especially for open source. There was a stat which was presented in the morning that 60% of the projects in under CNCF have more vulnerabilities today than they had last year. So that was, That's shocking actually. It's a big jump. It's a big jump. Like big jump means jump, jump means like it can be from from 40 to 60 or or 50 or 60. But still that percentage is high. What, what that means is that lot more people are contributing. It's very sort of di carmic or ironic that we say like, Oh this project has 10,000 contributors. Is that a good thing? Right. We do. Do we know the quality of that, where they're coming from? Are there any back doors being, you know, open there? How stringent is the process of rolling those things, which are being checked in, into production? You know, who is doing that? I've >>Wondered about that. Yeah. The quantity, quality, efficacy game. Yes. And what a balance that must be for someone like CNCF putting in the structure to try and >>That's >>Hard. Curate and regulate and, and you know, provide some bumpers on the bowling lane, so to speak, of, of all of these projects. Yeah. >>Yeah. We thought if anybody thought that the innovation coming from, or the number of services coming from AWS or Google Cloud or likes of them is overwhelming, look at open source, it's even more >>Overwhelming. What's your take on the supply chain discussion? More code more happening. What are you hearing there? >>The supply chain from the software? Yeah. >>Supply chain software, supply chain security pays. Are people talking about that? What are you >>Seeing? Yeah, actually people are talking about that. The creation, the curation, not creation. Curation of suppliers of software I think is best done in the cloud. Marketplaces Ive call biased or what, you know, but curation of open source is hard. It's hard to know which project to pick. It's hard to know which project will pan out. Many of the good projects don't see the day light of the day, but some decent ones like it becomes >>A marketing problem. Exactly. The more you have out there. Exactly. The more you gotta get above the noise. Exactly. And the noise echo that. And you got, you got GitHub stars, you got contributors, you have vanity metrics now coming in to this that are influencing what's real. But sometimes the best project could have smaller groups. >>Yeah, exactly. And another controversial thing a little bit I will say that is that there's a economics of the practitioner, right? I usually talk about that and economics of the, the enterprise, right? So practitioners in our world, in software world especially right in systems world, practitioners are changing jobs every two to three years. And number of developers doubles every three years. That's the stat I've seen from Uncle Bob. He's authority on that software side of things. Wow. So that means there's a lot more new entrance that means a lot of churn. So who is watching out for the enterprise enterprises economics, You know, like are we creating stable enterprises? How stable are our operations? On a side note to that, most of us see the software as like one band, which is not true. When we talk about all these roles and personas, somebody's writing software for, for core layer, which is the infrastructure part. Somebody's writing business applications, somebody's writing, you know, systems of bracket, some somebody's writing systems of differentiation. We talk about those things. We need to distinguish between those and have principle based technology consumption, which I usually write about in our Oh, >>So bottom line in Europe about it, in your opinion. Yeah. What's the top story here at coupon? >>Top story is >>Headline. Yeah, >>The, the headline. Okay. The open source cannot be ignored. That's a headline. >>And what should people be paying attention to if there's a trend coming out? See any kind of trends coming out or any kind of signal, What, what do you see that people should pay attention to here? The put top >>Two, three things. The signal is that, that if you are a big shop, like you'd need to assess your like capacity to absorb open source. You need to be certain size to absorb the open source. If you are below that threshold, I mean we can talk about that at some other time. Like what is that threshold? I will suggest you to go with the managed services from somebody, whoever is providing those managed services around open source. So manage es, right? So from, take it from aws, Google Cloud or Azure or IBM or anybody, right? So use open source as managed offering rather than doing it yourself. Because doing it yourself is a lot more heavy lifting. >>I I, >>There's so many thoughts coming, right? >>Mind it's, >>So I gotta ask you, what's your rapport? You have some swag, What's the swag look >>Like to you? I do. Just as serious of a report as you do on the to floor, but I do, so you know, I come from a marketing background and as I, I know that Lisa does as well. And one of the things that I think about that we touched on in this is, is you know, canceling the noise or standing out from the noise and, and on a show floor, that's actually a huge challenge for these startups, especially when you're up against a rancher or companies or a Cisco with a very large budget. And let's say you've only got a couple grand for an activation here. Like most of my clients, that's how I ended up in the CU County ecosystem, was here with the A client before. So there actually was a booth over there and I, they didn't quite catch me enough, but they had noise canceling headphones. >>So if you just wanted to take a minute on the show floor and just not hear anything, which I thought was a little bit clever, but gonna take you through some of my favorite swag from today and to all the vendors, you know, this is why you should really put some thought into your swag. You never know when you're gonna end up on the cube. So since most swag is injection molded plastic that's gonna end up in the landfill, I really appreciate that garden has given all of us a potable plant. And even the packaging is plantable, which is very exciting. So most sustainable swag goes to garden. Well done >>Rep replicated, I believe is their name. They do a really good job every year. They had some very funny pins that say a word that, I'm not gonna say live on television, but they have created, they brought two things for us, yet it's replicated little etch sketch for your inner child, which is very nice. And given that we are in Detroit, we are in Motor City, we are in the home of Ford. We had Ford on the show. I love that they have done the custom K eight s key chains in the blue oval logo. Like >>Fords right behind us by the way, and are on you >>Interviewed, we had 'em on earlier GitLab taking it one level more personal and actually giving out digital portraits today. Nice. Cool. Which is quite fun. Get lap house multiple booths here. They actually IPOed while they were on the show floor at CubeCon 2021, which is fun to see that whole gang again. And then last but not least, really embracing the ship wheel logo of a Kubernetes is the robusta accrue that is giving out bucket hats. And if you check out my Twitter at sabba Savvy, you can see me holding the ship wheel that they're letting everyone pose with. So we are all in on Kubernetes. That cove gone 2022, that's for sure. Yeah. >>And this is something, day one guys, we've got three. >>I wanna get one of those >>Hats. We we need to, we need a group photo >>By the end of Friday we will have a beverage and hats on to sign off. That's, that's my word. If I can convince John, >>Don, what's your takeaway? You guys did a great kind of kickoff about last week or so about what you were excited about, what your thoughts were going to be. We're only on day one, There's been thousands of people here, we've had great conversations with contributors, the community. What's your take on day one? What's your, what's your tagline? >>Well, Savannah and I had at we up, we, we were talking about what we might see and I think we, we were right. I think we had it right. There's gonna be a lot more people than there were last year. Okay, check. That's definitely true. We're in >>Person, which >>Is refreshing. I was very surprised about the mask mandate that kind of caught me up guard. I was major. Yeah. Cause I've been comfortable without the mask. I'm not a mask person, but I had to wear it and I was like, ah, mask. But I understand I support that. But whatever. It's >>Corporate travel policy. So you know, that's what it is. >>And then, you know, they, I thought that they did an okay job with the gates, but they wasn't slow like last time. But on the content side, definitely Kubernetes security, top line headline, Kubernetes at scale security, that's, that's to me the bumper sticker top things to pay attention to the supply chain and the role of docker and the web assembly was a surprise. You're starting to see containers ecosystem coming back to, I won't say tension growth in the functionality of containers cuz they have to solve the security problem in the container images. Okay, you got scanning technology so it's a little bit in the weeds, but there's a huge movement going on to fix that problem to scale it so it's not a problem area contain. And then Dr sent a great job with productivity interviews. Scott Johnston over a hundred million in revenue so far. That's my number. They have not publicly said that. That's what I'm reporting from sources extremely well financially. And they, and they love their business model. They make productivity for developers. That's a scoop. That's new >>Information. That's a nice scoop we just dropped there on the co casually. >>You're watching that. Pay attention to that. But that, that's proof. But guess what, Red Hat's got developers too. Yes. Other people have to, So developers gonna go where it's the best. Yeah. Developers are voting with their code, they're voting with their feet. You will see the winners with the developers and that's what we've talked about. >>Well and the companies are catering to the developers. Savannah and I had a great conversation with Ford. Yeah. You saw, you showed their fantastic swag was an E for Ev right behind us. They were talking about the, all the cultural changes that they've really focused on to cater towards the developers. The developers becoming the influencers as you say. But to see a company that is as, as historied as Ford Motor Company and what they're doing to attract and retain developer talent was impressive. And honestly that surprised me. Yeah. >>And their head of deb relations has been working for, for, for 29 years. Which I mean first of all, most companies on the show floor haven't been around for 29 years. Right. But what I love is when you put community first, you get employees to stick around. And I think community is one of the biggest themes here at Cuco. >>Great. My, my favorite story that surprised me and was cool was the Red Hat Lockheed Martin interview where they had edge deployments with micro edge, >>Micro shift, >>Micro >>Shift, new projects under, there's, there are three new projects under, >>Under that was so, so cool because it was an edge story in deployment for the military where lives are on the line, they actually had it working. That is a real world example of Kubernetes and tech orchestrating to deploy the industrial edge. And I think that's proof in my mind that Kubernetes and this ecosystem is gonna move faster through this next wave of growth. Because once things start clicking, you get hybrid on premise to super cloud and edge. That was, that was my favorite cause it was real. That was real >>Story that it can make is literally life and death on the battlefield. Yeah, that was amazing. With what they're doing and what >>They're talking check out the Lockheed Martin Red Hat edge story on Silicon Angle and then a press release all pillar. >>Yeah. Another actually it's impressive, which we knew this which is happening, but I didn't know that it was happening at this scale is the finops. The finops is, I saw your is a discipline which most companies are adopting bigger companies, which are spending like hundreds of millions dollars in cloud average. Si a team size of finops for finops is seven people. And average number of tools is I think 3.5 or around 3.7 or something like that. Average number of tools they use to control the cost. So finops is a very generic term for years. It's not financial operations, it's the financial operations for the cloud cost, you know, containing the cloud costs. So that's a finops that is a very emerging sort of discipline >>To keep an eye on. And well, not only is that important, I talked to, well one of the principles over there, it's growing and they have real big players in that foundation. Their, their events are highly attended. It's super important. It's just, it's the cost side of cloud. And, and of course, you know, everyone wants to know what's going on. No one wants to leave there. Their Amazon on Yeah, you wanna leave the lights on the cloud, as we always say, you never know what the bill's gonna look like. >>The cloud is gonna reach $3 billion in next few years. So we might as well control the cost there. Yeah, >>It was, it was funny to get the reaction I found, I don't know if I was, how I react, I dunno how I felt. But we, we did introduce Super Cloud to a couple of guests and a, there were a couple reactions, a couple drawn. There was a couple, right. There was a couple, couple reactions. And what I love about the super cloud is that some people are like, oh, cringing. And some people are like, yeah, go. So it's a, it's a solid debate. It is solid. I saw more in the segments that I did with you together. People leaning in. Yeah. Super fun. We had a couple sum up, we had a couple, we had a couple cringes, I'll say their names, but I'll go back and make sure I, >>I think people >>Get 'em later. I think people, >>I think people cringe on the, on the term not on the idea. Yeah. You know, so the whole idea is that we are building top of the cloud >>And then so I mean you're gonna like this, I did successfully introduce here on the cube, a new term called architectural list. He did? That's right. Okay. And I wanna thank Charles Fitzgerald for that cuz he called super cloud architectural list. And that's exactly the point of super cloud. If you have a great coding environment, you shouldn't have to do an architecture to do. You should code and let the architecture of the Super cloud make it happen. And of course Brian Gracely, who will be on tomorrow at his cloud cast said Super Cloud enables super services. Super Cloud enables what Super services, super service. The microservices underneath the covers have to be different. High performing, automated. So again, the debate and Susan, the goal is to keep it open. And that's our, that's our goal. But we had a lot of fun with that. It was fun to poke the bear a little bit. So >>What is interesting to see just how people respond to it too, with you throwing it out there so consistently, >>You wanna poke the bear, get a conversation going, you know, let let it go. We'll see, it's been positive so far. >>There, there I had a discussion outside somebody who is from Ford but not attending this conference and they have been there for a while. I, I just some moment hit like me, like I said, people, okay, technologists are horizontal, the codes are horizontal. They will go from four to GM to Chrysler to Bank of America to, you know, GE whatever, you know, like cross vertical within vertical different vendors. So, but the culture of a company is local, right? Right. Ford has been building cars for forever. They sort of democratize it. They commercialize it, right? But they have some intense culture. It's hard to change those cultures. And how do we bring in the new thinking? What is, what approach that should be? Is it a sandbox approach for like putting new sensors on the car? They have to compete with te likes our Tesla, right? Yeah. But they cannot, if they are afraid of deluding their existing market or they're afraid of failure there, right? So it's very >>Tricky. Great stuff. Sorry. Great to have you on as our cube analyst breaking down the stories. We'll document that, that we'll roll out a post on it. Lisa Savannah, let's wrap up the show for day one. We got day two and three. We'll start with you. What's your summary? Quick bumper sticker. What's today's show all about? >>I'm a community first gal and this entire experience is about community and it's really nice to see the community come together, celebrate that, share ideas, and to have our community together on stage. >>Yeah. To me, to me it was all real. It's happening. Kubernetes cloud native at scale, it's happening, it's real. And we see proof points and we're gonna have faster time to value. It's gonna accelerate faster from here. >>The proof points, the impact is real. And we saw that in some amazing stories. And this is just a one of the cubes >>Coverage. Ib final word on this segment was well >>Said Lisa. Yeah, I, I think I, I would repeat what I said. I got eight, nine years back at a rack space conference. Open source is amazing for one biggest reason. It gives the ability to the developing nations to be at somewhat at par where the dev develop nations and, and those people to lift up their masses through the automation. Cuz when automation happens, the corruption goes down and the economy blossoms. And I think it's great and, and we need to do more in it, but we have to be careful about the supply chains around the software so that, so our systems are secure and they are robust. Yeah, >>That's it. Okay. To me for SAR B and my two great co-host, Lisa Martin, Savannah Peterson. I'm John Furry. You're watching the Cube Day one in, in the Books. We'll see you tomorrow, day two Cuban Cloud Native live in Detroit. Thanks for watching.

>>Hey guys. Welcome back to the Cubes coverage of Ansible Fast 2022. This is day two of our wall to wall coverage. Lisa Martin here with John Ferer. John, we're seeing this world where companies are saying if we can't automate it, we need to, The automation market is transforming. There's been a lot of buzz about that. A lot of technical chops here at Ansible Fest. >>Yeah, I mean, we've got a great guest here coming on Cuba alumni, Dean Newman, future room. He travels every event he's got. He's got his nose to the grindstone ear to the ground. Great analysis. I mean, we're gonna get into why it's important. How does Ansible fit into the big picture? It's really gonna be a great segment. The >>Board do it well, John just did my job for me about, I'll introduce him again. Daniel Newman, one of our alumni is Back Principal Analyst at Future and Research. Great to have you back on the cube. >>Yeah, it's good to join you. Excited to be back in Chicago. I don't know if you guys knew this, but for 40 years, this was my hometown. Now I don't necessarily brag about that anymore. I'm, I live in Austin now. I'm a proud Texan, but I did grow up here actually out in the west suburbs. I got off the plane, I felt the cold air, and I almost turned around and said, Does this thing go back? Yeah. Cause I'm, I've, I've grown thin skin. It did not take me long. I, I like the warm, Come on, >>I'm the saying, I'm from California and I got off the plane Monday. I went, Whoa, I need a coat. And I was in Miami a week ago and it was 85. >>Oh goodness. >>Crazy. So you just flew in. Talk about what's going on, your take on, on Ansible. We've talked a lot with the community, with partners, with customers, a lot of momentum. The flywheel of the community is going around and round and round. What are some of your perspectives that you see? >>Yeah, absolutely. Well, let's you know, I'm gonna take a quick step back. We're entering an era where companies are gonna have to figure out how to do more with less. Okay? We've got exponential data growth, we've got more architectural complexity than ever before. Companies are trying to discern how to deal with many different environments. And just at a macro level, Red Hat is one of the companies that is almost certainly gonna be part of this multi-cloud hybrid cloud era. So that should initially give a lot of confidence to the buying group that are looking at how to automate their environments. You're automating workflows, but really with, with Ansible, we're focused on automating it, automating the network. So as companies are kind of dig out, we're entering this recessionary period, Okay, we're gonna call it what it is. The first thing that they're gonna look at is how do we tech our way out of it? >>I had a wonderful one-on-one conversation with ServiceNow ceo, Bill McDermott, and we saw ServiceNow was in focus this morning in the initial opening session. This is the integration, right? Ansible integrating with ServiceNow. What we need to see is infrastructure automation, layers and applications working in concert to basically enable enterprises to be up and running all the time. Let's first fix the problems that are most common. Let's, let's automate 'em, let's script them. And then at some point, let's have them self resolving, which we saw at the end with Project Wisdom. So as I see it, automation is that layer that enterprises, boards, technologists, all can agree upon are basically here's something that can make our business more efficient, more profitable, and it's gonna deal with this short term downturn in a way that tech is actually gonna be the answer. Just like Bill and I said, let's tech our way out of it. >>If you look at the Red Hat being bought by ibm, you see Project Wisdom Project, not a product, it's a project. Project Wisdom is the confluence of research and practitioners kind of coming together with ai. So bringing AI power to the Ansible is interesting. Red Hat, Linux, Rel OpenShift, I mean, Red Hat's kind of position, isn't it? Kind of be in that right spot where a puck might be coming maybe. I mean, what do you think? >>Yeah, as analysts, we're really good at predicting the, the recent past. It's a joke I always like to make, but Red Hat's been building toward the future. I think for some time. Project Wisdom, first of all, I was very encouraged with it. One of the things that many people in the market probably have commented on is how close is IBM in Red Hat? Now, again, it's a $34 billion acquisition that was made, but boy, the cultures of these two companies couldn't be more different. And of course, Red Hat kind of carries this, this sort of middle ground layer where they provide a lot of value in services to companies that maybe don't use IBM at, at, for the public cloud especially. This was a great indication of how you can take the power of IBM's research, which of course has some of the world's most prolific data scientists, engineers, building things for the future. >>You know, you see things like yesterday they launched a, you know, an AI solution. You know, they're building chips, semiconductors, and technologies that are gonna power the future. They're building quantum. Long story short, they have these really brilliant technologists here that could be adding value to Red Hat. And I don't know that the, the world has fully been able to appreciate that. So when, when they got on stage and they kind of say, Here's how IBM is gonna help power the next generation, I was immediately very encouraged by the fact that the two companies are starting to show signs of how they can collaborate to offer value to their customers. Because of course, as John kind of started off with, his question is, they've kind of been where the puck is going. Open source, Linux hybrid cloud, This is the future. In the future. Every company's multi-cloud. And I said in a one-on-one meeting this morning, every company is going to probably have workloads on every cloud, especially large enterprises. >>Yeah. And I think that the secret's gonna be how do you make that evolve? And one of the things that's coming out of the industry over the years, and looking back as historians, we would say, gotta have standards. Well, with cloud, now people standards might slow things down. So you're gonna start to figure out how does the community and the developers are thinking it'll be the canary in the coal mine. And I'd love to get your reaction on that, because we got Cuban next week. You're seeing people kind of align and try to win the developers, which, you know, I always laugh cuz like, you don't wanna win, you want, you want them on your team, but you don't wanna win them. It's like a, it's like, so developers will decide, >>Well, I, I think what's happening is there are multiple forces that are driving product adoption. And John, getting the developers to support the utilization and adoption of any sort of stack goes a long way. We've seen how sticky it can be, how sticky it is with many of the public cloud pro providers, how sticky it is with certain applications. And it's gonna be sticky here in these interim layers like open source automation. And Red Hat does have a very compelling developer ecosystem. I mean, if you sat in the keynote this morning, I said, you know, if you're not a developer, some of this stuff would've been fairly difficult to understand. But as a developer you saw them laughing at jokes because, you know, what was it the whole part about, you know, it didn't actually, the ping wasn't a success, right? And everybody started laughing and you know, I, I was sitting next to someone who wasn't technical and, and you know, she kinda goes, What, what was so funny? >>I'm like, well, he said it worked. Do you see that? It said zero data trans or whatever that was. So, but if I may just really quickly, one, one other thing I did wanna say about Project Wisdom, John, that the low code and no code to the full stack developer is a continuum that every technology company is gonna have to think deeply about as we go to the future. Because the people that tend to know the process that needs to be automated tend to not be able to code it. And so we've seen every automation company on the planet sort of figuring out and how to address this low code, no code environment. I think the power of this partnership between IBM Research and Red Hat is that they have an incredibly deep bench of capabilities to do things like, like self-training. Okay, you've got so much data, such significant size models and accuracy is a problem, but we need systems that can self teach. They need to be able self-teach, self learn, self-heal so that we can actually get to the crux of what automation is supposed to do for us. And that's supposed to take the mundane out and enable those humans that know how to code to work on the really difficult and hard stuff because the automation's not gonna replace any of that stuff anytime soon. >>So where do you think looking at, at the partnership and the evolution of it between IBM research and Red Hat, and you're saying, you know, they're, they're, they're finally getting this synergy together. How is it gonna affect the future of automation and how is it poised to give them a competitive advantage in the market? >>Yeah, I think the future or the, the competitive space is that, that is, is ecosystems and integration. So yesterday you heard, you know, Red Hat Ansible focusing on a partnership with aws. You know, this week I was at Oracle Cloud world and they're talking about running their database in aws. And, and so I'm kind of going around to get to the answer to your question, but I think collaboration is sort of the future of growth and innovation. You need multiple companies working towards the same goal to put gobs of resources, that's the technical term, gobs of resources towards doing really hard things. And so Ansible has been very successful in automating and securing and focusing on very certain specific workloads that need to be automated, but we need more and there's gonna be more data created. The proliferation, especially the edge. So you saw all this stuff about Rockwell, How do you really automate the edge at scale? You need large models that are able to look and consume a ton of data that are gonna be continuously learning, and then eventually they're gonna be able to deliver value to these companies at scale. IBM plus Red Hat have really great resources to drive this kind of automation. Having said that, I see those partnerships with aws, with Microsoft, with ibm, with ServiceNow. It's not one player coming to the table. It's a lot of players. They >>Gotta be Switzerland. I mean they have the Switzerland. I mean, but the thing about the Amazon deal is like that marketplace integration essentially puts Ansible once a client's in on, on marketplace and you get the central on the same bill. I mean, that's gonna be a money maker for Ansible. I >>Couldn't agree more, John. I think being part of these public cloud marketplaces is gonna be so critical and having Ansible land and of course AWS largest public cloud by volume, largest marketplace today. And my opinion is that partnership will be extensible to the other public clouds over time. That just makes sense. And so you start, you know, I think we've learned this, John, you've done enough of these interviews that, you know, you start with the biggest, with the highest distribution and probability rates, which in this case right now is aws, but it'll land on in Azure, it'll land in Google and it'll continue to, to grow. And that kind of adoption, streamlining make it consumption more consumable. That's >>Always, I think, Red Hat and Ansible, you nailed it on that whole point about multicloud, because what happens then is why would I want to alienate a marketplace audience to use my product when it could span multiple environments, right? So you saw, you heard that Stephanie yesterday talk about they, they didn't say multiple clouds, multiple environments. And I think that is where I think I see this layer coming in because some companies just have to work on all clouds. That's the way it has to be. Why wouldn't you? >>Yeah. Well every, every company will probably end up with some workloads in every cloud. I just think that is the fate. Whether it's how we consume our SaaS, which a lot of people don't think about, but it always tends to be running on another hyperscale public cloud. Most companies tend to be consuming some workloads from every cloud. It's not always direct. So they might have a single control plane that they tend to lead the way with, but that is only gonna continue to change. And every public cloud company seems to be working on figuring out what their niche is. What is the one thing that sort of drives whether, you know, it is, you know, traditional, we know the commoditization of traditional storage network compute. So now you're seeing things like ai, things like automation, things like the edge collaboration tools, software being put into the, to the forefront because it's a different consumption model, it's a different margin and economic model. And then of course it gives competitive advantages. And we've seen that, you know, I came back from Google Cloud next and at Google Cloud next, you know, you can see they're leaning into the data AI cloud. I mean, that is their focus, like data ai. This is how we get people to come in and start using Google, who in most cases, they're probably using AWS or Microsoft today. >>It's a great specialty cloud right there. That's a big use case. I can run data on Google and run something on aws. >>And then of course you've got all kinds of, and this is a little off topic, but you got sovereignty, compliance, regulatory that tends to drive different clouds over, you know, global clouds like Tencent and Alibaba. You know, if your workloads are in China, >>Well, this comes back down at least to the whole complexity issue. I mean, it has to get complex before it gets easier. And I think that's what we're seeing companies opportunities like Ansible to be like, Okay, tame, tame the complexity. >>Yeah. Yeah, I totally agree with you. I mean, look, when I was watching the demonstrations today, my take is there's so many kind of simple, repeatable and mundane tasks in everyday life that enterprises need to, to automate. Do that first, you know? Then the second thing is working on how do you create self-healing, self-teaching, self-learning, You know, and, and I realize I'm a little broken of a broken record at this, but these are those first things to fix. You know, I know we want to jump to the future where we automate every task and we have multi-term conversational AI that is booking our calendars and driving our cars for us. But in the first place, we just need to say, Hey, the network's down. Like, let's make sure that we can quickly get access back to that network again. Let's make sure that we're able to reach our different zones and locations. Let's make sure that robotic arm is continually doing the thing it's supposed to be doing on the schedule that it's been committed to. That's first. And then we can get to some of these really intensive deep metaverse state of automation that we talk about. Self-learning, data replication, synthetic data. I'm just gonna throw terms around. So I sound super smart. >>In your customer conversations though, from an looking at the automation journey, are you finding most of them, or some percentage is, is wanting to go directly into those really complex projects rather than starting with the basics? >>I don't know that you're, you're finding that the customers want to do that? I think it's the architecture that often ends up being a problem is we as, as the vendor side, will tend to talk about the most complex problems that they're able to solve before companies have really started solving the, the immediate problems that are before them. You know, it's, we talk about, you know, the metaphor of the cloud is a great one, but we talk about the cloud, like it's ubiquitous. Yeah. But less than 30% of our workloads are in the public cloud. Automation is still in very early days and in many industries it's fairly nascent. And doing things like self-healing networks is still something that hasn't even been able to be deployed on an enterprise-wide basis, let alone at the industrial layer. Maybe at the company's on manufacturing PLAs or in oil fields. Like these are places that have difficult to reach infrastructure that needs to be running all the time. We need to build systems and leverage the power of automation to keep that stuff up and running. That's, that's just business value, which by the way is what makes the world go running. Yeah. Awesome. >>A lot of customers and users are struggling to find what's the value in automating certain process, What's the ROI in it? How do you help them get there so that they understand how to start, but truly to make it a journey that is a success. >>ROI tends to be a little bit nebulous. It's one of those things I think a lot of analysts do. Things like TCO analysis Yeah. Is an ROI analysis. I think the businesses actually tend to know what the ROI is gonna be because they can basically look at something like, you know, when you have an msa, here's the downtime, right? Business can typically tell you, you know, I guarantee you Amazon could say, Look for every second of downtime, this is how much commerce it costs us. Yeah. A company can generally say, if it was, you know, we had the energy, the windmills company, like they could say every minute that windmill isn't running, we're creating, you know, X amount less energy. So there's a, there's a time value proposition that companies can determine. Now the question is, is about the deployment. You know, we, I've seen it more nascent, like cybersecurity can tend to be nascent. >>Like what does a breach cost us? Well there's, you know, specific costs of actually getting the breach cured or paying for the cybersecurity services. And then there's the actual, you know, ephemeral costs of brand damage and of risks and customer, you know, negative customer sentiment that potentially comes out of it. With automation, I think it's actually pretty well understood. They can look at, hey, if we can do this many more cycles, if we can keep our uptime at this rate, if we can reduce specific workforce, and I'm always very careful about this because I don't believe automation is about replacement or displacement, but I do think it is about up-leveling and it is about helping people work on things that are complex problems that machines can't solve. I mean, said that if you don't need to put as many bodies on something that can be immediately returned to the organization's bottom line, or those resources can be used for something more innovative. So all those things are pretty well understood. Getting the automation to full deployment at scale, though, I think what often, it's not that roi, it's the timeline that gets misunderstood. Like all it projects, they tend to take longer. And even when things are made really easy, like with what Project Wisdom is trying to do, semantically enable through low code, no code and the ability to get more accuracy, it just never tends to happen quite as fast. So, but that's not an automation problem, That's just the crux of it. >>Okay. What are some of the, the next things on your plate? You're quite a, a busy guy. We, you, you were at Google, you were at Oracle, you're here today. What are some of the next things that we can expect from Daniel Newman? >>Oh boy, I moved Really, I do move really quickly and thank you for that. Well, I'm very excited. I'm taking a couple of work personal days. I don't know if you're a fan, but F1 is this weekend. I'm the US Grand Prix. Oh, you're gonna Austin. So I will be, I live in Austin. Oh. So I will be in Austin. I will be at the Grand Prix. It is work because it, you know, I'm going with a number of our clients that have, have sponsorships there. So I'll be spending time figuring out how the data that comes off of these really fun cars is meaningfully gonna change the world. I'll actually be talking to Splunk CEO at the, at the race on Saturday morning. But yeah, I got a lot of great things. I got a, a conversation coming up with the CEO of Twilio next week. We got a huge week of earnings ahead and so I do a lot of work on that. So I'll be on Bloomberg next week with Emily Chang talking about Microsoft and Google. Love talking to Emily, but just as much love being here on, on the queue with you >>Guys. Well we like to hear that. Who you're rooting for F one's your favorite driver. I, >>I, I like Lando. Do you? I'm Norris. I know it's not necessarily a fan favorite, but I'm a bit of a McLaren guy. I mean obviously I have clients with Oracle and Red Bull with Ball Common Ferrari. I've got Cly Splunk and so I have clients in all. So I'm cheering for all of 'em. And on Sunday I'm actually gonna be in the Williams Paddock. So I don't, I don't know if that's gonna gimme me a chance to really root for anything, but I'm always, always a big fan of the underdog. So maybe Latifi. >>There you go. And the data that comes off the how many central unbeliev, the car, it's crazy's. Such a scientific sport. Believable. >>We could have Christian, I was with Christian Horner yesterday, the team principal from Reside. Oh yeah, yeah. He was at the Oracle event and we did a q and a with him and with the CMO of, it's so much fun. F1 has been unbelievable to watch the momentum and what a great, you know, transitional conversation to to, to CX and automation of experiences for fans as the fan has grown by hundreds of percent. But just to circle back full way, I was very encouraged with what I saw today. Red Hat, Ansible, IBM Strong partnership. I like what they're doing in their expanded ecosystem. And automation, by the way, is gonna be one of the most robust investment areas over the next few years, even as other parts of tech continue to struggle that in cyber security. >>You heard it here. First guys, investment in automation and cyber security straight from two analysts. I got to sit between. For our guests and John Furrier, I'm Lisa Martin, you're watching The Cube Live from Chicago, Ansible Fest 22. John and I will be back after a short break. SO'S stick around.

(upbeat music) >> Welcome back everyone to The Cubes coverage here in Seattle, Washington. For AWS's Marketplace Seller Conference. It's the big news within the Amazon partner network, combining with marketplace, forming the Amazon partner organization. Part of a big reorg as they grow to the next level, NextGen cloud, mid-game on the chessboard. Cube's got it covered. I'm John Furry, your host at Cube. Great guests here from Data bricks. Both cube alumni's. Jack Anderson, GM and VP of the Databricks partnership team for AWS. You handle that relationship and Joel Minick vice president of product and partner marketing. You guys have the keys to the kingdom with Databricks and AWS. Thanks for joining. Good to see you again. >> Thanks for having us back. >> Yeah, John, great to be here. >> So I feel like we're at Reinvent 2013. Small event, no stage, but there's a real shift happening with procurement. Obviously it's a no brainer on the micro, you know, people should be buying online. Self-service, Cloud Scale. But Amazon's got billions being sold through their marketplace. They've reorganized their partner network. You can see kind of what's going on. They've kind of figured it out. Like let's put everything together and simplify and make it less of a website, marketplace. Merge our partner organizations, have more synergy and frictionless experiences so everyone can make more money and customer's are going to be happier. >> Yeah, that's right. >> I mean, you're running relationship. You're in the middle of it. >> Well, Amazon's mental model here is that they want the world's best ISVs to operate on AWS so that we can collaborate and co architect on behalf of customers. And that's exactly what the APO and marketplace allow us to do, is to work with Amazon on these really, you know, unique use cases. >> You know, I interviewed Ali many times over the years. I remember many years ago, maybe six, seven years ago, we were talking. He's like, "we're all in on AWS." Obviously now the success of Databricks, you've got multiple clouds, see that. Customers have choice. But I remember the strategy early on. It was like, we're going to be deep. So this is, speaks volumes to the relationship you have. Years. Jack, take us through the relationship that Databricks has with AWS from a partner perspective. Joel, and from a product perspective. Because it's not like you guys are Johnny come lately, new to the scene. >> Right. >> You've been there, almost president creation of this wave. What's the relationship and how does it relate to what's going on today? >> So most people may not know that Databricks was born on AWS. We actually did our first $100 million of revenue on Amazon. And today we're obviously available on multiple clouds. But we're very fond of our Amazon relationship. And when you look at what the APN allows us to do, you know, we're able to expand our reach and co-sell with Amazon, and marketplace broadens our reach. And so, we think of marketplace in three different aspects. We've got the marketplace private offer business, which we've been doing for a number of years. Matter of fact, we were driving well over a hundred percent year over year growth in private offers. And we have a nine figure business. So it's a very significant business. And when a customer uses a private offer, that private offer counts against their private pricing agreement with AWS. So they get pricing power against their private pricing. So it's really important it goes on their Amazon bill. In may we launched our pay as you go, on demand offering. And in five short months, we have well over a thousand subscribers. And what this does, is it really reduces the barriers to entry. It's low friction. So anybody in an enterprise or startup or public sector company can start to use Databricks on AWS, in a consumption based model, and have it go against their monthly bill. And so we see customers, you know, doing rapid experimentation, pilots, POCs. They're really learning the value of that first, use case. And then we see rapid use case expansion. And the third aspect is the consulting partner, private offer, CPPO. Super important in how we involve our partner ecosystem of our consulting partners and our resellers that are able to work with Databricks on behalf of customers. >> So you got the big contracts with the private offer. You got the product market fit, kind of people iterating with data, coming in with the buyers you get. And obviously the integration piece all fitting in there. >> Exactly. >> Okay, so those are the offers, that's current, what's in marketplace today. Is that the products... What are people buying? >> Yeah. >> I mean, I guess what's the... Joel, what are people buying in the marketplace? And what does it mean for them? >> So fundamentally what they're buying is the ability to take silos out of their organization. And that is the problem that Databricks is out there to solve. Which is, when you look across your data landscape today, you've got unstructured data, you've got structured data, you've got real time streaming data. And your teams are trying to use all of this data to solve really complicated problems. And as Databricks, as the Lakehouse Company, what we're helping customers do is, how do they get into the new world? How do they move to a place where they can use all of that data across all of their teams? And so we allow them to begin to find, through the marketplace, those rapid adoption use cases where they can get rid of these data warehousing, data lake silos they've had in the past. Get their unstructured and structured data onto one data platform, an open data platform, that is no longer adherent to any proprietary formats and standards and something they can, very much, very easily, integrate into the rest of their data environment. Apply one common data governance layer on top of that. So that from the time they ingest that data, to the time they use that data, to the time they share that data, inside and outside of their organization, they know exactly how it's flowing. They know where it came from. They know who's using it. They know who has access to it. They know how it's changing. And then with that common data platform, with that common governance solution, they'd being able to bring all of those use cases together. Across their real time streaming, their data engineering, their BI, their AI. All of their teams working on one set of data. And that lets them move really, really fast. And it also lets them solve challenges they just couldn't solve before. A good example of this, you know, one of the world's now largest data streaming platforms runs on Databricks with AWS. And if you think about what does it take to set that up? Well, they've got all this customer data that was historically inside of data warehouses. That they have to understand who their customers are. They have all this unstructured data, they've built their data science model, so they can do the right kinds of recommendation engines and forecasting around. And then they've got all this streaming data going back and forth between click stream data, from what the customers are doing with their platform and the recommendations they want to push back out. And if those teams were all working in individual silos, building these kinds of platforms would be extraordinarily slow and complex. But by building it on Databricks, they were able to release it in record time and have grown at a record pace to now be the number one platform. >> And this product, it's impacting product development. >> Absolutely. >> I mean, this is like the difference between lagging months of product development, to like days. >> Yes. >> Pretty much what you're getting at. >> Yes. >> So total agility. >> Mm-hmm. >> I got that. Okay, now, I'm a customer I want to buy in the marketplace, but you got direct Salesforce up there. So how do you guys look at this? Is there channel conflict? Are there comp programs? Because one of the things I heard today in on the stage from AWS's leadership, Chris, was up there speaking, and Mona was, "Hey, he's a CRO conference chief revenue officer" conversation. Which means someone's getting compensated. So, if I'm the sales rep at Databricks, what's my motion to the customer? Do I get paid? Does Amazon sell it? Take us through that. Is there channel conflict? Or, how do you handle it? >> Well, I'd add what Joel just talked about with, you know, with the solution, the value of the solution our entire offering is available on AWS marketplace. So it's not a subset, it's the entire Data Bricks offering. And- >> The flagship, all the, the top stuff. >> Everything, the flagship, the complete offering. So it's not segmented. It's not a sub segment. >> Okay. >> It's, you know, you can use all of our different offerings. Now when it comes to seller compensation, we view this two different ways, right? One is that AWS is also incented, right? Versus selling a native service to recommend Databricks for the right situation. Same thing with Databricks, our sales force wants to do the right thing for the customer. If the customer wants to use marketplace as their procurement vehicle. And that really helps customers because if you get Databricks and five other ISVs together, and let's say each ISV is spending, you're spending a million dollars. You have $5 million of spend. You put that spend through the flywheel with AWS marketplace, and then you can use that in your negotiations with AWS to get better pricing overall. So that's how we view it. >> So customers are driving. This sounds like. >> Correct. For sure. >> So they're looking at this as saying, Hey, I'm going to just get purchasing power with all my relationships. Because it's a solution architectural market, right? >> Yeah. It makes sense. Because if most customers will have a primary and secondary cloud provider. If they can consolidate, you know, multiple ISV spend through that same primary provider, you get pricing power. >> Okay, Joel, we're going to date ourselves. At least I will. So back in the old days, (group laughter) It used to be, do a Barney deal with someone, Hey, let's go to market together. You got to get paper, you do a biz dev deal. And then you got to say, okay, now let's coordinate our sales teams, a lot of moving parts. So what you're getting at here is that the alternative for Databricks, or any company is, to go find those partners and do deals, versus now Amazon is the center point for the customer. So you can still do those joint deals, but this seems to be flipping the script a little bit. >> Well, it is, but we still have vars and consulting partners that are doing implementation work. Very valuable work, advisory work, that can actually work with marketplace through the CPPO offering. So the marketplace allows multiple ways to procure your solution. >> So it doesn't change your business structure. It just makes it more efficient. >> That's correct. >> That's a great way to say it. >> Yeah, that's great. >> Okay. So, that's it. So that's just makes it more efficient. So you guys are actually incented to point customers to the marketplace. >> Yes. >> Absolutely. >> Economically. >> Economically, it's the right thing to do for the customer. It's the right thing to do for our relationship with Amazon. Especially when it comes back to co-selling, right? Because Amazon now is leaning in with ISVs and making recommendations for, you know, an ISV solution. And our teams are working backwards from those use cases, you know, to collaborate and land them. >> Yeah. I want to get that out there. Go ahead, Joel. >> So one of the other things I might add to that too, you know, and why this is advantageous for companies like Databricks to work through the marketplace. Is it makes it so much easier for customers to deploy a solution. It's very, literally, one click through the marketplace to get Databricks stood up inside of your environment. And so if you're looking at how do I help customers most rapidly adopt these solutions in the AWS cloud, the marketplace is a fantastic accelerator to that. >> You know, it's interesting. I want to bring this up and get your reaction to it because to me, I think this is the future of procurement. So from a procurement standpoint, I mean, again, dating myself, EDI back in the old days, you know, all that craziness. Now this is all the internet, basically through the console. I get the infrastructure side, you know, spin up and provision some servers, all been good. You guys have played well there in the marketplace. But now as we get into more of what I call the business apps, and they brought this up on stage. A little nuanced. Most enterprises aren't yet there of integrating tech, on the business apps, into the stack. This is where I think you guys are a use case of success where you guys have been successful with data integration. It's an integrators dilemma, not an innovator's dilemma. So like, I want to integrate. So now I have integration points with Databricks, but I want to put an app in there. I want to provision an application, but it has to be built. It's not, you don't buy it. You build, you got to build stuff. And this is the nuance. What's your reaction to that? Am I getting this right? Or am I off because, no one's going to be buying software like they used to. They buy software to integrate it. >> Yeah, no- >> Because everything's integrated. >> I think AWS has done a great job at creating a partner ecosystem, right? To give customers the right tools for the right jobs. And those might be with third parties. Databricks is doing the same thing with our partner connect program, right? We've got customer partners like Five Tran and DBT that, you know, augment and enhance our platform. And so you're looking at multi ISV architectures and all of that can be procured through the AWS marketplace. >> Yeah. It's almost like, you know, bundling and un bundling. I was talking about this with, with Dave Alante about Supercloud. Which is why wouldn't a customer want the best solution in their architecture? Period. In its class. If someone's got API security or an API gateway. Well, you know, I don't want to be forced to buy something because it's part of a suite. And that's where you see things get sub optimized. Where someone dominates a category and they have, oh, you got to buy my version of this. >> Joel and I were talking, we were actually saying, what's really important about Databricks, is that customers control the data, right? You want to comment on that? >> Yeah. I was going to say, you know, what you're pushing on there, we think is extraordinarily, you know, the way the market is going to go. Is that customers want a lot of control over how they build their data stack. And everyone's unique in what tools are the right ones for them. And so one of the, you know, philosophically, I think, really strong places, Databricks and AWS have lined up, is we both take an approach that you should be able to have maximum flexibility on the platform. And as we think about the Lakehouse, one thing we've always been extremely committed to, as a company, is building the data platform on an open foundation. And we do that primarily through Delta Lake and making sure that, to Jack's point, with Databricks, the data is always in your control. And then it's always stored in a completely open format. And that is one of the things that's allowed Databricks to have the breadth of integrations that it has with all the other data tools out there. Because you're not tied into any proprietary format, but instead are able to take advantage of all the innovation that's happening out there in the open source ecosystem. >> When you see other solutions out there that aren't as open as you guys, you guys are very open by the way, we love that too. We think that's a great strategy, but what am I foreclosing if I go with something else that's not as open? What's the customer's downside as you think about what's around the corner in the industry? Because if you believe it's going to be open, open source, which I think open source software is the software industry, and integration is a big deal. Because software's going to be plentiful. >> Sure. >> Let's face it. It's a good time to be in software business. But Cloud's booming. So what's the downside, from your Databricks perspective? You see a buyer clicking on Databricks versus that alternative. What's potentially should they be a nervous about, down the road, if they go with a more proprietary or locked in approach? >> Yeah. >> Well, I think the challenge with proprietary ecosystems is you become beholden to the ability of that provider to both build relationships and convince other vendors that they should invest in that format. But you're also, then, beholden to the pace at which that provider is able to innovate. >> Mm-hmm. >> And I think we've seen lots of times over history where, you know, a proprietary format may run ahead, for a while, on a lot of innovation. But as that market control begins to solidify, that desire to innovate begins to degrade. Whereas in the open formats- >> So extract rents versus innovation. (John laughs) >> Exactly. Yeah, exactly. >> I'll say it. >> But in the open world, you know, you have to continue to innovate. >> Yeah. >> And the open source world is always innovating. If you look at the last 10 to 15 years, I challenge you to find, you know, an example where the innovation in the data and AI world is not coming from open source. And so by investing in open ecosystems, that means you are always going to be at the forefront of what is the latest. >> You know, again, not to date myself again, but you look back at the eighties and nineties, the protocol stacked with proprietary. >> Yeah. >> You know, SNA and IBM, deck net was digital. You know the rest. And then TCPIP was part of the open systems interconnect. >> Mm-hmm. >> Revolutionary (indistinct) a big part of that, as well as my school did. And so like, you know, that was, but it didn't standardize the whole stack. It stopped at IP and TCP. >> Yeah. >> But that helped inter operate, that created a nice defacto. So this is a big part of this mid game. I call it the chessboard, you know, you got opening game and mid-game, then you get the end game. You're not there at the end game yet at Cloud. But Cloud- >> There's, always some form of lock in, right? Andy Jazzy will address it, you know, when making a decision. But if you're going to make a decision you want to reduce- You don't want to be limited, right? So I would advise a customer that there could be limitations with a proprietary architecture. And if you look at what every customer's trying to become right now, is an AI driven business, right? And so it has to do with, can you get that data out of silos? Can you organize it and secure it? And then can you work with data scientists to feed those models? >> Yeah. >> In a very consistent manner. And so the tools of tomorrow will, to Joel's point, will be open and we want interoperability with those tools. >> And choice is a matter too. And I would say that, you know, the argument for why I think Amazon is not as locked in as maybe some other clouds, is that they have to compete directly too. Redshift competes directly with a lot of other stuff. But they can't play the bundling game because the customers are getting savvy to the fact that if you try to bundle an inferior product with something else, it may not work great at all. And they're going to be, they're onto it. This is the- >> To Amazon's credit by having these solutions that may compete with native services in marketplace, they are providing customers with choice, low price- >> And access to the core value. Which is the hardware- >> Exactly. >> Which is their platform. Okay. So I want to get you guys thought on something else I see emerging. This is, again, kind of Cube rumination moment. So on stage, Chris unpacked a lot of stuff. I mean this marketplace, they're touching a lot of hot buttons here, you know, pricing, compensation, workflows, services behind the curtain. And one of those things he mentioned was, they talk about resellers or channel partners, depending upon what you talk about. We believe, Dave and I believe on the Cube, that the entire indirect sales channel of the industry is going to be disrupted radically. Because those players were selling hardware in the old days and software. That game is going to change. You mentioned you guys have a program, let me get your thoughts on this. We believe that once this gets set up, they can play in this game and bring their services in. Which means that the old reseller channels are going to be rewritten. They're going to be refactored with this new kinds of access. Because you've got scale, you've got money and you've got product. And you got customers coming into the marketplace. So if you're like a reseller that sold computers to data centers or software, you know, a value added reseller or VAB or business. >> You've got to evolve. >> You got to, you got to be here. >> Yes. >> Yeah. >> How are you guys working with those partners? Because you say you have a product in your marketplace there. How do I make money if I'm a reseller with Databricks, with Amazon? Take me through that use case. >> Well I'll let Joel comment, but I think it's pretty straightforward, right? Customers need expertise. They need knowhow. When we're seeing customers do mass migrations to the cloud or Hadoop specific migrations or data transformation implementations. They need expertise from consulting and SI partners. If those consulting and SI partners happen to resell the solution as well. Well, that's another aspect of their business. But I really think it is the expertise that the partners bring to help customers get outcomes. >> Joel, channel big opportunity for Amazon to reimagine this. >> For sure. Yeah. And I think, you know, to your comment about how do resellers take advantage of that, I think what Jack was pushing on is spot on. Which is, it's becoming more and more about the expertise you bring to the table. And not just transacting the software. But now actually helping customers make the right choices. And we're seeing, you know, both SIs begin to be able to resell solutions and finding a lot of opportunity in that. >> Yeah. And I think we're seeing traditional resellers begin to move into that SI model as well. And that's going to be the evolution that this goes. >> At the end of the day, it's about services, right? >> For sure. Yeah. >> I mean... >> You've got a great service. You're going to have high gross profits. >> Yeah >> Managed service provider business is alive and well, right? Because there are a number of customers that want that type of a service. >> I think that's going to be a really hot, hot button for you guys. I think being the way you guys are open, this channel, partner services model coming in, to the fold, really kind of makes for kind of that Supercloud like experience, where you guys now have an ecosystem. And that's my next question. You guys have an ecosystem going on, within Databricks. >> For sure. >> On top of this ecosystem. How does that work? This is kind of like, hasn't been written up in business school and case studies yet. This is new. What is this? >> I think, you know, what it comes down to is, you're seeing ecosystems begin to evolve around the data platforms. And that's going to be one of the big, kind of, new horizons for us as we think about what drives ecosystems. It's going to be around, well, what's the data platform that I'm using? And then all the tools that have to encircle that to get my business done. And so I think there's, you know, absolutely ecosystems inside of the AWS business on all of AWS's services, across data analytics and AI. And then to your point, you are seeing ecosystems now arise around Databricks in its Lakehouse platform as well. As customers are looking at well, if I'm standing these Lakehouses up and I'm beginning to invest in this, then I need a whole set of tools that help me get that done as well. >> I mean you think about ecosystem theory, we're living a whole nother dream. And I'm not kidding. It hasn't yet been written up and for business school case studies is that, we're now in a whole nother connective tissue, ecology thing happening. Where you have dependencies and value proposition. Economics, connectedness. So you have relationships in these ecosystems. >> And I think one of the great things about the relationships with these ecosystems, is that there's a high degree of overlap. >> Yeah. >> So you're seeing that, you know, the way that the cloud business is evolving, the ecosystem partners of Databricks, are the same ecosystem partners of AWS. And so as you build these platforms out into the cloud, you're able to really take advantage of best of breed, the broadest set of solutions out there for you. >> Joel, Jack, I love it because you know what it means? The best ecosystem will win, if you keep it open. >> Sure, sure. >> You can see everything. If you're going to do it in the dark, you know, you don't know the outcome. I mean, this is really kind of what we're talking about. >> And John, can I just add that when I was at Amazon, we had a theory that there's buyers and builders, right? There's very innovative companies that want to build things themselves. We're seeing now that that builders want to buy a platform. Right? >> Yeah. >> And so there's a platform decision being made and that ecosystem is going to evolve around the platform. >> Yeah, and I totally agree. And the word innovation gets kicked around. That's why, you know, when we had our Supercloud panel, it was called the innovators dilemma, with a slash through it, called the integrater's dilemma. Innovation is the digital transformation. So- >> Absolutely. >> Like that becomes cliche in a way, but it really becomes more of a, are you open? Are you integrating? If APIs are connective tissue, what's automation, what's the service messages look like? I mean, a whole nother set of, kind of thinking, goes on in these new ecosystems and these new products. >> And that thinking is, has been born in Delta Sharing, right? So the idea that you can have a multi-cloud implementation of Databricks, and actually share data between those two different clouds, that is the next layer on top of the native cloud solution. >> Well, Databricks has done a good job of building on top of the goodness of, and the CapEx gift from AWS. But you guys have done a great job taking that building differentiation into the product. You guys have great customer base, great growing ecosystem. And again, I think a shining example of what every enterprise is going to do. Build on top of something, operating model, get that operating model, driving revenue. >> Mm-hmm. >> Yeah. >> Whether, you're Goldman Sachs or capital one or XYZ corporation. >> S and P global, NASDAQ. >> Yeah. >> We've got, you know, the biggest verticals in the world are solving tough problems with Databricks. I think we'd be remiss because if Ali was here, he would really want to thank Amazon for all of the investments across all of the different functions. Whether it's the relationship we have with our engineering and service teams. Our marketing teams, you know, product development. And we're going to be at Reinvent. A big presence at Reinvent. We're looking forward to seeing you there, again. >> Yeah. We'll see you guys there. Yeah. Again, good ecosystem. I love the ecosystem evolutions happening. This NextGen Cloud is here. We're seeing this evolve, kind of new economics, new value propositions kind of scaling up. Producing more. So you guys are doing a great job. Thanks for coming on the Cube and taking the time. Joel, great to see you at the check. >> Thanks for having us, John. >> Okay. Cube coverage here. The world's changing as APN comes together with the marketplace for a new partner organization at Amazon web services. The Cube's got it covered. This should be a very big, growing ecosystem as this continues. Billions of being sold through the marketplace. And of course the buyers are happy as well. So we've got it all covered. I'm John Furry. your host of the cube. Thanks for watching. (upbeat music)

>>The past two and a half 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 CISO 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, emerges 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 resilient 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 the Cube made possible by dva. And in collaboration with idc. I'm your host, Dave Ante, and today we're present 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 summarize the findings from a recent research report on the topic. >>After that, we're gonna 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 in 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 dva, Steven Manly and Anja Serenas. Steven is a 10 time cubo and Chief technology officer at dva. And Anjan is vice president and general manager of product management at the company. And these individuals will specifically address how DVA is closing the gaps presented in the IDC survey through their product innovation. Or right now I'm gonna toss it to Lisa Martin, another one of the hosts for today's program. Lisa, over to you. >>Bill Goodwin joins me next, the VP of research at idc. We're gonna be breaking down what's going on in the threat landscape. Phil, welcome to the program. It's great to have you back on the cube. >>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 cyber attacks massively increasing, the threat landscape changing so much, what is IDC seeing? >>You know, you, you really hit the, the top topic that we find from IT organizations as well as business organizations. And really it's that digital resilience that 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 is 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 be, have the scale, upper 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 gonna 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, what some of the research that we did is we found that about 77% of organizations have digital resilience as a, as a top priority within their organization. And so what you're seeing is organizations trying to leverage things to become more, more resilient, more digitally resilient, and to be able to really hone in on those kinds of issues that are keeping 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, 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 data resilience to find as something a little bit different? >>Well, sometimes yeah, that we do get caught using them when, when one is the other. But data resilience is really a part of digital resilience, if you think about the data itself and the context of of IT computing. So it really is a subset of that, but it is foundational to IT resilience. You, you really, you can't have it resilience about data resilience. So that, 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, what you mentioned at the, at the top of the segment. And, and that is the, 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, to defend against these ransoms. The other thing about it is it's really a lot like whackamole. You know, they attack us in one area and and, and we defend against it. They, so they attack us in another area and we defend against it. >>And in fact, I had a, an individual come up to me at a show not long ago and said, You know, one of these days we're gonna get pretty well defended against ransomware and it's gonna 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 gonna 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 here is here for the long term and something that we, we have to address and have to get proactive about. >>You mentioned some stats there and, and recently IDC and DVA did a white paper together that really revealed some quite shocking results. Talk to me about some of the things. Let, 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 concern concerning ransomware. >>Yeah, this, this was a worldwide study. It was sponsored by DVA and conducted by IDC as an independent study. And what we did, we surveyed 500 is a little over 500 different individuals across the globe in North America select countries in in western Europe, as well as several in, in Asia Pacific. And we did it across industries with our 20 different industries represented. They're all evenly represented. We had surveys that included IT practitioners, primarily CIOs, CTOs, VP of of infrastructure, you know, managers of data centers, things like that. And the, 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, when they get attacked. Some of the, some of the statistics that we learned from this, Lisa, include 83% of organizations believe or tell, told us that they have a, a playbook that, 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, 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 a third of organizations were able to fully recover their data without paying the ransom. And some two thirds 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, aren't necessarily to be trusted. And, and so the software that they provide sometimes is, is fully recovered. Sometimes it's not. So you look at that and you go, Wow. On, on the one hand, people think they're really, really prepared, and on the other hand, the results are, are absolutely horrible. >>You know, two thirds of people having, having to pay their ransom. So you start to ask yourself, well, well, what is, 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, you think you know what you're, you're doing, you think you're ready based on the information you have. And these people are smart people and, and they're professionals, but oftentimes you don't know what you don't know. And like I say, 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 in 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 half being the victims of ransomware in the last three years, and then half 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 it's, as we said, this is a matter of this is gonna happen just a matter of when and how often >>It it is a matter, Yeah, as you said, it's not if when or, or how often. It's really how badly. So I think what organizations are really do 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, 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, to plan the kinds of recovery associated with cyber recovery in terms of forensics, in terms of, of scanning, in terms of analysis and so forth. So they're, they're turning to professionals in the cloud much more in order to get that breadth of experience and, 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 are is IDC seeing this big shift to cloud where, where data resilience is concerned? >>Well, the first and foremost is the economics of it. You know, you can, you can have on demand resources. And in the old days when we had disaster recoveries where there we had two different data centers and a failover and so forth, you know, you had double the infrastructure. If your financial services, it might even be triple, the infrastructure is very complicated, very difficult by going to the cloud. Organizations can subscribe to disaster recovery as a service. It 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 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, 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 recover going as quickly as possible. >>So what do you think the big issue here is, is it that these, these I p T practitioners over 500 that you surveyed across 20 industries is a global survey? Do they not know what they don't know? What's the the overlying issue here? >>Yeah, I think that's right. It's, you don't know what you don't know and until you get into a specific attack, you know, there, there are so many different ways that, 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%. And when you think about that, the, the issue is, once I have your data, what are you gonna do? I mean, there's no amount of recovery that is gonna 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, and taking their chances. So best practice things like encryption, immutability, you know, things like that that organizations can put into place. Certainly air gaps. Having a, a solid backup foundation to, 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 is 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, the, the disconnect that you articulated, the, the stats that show so many think we are prepared, we've got a playbook, yet so many are being, are being attacked. The vulnerabilities and the, and the, as the, the landscape threat landscape just gets more and more amorphous. Why, what do you recommend organizations? Do you talk 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 gonna happen, we've gotta make sure that we are truly resilient and proactive? >>Yes, and in fact, what we found from this research is in more than half 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, the, the consequences of ransom where it's not just the ransom, it's the loss productivity, it's, it's the loss of, of revenue. It's, it's the loss of, of customer faith and, and, and goodwill and organizations that have been attacked have, have suffered those consequences. And, and many of them are permanent. So people at the board level where it's, whether it's the ceo, the cfo, the cio, the c cso, you know, whoever it is, they're extremely concerned about these. And I can tell you they are fully engaged in addressing these issues within their organization. >>So all the way at the top 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 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 business, it's very profitable. But what is IDCs prediction where ransomware is concerned? Do you think that organizations, if they truly adopt cloud and status based technologies, can they get to a place where the C-suite doesn't have to be involved to the point where they're, they really actually have i i functioning playbook? >>I i, I don't know if we'll ever get to the point where the CCC C suite is not involved. It's probably very important to have that, that level of executive sponsorship. But, but what we are seeing is, in fact, we predicted by 20 25, 50 5% of organizations we'll 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, 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, of cloud resources like immutable storage, being able to move data from region to region inexpensively and easily and, 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 Juba sponsored IDC White paper. Fascinating finds. I encourage all of you to download that, Take a read, you're gonna 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 the Cube, 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 of 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 dr. A data resiliency cloud where full data protection and beautiful simplicity converge. No hardware, no upgrades, no management, just total data resili. 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 DR A 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 dr A 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. DVA is trusted with billions of backups annually by thousands of enterprises, including more than 60 of the Fortune 500 costing up to 50% less in 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. Dr. A makes it simple. >>Welcome back everyone to the cube and the drew of a special presentation of why ransomware isn't your only problem. I'm John Furrier, host of the Cube. We're here with w Curtis Preston. Curtis Preston, he 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 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 to get your thoughts and I'd like you to reflect on the analysis that we've been covering here and the survey data, how it lines up with the real world that you're seeing out there. >>Yeah, I think it's the, the survey results really, I'd like to say, I'd like to say that they surprised me, but unfortunately they didn't. The, the, the, the data protection world has been this way for a while where there's this, 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, and, and or lost data. And yet the same people that were surveyed, they had to high degrees of confidence in their backup system. And I, you know, I, I could, I could probably go on for an hour as to the various reasons why that would be the case, but I, 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, and people often just, they, they, they don't wanna 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. Good, >>It's all good, it's all good, >>You know, and the fingers crossed, right? So again, this is the reality and, and, and as it becomes backup and recovery, which we've talked about many times on the cube, 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, 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 surprised 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, the, the one part in the survey that surprised me the most was people that had a huge, you know, that there, there was a huge percentage of people that said that they had a, a, a, you know, a a a ransomware response, you know, in readiness program. And you look at that and you, how could you be, you know, that high percentage of people be comfortable with their ransomware readiness program and a, you know, which includes a number of things, right? There's the cyber attack aspect of responding to a ransomware attack, and then there's the recovery aspect. And so your, you believe that your company was ready for that, and then you go, and I, I think it was 67% of the people in the survey paid the ransom, which as, 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, you talked about re infections, the surest way to guarantee that you get rein attacked and reinfected is to pay the ransom. This goes back all the way ransom since the beginning of time, right? Everyone knows if you pay the blackmail, all you're telling people is that you pay blackmail and >>You're in business, you're a good customer arr for ransomware. >>Yeah. So the, the fact that, you know, 60 what two thirds of the people that were attacked by ransomware paid the ransom. That one statistic just, 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 back in 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, the arr joking, but there's recurring revenue for the, for the bad guys if they know you're paying up and if you're stupid enough not to change, you're tooling, right? So, so again, it works both ways. So I gotta ask you, why do you think so many are unable to successfully respond after an attack? Is it because they know it's coming? I mean, I mean, they're not that dumb. I mean, they have to know it's coming. Why aren't they responding and successfully to this? >>I I think it's a, it's a litany of thing starting with the, 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, if you're the one that raises their hand, you know what, that's a good idea, Curtis, why don't you look into that? Right. Nobody, nobody wants to be, Where's >>That guy now? He doesn't work here anymore. Yeah, but I I I hear where you come from exactly. Psychology. >>Yeah. So there, 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, they, 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 for from your environment. The login and authentication and authorization system needs to be completely separate from your typical environment. Why? Because if you, 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 you've, if, if the production system is compromised, then the backup system is compromised. So you've got to segregate all of that. And I, and I just don't think that people are thinking about that. Yeah. 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 backup. So we got the ransomware it >>Makes Yeah, exactly. The the largest ransomware group out there, the KTI 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 this 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, you've got to fully segregate that data. There are, and, 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, a, a standard product and put a number of layers of defense on top of it, or you can switch to the, the way Druva does things, which is a SAS 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. And the, the, 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, the way juva 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, how do you break the laws of physics? I guess that's the question here. >>Well, when, because that's the other thing is that by storing the data in the cloud, we, we do, and I've said this a few times, that you get to break the laws of physics and the, the only way to do that is to, is time travel and what, that's what it, so yeah, so Druva has time travel. What, and this is a criticism by the way. I don't think this is our official position, but Yeah. But the, 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 what kind of what I mean by time travel in that you basically, you configure your dr your disaster recovery environment in, in DVA 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, 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, the data should already be restored. And that's the, i that's the way that you break the laws of physics is you break the laws of time. >>Well, I, everyone wants to know the next question, and this is the real big question, is, are you from the future? >>Yeah. Very much the future. >>What's it like in the future? Backup recovery as a restore, Is it air gaping? Everything? >>Yeah. It, it, it, Well it's a world where people don't have to worry about their backups. I I like to use the phrase, get outta the backup business. Just get into the ReSTOR business. I I, you know, I'm, I'm a grandfather now and I, and I love having a granddaughter and I often make the joke that if I don't, 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 SAS 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 been in the ways of innovation now it's really is about the recovery and real time. So a lot of good stuff going on. And God think automated thingss gotta 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, 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, right 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, I wish that, 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 Chris, 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 Steven Manley, the cto and on John Shva, the GM and VP of Product Manage will join me. You're watching the cube, 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 DR A data resiliency cloud on your side. The DR A 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. DVA also makes zero trust security easy with builtin 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 builtin 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. Cyber attacks are a major threat, but you can make protection and recovery easy with dva. >>Welcome back everyone to the Cubes special presentation with DVA on why ransomware isn't your only problem. I'm John er, host of the Cube. Our next guest are Steven Manley, Chief Technology Officer of dva and I, John Trini VAs, who is the general manager and vice president of product management and Druva. Gentleman, 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? I've obviously the resilience is huge. Ransomware is continues to thunder away at businesses and causes a lot of problems. Disruption, I mean just it's endless ransomware problems. What's your thoughts on the con conclusion? >>So I'll say the, the thing that pops out to me is, is on the one hand, everybody who sees the survey, who reads, it's gonna say, well that's obvious. Of course ransomware continues to be a problem. Cyber resilience is an issue that's plaguing everybody. But, but I think when you dig deeper and there and there's a lot of subtleties to look into, but, but one of the things that, that I hear on a daily basis from the customers is it's because the problem keeps evolving. It, 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 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 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 stay this >>Way. Yeah, I mean I hear this whole time and our cube conversations with practitioners, you know there, 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 fine points of, of recovery opportunities but they can't get there. So it seems to be that there's a confidence problem here in the market. What, how do you guys see that? Cuz I think this is where the rubber meets the road with ransomware cuz it's, it is a moving train, it's always changing but it doesn't seem as confidence. Can you guys talk about that? What's your reaction? >>Yeah, let me jump in first and Steven 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 could solve your problem, but they haven't had a chance to take a re-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 recite and what in Drew we are watching people do and people do it successfully, is that as they have adopted through our 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 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 tried to identify the right set of ecosystem to really bring together to solve it meaningfully. >>Steven, >>I was gonna say, I mean one, one of the, one of the really interesting things in the survey for me and, and, and for a moment, 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 backup 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, and, and I think that's the moment when we, we dug deeper and we realized, you know, if you've got a traditional architecture and let's face the dis base architecture's been around for almost two decades now in terms of dis based backup, you can have that tune to the help that can be running as efficiently, efficiently as you want it, but it was built before the ransomware attacks before, 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 Angen pointed out, the architecture, the tooling isn't there to support what, 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 wanna get to in second, you know, I interviewed Jare, the the founder CEO many years ago, even before the pandemic. You mentioned modern, you guys have always had the cloud, which r this is huge. Now that you're past the pandemic, what is that modern cloud edge you guys have? Cuz that's a great point. A lot of stuff was built kind of Beckham recovery bolted on, not really kind of designed into the, the current state of the infrastructure and the cloud native application modern environment we're seeing. Right? Now's a huge issue >>I think. I think it's, it's to me there's, there's three things that come up over and over and over again as, as we talk to people in terms of, you know, being built in cloud, being cloud native, why is an advantage? The first one is, is security and ransomware. And, and, and we can go deeper, but the most obvious one that always comes up is every single backup you do with DVA is air gap 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. I think the second advantage is the scalability. And you know this, this certainly plays into account as your, 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 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 a basically things evolving new workloads, data sprawl, new threat vectors. And one of the nice parts of being a SA service in the cloud is you're able to roll out new functionality every two weeks and there's no upgrade cycle, there's no waiting, you know, the customer doesn't have to say, Wow, I need it 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. >>That says on John, you know, you got the, the product side, you know, it's challenging job cuz you have so many customers asking for things probably on the roadmap you probably go hour for that one. But I wanna get your thoughts on what you're hearing and seeing from customers. You know, 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 on the, probably on the feature request, but also structurally as 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 challenge 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 rua 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 just not 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 faster, with less. And that has been this age old problem, do more with less. But in this, in this whole, they're like trying to innovate in the middle of the war so to say, right, 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 a hundred miles per hour while they're just, you know, 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 kind of 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. Drew 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 EC two offering to protect EC two virtual machines back in aws and we are gonna be continuing to evolve that to further many services that public cloud software cuz our customers are really kind of consuming them at breakneck speed. >>So the new workloads, the new security capabilities. Love that. Good, good call out there. Steven, this 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? Because this is, you got new workloads, you got the new security needs, what's the disruption impact? Cause you know, you won't avoid that. How much is it gonna cost you? And you guys have this guarantee, can you explain that? >>Yeah, absolutely. So, so Dr launched our 10 million data resiliency guarantee. And, and for us, you know, there were, there were really two key parts to this. The first obviously is 10 million means that, you know, again we're, we're we're willing to put our money where our mouth is and, and that's a big deal, right? That that, that we're willing to back this with the guarantee. But then the second part, and, and, and this is the part that I think reflects that, that sort of model that Angen was talking about, we, we sort of look at this and we say the goal of DVA 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, you know, your data's gonna be recoverable in the case of a ransomware attack. >>Okay, that's good. Of course for it to be recoverable, we're also guaranteeing, you know, your backup, your backup success rate. We're also guaranteeing the availability of the service. You know, we're, we're guaranteeing that the data that we're storing for you can't be compromised or leaked externally and you know, we're guaranteeing the long term durability of the data so that if you back up with us today and you need to recover 30 years from now, that data's gonna be recovered. So we wanted to really attack the end to end, you know, risks that, that, 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, again, as a SAS 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 is a big one. People 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 dva. You mentioned the new workloads on John, you mentioned this new security hearing 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 vo high velocity as possible for the developers and enterprises. What's on the horizon, Ava? 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 before they can start to get into much more advanced level of insights and analytics on 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 thwa because only we can look at multiple tenants, multiple customers because we are a SAS 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 gonna build all the way from a feature level where we have things like recycle bin 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 Steven can add a few more things around services that Steven is looking to build in launch. >>Sure. So, so yeah, so, so John, I think one of the other areas that we see just an enormous groundswell of interest. So, 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, you know, if you, if if someone you know deletes some really important records in Salesforce, that's, that's actually actually kind of the record of your business. And so, you know, we're looking at more and more SaaS application protection and, and really getting deep in that application awareness. It's not just about backup and recovery. When you look at something like, like a sales force or something like Microsoft 365, you do wanna look into sandboxing, you wanna, you wanna look into long term archival because again, 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, what engine said is, you know, 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. And 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, will 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, your data up more cleanly, you're gonna be a lot less worried and a lot less exposed from 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. Run John. >>And remember John, I think all this while keeping things really easy to consume consumer grade UI APIs and the, the really, the power of SaaS as a service simplicity to kind of continue on amongst kind of keeping these complex technologies together. >>Aj, that's a great call out. I was gonna mention ease of use is 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 the end of the day automation, cross cloud protection and security to protect and recover. This is huge and this is 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 of the product. Thanks for coming on. Appreciate it. >>Thank you very much. >>Okay, there it is. You got the experts talking 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 Ante will give you some closing thoughts on the subject here you're watching the cube, 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 dr. A Data Resiliency Cloud is the only 100% SAS data resiliency platform that provides centralized, secure air gapped and immutable backup and recovery. With dva, your data is safe with multiple layers of protection and is ready for fast recovery from cyber attack, data corruption, or accidental data loss. Through a simple, easy to manage platform, you can seamlessly protect fragmented, diverse data at scale, across public clouds and your business critical SaaS applications. Druva is the only 100% SAS fender that can manage, govern, and protect data across multiple clouds and business critical SAS applications. It supports not just backup and recovery, but also data resiliency across high value use cases such as e-discovery, sensitive data governance, ransomware, and security. No other vendor can match Druva for customer experience, infinite scale storage optimization, data immutability and ransomware protection. The DVA data resiliency cloud your data always safe, always ready. Visit druva.com today to schedule a free demo. >>One of the big takeaways from today's program is that in the scramble to keep business flowing over the past two plus 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 systems' 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. You know, 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 gotta do is go to the cube.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 dva, a collaboration with IDC and presented by the Cube, your leader in enterprise and emerging tech coverage.

>>The Cube Presents UI Path Forward five. Brought to you by UI Path. >>Hi everybody. Welcome back to UI Path Forward at five. You're watching the Cubes coverage. Everybody here is automating everything. Mundane tasks, Enterprisewide Automation Platform Beats product. Dave Nicholson. Dave Ante, Garish Pie is here. He is the Global head of Intelligent Enterprise Automation at Cognizant Global. Si, good to see you. Thanks for coming to the queue. Thank you for having me. Tell us about your role. What are you focused on? So, >>So I lead the enterprise automation practice at Cognizant, and we are focused on three broad segments, right? So we help customers anchor to business outcomes in, in looking at the business outcomes, what we look to do is help them drive transformation at a process level, looking at it from a technology standpoint, and then helping them look at how they're trying to drive change across their entire enterprise and bringing that together, you know, and helping them harmonize both at a technology and at a process level in terms of, you know, the outcomes they're trying to achieve. So >>You guys are a partner, I see your booth over there, and you're also a customer, right? Yes, we are. So are you involved in the both sides? One side, what, what, what's your purpose? >>So we do, so we, we sort of work, So we have a full 360 degree relationship with the i p. So we work with them, you know, in a professional services capacity. They, they support us as a partnership in the marketplace where we go into a number of our customers jointly to drive turnkey transformational engagements from an automation standpoint and second from a, as a, as a, as a customer to UiPath, they've been supporting us, you know, drive a number of automation initiatives across our operations book over the course of the last two years. >>Okay. So tell us more about that. So you started your internal journey, we had you guys on last year. Yep. It were just getting started I think, I think I think you, your head count is what, 60,000 somewhere around? Yeah. 70,000. Yeah, $70,000 growing. I think at the time it was maybe less than 10% of the workforce was kind of automated and the goal was to automate everybody. How are you guys doing along >>The, I think it's starting to in industrialize quite significantly. So over the course of the last year since we last spoke to you, probably, you know, we've doubled the head count in terms of the number of people that are now, you know, officially what we call quote unquote citizen developers. And you know, how they are driving automation at a personal level, we've probably gone about 2.5 x in terms of the number of RS we've saved. So we've done about, I think 450,000 rs, you know, in terms of actual saves at a personal automation level. And look, it's, it's been a great, you know, last 12 months too, right? Because, you know, as we've sort of started to get the message percolated more and more, our teams have started to get energized. They are happy that they are, you know, getting a release in terms of what they're doing on a day to day basis, which is largely repetitive at times, very mundane. And now they have the ability to bring in technology to be able to embrace that and drive that, that you know, much more efficiently. >>Are you talking dozens of bots? Thousands of bots? What's the scope of? >>So I think we've, we've scaled to about 3,500 today in terms of the bots and, and it's, it's a journey that continues to evolve. For me, the number is probably something which I wouldn't anchor to because it's, look, it's end of the day what you end up releasing and what you end up freeing and what the teams are doing. And I think, you know, that's the way we are >>Leading. So you're saying like, we always talk about number of boss, but you're saying it's largely in a relevant metric? Well, and not if it's five versus a thousand. Okay. That's meaningful, right? But, but >>Yeah, I think look a number for me, I think it's not about the number, right? It's about the outcome and it's about what impact you're having in, in terms of, you know, what you're trying to get done at the end of the day, right? Because ultimately you're trying to better, you know, what you do on a day to day basis and you know, whether it's done through 10 or whether that's done through 10,000. >>Yeah. But you pay >>Form, >>Right? Exactly. So, so you better get some value out. Exactly. It's about the value. >>But is there, is there a, is there a curve in terms, you know, an s-curve in terms of scalability though? I mean we, we, we've heard organizations doing, from organizations doing an amazing amount of modernization and automation and they say they've got 15 bots running, you have 3,500. Is there a number where it becomes harder to manage or, or is there scalability involved? >>So look, for me, so let me answer it this way, right? I think, I think there are two aspects to it. I think the, the, the, the more you have, you know, the bigger the challenge in terms of how you run the controls, the governance and the residency in terms of, you know, how you manage the, you know, the, the setup of the bots itself. So I think, yeah, I mean we want to have it to a manageable number, but for us, in the way we've looked at the number of bots, one of the things that we've done is we also look at, you know, what's foundational versus what's nuanced in terms of the kind of use cases that you're trying to deliver. So, so any program of this nature, you need to have a setup, which is, you know, which allows you to sort of orchestrate it in the right manner so that as you sort of scale and you bring more people into that equation, you, it's, you're not just creating bots for the sake of it, but you're actually, you know, trying to look at what you can reuse, what you can orchestrate better. >>And then in the context of that, figuring out where you have the gaps and then hence, you know, sort of taking the delta approach of what else and what more you need to build it. >>So you guys have a big observation space. You work with a lot of customers and, and so what are you seeing as the trends when you look out there? How are you applying it to your own business and your customer's businesses? >>So look, for me, I think the last two years, if anything, the one thing I've taken away is that transformation is now extremely, extremely compressed, right? So, so it's almost, you know, what's true today is probably irrelevant tomorrow. So, which means you have to continually evolve in terms of what needs to be done, right? Second is experiences have become extremely, extremely crucial and critical and experiences of, in, in my mind, you know, two or three kinds, right? One the end customer second from an employee standpoint, and third, in terms of the partner ecosystem that you will have as an enterprise that you have to cater to, right? The other element that you know, which becomes true will always remain true is the whole outcome story in terms of, you know, how we have an anchor to why you're trying to do what you're trying to do. >>And that is, you know, core to what you need to get done. So in the way we've looked at it, as we've said, you know, as you sort of look at how transformation is now evolving and how compressed it's starting to become, the more you are able to orchestrate for what the enterprise is trying to get done in terms of modernization, in terms of digitization, in terms of end goals and end outcomes that they're trying to achieve. And the more you're able to sweat what sits within, you know, the enterprise bring that together as you think about automation is, you know, where the true value lies in terms of being able to create an agile enterprise. >>When you think about digital transformation, digital experiences, if it's, if it's a layer cake, where is automation in that, in that layer? Is it, is it sort of the bottom of the stack? Is it, is it the whole stack? >>So for me it's, I mean it's, it's evolved. If you take today's view, I think what's emerging is a very pervasive view of how you think about automation. It sits across, you know, the entire enterprise. It, it, it, it takes a people process, technology dimension, which is age old. It has to cover, you know, all forms of transformation. You know, whether you're looking at end, how do I say, impact in terms of how you're dealing with customers, whether you're looking at the infrastructure, whether you're looking at the data layer in between, it has to be embedded across the base, right? It, it, you have to take a pervasive approach. And for me, I think automation increasingly in the days ahead is gonna be an enterprise capability. You know, it has to be, you know, all pervasive in the way it needs to be set up. >>The key, the operative word there is pervasive. And that seems to be, you know, the era that we're entering, I don't know what you call it, call it the metaverse, I mean, you know, it's more than cloud and cloud is basically just the infrastructure, right? You're building on top of that, whether it's natural language processing or cryptography or virtual, I mean, there's so many different, you know, technology dimensions, right? But it, but the point about pervasive, okay, it's everywhere. It's sensing, it's anticipatory, it feels like there's this new, you know, construct, emerging of platform that is the basis for digital business, right? And I, and I feel like every 15 years our industry goes through some big transformation. How, how do you see it? You know, do you agree that you, it feels like, okay, something new is happening. It's, it's not gonna be the social media, you know, Facebook's not gonna continue to dominate the world as it does. You already seen some cracks in that armor. We saw Microsoft after the pc, and then of course it came back with cloud Amazon looks, you know, indestructible. But that, that's never the end story, right? In our, in our world, how do you see that? >>No, I think all of what you said, I, I would sort of tend to agree with, for me, look, I don't have a crystal ball to say, you know, what's gonna happen with Facebook or Amazon or >>Otherwise. Yeah. But that's what makes this fun. But >>I, Yeah, but, but I think for me, the, the core is I think you're dictated by, you know, us as end consumers, if you're a B2B or a b2b, b2c, you know, depending upon what business you're in, I think the end customer value dictates, you know, what evolves in terms of, you know, the, the manifestation of, you know, how you will two minutes sort of deliver services, the products that you'll get into. And in that context then, you know, whether you take a, a TikTok view to it or whether you take an Amazon view to it, or whether YouTube becomes relevant in the days ahead, I think it's gonna be dictated by, >>By customer, but it tends to be a technology that's the disruptor, it's the microprocessor or it's the social capability or, or maybe it's ai that, that is the catalyst for that. And then the customer adoption dictates, oh, you're right about that. But there, but the, the match is usually technology. Is that fair or not necessarily? Yeah, >>I still look, I mean you talked about metaverse earlier, right? I think we are, I think we are, it's probably hype more than it is reality right now, at least in my view. And it's, I think we are significantly out in terms of, you know, large scale adoption in terms of what needs to be done. You talk about blockchain, blockchains been around, you know, for at least a decade if not more in, in, right. The way it's being talked about, the adoption, you know, in terms of the, the, the applicability of the, you know, of what is that technology I think is understood, but the actual use cases in terms of how it can be taken into the market and how you can scale it across industries, I think is, you know, is still because >>The economics determine ultimately exactly the outcome. So, Okay, that makes sense. >>Yeah. Now you said you don't have a crystal ball. I, I have one, but when I look into it, it's sort of murky when I try to figure out the answer to the question, Is a platform necessary for this, for automation? I mean, this is really the direction, the question, the existential question in terms of the trajectory of UI path. It seems obvious that automation is critical. It's not as obvious where that automation is going to end up eventually because it's so critical. It feels like it's almost the same as, okay, there's an interface between my keystrokes and filling in a box with text. Well, of course there has to be, there has to be that interface, right? So why wouldn't everyone deliver that by default? So as you gaze into my crystal ball with me, tell me about the things that only a platform can do from your perspective. >>So, >>So, so, so think of it this way, right? I mean, any enterprise probably has hundreds of technologies that they've invested in some platform, some applications that you would've built and evolved over time, which are bespoke custom in nature. So for me, I think when you think about automation, I think it's the balance between the two. What a platform allows you to do is to be able to orchestrate, given the complexity and the, the spa that is any enterprise, you know, that's probably got the burden of, you know, what they've done over the course of the, the previous years. And then in that context then, you know, how do you sort of help get the, the best value out of that in terms of what you want to deliver as the end, end outcomes, if I can call it that, right? So for me, I don't think you can say it's, it's her platform versus the rest. >>I think it's gonna be, it's always gonna be a balance and to the question that you asked earlier. And in terms of saying where does an automation end up at? I think if it's gonna be a pervasive view, look, you know, if, if clients are trying to modernize and get onto the cloud, you can do automation at a cloud level too. Now, you know, do I say then, you know, is it, is it sort of inclusive or it's native to what the cloud providers offer? Or do I then go and say automation needs to be something which I will, you know, sort of overlay on top of what the cloud providers offer. So I think it depends upon what dimension that you come at it. So I don't think you can say it's one or the other. You have a platform, I think it helps you orchestrate quite significantly. But there are gonna be aspects within any enterprise, given the complexity that exists that you will have to balance out, you know, platform versus, you know, how you have to address it maybe in a more individual capacity. >>Garris, gotta go. Thank you so much. Appreciate your perspectives. Good conversation. All right, keep it right there. But trains will back it up. We'll be right back right after this short break. The cube live at UI path forward, five from Las Vegas.

>>The Cube presents UI Path Forward five, brought to you by UI Path. >>Hi everybody. Welcome to Las Vegas. We're here in the Venetian, formerly the Sans Convention Center covering UI Path Forward five. This is the fourth time the Cube has covered forward, not counting the years during Covid, but UiPath was one of the first companies last year to bring back physical events. We did it at the Bellagio last year, Lisa Martin and myself. Today, my co-host is David Nicholson, coming off of last week's awesome CrowdStrike show back here in Vegas. David talking about UI path. UI path is a company that had a very strange path, as I wrote one time to IPO this company that was founded in 2005 and was basically a development shop. And then they realized they got lightning in a bottle with this RPA thing. Yeah. And Daniel Deez, the founder of the company, just really drove it hard and they really didn't do any big kind of VC raise for several years. >>And then all of a sudden, boom, the rocket ship took off, kind of really got out over their skis a little bit, but then got to IPO and, and has had a very successful sort of penetration into the market. The IPO obviously has not gone as well. We can talk about that, but, but they've hit a billion dollars in arr. There aren't a lot of companies that, you know, have hit a billion dollars in ARR that quickly. These guys had massive valuations that were cut back, obviously with the, with the downturn, but also some execution misuses. But the one thing about UiPath, Dave, is they've been very successful at penetrating customers. And that's the thing you always get at forward customer stories. And the other thing I'll, I'll, I'll add is that it started out with the narrative was, oh, automation software, robots, they're gonna take away jobs. The opposite has happened, the zero unemployment. Now basically we're heading into a recession, we're actually probably in a recession. And so how do you combat a recession? You put automation to work and gain if, if, if, if inflation is five to 7% and you can get 20% from automation. Well, it's a good roi. But you sat in the keynotes, it was really your first exposure to the company. What were your thoughts? >>Yeah, I think the whole subject is interesting. I think if you've been involved in tech for a while, the first thing you think of is, well, hold on a second. Isn't this just high tech scripting? Aren't you essentially just automating stuff? How, how cool can that possibly be? >>Well, it kinda was in the >>Beginning. Yeah, yeah. But, but, but when you dig into it, to your, to your point about the concern about displacing human beings, the first things that can automate it are the mundane and the repetitive tasks, which then frees individuals up frontline individuals who are doing those tasks to do more strategic things for the business. So when you, when we, you know, one of the things that was talked about in the keynote was this idea of an army of citizen developers within an organization. Not, you know, not just folks who are innovating and automating at the core of enterprise applications, but also folks out on the front line automating the tasks that are interfering with their productivity. So it seems like it's a win-win for, for everybody throughout the enterprise. >>Yeah. So let's take a, let's take folks through the, the keynote to, basically we learned there are 3,500 people here, roughly, you know, we're in the Venetian and we do a lot of shows at, at the Venetian, formerly the San Convention Center. The one thing about UiPath, they, they are a cool company. Yeah, they are orange colors, kinda like pure storage, but they got the robots moving around. The setup is very nice, it's very welcoming and very cool, but 300 3500 attendees, including partners and UiPath employees, 250 sessions. They've got a CIO, automation council and a pickleball court inside this hall, which pickleball is, you know, all the rage. So Bobby, Patrick and Mary Telo kicked it off. Bobby's the cmo, Mary's the head of branding, and Bobby raised four themes. It it, this is a tool that it's, this is RPA is going from a tool to a way of operating and innovating. >>The second thing is, the big news here is the UI path business platform, something like that. They're calling, but they're talking about about platform and they're really super gluing that to digital transformation. The third is really outcomes shifting from tactical. I have a robot, a software robot on my desk doing, you know, mimicking what I do with the script to something that's transformative. We're seeing this operationalized very deeply. We'll go into some examples. And then the fourth theme is automation is being featured as a strategic line item in annual reports. Bobby Patrick, as he left the stage, I think he was commenting on my piece where I said that RPA automation is more discretionary than some other things. He said, this is not discretionary, it's strategic. You know, unfortunately when you're heading into a recession, you can, you can put off some of the more strategic items. However, the flip side of that, Dave, is as they were saying before, if you're gonna, if if you're, if you're looking at five to 7% inflation may be a way to attack that is with automation. Yeah. >>There's no question, there's no question that automation is a way to attack that. There's no question that automation is critical moving forward. There's no question that we have moved. We're in the, you know, we're, we're still in the age of cloud, but automation is gonna be absolutely critical. The question is, what will UI path's role be in that market? And, and, and when you hear, when you hear UI path talk about platform versus tool sets and things like that, that's a critical differentiator because if they are just a tool, then why wouldn't someone exploit a tool that is within an application environment instead of exploiting a platform? So what I'm gonna be looking for in terms of the, the folks we talked to over the next few days is this question of, you know, make the case that this is actually a platform that extends across all kinds of application environments. If they can't seize that high ground moving forward, it's it's gonna be, it's gonna be tough for them. >>Well, they're betting the company on >>That, that's Rob Ensslin coming in. That's why he's part of the, the equation. But >>That platform play is they are betting the company. And, and the reason is, so the, the, the history here is in the early days of this sort of RPA craze, Automation Anywhere and UI path went out, they both raised a ton of money. UI Path rocketed out to the lead. They had a much e easier to install, you know, Automation Anywhere, Blue Prism, some of the other legacy business process folks, you know, kind of had on-prem, Big Stacks, UiPath came in a really simple self-serve platform and took off and really got a foothold in the market. And then started building or or making some of these acquisitions like Process Gold, like cloud elements, which is API automation. More recently Reiner, We, which is natural language processing. We heard them up on the stage today and they've been putting that together to do not just rpa but process mining, task mining, you know, document automation, et cetera. >>And so Rob Ins insulin was brought in from Google, formerly Google and SAP, to really provide that sort of financial and go to market expertise as well as Shim Gupta who's, who's the cfo. So they, they, and they were kinda late with that. They sort of did all this post ipo. I wish they had done it, you know, somewhat beforehand, but they're sort of bringing in that adult supervision supervision that's necessary. Rob Sland, I thought was very cogent. He was assertive on stage, he was really clear, he was energetic. He talked about the phases, e r p, Internet cloud and the now automation is a new S-curve. He quoted a Forester analyst talking about that. He also had a great quote. He said, you know, the old adage better, faster, cheaper, pick two. He said, You don't have to do that anymore with automation. He cited reports from analysts, 50% efficiency improvement, 40% productivity improvement, 40% improvement in customer satisfaction. >>And then what I always, again, love about UiPath is they're no shortage of customers. They do as good a job as anybody, and I think I would say the best of, of, of getting customers to talk about their experiences. You'll see that on the cube all this week, talked about Changi airport from Singapore. They're adding 50 able to service 50 million new customers, new travelers with no new headcount company called Vital or retail. And how you say that a hundred thousand employees having access to it. Uber, 150% ROI in one year. New York state getting 1.2 million relief checks out in two weeks and identifying potentially 12 billion in fraud. They also talk about 25% of the, of the UI path finance team is digital. And they've, they've only incremented headcount, you know, very slightly one and a half times their revenue's grown. What a 10 x? And really he talked about how to, for how to turn automation into a force multiplier for growth. And to your point, I think that's their challenge. What were your thoughts on Rob ens insulin's keynote? >>First of all, in addition to his background, Rob brings a brand with him. Rob Ensslin is a brand, and that brand is enterprise overarching platform. Someone you go to for that platform play, not for a tool set. And again, I'll, I'll say it again. It's critically important that they, that they demonstrate this to the marketplace, that they are a platform worth embracing as opposed to simply a tool set. Because the large enterprise software providers are going to provide their own tool sets within their platforms. And if you can't convince someone that it's worth doing two things instead of one thing, you're, you're, you're never gonna make it. So I've had experiences with Rob when he was at Google. He's, he's, he's the right person for the job and I, and I I I buy into his strategy and narrative about where we are and the critical nature of automation question remains, will you I path to be able to benefit from that trend. >>So a couple things on that. So your point about sap, you know, is right on EY was up on stage. They, EY is a huge SAP customer and they chose UI path to automate their SAP installation, right? And they're going all in with UI path as a partner. Of course. I I often like to say that the global system integrators, they like to eat at the trough, right? When you see GSIs like EY and others coming into the ecosystem, that means there's business being done. We saw Orange up on stage, which was really interesting. >>Javier from Spain. Yeah. Yep. >>Talking about he had this really cool dashboard and then Ted Coomer was talking about the business automation platform and all the different chapters and the evolution. They've gotta get to a platform play because the thing I failed to mention is Microsoft a couple years ago made a tuck in acquisition and got it to this market really providing individual automations and making it, you know, it's Microsoft, they're gonna make it really easy to add it really >>Cheaply. SAP would tell you that they have the same thing and, >>And then, and then just grow from that. So UiPath has to pivot to a platform play. They started this back in 2019, but as you know, it takes a long time to integrate stuff. Okay. So they're, they're, they're working through that. But this is, you know, Rob ends and put up on the, the slide go big, I, I tweeted, took a page outta Michael Dell. Go big or go home. Final thoughts before we break? >>I think go big or go home is pretty much sums it up. I mean this is, this is an existential mission that UiPath is on right now, starting to stay forward. They need to seize that high ground of platform versus tool set. Otherwise they will never get beyond where they are now. I I I, I do wanna mention too, to folks in the audience, there's a huge difference between a billion dollar valuation and a billion dollars in revenue every year. So, so, you know, these, these guys have reached a milestone, there's no question about that. But to get to that next level platform, platform, platform, and I know we'll be, we'll be probing our guests on that question over the next couple years. >>Yeah. And the key is obviously gonna be keep servicing the customers, you know, all the financial machinations and you know, they reduced yesterday their guidance from the high end being 25% ARR growth down to roughly 20% when you, when you factor out currency conversions. UiPath has a lot of business overseas. They're taking that overseas revenue and converting it back to dollars though dollars are appreciated. So they're less of them. I know this is kind of the inside baseball, but, but we're gonna get into that over the next two days. Dave Ante and Dave, you're watching the Cubes coverage of UI path forward, five from Las Vegas. We'll be right back, right after this short break.

>>The Cube Presents UI Path Forward five. Brought to you by UI Path. >>Welcome back to the Cube's Coverage of Forward five UI Path Customer event. This is the fourth forward that we've been at. We started in Miami, had some great events. It's all about the customer stories. Dave Valante with Dave Nicholson, Flow Yees here. She's the director of engineering and development at dsu and Kate Hall is to her right. And Kate is the director of Automation Solutions at dsu. Ladies, welcome to the Cube. Thanks so much. Thanks >>You to >>Be here. Tell us about dsu. You guys are huge company, but but give us the focus. >>Yeah, absolutely. Dentsu, it's one of the largest advertising networks out there. One of the largest in the world with over 66,000 employees and we're operating in a hundred plus countries. We're really proud to serve 95% of the Fortune 100 companies. Household names like Microsoft Factor and Gamble. If you seen the Super Bowls ads last year, Larry, Larry Davids ads for the crypto brand. That's a hilarious one for anyone who haven't seen it. So we're just really proud to be here and we really respect the creatives of our company. >>That was the best commercial, the Super Bowl by far. For sure. I, I said at the top of saying that Dave and I were talking UI pass, a cool company. You guys kinda look like cool people. You got cool jobs. Tell, tell us about your respective roles. What do you guys do? Yeah, >>Absolutely, absolutely. Well, I'm the director of engineering and automation, so what I really do is to implement the automation operating model and connecting developers across five continents together, making sure that we're delivering and deploying automation projects up to our best standards setting by the operating model. So it's a really, really great job. And when we get to see all these brilliant minds across the world >>And, And Kate, what's your role? Yeah, >>And the Automation Solutions vertical that I head up, the focus is really on converting business requirements into technical designs for flows, developers to deliver. So making sure that we are managing our pipeline, sourcing the right ideas, prioritizing them according to the business businesses objectives and making sure that we route them to the right place. So is it, does it need to be an automation first? Do we need to optimize the process? Does this make sense for citizen developers or do we need to bring in the professional resources on flow's >>Team? So you're bilingual, you speak, you're like the translator, you speak geek and wall, right? Is that fair? Okay. So take me back to the, let's, let's do a little mini case study here. How did you guys get started? I'm always interested, was this a top down? Is, is is top down required to be successful? Cuz it does feel like you can have bottom up bottoms up with rpa, but, but how did you guys get started? What was the journey like? >>Yeah, we started back in 2017, very traditional top down approach. So we delivered a couple POCs working directly with UiPath. You know, going back those five years, delivered those really highly scalable top down solutions that drove hundreds of thousands of hours of ROI for the business. However, as people kind of began to embrace automation and they learned that this is something that they could, that could help them, it's not something that they should be afraid of to take away their jobs. You know, DSU is a young company with a lot of young, young creatives. They wanna make their lives better. So we were absolutely inundated with all of these use cases of, hey I, I need a bot to do this. I need a bot to do that i's gonna save me, you know, 10 hours a week. It's gonna save my team a hundred hours a month, et cetera, et cetera. All of these smaller use cases that were gonna be hugely impactful for the individuals, their teams, even in entire department, but didn't have that scalable ROI for us to put professional development resources against it. So starting in 2020 we really introduced the citizen development program to put the power into those people's hands so that they could create their own solutions. And that was really just a snowball effect to tackle it from the bottom up as well as the top down. >>So a lot of young people, Dave, they not not threatened by robots that racing it. So >>They've grown up with the technology, they know that they can order an Uber from their phone, right? Why am I, you know, sitting here at MITs typing data from Excel into a program that might be older than some of our youngest employees. >>Yeah. Now, now the way you described it, correct me if I'm wrong, the way you described it, it sounds like there's sort of a gating function though. You're not just putting these tools in the hands of people sitting, especially creatives who are there to create. You're not saying, Oh you want things automated, here are the tools. Go ahead. Automated. We'll we, for those of you who want to learn how to use the tools, we'll have you automate that there. Did I hear that right? You're, you're sort of making decisions about what things will be developed even by citizen developers. >>Let me, Do you wanna talk to them about governance? Yeah, absolutely. >>Yeah, so I think we started out with assistant development program, obviously the huge success, right? Last year we're also here at the Cubes. We're very happy to be back again. But I think a lot, a lot had changed and we've grown a lot since last year. One, I have the joy being a part of this team. And then the other thing is that we really expanded and implemented an automation operating model that I mentioned briefly just earlier. So what that enabled us to do is to unite developers from five continents together organically and we're now able to tap into their talent at a global scale. So we are really using this operating model to grow our automation practice in a scalable and also controlled manner. Okay. What I mean by that is that these developer originally were sitting in 18 plus markets, right? There's not much communication collaboration between them. >>And then we went in and bridged them together. What happened is that originally they were only delivering projects and use cases within their region and sometimes these use cases could be very, very much, you know, small scale and not really maximizing their talent. What we are now able to do is tap into a global automation pipeline. So we connecting these highly skilled people to the pipeline elsewhere, the use cases elsewhere that might not be within their regions because one of our focus, a lot of change I mentioned, right? One thing that will never change with our team, it's used automation to elevate people's potential. Now it's really a win-win situation cuz we are connecting the use cases from different pipelines. So the business is happy cuz we are delivering these high scalable solutions. We also utilizing these developers and they're happy because their skills are being maximized and then at the same time growing our automation program. So then that way the citizen development program so that the lower complexities projects are being delivered at a local level and we are able to innovate at a local level. >>I, I have so many questions flow based on what you just said. It's blowing my mind >>Here. It's a whole cycle. >>So let me start with how do you, you know, one of the, one of the concerns I had initially with RPA, cuz just you're talking about some very narrow use cases and your goal is to expand that to realize the potential of each individual, right? But early days I saw a lot of what I call paving the cow path, taking a process that was not a great process and then automating it, right? And that was limiting the potential. So how do you guys prioritize which processes to focus on and maybe which processes should be rethought, >>Right? Exactly. A lot of time when we do automation, right, we talk about innovations and all that stuff, but innovation doesn't happen with the same people sitting in the same room doing the same thing. So what we are doing now, able to connect all these people, different developers from different groups, we really bring the diversity together. That's diversity D diverse diversity in the mindset, diversity in the skill. So what are we really able to do and we see how we tackle this problem is to, and that's a problem for a lot of business out there is the short-termism. So there's something, what we do is that we take two approaches. One, before we, you know, for example, when we used to receive a use case, right? Maybe it's for the China market involving a specific tool and we just go right into development and start coding and all that good stuff, which is great. >>But what we do with this automation framework, which we think it's a really great service for any company out there that want to grow and mature their automation practice, it's to take a step back, think about, okay, so the China market would be beneficial from this automation. Can we also look at the Philippine market? Can we also look at the Thailand market? Because we also know that they have similar processes and similar auto tools that they use. So we are really able to make our automation in a more meaningful way by scaling a project just beyond one market. Now it's impacting the entire region and benefiting people in the entire region. That is what we say, you know, putting automation for good and then that's what we talked about at dsu, Teaming without limits. And that's a, so >>By taking, we wanna make sure that we're really like taking a step back, connecting all of the dots, building the one thing the right way, the first time. Exactly. And what's really integral into being able to have that transparency, that visibility is that now we're all working on the same platform. So you know, Brian spoke to you last year about our migration into automation cloud, having everything that single pipeline in the cloud. Anybody at DSU can often join the automation community and get access to automation hub, see what's out there, submit their own ideas, use the launchpad to go and take training. Yeah. And get started on their own automation journey as a citizen developer and you know, see the different paths that are available to them from that one central space. >>So by taking us a breath, stepping back, pausing just a bit, the business impact at the tail end is much, much higher. Now you start in 2017 really before you UI path made it's big enterprise play, it acquired process gold, you know, cloud elements now most recently referenced some others. How much of what you guys are, are, are doing is platform versus kind of the initial sort of robot installation? Yeah, >>I mean platforms power people and that's what we're here to do as the global automation team. Whether it's powering the citizen developers, the professional developers, anybody who's interacting with our automations at dsu, we wanna make sure that we're connecting the docs for them on a platform basis so that developers can develop and they don't need to develop those simple use cases that could be done by a citizen developer. You know, they're super smart technical people, they wanna do the cool shit with the new stuff. They wanna branch into, you know, using AI center and doing document understanding. That's, you know, the nature of human curiosity. Citizen developers, they're thrilled that we're making an investment to upscale them, to give them a new capability so that they can automate their own work. And they don't, they, they're the process experts. They don't need to spend a month talking to us when they could spend that time taking the training, learning how to create something themselves. >>How, how much sort of use case runway when you guys step back and look at your business, do you see a limit to the use cases? I mean where are you, if you had on a spectrum of, you know, maturity, how much more opportunity is there for DSU to automate? >>There's so much I think the, you feel >>Like it's limitless? >>No, I absolutely feel like it's limitless because there one thing, it's, there's the use cases and I think it's all about connecting the talent and making sure that something we do really, you know, making sure that we deliver these use cases, invest the time in our people so we make sure our professional developers part of our team spending 10 to 20% of the time to do learning and development because only limitless if our people are getting the latest and the greatest technology and we want to invest the time and we see this as an investment in the people making sure that we deliver the promise of putting people first. And the second thing, it's also investment in our company's growth. And that's a long term goal. And overcoming just focusing on things our short term. So that is something we really focus to do. And not only the use cases we are doing what we are doing as an operating model for automation. That is also something that we really value because then this is a kind of a playbook and a success model for many companies out there to grow their automation practice. So that's another angle that we are also focusing >>On. Well that, that's a relief because you guys are both seem really cool and, and I'm sitting here thinking they don't realize they're working themselves out of a job once they get everything automated, what are they gonna do? Right? But, but so, so it sounds like it's a never ending process, but because you guys are, are such a large global organization, it seems like you might have a luxury of being able to benchmark automations from one region and then benchmark them against other regions that aren't using that automation to be able to see very, very quickly not only realize ROI really quickly from the region where it's been implemented, but to be able to compare it to almost a control. Is that, is that part of your process? Yeah, >>Absolutely. Because we are such a global brand and with the automation, automation operating model, what we are able to do, not only focusing on the talent and the people, but also focusing on the infrastructure. So for example, right, maybe there's a first use case developing in Argentina and they have never done these automation before. And when they go to their security team and asking for an Okta bypass service account and the security team Argentina, like we never heard of automation, we don't know what UiPath is, why would I give you a service account for good reason, right? They're doing their job right. But what we able to do with automation model, it's to establish trust between the developers and the security team. So now we have a set up standing infrastructure that we are ready to go whenever an automation's ready to deploy and we're able to get the set up standing infrastructure because we have the governance to make sure the quality would delivered and making sure anything that we deployed, automation that we deploy are developed and governed by the best practice. So that's how we able to kind of get this automation expand globally in a very control and scalable manner because the people that we have build a relationship with. What are >>The governors to how fast you can adopt? Is it just expertise or bandwidth of that expertise or what's the bottleneck? >>Yeah, >>If >>You wanna talk more about, >>So in terms of the pipeline, we really wanna make sure that we are taking that step back and instead of just going, let's develop, develop, develop, here are the requirements like get started and go, we've prove the value of automation at Densu. We wanna make sure we are taking that step back and observing the pipeline. And it's, it's up to us to work with the business to really establish their priorities and the priorities. It's a, it's a big global organization. There might be different priorities in APAC than there are in EM for a good reason. APAC may not be adopted on the same, you know, e r P system for example. So they might have those smaller scale ROI use cases, but that's where we wanna work with them to identify, you know, maybe this is a legitimate need, the ROI is not there, let's upscale some citizen developers so that they can start, you know, working for themselves and get those results faster for those simpler use cases. >>Does, does the funding come from the line of business or IT or a combination? I mean there are obviously budget constraints are very concerned about the macro and the recession. You guys have some global brands, you know, as, as things ebb and flow in the economy, you're competing with other budgets. But where are the budgets coming from inside of dsu? Is it the business, is it the tech >>Group? Yeah, we really consider our automation group is the cause of doing business because we are here connecting people with bridging people together and really elevating. And the reason why we structure it that way, it's people, we do automation at dsu not to reduce head count, not to, you know, not, not just those matrix number that we measure, but really it's to giving time back to the people, giving time back to our business. So then that way they can focus on their wellbeing and that way they can focus on the work-life balance, right? So that's what we say. We are forced for good and by using automation for good as one really great example. So I think because of this agenda and because DSU do prioritize people, you know, so that's why we're getting the funding, we're getting the budget and we are seeing as a cause of doing business. So then we can get these time back using innovation to make people more fulfilling and applying automation in meaningful ways. >>Kate and Flo, congratulations. Your energy is palpable and really great success, wonderful story. Really appreciate you sharing. Thank you so >>Much for having us today. >>You're very welcome. All keep it right there. Dave Nicholson and Dave Ante. We're live from UI path forward at five from Las Vegas. We're in the Venetian Consent Convention Center. Will be right back, right for the short break.

>>The Cube Presents UI Path Forward five. Brought to you by UI Path, >>Everybody. We're back in Las Vegas. The cube's coverage we're day one at UI Path forward. Five. Pascal Borne is here. He's an expert and bestselling author in the topic of AI and automation and the book Intelligent Automation. Welcome to the world of Hyper Automation, the first book on the topic. And of course, Ray Wong is back on the cube. He's the founder, chairman and principal analyst, Constellation Reese, also bestselling author of Everybody Wants To Rule the World. Guys, thanks so much for coming on The Cubes. Always a pleasure. Ray Pascal, First time on the Cube, I believe. >>Yes, thank you. Thanks for the invitation. Thank you. >>So what is artificial about artificial intelligence, >>For sure, not people. >>So, okay, so you guys are both speaking at the conference, Ray today. I think you're interviewing the co CEOs. What do you make of that? What's, what are you gonna, what are you gonna probe with these guys? Like, how they're gonna divide their divide and conquer, and why do you think the, the company Danielle in particular, decided to bring in Rob Sland? >>Well, you know what I mean, Like, you know, these companies are now at a different stage of growth, right? There's that early battle between RPA vendors. Now we're actually talking something different, right? We're talking about where does automation go? How do we get the decisioning? What's the next best action? That's gonna be the next step. And to take where UI path is today to somewhere else, You really want someone with that enterprise cred and experience the sales motions, the packages, the partnership capabilities, and who else better than Roblin? He, that's, he's done, he can do that in his sleep, but now he's gotta do that in a new space, taking whole category to another level. Now, Daniel on the other hand, right, I mean, he's the visionary founder. He put this thing from nothing to where he is today, right? I mean, at that point you want your founder thinking about the next set of ideas, right? So you get this interesting dynamic that we've seen for a while with co CEOs, those that are doing the operations, getting the stuff out the door, and then letting the founders get a chance to go back and rethink, take a look at the perspective, and hopefully get a chance to build the next idea or take the next idea back into the organization. >>Right? Very well said. Pascal, why did you write your book on intelligent automation and, and hyper automation, and what's changed since you've written that book? >>So, I, I wrote this book, An Intelligent Automation, two years ago. At that time, it was really a new topic. It was really about the key, the, the key, the key content of the, of the book is really about combining different technologies to automate the most complex end to end business processes in companies. And when I say capabilities, it's, we, we hear a lot about up here, especially here, robotic process automation. But up here alone, if you just trying to transform a company with only up here, you just fall short. Okay? A lot of those processes need more than execution. They need language, they need the capacity to view, to see, they need the capacity to understand and to, and to create insights. So by combining process automation with ai, natural language processing, computer vision, you give this capability to create impact by automating end to end processes in companies. >>I, I like the test, what I hear in the keynote with independent experts like yourself. So we're hearing that that intelligent automation or automation is a fundamental component of digital transformation. Is it? Or is it more sort of a back office sort of hidden in inside plumbing Ray? What do you think? >>Well, you start by understanding what's going on in the process phase. And that's where you see discover become very important in that keynote, right? And that's where process mining's playing a role. Then you gotta automate stuff. But when you get to operations, that's really where the change is going to happen, right? We actually think that, you know, when you're doing the digital transformation pieces, right? Analytics, automation and AI are coming together to create a concept we call decision velocity. You and I make a quick decision, boom, how long does it take to get out? Management committee could free forever, right? A week, two months, never. But if you're thinking about competing with the automation, right? These decisions are actually being done a hundred times per second by machine, even a thousand times per second. That asymmetry is really what people are facing at the moment. >>And the companies that are gonna be able to do that and start automating decisions are gonna be operating at another level. Back to what Pascal's book talking about, right? And there are four questions everyone has to ask you, like, when do you fully intelligently automate? And that happens right in the background when you augment the machine with a human. So we can find why did you make an exception? Why did you break a roll? Why didn't you follow this protocol so we can get it down to a higher level confidence? When do you augment the human with the machine so we can give you the information so you can act quickly. And the last one is, when do you wanna insert a human in the process? That's gonna be the biggest question. Order to cash, incident or resolution, Hire to retire, procure to pay. It doesn't matter. When do you want to put a human in the process? When do you want a man in the middle, person in the middle? And more importantly, when do you want insert friction? >>So Pascal, you wrote your book in the middle of the, the pandemic. Yes. And, and so, you know, pre pandemic digital transformation was kind of a buzzword. A lot of people gave it lip service, eh, not on my watch, I don't have to worry about that. But then it became sort of, you're not a digital business, you're out of business. So, so what have you seen as the catalyst for adoption of automation? Was it the, the pandemic? Was it sort of good runway before that? What's changed? You know, pre isolation, post isolation economy. >>You, you make me think about a joke. Who, who did your best digital transformation over the last years? The ceo, C H R O, the Covid. >>It's a big record ball, right? Yeah. >>Right. And that's exactly true. You know, before pandemic digital transformation was a competitive advantage. >>Companies that went into it had an opportunity to get a bit better than their, their competitors during the pandemic. Things have changed completely. Companies that were not digitalized and automated could not survive. And we've seen so many companies just burning out and, and, and those companies that have been able to capitalize on intelligent automation, digital transformations during the pandemic have been able not only to survive, but to, to thrive, to really create their place on the market. So that's, that has been a catalyst, definitely a catalyst for that. That explains the success of the book, basically. Yeah. >>Okay. Okay. >>So you're familiar with the concept of Stew the food, right? So Stew by definition is something that's delicious to eat. Stew isn't simply taking one of every ingredient from the pantry and throwing it in the pot and stirring it around. When we start talking about intelligent automation, artificial intelligence, augmented intelligence, it starts getting a bit overwhelming. My spy sense goes off and I start thinking, this sounds like mush. It doesn't sound like Stew. So I wanna hear from each of you, what is the methodical process that, that people need to go through when they're going through digital trans transmission, digital transformation, so that you get delicious stew instead of a mush that's just confused everything in your business. So you, Ray, you want, you want to, you wanna answer that first? >>Yeah. You know, I mean, we've been talking about digital transformation since 2010, right? And part of it was really getting the business model, right? What are you trying to achieve? Is that a new type of offering? Are you changing the way you monetize something? Are you taking existing process and applying it to a new set of technologies? And what do you wanna accomplish, right? Once you start there, then it becomes a whole lot of operational stuff. And it's more than st right? I mean, it, it could be like, well, I can't use those words there. But the point being is it could be a complete like, operational exercise. It could be a complete revenue exercise, it could be a regulatory exercise, it could be something about where you want to take growth into the next level. And each one of those processes, some of it is automation, right? There's a big component of it today. But most of it is really rethinking about what you want things to do, right? How do you actually make things to be successful, right? Do I reorganize a process? Do I insert a place to do monetization? Where do I put engagement in place? How do I collect data along the way so I can build better feedback loop? What can I do to build the business graph so that I have that knowledge for the future so I can go forward doing that so I can be successful. >>The Pascal should, should, should the directive be first ia, then ai? Or are these, are these things going to happen in parallel naturally? What's your position on that? Is it first, >>So it, so, >>So AI is part of IA because that's, it's, it's part of the big umbrella. And very often I got the question. So how do you differentiate AI in, I a, I like to say that AI is only the brain. So think of ai cuz I'm consider, I consider AI as machine learning, Okay? Think of AI in a, like a brain near jar that only can think, create, insight, learn, but doesn't do anything, doesn't have any arms, doesn't have any eyes, doesn't not have any mouth and ears can't talk, can't understand with ia, you, you give those capabilities to ai. You, you basically, you create a cap, the capability, technological capability that is able to do more than just thinking, learning and, and create insight, but also acting, speaking, understanding the environment, viewing it, interacting with it. So basically performing these, those end to end processes that are performed currently by people in companies. >>Yeah, we're gonna get to a point where we get to what we call a dynamic scenario generation. You're talking to me, you get excited, well, I changed the story because something else shows up, or you're talking to me and you're really upset. We're gonna have to actually ch, you know, address that issue right away. Well, we want the ability to have that sense and respond capability so that the next best action is served. So your data, your process, the journey, all the analytics on the top end, that's all gonna be served up and changed along the way. As we go from 2D journeys to 3D scenarios in the metaverse, if we think about what happens from a decentralized world to decentralized, and we think about what's happening from web two to web three, we're gonna make those types of shifts so that things are moving along. Everything's a choose your end venture journey. >>So I hope I remember this correctly from your book. You talked about disruption scenarios within industries and within companies. And I go back to the early days of, of our industry and East coast Prime, Wang, dg, they're all gone. And then, but, but you look at companies like Microsoft, you know, they were, they were able to, you know, get through that novel. Yeah. Ibm, you know, I call it survived. Intel is now going through their, you know, their challenge. So, so maybe it's inevitable, but how do you see the future in terms of disruption with an industry, Forget our industry for a second, all industry across, whether it's healthcare, financial services, manufacturing, automobiles, et cetera. How do you see the disruption scenario? I'm pretty sure you talked about this in your book, it's been a while since I read it, but I wonder if you could talk about that disruption scenario and, and the role that automation is going to play, either as the disruptor or as the protector of the incumbents. >>Let's take healthcare and auto as an example. Healthcare is a great example. If we think about what's going on, not enough nurses, massive shortage, right? What are we doing at the moment? We're setting five foot nine robots to do non-patient care. We're trying to capture enough information off, you know, patient analytics like this watch is gonna capture vitals from a going forward. We're doing a lot what we can do in the ambient level so that information and data is automatically captured and decisions are being rendered against that. Maybe you're gonna change your diet along the way, maybe you're gonna walk an extra 10 minutes. All those things are gonna be provided in that level of automation. Take the car business. It's not about selling cars. Tesla's a great example. We talk about this all the time. What Tesla's doing, they're basically gonna be an insurance company with all the data they have. They have better data than the insurance companies. They can do better underwriting, they've got better mapping information and insights they can actually suggest next best action do collision avoidance, right? Those are all the things that are actually happening today. And automation plays a big role, not just in the collection of that, that information insight, but also in the ability to make recommendations, to do predictions and to help you prevent things from going wrong. >>So, you know, it's interesting. It's like you talk about Tesla as the, the disrupting the insurance companies. It's almost like the over the top vendors have all the data relative to the telcos and mopped them up for lunch. Pascal, I wanna ask you, you know, the topic of future of work kind of was a bromide before, but, but now I feel like, you know, post pandemic, it, it actually has substance. How do you see the future of work? Can you even summarize what it's gonna look like? It's, it's, Or are we here? >>It's, yeah, it's, and definitely it's, it's more and more important topic currently. And you, you all heard about the great resignation and how employee experience is more and more important for companies according to have a business review. The companies that take care of their employee experience are four times more profitable that those that don't. So it's a, it's a, it's an issue for CEOs and, and shareholders. Now, how do we get there? How, how do we, how do we improve the, the quality of the employee experience, understanding the people, getting information from them, educating them. I'm talking about educating them on those new technologies and how they can benefit from those empowering them. And, and I think we've talked a lot about this, about the democratization local type of, of technologies that democratize the access to those technologies. Everyone can be empowered today to change their work, improve their work, and finally, incentivization. I think it's a very important point where companies that, yeah, I >>Give that. What's gonna be the key message of your talk tomorrow. Give us the bumper sticker, >>If you will. Oh, I'm gonna talk, It's a little bit different. I'm gonna talk for the IT community in this, in the context of the IT summit. And I'm gonna talk about the future of intelligent automation. So basically how new technologies will impact beyond what we see today, The future of work. >>Well, I always love having you on the cube, so articulate and, and and crisp. What's, what's exciting you these days, you know, in your world, I know you're traveling around a lot, but what's, what's hot? >>Yeah, I think one of the coolest thing that's going on right now is the fact that we're trying to figure out do we go to work or do we not go to work? Back to your other point, I mean, I don't know, work, work is, I mean, for me, work has been everywhere, right? And we're starting to figure out what that means. I think the second thing though is this notion around mission and purpose. And everyone's trying to figure out what does that mean for themselves? And that's really, I don't know if it's a great, great resignation. We call it great refactoring, right? Where you work, when you work, how we work, why you work, that's changing. But more importantly, the business models are changing. The monetization models are changing macro dynamics that are happening. Us versus China, G seven versus bricks, right? War on the dollar. All these things are happening around us at this moment and, and I think it's gonna really reshape us the way that we came out of the seventies into the eighties. >>Guys, always a pleasure having folks like yourself on, Thank you, Pascal. Been great to see you again. All right, Dave Nicholson, Dave Ante, keep it right there. Forward five from Las Vegas. You're watching the cue.