produced from the cube studios this is strong by science in-depth conversations about science based training sports performance and all things health and wellness here's your host max smart [Music] [Applause] [Music] all right thank you guys tune in today I have the one and only Dean of big data the man the myth the legend bill Schwarz oh also my dad is the CTO of Hitachi van Tara and IOC in analytics he has a very interesting background because he is the well he's known as the Dean of big data but also the king of the court and all things basketball related when it comes to our household and unlike most people in the data world and I want to say most as an umbrella term but a some big bill has an illustrious sports career playing at Coe College the Harvard of the Midwest my alma mater as well but I think having that background of not just being computer science but where you have multiple disciplines involved when it comes to your jazz career you had basketball career you have obviously the career Iran now all that plays a huge role in being able to interpret and take multiple domains and put it into one so thank you for being here dad yeah thanks max that's a great introduction I rep reciate that no it's it's wonderful to have you and for our listeners who are not aware bill is referring him is Bill like my dad but I call my dad the whole time is gonna drive me crazy bill has a mind that thinks not like most so he he sees things he thinks about it not just in terms of the single I guess trajectory that could be taken but the multiple domains that can go so both vertically and horizontally and when we talk about data data is something so commonly brought up in sports so commonly drop in performance and athletic development big data is probably one of the biggest guess catchphrases or hot words or sayings that people have nowadays but doesn't always have a lot of meaning to it because a lot of times we get the word big data and then we don't have action out of big data and bill specialty is not just big data but it's giving action out of big data with that going forward I think a lot of this talk to be talking about how to utilize Big Data how do you guys data in general how to organize it how to put yourself in a situation to get actionable insights and so just to start it off Becky talked a little bit on your background some of the things you've done and how you develop the insights that you have thanks max I have kind of a very nos a deep background but I've been doing data analytics a long time and I was very fortunate one of those you know Forrest Gump moments in life where in the late 1980s I was involved in a project at Procter & Gamble I ran the project where we brought in Walmart's point of sales data for the first time into a what we would now call a data warehouse and for many of this became the launching point of the data warehouse bi marketplace and we can trace the effect the origins of many of the BI players to that project at Procter & Gamble in 87 and 88 and I spent a big chunk of my life just a big believer in business intelligence and data warehousing and trying to amass data together and trying to use that data to report on what's going on and writing insights and I did that for 20 25 years of my life until as you probably remember max I was recruited out Business Objects where I was the vice president of analytic applications I was recruited out of there by Yahoo and Yahoo had a very interesting problem which is they needed to build analytics for their advertisers to help those advertisers to optimize or spend across the Yahoo ad network and what I learned there in fact what I unlearned there was that everything that I had learned about bi and data warehouse and how you constructed data warehouses how you were so schema centric how everything was evolved around tabular data at Yahoo there was an entirely different approach the of my first introduction to Hadoop and the concept of a data Lake that was my first real introduction into data science and how to do predictive analytics and prescriptive analytics and in fact it was it was such a huge change for me that I was I was asked to come back to the TD WI data world Institute right was teaching for many years and I was asked to do a keynote after being at Yahoo for a year or so to share sort of what were the observations what did I learn and I remember I stood up there in front of about 600 people and I started my presentation by saying everything I've taught you the past 20 years is wrong and it was well I didn't get invited back for 10 years so that probably tells you something but it was really about unlearning a lot about what I had learned before and probably max one of the things that was most one of the aha moments for me was bi was very focused on understanding the questions that people were trying to ask an answer davus science is about us to understand the decisions they're trying to take action on questions by their very nature our informative but decisions are actionable and so what we did at Yahoo in order to really drive the help our advertisers optimize your spend across the Yahoo ad network is we focus on identifying the decisions the media planners and buyers and the campaign managers had to make around running a campaign know what what how much money to allocate to what sides how much how many conversions do I want how many impressions do I want so all the decisions we built predictive analytics around so that we can deliver prescriptive actions to these two classes of stakeholders the media planners and buyers and the campaign managers who had no aspirations about being analysts they're trying to be the best digital marketing executives or you know or people they could possibly be they didn't want to be analysts so and that sort of leads me to where I am today and my my teaching my books my blogs everything I do is very much around how do we take data and analytics and help organizations become more effective so everything I've done since then the books I've written the teaching I do with University of San Francisco and next week at the National University of Ireland and Galway and all the clients I work with is really how do we take data and analytics and help organizations become more effective at driving the decisions that optimize their business and their operational models it's really about decisions and how do we leverage data and analytics to drive those decisions so what would how would you define the difference between a question that someone's trying to answer versus a decision but they're trying to be better informed on so here's what I'd put it I call it the Sam test I am and that is it strategic is it actionable is it material and so you can ask questions that are provocative but you might not fast questions that are strategic to the problems you're trying to solve you may not be able to ask questions that are actionable in a sense you know what to do and you don't necessarily ask questions that are material in the sense that the value of that question is greater than the cost of answering that question right and so if I think about the Sam test when I apply it to data science and decisions when I start mining the data so I know what decisions are most important I'm going through a process to identify to validate the value and prioritize those decisions right I understand what decisions are most important now when I start to dig through the data all this structured unstructured data across a number different data sources I'm looking for I'm trying to codify patterns and relationships buried in that data and I'm applying the Sam test is that against those insights is it strategic to the problem I'm trying to solve can I actually act on it and is it material in the sense that it's it's it's more valuable to act than it is to create the action around it so that's the to me that big difference is by their very nature decisions are actually trying to make a decision I'm going to take an action questions by their nature are informative interesting they could be very provocative you know questions have an important role but ultimately questions do not necessarily lead to actions so if I'm a a sport coach I'm writing a professional basketball team some of the decisions I'm trying to make are I'm deciding on what program best develops my players what metrics will help me decide who the best prospect is is that the right way of looking at it yeah so we did an exercise at at USF too to have the students go through an exercise - what question what decisions does Steve Kerr need to make over the next two games he's playing right and we go through an exercise of the identifying especially in game decisions exercise routes oh no how often are you gonna play somebody no how long are they gonna play what are the right combinations what are the kind of offensive plays that you're gonna try to run so there's a know a bunch of decisions that Steve Kerr is coach of the Warriors for example needs to make in the game to not only try to win the game but to also minimize wear and tear on his players and by the way that's a really good point to think about the decisions good decisions are always a conflict of other ideas right win the game while minimizing wear and tear on my players right there's there are there are all the important decisions in life have two three or four different variables that may not be exactly the same which is by this is where data science comes in the data science is going to look across those three or four very other metrics against what you're going to measure success and try to figure out what's the right balance of those given the situation I'm in so if going back to the decision about about playing time well think about all the data you might want to look at in order to optimize that so when's the next game how far are they in this in this in the season where do they currently sit ranking wise how many minutes per game has player X been playing looking over the past few years what's there you know what's their maximum point so there's there's a there's not a lot of decisions that people are trying to make and by the way the beauty of the decisions is the decisions really haven't changed in years right what's changed is not the decisions it's the answers and the answers have changed because we have this great bound of data available to us in game performance health data you know all DNA data all kinds of other data and then we have all these great advanced analytic techniques now neural networks and unstructured supervised machine learning on right all this great technology now that can help us to uncover those relationships and patterns that are buried in the data that we can use to help individualize those decisions one last point there the point there to me at the end when when people talk about Big Data they get fixated on the big part the volume part it's not the volume of big data that I'm going to monetize it's the granularity and what I mean by that is I now have the ability to build very detailed profiles going back to our basketball example I can build a very detailed performance profile on every one of my players so for every one of the players on the Warriors team I can build a very detailed profile it the details out you know what's their optimal playing time you know how much time should they spend before a break on the feet on the on the on the court right what are the right combinations of players in order to generate the most offense or the best defense I can build these very detailed individual profiles and then I can start mission together to find the right combination so when we talk about big it's not the volume it's interesting it's the granularity gotcha and what's interesting from my world is so when you're dealing with marketing and business a lot of that when you're developing whether it be a company that you're trying to find more out about your customers or your startup trying to learn about what product you should develop there's tons of unknowns and a lot of big data from my understanding it can help you better understand some patterns within customers how to market you know in your book you talk about oh we need to increase sales at Chipotle because we understand X Y & Z our current around us now in the sports science world we have our friend called science and science has helped us early identify certain metrics that are very important and correlated to different physiological outcomes so it almost gives us a shortcut because in the big data world especially when you're dealing with the data that you guys are dealing with and trying to understand customer decisions each customer is individual and you're trying to compile all together to find patterns no one's doing science on that right it's not like a lab work where someone is understanding muscle protein synthesis and the amount of nutrients you need to recover from it so in my position I have all these pillars that maybe exist already where I can begin my search there's still a bunch of unknowns with that kind of environment do you take a different approach or do you still go with the I guess large encompassing and collect everything you can and siphon after maybe I'm totally wrong I'll let you take it away no that's it's a it's a good question and what's interesting about that max is that the human body is governed by a series of laws we'll say in each me see ology and the things you've talked about physics they have laws humans as buyers you know shoppers travelers we have propensity x' we don't have laws right I have a propensity that I'm gonna try to fly United because I get easier upgrades but I might fly you know Southwest because of schedule or convenience right I have propensity x' I don't have laws so you have laws that work to your advantage what's interesting about laws that they start going into the world of IOT and this concept called digital twins they're governed by laws of physics I have a compressor or a chiller or an engine and it's got a bunch of components in it that have been engineered together and I can actually apply the laws I can actually run simulations against my digital twins to understand exactly when is something likely to break what's the remaining useful life in that product what's the severity of the the maintenance I need to do on that so the human body unlike the human psyche is governed by laws human behaviors are really hard right and we move the las vegas is built on the fact that human behaviors are so flawed but body mate but bat body physics like the physics that run these devices you can actually build models and one simulation to figure out exactly how you know what's the wear and tear and what's the extensibility of what you can operate in gotcha yeah so that's when from our world you start looking at subsystems and you say okay this is your muscular system this is your autonomic nervous system this is your central nervous system these are ways that we can begin to measure it and then we can wrote a blog on this that's a stress response model where you understand these systems and their inferences for the most part and then you apply a stress and you see how the body responds and even you determine okay well if I know the body I can only respond in a certain number of ways it's either compensatory it's gonna be you know returning to baseline and by the mal adaptation but there's only so many ways when you look at a cell at the individual level that that cell can actually respond and it's the aggregation of all these cellular responses that end up and manifest in a change in a subsystem and that subsystem can be measured inferential II through certain technology that we have but I also think at the same time we make a huge leap and that leap is the word inference right we're making an assumption and sometimes those assumptions are very dangerous and they lead to because that assumptions unknown and we're wrong on it then we kind of sway and missed a little bit on our whole projection so I like the idea of looking at patterns and look at the probabilistic nature of it and I'm actually kind of recently change my view a little bit from my room first I talked about this I was much more hardwired and laws but I think it's a law but maybe a law with some level of variation or standard deviation and it we have guardrails instead so that's kind of how I think about it personally is that something that you say that's on the right track for that or how would you approach it yeah actually there's a lot of similarities max so your description of the human body made up of subsystems when we talk to organizations about things like smart cities or smart malls or smart hospitals a smart city is comprised of a it's made up of a series of subsystems right I've got subsystems regarding water and wastewater traffic safety you know local development things like this look there's a bunch of subsystems that make a city work and each of those subsystems is comprised of a series of decisions or clusters of decisions with equal use cases around what you're trying to optimize so if I'm trying to improve traffic flow if one of my subsystems is practically flow there are a bunch of use cases there about where do I do maintenance where do I expand the roads you know where do I put HOV lanes right so and so you start taking apart the smart city into the subsystems and then know the subsystems are comprised of use cases that puts you into really good position now here's something we did recently with a client who is trying to think about building the theme park of the future and how do we make certain that we really have a holistic view of the use cases that I need to go after it's really easy to identify the use cases within your own four walls but digital transformation in particular happens outside the four walls of an organization and so what we what we're doing is a process where we're building journey maps for all their key stakeholders so you've got a journey map for a customer you have a journey map for operations you have a journey map for partners and such so you you build these journey maps and you start thinking about for example I'm a theme park and at some point in time my guest / customer is going to have a pity they want to go do something you want to go on vacation at that point in time that theme park is competing against not only all the other theme parks but it's competing against major league baseball who's got things it's competing against you know going to the beach in Sanibel Island just hanging around right there they're competing at that point and if they only start engaging the customer when the customers actually contacted them they must a huge part of the market they made you miss a huge chance to influence that person's agenda and so one of the things that think about I don't know how this applies to your space max but as we started thinking about smart entities we use design thinking and customer journey match there's a way to make certain that we're not fooling ourselves by only looking within the four walls of our organization that we're knocking those walls down making them very forest and we're looking at what happens before somebody engages it with us and even afterwards so again going back to the theme park example once they leave the theme park they're probably posting on social media what kind of fun they had or fun they didn't have they're probably making plans for next year they're talking to friends and other things so there's there's a bunch of stuff we're gonna call it afterglow that happens after event that you want to make certain that you're in part of influencing that so again I don't know how when you combined the data science of use cases and decisions with design thinking of journey Maps what that might mean to do that your business but for us in thinking about smart cities it's opened up all kinds of possibilities and most importantly for our customers it's opened up all kinds of new areas where they can create new sources of value so anyone listening to this need to understand that when the word client or customer is used it can be substituted for athlete and what I think is really important is that when we hear you talk about your the the amount of infrastructure you do for an idea when you approach a situation is something that sports science for in my opinion especially across multiple domains it's truly lacking what happens is we get a piece of technology and someone says go do science while you're taking the approach of let's actually think out what we're doing beforehand let's determine our key performance indicators let's understand maybe the journey that this piece of technology is going to take with the athlete or how the athletes going to interact with this piece of technology throughout their four years if you're in the private sector right that afterglow effect might be something that you refer to as a client retention and their ability to come back over and over and spread your own word for you if you're in the sector with student athletes maybe it's those athletes talking highly about your program to help with recruiting and understanding that developing athletes is going to help you know make that college more enticing to go to or that program or that organization but what really stood out was the fact that you have this infrastructure built beforehand and the example I give I spoke with a good number of organizations and teams about data utilization is that if if you're to all of a sudden be dropped in the middle of the woods and someone says go build a cabin now how was it a giant forest I could use as much wood as I want I could just keep chopping down trees until I had something that had with a shelter of some sort right even I could probably do that well if someone said you know what you have three trees to cut down to make a cabin you could become very efficient and you're going to think about each chop in each piece of wood and how it's going to be used and your interaction with that wood and conjunction with that woods interaction with yourself and so when we start looking at athlete development and we're looking at client retention or we're looking at general health and wellness it's not just oh this is a great idea right we want to make the world's greatest theme park and we want to make the world's greatest training facility but what infrastructure and steps you need to take and you said stakeholders so what individuals am i working with am I talking with the physical therapist am i talking with the athletic trainer am I talking with the skill coach how does the skill coach want the data presented to them maybe that's different than how the athletic trainer is going to have a day to present it to them maybe the sport coach doesn't want to see the data unless something a red flag comes up so now you have all these different entities just like how you're talking about developing this customer journey throughout the theme park and making sure that they have a you know an experience that's memorable and causes an afterglow and really gives that experience meaning how can we now take data and apply it in the same way so we get the most value like you said on the granular aspect of data and really turn that into something valuable max you said something really important and one of the things that let me share one of many horror stories that that that comes up in my daily life which is somebody walking up to me and saying hey I got a client here's their data you know go do some science on it like well well what the heck right so when we created this thing called the hypothesis development canvas our sales teams hate it or do the time our data science teams love it because we do all this pre work we just say we make sure we understand the problem we're going after the decision they're trying to make the KPI is it's what you're going to measure success in progress what are they the operational and financial business benefits what are the data sources we want to consider here's something by the way that's it's important that maybe I wish Boeing would have thought more about which is what are the costs of false positives and false negatives right do you really understand where your risks points are and the reason why false positive and false negatives are really important in data science because data size is making predictions and by virtue of making predictions we are never 100% certain that's right or not predictions hath me built on I'm good enough well when is good enough good enough and a lot of that determination as to when is good enough good enough is really around the cost of false positives and false negatives think about a professional athlete like the false the you know the ramifications of overtraining professional athlete like a Kevin Durant or Steph Curry and they're out for the playoffs as huge financial implications them personally and for the organization so you really need to make sure you understand exactly what's the cost of being wrong and so this hypothesis development canvas is we do a lot of this work before we ever put science to the data that yeah it's it's something that's lacking across not just sports science but many fields and what I mean by that is especially you referred to the hypothesis canvas it's a piece of paper that provides a common language right it's you can sit it out before and for listeners who aren't aware a hypothesis canvas is something bill has worked and developed with his team and it's about 13 different squares and boxes and you can manipulate it based on your own profession and what you're diving into but essentially it goes through the infrastructure that you need to have setup in order for this hypothesis or idea or decision to actually be worth a damn and what I mean by that is that so many times and I hate this but I'm gonna go in a little bit of a rant and I apologize that people think oh I get an idea and they think Thomas Edison all son just had an idea and he made a light bulb Thomas Edison's famous for saying you know I did you know make a light bulb I learned was a 9000 ways to not make a light bulb and what I mean by that is he set an environment that allowed for failure and allowed for learning but what happens often people think oh I have an idea they think the idea comes not just you know in a flash because it always doesn't it might come from some research but they also believe that it comes with legs and it comes with the infrastructure supported around it that's kind of the same way that I see a lot of the data aspect going in regards to our field is that we did an idea we immediately implement and we hope it works as opposed to set up a learning environment that allows you to go okay here's what I think might happen here's my hypothesis here's I'm going to apply it and now if I fail because I have the infrastructure pre mapped out I can look at my infrastructure and say you know what that support beam or that individual box itself was the weak link and we made a mistake here but we can go back and fix it

>> Hello everyone. Welcome to theCUBE's coverage of International Women's Day. I'm John Furrier, host of theCUBE been profiling the leaders in the technology world, women in technology from developers to the boardroom, everything in between. We have two great guests promoting in from Malaysia. Nancy Wang is the general manager, also CUBE alumni from AWS Data Protection, and founder and board chair of Advancing Women in Tech, awit.org. And of course Kate Watts who's the executive director of Advancing Women in Tech.org. So it's awit.org. Nancy, Kate, thanks for coming all the way across remotely from Malaysia. >> Of course, we're coming to you as fast as our internet bandwidth will allow us. And you know, I'm just thrilled today that you get to see a whole nother aspect of my life, right? Because typically we talk about AWS, and here we're talking about a topic near and dear to my heart. >> Well, Nancy, I love the fact that you're spending a lot of time taking the empowerment to go out and help the industries and helping with the advancement of women in tech. Kate, the executive director it's a 501C3, it's nonprofit, dedicating to accelerating the careers of women in groups in tech. Can you talk about the organization? >> Yes, I can. So Advancing Women in Tech was founded in 2017 in order to fix some of the pathway problems that we're seeing on the rise to leadership in the industry. And so we specifically focus on supporting mid-level women in technical roles, get into higher positions. We do that in a few different ways through mentorship programs through building technical skills and by connecting people to a supportive community. So you have your peer network and then a vertical sort of relationships to help you navigate the next steps in your career. So to date we've served about 40,000 individuals globally and we're just looking to expand our reach and impact and be able to better support women in the industry. >> Nancy, talk about the creation, the origination story. How'd this all come together? Obviously the momentum, everyone in the industry's been focused on this for a long time. Where did AWIT come from? Advancing Women in Technology, that's the acronym. Advancing Women in Technology.org, where'd it come from? What's the origination story? >> Yeah, so AWIT really originated from this desire that I had, to Kate's point around, well if you look around right and you know, don't take my word for it, right? Look at stats, look at news reports, or just frankly go on your LinkedIn and see how many women in underrepresented groups are in senior technical leadership roles right out in the companies whose names we all know. And so that was my case back in 2016. And so when I first got the idea and back then I was actually at Google, just another large tech company in the valley, right? It was about how do we get more role models, how we get more, for example, women into leadership roles so they can bring up the next generation, right? And so this is actually part of a longer speech that I'm about to give on Wednesday and part of the US State Department speaker program. In fact, that's why Kate and I are here in Malaysia right now is working with over 200 women entrepreneurs from all over in Southeast Asia, including Malaysia Philippines, Vietnam, Borneo, you know, so many countries where having more women entrepreneurs can help raise the GDP right, and that fits within our overall mission of getting more women into top leadership roles in tech. >> You know, I was talking about Teresa Carlson she came on the program as well for this year this next season we're going to do. And she mentioned the decision between the US progress and international. And she's saying as much as it's still bad numbers, it's worse than outside the United States and needs to get better. Can you comment on the global aspect? You brought that up. I think it's super important to highlight that it's just not one area, it's a global evolution. >> Absolutely, so let me start, and I'd love to actually have Kate talk about our current programs and all of the international groups that we're working with. So as Teresa aptly mentioned there is so much work to be done not just outside the US and North Americas where typically tech nonprofits will focus, but rather if you think about the one to end model, right? For example when I was doing the product market fit workshop for the US State Department I had women dialing in from rice fields, right? So let me just pause there for a moment. They were holding their cell phones up near towers near trees just so that they can get a few minutes of time with me to do a workshop and how to accelerate their business. So if you don't call that the desire to propel oneself or accelerate oneself, not sure what is, right. And so it's really that passion that drove me to spend the next week and a half here working with local entrepreneurs working with policy makers so we can take advantage and really leverage that passion that people have, right? To accelerate more business globally. And so that's why, you know Kate will be leading our contingent with the United Nations Women Group, right? That is focused on women's economic empowerment because that's super important, right? One aspect can be sure, getting more directors, you know vice presidents into companies like Google and Amazon. But another is also how do you encourage more women around the world to start businesses, right? To reach economic and freedom independence, right? To overcome some of the maybe social barriers to becoming a leader in their own country. >> Yes, and if I think about our own programs and our model of being very intentional about supporting the learning development and skills of women and members of underrepresented groups we focused very much on providing global access to a number of our programs. For instance, our product management certification on Coursera or engineering management our upcoming women founders accelerator. We provide both access that you can get from anywhere. And then also very intentional programming that connects people into the networks to be able to further their networks and what they've learned through the skills online, so. >> Yeah, and something Kate just told me recently is these courses that Kate's mentioning, right? She was instrumental in working with the American Council on Education and so that our learners can actually get up to six college credits for taking these courses on product management engineering management, on cloud product management. And most recently we had our first organic one of our very first organic testimonials was from a woman's tech bootcamp in Nigeria, right? So if you think about the worldwide impact of these upskilling courses where frankly in the US we might take for granted right around the world as I mentioned, there are women dialing in from rice patties from other, you know, for example, outside the, you know corporate buildings in order to access this content. >> Can you think about the idea of, oh sorry, go ahead. >> Go ahead, no, go ahead Kate. >> I was going to say, if you can't see it, you can't become it. And so we are very intentional about ensuring that we have we're spotlighting the expertise of women and we are broadcasting that everywhere so that anybody coming up can gain the skills and the networks to be able to succeed in this industry. >> We'll make sure we get those links so we can promote them. Obviously we feel the same way getting the word out. I think a couple things I'd like to ask you guys cause I think you hit a great point. One is the economic advantage the numbers prove that diverse teams perform better number one, that's clear. So good point there. But I want to get your thoughts on the entrepreneurial equation. You mentioned founders and startups and there's also different makeups in different countries. It's not like the big corporations sometimes it's smaller business in certain areas the different cultures have different business sizes and business types. How do you guys see that factoring in outside the United States, say the big tech companies? Okay, yeah. The easy lower the access to get in education than stay with them, in other countries is it the same or is it more diverse in terms of business? >> So what really actually got us started with the US State Department was around our work with women founders. And I love for Kate to actually share her experience working with AWS startups in that capacity. But frankly, you know, we looked at the content and the mentor programs that were providing women who wanted to be executives, you know, quickly realize a lot of those same skills such as finding customers, right? Scaling your product and building channels can also apply to women founders, not just executives. And so early supporters of our efforts from firms such as Moderna up in Seattle, Emergence Ventures, Decibel Ventures in, you know, the Bay Area and a few others that we're working with right now. Right, they believed in the mission and really helped us scale out what is now our existing platform and offerings for women founders. >> Those are great firms by the way. And they also are very founder friendly and also understand the global workforce. I mean, that's a whole nother dimension. Okay, what's your reaction to all that? >> Yes, we have been very intentional about taking the product expertise and the learnings of women and in our network, we first worked with AWS startups to support the development of the curriculum for the recent accelerator for women founders that was held last spring. And so we're able to support 25 founders and also brought in the expertise of about 20 or 30 women from Advancing Women in Tech to be able to be the lead instructors and mentors for that. And so we have really realized that with this network and this individual sort of focus on product expertise building strong teams, we can take that information and bring it to folks everywhere. And so there is very much the intentionality of allowing founders allowing individuals to take the lessons and bring it to their individual circumstances and the cultures in which they are operating. But the product sense is a skill that we can support the development of and we're proud to do so. >> That's awesome. Nancy, I want to ask you some never really talk about data storage and AWS cloud greatness and goodness, here's different and you also work full-time at AWS and you're the founder or the chairman of this great organization. How do you balance both and do you get, they're getting behind you on this, Amazon is getting behind you on this. >> Well, as I say it's always easier to negotiate on the way in. But jokes aside, I have to say the leadership has been tremendously supportive. If you think about, for example, my leaders Wayne Duso who's also been on the show multiple times, Bill Vaas who's also been on the show multiple times, you know they're both founders and also operators entrepreneurs at heart. So they understand that it is important, right? For all of us, it's really incumbent on all of us who are in positions to do so, to create a pathway for more people to be in leadership roles for more people to be successful entrepreneurs. So, no, I mean if you just looked at LinkedIn they're always uploading my vote so they reach to more audiences. And frankly they're rooting for us back home in the US while we're in Malaysia this week. >> That's awesome. And I think that's a good culture to have that empowerment and I think that's very healthy. What's next for you guys? What's on the agenda? Take us through the activities. I know that you got a ton of things happening. You got your event out there, which is why you're out there. There's a bunch of other activities. I think you guys call it the Advancing Women in Tech week. >> Yes, this week we are having a week of programming that you can check out at Advancing Women in Tech.org. That is spotlighting the expertise of a number of women in our space. So it is three days of programming Tuesday, Wednesday and Thursday if you are in the US so the seventh through the ninth, but available globally. We are also going to be in New York next week for the event at the UN and are looking to continue to support our mentorship programs and also our work supporting women founders throughout the year. >> All right. I have to ask you guys if you don't mind get a little market data so you can share with us here at theCUBE. What are you hearing this year that's different in the conversation space around the topics, the interests? Obviously I've seen massive amounts of global acceleration around conversations, more video, things like this more stories are scaling, a lot more LinkedIn activity. It just seems like it's a lot different this year. Can you guys share any kind of current trends you're seeing relative to the conversations and topics being discussed across the the community? >> Well, I think from a needle moving perspective, right? I think due to the efforts of wonderful organizations including the Q for spotlighting all of these awesome women, right? Trailblazing women and the nonprofits the government entities that we work with there's definitely more emphasis on creating access and creating pathways. So that's probably one thing that you're seeing is more women, more investors posting about their activities. Number two, from a global trend perspective, right? The rise of women in security. I noticed that on your agenda today, you had Lena Smart who's a good friend of mine chief information security officer at MongoDB, right? She and I are actually quite involved in helping founders especially early stage founders in the security space. And so globally from a pure technical perspective, right? There's right more increasing regulations around data privacy, data sovereignty, right? For example, India's in a few weeks about to get their first data protection regulation there locally. So all of that is giving rise to yet another wave of opportunity and we want women founders uniquely positioned to take advantage of that opportunity. >> I love it. Kate, reaction to that? I mean founders, more pathways it sounds like a neural network, it sounds like AI enabled. >> Yes, and speaking of AI, with the rise of that we are also hearing from many community members the importance of continuing to build their skills upskill learn to be able to keep up with the latest trends. There's a lot of people wondering what does this mean for my own career? And so they're turning to organizations like Advancing Women in Tech to find communities to both learn the latest information, but also build their networks so that they are able to move forward regardless of what the industry does. >> I love the work you guys are doing. It's so impressive. I think the economic angle is new it's more amplified this year. It's always kind of been there and continues to be. What do you guys hope for by next year this time what do you hope to see different from a needle moving perspective, to use your word Nancy, for next year? What's the visual output in your mind? >> I want to see real effort made towards 50-50 representation in all tech leadership roles. And I'd like to see that happen by 2050. >> Kate, anything on your end? >> I love that. I'm going to go a little bit more touchy-feely. I want everybody in our space to understand that the skills that they build and that the networks they have carry with them regardless of wherever they go. And so to be able to really lean in and learn and continue to develop the career that you want to have. So whether that be at a large organization or within your own business, that you've got the potential to move forward on that within you. >> Nancy, Kate, thank you so much for your contribution. I'll give you the final word. Put a plug in for the organization. What are you guys looking for? Any kind of PSA you want to share with the folks watching? >> Absolutely, so if you're in a position to be a mentor, join as a mentor, right? Help elevate and accelerate the next generation of women leaders. If you're an investor help us invest in more women started companies, right? Women founded startups and lastly, if you are women looking to accelerate your career, come join our community. We have resources, we have mentors and who we have investors who are willing to come in on the ground floor and help you accelerate your business. >> Great work. Thank you so much for participating in our International Women's Day 23 program and we'd look to keep this going quarterly. We'll see you next year, next time. Thanks for coming on. Appreciate it. >> Thanks so much John. >> Thank you. >> Okay, women leaders here. >> Nancy: Thanks for having us >> All over the world, coming together for a great celebration but really highlighting the accomplishments, the pathways the investment, the mentoring, everything in between. It's theCUBE. Bring as much as we can. I'm John Furrier, your host. Thanks for watching.

(upbeat intro music) >> Hello everyone. Welcome to theCUBE's coverage of International Women's Day. I'm your host, John Furrier, here in Palo Alto, California. Got a special remote guest coming in. Teresa Carlson, President and Chief Commercial Officer at Flexport, theCUBE alumni, one of the first, let me go back to 2013, Teresa, former AWS. Great to see you. Thanks for coming on. >> Oh my gosh, almost 10 years. That is unbelievable. It's hard to believe so many years of theCUBE. I love it. >> It's been such a great honor to interview you and follow your career. You've had quite the impressive run, executive level woman in tech. You've done such an amazing job, not only in your career, but also helping other women. So I want to give you props to that before we get started. Thank you. >> Thank you, John. I, it's my, it's been my honor and privilege. >> Let's talk about Flexport. Tell us about your new role there and what it's all about. >> Well, I love it. I'm back working with another Amazonian, Dave Clark, who is our CEO of Flexport, and we are about 3,000 people strong globally in over 90 countries. We actually even have, we're represented in over 160 cities and with local governments and places around the world, which I think is super exciting. We have over 100 network partners and growing, and we are about empowering the global supply chain and trade and doing it in a very disruptive way with the use of platform technology that allows our customers to really have visibility and insight to what's going on. And it's a lot of fun. I'm learning new things, but there's a lot of technology in this as well, so I feel right at home. >> You quite have a knack from mastering growth, technology, and building out companies. So congratulations, and scaling them up too with the systems and processes. So I want to get into that. Let's get into your personal background. Then I want to get into the work you've done and are doing for empowering women in tech. What was your journey about, how did it all start? Like, I know you had a, you know, bumped into it, you went Microsoft, AWS. Take us through your career, how you got into tech, how it all happened. >> Well, I do like to give a shout out, John, to my roots and heritage, which was a speech and language pathologist. So I did start out in healthcare right out of, you know, university. I had an undergraduate and a master's degree. And I do tell everyone now, looking back at my career, I think it was super helpful for me because I learned a lot about human communication, and it has done me very well over the years to really try to understand what environments I'm in and what kind of individuals around the world culturally. So I'm really blessed that I had that opportunity to work in healthcare, and by the way, a shout out to all of our healthcare workers that has helped us get through almost three years of COVID and flu and neurovirus and everything else. So started out there and then kind of almost accidentally got into technology. My first small company I worked for was a company called Keyfile Corporation, which did workflow and document management out of Nashua, New Hampshire. And they were a Microsoft goal partner. And that is actually how I got into big tech world. We ran on exchange, for everybody who knows that term exchange, and we were a large small partner, but large in the world of exchange. And those were the days when you would, the late nineties, you would go and be in the same room with Bill Gates and Steve Ballmer. And I really fell in love with Microsoft back then. I thought to myself, wow, if I could work for a big tech company, I got to hear Bill on stage about saving, he would talk about saving the world. And guess what my next step was? I actually got a job at Microsoft, took a pay cut and a job downgrade. I tell this story all the time. Took like three downgrades in my role. I had been a SVP and went to a manager, and it's one of the best moves I ever made. And I shared that because I really didn't know the world of big tech, and I had to start from the ground up and relearn it. I did that, I just really loved that job. I was at Microsoft from 2000 to 2010, where I eventually ran all of the U.S. federal government business, which was a multi-billion dollar business. And then I had the great privilege of meeting an amazing man, Andy Jassy, who I thought was just unbelievable in his insights and knowledge and openness to understanding new markets. And we talked about government and how government needed the same great technology as every startup. And that led to me going to work for Andy in 2010 and starting up our worldwide public sector business. And I pinch myself some days because we went from two people, no offices, to the time I left we had over 10,000 people, billions in revenue, and 172 countries and had done really amazing work. I think changing the way public sector and government globally really thought about their use of technology and Cloud computing in general. And that kind of has been my career. You know, I was there till 2020, 21 and then did a small stint at Splunk, a small stint back at Microsoft doing a couple projects for Microsoft with CEO, Satya Nadella, who is also an another amazing CEO and leader. And then Dave called me, and I'm at Flexport, so I couldn't be more honored, John. I've just had such an amazing career working with amazing individuals. >> Yeah, I got to say the Amazon One well-documented, certainly by theCUBE and our coverage. We watched you rise and scale that thing. And like I said at a time, this will when we look back as a historic run because of the build out. I mean as a zero to massive billions at a historic time where government was transforming, I would say Microsoft had a good run there with Fed, but it was already established stuff. Federal business was like, you know, blocking and tackling. The Amazon was pure build out. So I have to ask you, what was your big learnings? Because one, you're a Seattle big tech company kind of entrepreneurial in the sense of you got, here's some working capital seed finance and go build that thing, and you're in DC and you're a woman. What did you learn? >> I learned that you really have to have a lot of grit. You, my mom and dad, these are kind of more southern roots words, but stick with itness, you know. you can't give up and no's not in your vocabulary. I found no is just another way to get to yes. That you have to figure out what are all the questions people are going to ask you. I learned to be very patient, and I think one of the things John, for us was our secret sauce was we said to ourselves, if we're going to do something super transformative and truly disruptive, like Cloud computing, which the government really had not utilized, we had to be patient. We had to answer all their questions, and we could not judge in any way what they were thinking because if we couldn't answer all those questions and prove out the capabilities of Cloud computing, we were not going to accomplish our goals. And I do give so much credit to all my colleagues there from everybody like Steve Schmidt who was there, who's still there, who's the CISO, and Charlie Bell and Peter DeSantis and the entire team there that just really helped build that business out. Without them, you know, we would've just, it was a team effort. And I think that's the thing I loved about it was it was not just sales, it was product, it was development, it was data center operations, it was legal, finance. Everybody really worked as a team and we were on board that we had to make a lot of changes in the government relations team. We had to go into Capitol Hill. We had to talk to them about the changes that were required and really get them to understand why Cloud computing could be such a transformative game changer for the way government operates globally. >> Well, I think the whole world and the tech world can appreciate your work and thank you later because you broke down those walls asking those questions. So great stuff. Now I got to say, you're in kind of a similar role at Flexport. Again, transformative supply chain, not new. Computing wasn't new when before Cloud came. Supply chain, not a new concept, is undergoing radical change and transformation. Online, software supply chain, hardware supply chain, supply chain in general, shipping. This is a big part of our economy and how life is working. Similar kind of thing going on, build out, growth, scale. >> It is, it's very much like that, John, I would say, it's, it's kind of a, the model with freight forwarding and supply chain is fairly, it's not as, there's a lot of technology utilized in this global supply chain world, but it's not integrated. You don't have a common operating picture of what you're doing in your global supply chain. You don't have easy access to the information and visibility. And that's really, you know, I was at a conference last week in LA, and it was, the themes were so similar about transparency, access to data and information, being able to act quickly, drive change, know what was happening. I was like, wow, this sounds familiar. Data, AI, machine learning, visibility, common operating picture. So it is very much the same kind of themes that you heard even with government. I do believe it's an industry that is going through transformation and Flexport has been a group that's come in and said, look, we have this amazing idea, number one to give access to everyone. We want every small business to every large business to every government around the world to be able to trade their goods, think about supply chain logistics in a very different way with information they need and want at their fingertips. So that's kind of thing one, but to apply that technology in a way that's very usable across all systems from an integration perspective. So it's kind of exciting. I used to tell this story years ago, John, and I don't think Michael Dell would mind that I tell this story. One of our first customers when I was at Keyfile Corporation was we did workflow and document management, and Dell was one of our customers. And I remember going out to visit them, and they had runners and they would run around, you know, they would run around the floor and do their orders, right, to get all those computers out the door. And when I think of global trade, in my mind I still see runners, you know, running around and I think that's moved to a very digital, right, world that all this stuff, you don't need people doing this. You have machines doing this now, and you have access to the information, and you know, we still have issues resulting from COVID where we have either an under-abundance or an over-abundance of our supply chain. We still have clogs in our shipping, in the shipping yards around the world. So we, and the ports, so we need to also, we still have some clearing to do. And that's the reason technology is important and will continue to be very important in this world of global trade. >> Yeah, great, great impact for change. I got to ask you about Flexport's inclusion, diversity, and equity programs. What do you got going on there? That's been a big conversation in the industry around keeping a focus on not making one way more than the other, but clearly every company, if they don't have a strong program, will be at a disadvantage. That's well reported by McKinsey and other top consultants, diverse workforces, inclusive, equitable, all perform better. What's Flexport's strategy and how are you guys supporting that in the workplace? >> Well, let me just start by saying really at the core of who I am, since the day I've started understanding that as an individual and a female leader, that I could have an impact. That the words I used, the actions I took, the information that I pulled together and had knowledge of could be meaningful. And I think each and every one of us is responsible to do what we can to make our workplace and the world a more diverse and inclusive place to live and work. And I've always enjoyed kind of the thought that, that I could help empower women around the world in the tech industry. Now I'm hoping to do my little part, John, in that in the supply chain and global trade business. And I would tell you at Flexport we have some amazing women. I'm so excited to get to know all. I've not been there that long yet, but I'm getting to know we have some, we have a very diverse leadership team between men and women at Dave's level. I have some unbelievable women on my team directly that I'm getting to know more, and I'm so impressed with what they're doing. And this is a very, you know, while this industry is different than the world I live in day to day, it's also has a lot of common themes to it. So, you know, for us, we're trying to approach every day by saying, let's make sure both our interviewing cycles, the jobs we feel, how we recruit people, how we put people out there on the platforms, that we have diversity and inclusion and all of that every day. And I can tell you from the top, from Dave and all of our leaders, we just had an offsite and we had a big conversation about this is something. It's a drum beat that we have to think about and live by every day and really check ourselves on a regular basis. But I do think there's so much more room for women in the world to do great things. And one of the, one of the areas, as you know very well, we lost a lot of women during COVID, who just left the workforce again. So we kind of went back unfortunately. So we have to now move forward and make sure that we are giving women the opportunity to have great jobs, have the flexibility they need as they build a family, and have a workplace environment that is trusted for them to come into every day. >> There's now clear visibility, at least in today's world, not withstanding some of the setbacks from COVID, that a young girl can look out in a company and see a path from entry level to the boardroom. That's a big change. A lot than even going back 10, 15, 20 years ago. What's your advice to the folks out there that are paying it forward? You see a lot of executive leaderships have a seat at the table. The board still underrepresented by most numbers, but at least you have now kind of this solidarity at the top, but a lot of people doing a lot more now than I've seen at the next levels down. So now you have this leveled approach. Is that something that you're seeing more of? And credit compare and contrast that to 20 years ago when you were, you know, rising through the ranks? What's different? >> Well, one of the main things, and I honestly do not think about it too much, but there were really no women. There were none. When I showed up in the meetings, I literally, it was me or not me at the table, but at the seat behind the table. The women just weren't in the room, and there were so many more barriers that we had to push through, and that has changed a lot. I mean globally that has changed a lot in the U.S. You know, if you look at just our U.S. House of Representatives and our U.S. Senate, we now have the increasing number of women. Even at leadership levels, you're seeing that change. You have a lot more women on boards than we ever thought we would ever represent. While we are not there, more female CEOs that I get an opportunity to see and talk to. Women starting companies, they do not see the barriers. And I will share, John, globally in the U.S. one of the things that I still see that we have that many other countries don't have, which I'm very proud of, women in the U.S. have a spirit about them that they just don't see the barriers in the same way. They believe that they can accomplish anything. I have two sons, I don't have daughters. I have nieces, and I'm hoping someday to have granddaughters. But I know that a lot of my friends who have granddaughters today talk about the boldness, the fortitude, that they believe that there's nothing they can't accomplish. And I think that's what what we have to instill in every little girl out there, that they can accomplish anything they want to. The world is theirs, and we need to not just do that in the U.S., but around the world. And it was always the thing that struck me when I did all my travels at AWS and now with Flexport, I'm traveling again quite a bit, is just the differences you see in the cultures around the world. And I remember even in the Middle East, how I started seeing it change. You've heard me talk a lot on this program about the fact in both Saudi and Bahrain, over 60% of the tech workers were females and most of them held the the hardest jobs, the security, the architecture, the engineering. But many of them did not hold leadership roles. And that is what we've got to change too. To your point, the middle, we want it to get bigger, but the top, we need to get bigger. We need to make sure women globally have opportunities to hold the most precious leadership roles and demonstrate their capabilities at the very top. But that's changed. And I would say the biggest difference is when we show up, we're actually evaluated properly for those kind of roles. We have a ways to go. But again, that part is really changing. >> Can you share, Teresa, first of all, that's great work you've done and I wan to give you props of that as well and all the work you do. I know you champion a lot of, you know, causes in in this area. One question that comes up a lot, I would love to get your opinion 'cause I think you can contribute heavily here is mentoring and sponsorship is huge, comes up all the time. What advice would you share to folks out there who were, I won't say apprehensive, but maybe nervous about how to do the networking and sponsorship and mentoring? It's not just mentoring, it's sponsorship too. What's your best practice? What advice would you give for the best way to handle that? >> Well yeah, and for the women out there, I would say on the mentorship side, I still see mentorship. Like, I don't think you can ever stop having mentorship. And I like to look at my mentors in different parts of my life because if you want to be a well-rounded person, you may have parts of your life every day that you think I'm doing a great job here and I definitely would like to do better there. Whether it's your spiritual life, your physical life, your work life, you know, your leisure life. But I mean there's, and there's parts of my leadership world that I still seek advice from as I try to do new things even in this world. And I tried some new things in between roles. I went out and asked the people that I respected the most. So I just would say for sure have different mentorships and don't be afraid to have that diversity. But if you have mentorships, the second important thing is show up with a real agenda and questions. Don't waste people's time. I'm very sensitive today. If you're, if you want a mentor, you show up and you use your time super effectively and be prepared for that. Sponsorship is a very different thing. And I don't believe we actually do that still in companies. We worked, thank goodness for my great HR team. When I was at AWS, we worked on a few sponsorship programs where for diversity in general, where we would nominate individuals in the company that we felt that weren't, that had a lot of opportunity for growth, but they just weren't getting a seat at the table. And we brought 'em to the table. And we actually kind of had a Chatham House rules where when they came into the meetings, they had a sponsor, not a mentor. They had a sponsor that was with them the full 18 months of this program. We would bring 'em into executive meetings. They would read docs, they could ask questions. We wanted them to be able to open up and ask crazy questions without, you know, feeling wow, I just couldn't answer this question in a normal environment or setting. And then we tried to make sure once they got through the program that we found jobs and support and other special projects that they could go do. But they still had that sponsor and that group of individuals that they'd gone through the program with, John, that they could keep going back to. And I remember sitting there and they asked me what I wanted to get out of the program, and I said two things. I want you to leave this program and say to yourself, I would've never had that experience if I hadn't gone through this program. I learned so much in 18 months. It would probably taken me five years to learn. And that it helped them in their career. The second thing I told them is I wanted them to go out and recruit individuals that look like them. I said, we need diversity, and unless you all feel that we are in an inclusive environment sponsoring all types of individuals to be part of this company, we're not going to get the job done. And they said, okay. And you know, but it was really one, it was very much about them. That we took a group of individuals that had high potential and a very diverse with diverse backgrounds, held 'em up, taught 'em things that gave them access. And two, selfishly I said, I want more of you in my business. Please help me. And I think those kind of things are helpful, and you have to be thoughtful about these kind of programs. And to me that's more sponsorship. I still have people reach out to me from years ago, you know, Microsoft saying, you were so good with me, can you give me a reference now? Can you talk to me about what I should be doing? And I try to, I'm not pray 100%, some things pray fall through the cracks, but I always try to make the time to talk to those individuals because for me, I am where I am today because I got some of the best advice from people like Don Byrne and Linda Zecker and Andy Jassy, who were very honest and upfront with me about my career. >> Awesome. Well, you got a passion for empowering women in tech, paying it forward, but you're quite accomplished and that's why we're so glad to have you on the program here. President and Chief Commercial Officer at Flexport. Obviously storied career and your other jobs, specifically Amazon I think, is historic in my mind. This next chapter looks like it's looking good right now. Final question for you, for the few minutes you have left. Tell us what you're up to at Flexport. What's your goals as President, Chief Commercial Officer? What are you trying to accomplish? Share a little bit, what's on your mind with your current job? >> Well, you kind of said it earlier. I think if I look at my own superpowers, I love customers, I love partners. I get my energy, John, from those interactions. So one is to come in and really help us build even a better world class enterprise global sales and marketing team. Really listen to our customers, think about how we interact with them, build the best executive programs we can, think about new ways that we can offer services to them and create new services. One of my favorite things about my career is I think if you're a business leader, it's your job to come back around and tell your product group and your services org what you're hearing from customers. That's how you can be so much more impactful, that you listen, you learn, and you deliver. So that's one big job. The second job for me, which I am so excited about, is that I have an amazing group called flexport.org under me. And flexport.org is doing amazing things around the world to help those in need. We just announced this new funding program for Tech for Refugees, which brings assistance to millions of people in Ukraine, Pakistan, the horn of Africa, and those who are affected by earthquakes. We just took supplies into Turkey and Syria, and Flexport, recently in fact, just did sent three air shipments to Turkey and Syria for these. And I think we did over a hundred trekking shipments to get earthquake relief. And as you can imagine, it was not easy to get into Syria. But you know, we're very active in the Ukraine, and we are, our goal for flexport.org, John, is to continue to work with our commercial customers and team up with them when they're trying to get supplies in to do that in a very cost effective, easy way, as quickly as we can. So that not-for-profit side of me that I'm so, I'm so happy. And you know, Ryan Peterson, who was our founder, this was his brainchild, and he's really taken this to the next level. So I'm honored to be able to pick that up and look for new ways to have impact around the world. And you know, I've always found that I think if you do things right with a company, you can have a beautiful combination of commercial-ity and giving. And I think Flexport does it in such an amazing and unique way. >> Well, the impact that they have with their system and their technology with logistics and shipping and supply chain is a channel for societal change. And I think that's a huge gift that you have that under your purview. So looking forward to finding out more about flexport.org. I can only imagine all the exciting things around sustainability, and we just had Mobile World Congress for Big Cube Broadcast, 5Gs right around the corner. I'm sure that's going to have a huge impact to your business. >> Well, for sure. And just on gas emissions, that's another thing that we are tracking gas, greenhouse gas emissions. And in fact we've already reduced more than 300,000 tons and supported over 600 organizations doing that. So that's a thing we're also trying to make sure that we're being climate aware and ensuring that we are doing the best job we can at that as well. And that was another thing I was honored to be able to do when we were at AWS, is to really cut out greenhouse gas emissions and really go global with our climate initiatives. >> Well Teresa, it's great to have you on. Security, data, 5G, sustainability, business transformation, AI all coming together to change the game. You're in another hot seat, hot roll, big wave. >> Well, John, it's an honor, and just thank you again for doing this and having women on and really representing us in a big way as we celebrate International Women's Day. >> I really appreciate it, it's super important. And these videos have impact, so we're going to do a lot more. And I appreciate your leadership to the industry and thank you so much for taking the time to contribute to our effort. Thank you, Teresa. >> Thank you. Thanks everybody. >> Teresa Carlson, the President and Chief Commercial Officer of Flexport. I'm John Furrier, host of theCUBE. This is International Women's Day broadcast. Thanks for watching. (upbeat outro music)

(upbeat music beginning) >> From the Cube Studios in Palo Alto and Boston, bringing you data-driven insights from the Cube and ETR, this is "Breaking Analysis" with Dave Vellante. >> Making predictions about the future of enterprise tech is more challenging if you strive to lay down forecasts that are measurable. In other words, if you make a prediction, you should be able to look back a year later and say, with some degree of certainty, whether the prediction came true or not, with evidence to back that up. Hello and welcome to this week's Wikibon Cube Insights, powered by ETR. In this breaking analysis, we aim to do just that, with predictions about the macro IT spending environment, cost optimization, security, lots to talk about there, generative AI, cloud, and of course supercloud, blockchain adoption, data platforms, including commentary on Databricks, snowflake, and other key players, automation, events, and we may even have some bonus predictions around quantum computing, and perhaps some other areas. To make all this happen, we welcome back, for the third year in a row, my colleague and friend Eric Bradley from ETR. Eric, thanks for all you do for the community, and thanks for being part of this program. Again. >> I wouldn't miss it for the world. I always enjoy this one. Dave, good to see you. >> Yeah, so let me bring up this next slide and show you, actually come back to me if you would. I got to show the audience this. These are the inbounds that we got from PR firms starting in October around predictions. They know we do prediction posts. And so they'll send literally thousands and thousands of predictions from hundreds of experts in the industry, technologists, consultants, et cetera. And if you bring up the slide I can show you sort of the pattern that developed here. 40% of these thousands of predictions were from cyber. You had AI and data. If you combine those, it's still not close to cyber. Cost optimization was a big thing. Of course, cloud, some on DevOps, and software. Digital... Digital transformation got, you know, some lip service and SaaS. And then there was other, it's kind of around 2%. So quite remarkable, when you think about the focus on cyber, Eric. >> Yeah, there's two reasons why I think it makes sense, though. One, the cybersecurity companies have a lot of cash, so therefore the PR firms might be working a little bit harder for them than some of their other clients. (laughs) And then secondly, as you know, for multiple years now, when we do our macro survey, we ask, "What's your number one spending priority?" And again, it's security. It just isn't going anywhere. It just stays at the top. So I'm actually not that surprised by that little pie chart there, but I was shocked that SaaS was only 5%. You know, going back 10 years ago, that would've been the only thing anyone was talking about. >> Yeah. So true. All right, let's get into it. First prediction, we always start with kind of tech spending. Number one is tech spending increases between four and 5%. ETR has currently got it at 4.6% coming into 2023. This has been a consistently downward trend all year. We started, you know, much, much higher as we've been reporting. Bottom line is the fed is still in control. They're going to ease up on tightening, is the expectation, they're going to shoot for a soft landing. But you know, my feeling is this slingshot economy is going to continue, and it's going to continue to confound, whether it's supply chains or spending. The, the interesting thing about the ETR data, Eric, and I want you to comment on this, the largest companies are the most aggressive to cut. They're laying off, smaller firms are spending faster. They're actually growing at a much larger, faster rate as are companies in EMEA. And that's a surprise. That's outpacing the US and APAC. Chime in on this, Eric. >> Yeah, I was surprised on all of that. First on the higher level spending, we are definitely seeing it coming down, but the interesting thing here is headlines are making it worse. The huge research shop recently said 0% growth. We're coming in at 4.6%. And just so everyone knows, this is not us guessing, we asked 1,525 IT decision-makers what their budget growth will be, and they came in at 4.6%. Now there's a huge disparity, as you mentioned. The Fortune 500, global 2000, barely at 2% growth, but small, it's at 7%. So we're at a situation right now where the smaller companies are still playing a little bit of catch up on digital transformation, and they're spending money. The largest companies that have the most to lose from a recession are being more trepidatious, obviously. So they're playing a "Wait and see." And I hope we don't talk ourselves into a recession. Certainly the headlines and some of their research shops are helping it along. But another interesting comment here is, you know, energy and utilities used to be called an orphan and widow stock group, right? They are spending more than anyone, more than financials insurance, more than retail consumer. So right now it's being driven by mid, small, and energy and utilities. They're all spending like gangbusters, like nothing's happening. And it's the rest of everyone else that's being very cautious. >> Yeah, so very unpredictable right now. All right, let's go to number two. Cost optimization remains a major theme in 2023. We've been reporting on this. You've, we've shown a chart here. What's the primary method that your organization plans to use? You asked this question of those individuals that cited that they were going to reduce their spend and- >> Mhm. >> consolidating redundant vendors, you know, still leads the way, you know, far behind, cloud optimization is second, but it, but cloud continues to outpace legacy on-prem spending, no doubt. Somebody, it was, the guy's name was Alexander Feiglstorfer from Storyblok, sent in a prediction, said "All in one becomes extinct." Now, generally I would say I disagree with that because, you know, as we know over the years, suites tend to win out over, you know, individual, you know, point products. But I think what's going to happen is all in one is going to remain the norm for these larger companies that are cutting back. They want to consolidate redundant vendors, and the smaller companies are going to stick with that best of breed and be more aggressive and try to compete more effectively. What's your take on that? >> Yeah, I'm seeing much more consolidation in vendors, but also consolidation in functionality. We're seeing people building out new functionality, whether it's, we're going to talk about this later, so I don't want to steal too much of our thunder right now, but data and security also, we're seeing a functionality creep. So I think there's further consolidation happening here. I think niche solutions are going to be less likely, and platform solutions are going to be more likely in a spending environment where you want to reduce your vendors. You want to have one bill to pay, not 10. Another thing on this slide, real quick if I can before I move on, is we had a bunch of people write in and some of the answer options that aren't on this graph but did get cited a lot, unfortunately, is the obvious reduction in staff, hiring freezes, and delaying hardware, were three of the top write-ins. And another one was offshore outsourcing. So in addition to what we're seeing here, there were a lot of write-in options, and I just thought it would be important to state that, but essentially the cost optimization is by and far the highest one, and it's growing. So it's actually increased in our citations over the last year. >> And yeah, specifically consolidating redundant vendors. And so I actually thank you for bringing that other up, 'cause I had asked you, Eric, is there any evidence that repatriation is going on and we don't see it in the numbers, we don't see it even in the other, there was, I think very little or no mention of cloud repatriation, even though it might be happening in this in a smattering. >> Not a single mention, not one single mention. I went through it for you. Yep. Not one write-in. >> All right, let's move on. Number three, security leads M&A in 2023. Now you might say, "Oh, well that's a layup," but let me set this up Eric, because I didn't really do a great job with the slide. I hid the, what you've done, because you basically took, this is from the emerging technology survey with 1,181 responses from November. And what we did is we took Palo Alto and looked at the overlap in Palo Alto Networks accounts with these vendors that were showing on this chart. And Eric, I'm going to ask you to explain why we put a circle around OneTrust, but let me just set it up, and then have you comment on the slide and take, give us more detail. We're seeing private company valuations are off, you know, 10 to 40%. We saw a sneak, do a down round, but pretty good actually only down 12%. We've seen much higher down rounds. Palo Alto Networks we think is going to get busy. Again, they're an inquisitive company, they've been sort of quiet lately, and we think CrowdStrike, Cisco, Microsoft, Zscaler, we're predicting all of those will make some acquisitions and we're thinking that the targets are somewhere in this mess of security taxonomy. Other thing we're predicting AI meets cyber big time in 2023, we're going to probably going to see some acquisitions of those companies that are leaning into AI. We've seen some of that with Palo Alto. And then, you know, your comment to me, Eric, was "The RSA conference is going to be insane, hopping mad, "crazy this April," (Eric laughing) but give us your take on this data, and why the red circle around OneTrust? Take us back to that slide if you would, Alex. >> Sure. There's a few things here. First, let me explain what we're looking at. So because we separate the public companies and the private companies into two separate surveys, this allows us the ability to cross-reference that data. So what we're doing here is in our public survey, the tesis, everyone who cited some spending with Palo Alto, meaning they're a Palo Alto customer, we then cross-reference that with the private tech companies. Who also are they spending with? So what you're seeing here is an overlap. These companies that we have circled are doing the best in Palo Alto's accounts. Now, Palo Alto went and bought Twistlock a few years ago, which this data slide predicted, to be quite honest. And so I don't know if they necessarily are going to go after Snyk. Snyk, sorry. They already have something in that space. What they do need, however, is more on the authentication space. So I'm looking at OneTrust, with a 45% overlap in their overall net sentiment. That is a company that's already existing in their accounts and could be very synergistic to them. BeyondTrust as well, authentication identity. This is something that Palo needs to do to move more down that zero trust path. Now why did I pick Palo first? Because usually they're very inquisitive. They've been a little quiet lately. Secondly, if you look at the backdrop in the markets, the IPO freeze isn't going to last forever. Sooner or later, the IPO markets are going to open up, and some of these private companies are going to tap into public equity. In the meantime, however, cash funding on the private side is drying up. If they need another round, they're not going to get it, and they're certainly not going to get it at the valuations they were getting. So we're seeing valuations maybe come down where they're a touch more attractive, and Palo knows this isn't going to last forever. Cisco knows that, CrowdStrike, Zscaler, all these companies that are trying to make a push to become that vendor that you're consolidating in, around, they have a chance now, they have a window where they need to go make some acquisitions. And that's why I believe leading up to RSA, we're going to see some movement. I think it's going to pretty, a really exciting time in security right now. >> Awesome. Thank you. Great explanation. All right, let's go on the next one. Number four is, it relates to security. Let's stay there. Zero trust moves from hype to reality in 2023. Now again, you might say, "Oh yeah, that's a layup." A lot of these inbounds that we got are very, you know, kind of self-serving, but we always try to put some meat in the bone. So first thing we do is we pull out some commentary from, Eric, your roundtable, your insights roundtable. And we have a CISO from a global hospitality firm says, "For me that's the highest priority." He's talking about zero trust because it's the best ROI, it's the most forward-looking, and it enables a lot of the business transformation activities that we want to do. CISOs tell me that they actually can drive forward transformation projects that have zero trust, and because they can accelerate them, because they don't have to go through the hurdle of, you know, getting, making sure that it's secure. Second comment, zero trust closes that last mile where once you're authenticated, they open up the resource to you in a zero trust way. That's a CISO of a, and a managing director of a cyber risk services enterprise. Your thoughts on this? >> I can be here all day, so I'm going to try to be quick on this one. This is not a fluff piece on this one. There's a couple of other reasons this is happening. One, the board finally gets it. Zero trust at first was just a marketing hype term. Now the board understands it, and that's why CISOs are able to push through it. And what they finally did was redefine what it means. Zero trust simply means moving away from hardware security, moving towards software-defined security, with authentication as its base. The board finally gets that, and now they understand that this is necessary and it's being moved forward. The other reason it's happening now is hybrid work is here to stay. We weren't really sure at first, large companies were still trying to push people back to the office, and it's going to happen. The pendulum will swing back, but hybrid work's not going anywhere. By basically on our own data, we're seeing that 69% of companies expect remote and hybrid to be permanent, with only 30% permanent in office. Zero trust works for a hybrid environment. So all of that is the reason why this is happening right now. And going back to our previous prediction, this is why we're picking Palo, this is why we're picking Zscaler to make these acquisitions. Palo Alto needs to be better on the authentication side, and so does Zscaler. They're both fantastic on zero trust network access, but they need the authentication software defined aspect, and that's why we think this is going to happen. One last thing, in that CISO round table, I also had somebody say, "Listen, Zscaler is incredible. "They're doing incredibly well pervading the enterprise, "but their pricing's getting a little high," and they actually think Palo Alto is well-suited to start taking some of that share, if Palo can make one move. >> Yeah, Palo Alto's consolidation story is very strong. Here's my question and challenge. Do you and me, so I'm always hardcore about, okay, you've got to have evidence. I want to look back at these things a year from now and say, "Did we get it right? Yes or no?" If we got it wrong, we'll tell you we got it wrong. So how are we going to measure this? I'd say a couple things, and you can chime in. One is just the number of vendors talking about it. That's, but the marketing always leads the reality. So the second part of that is we got to get evidence from the buying community. Can you help us with that? >> (laughs) Luckily, that's what I do. I have a data company that asks thousands of IT decision-makers what they're adopting and what they're increasing spend on, as well as what they're decreasing spend on and what they're replacing. So I have snapshots in time over the last 11 years where I can go ahead and compare and contrast whether this adoption is happening or not. So come back to me in 12 months and I'll let you know. >> Now, you know, I will. Okay, let's bring up the next one. Number five, generative AI hits where the Metaverse missed. Of course everybody's talking about ChatGPT, we just wrote last week in a breaking analysis with John Furrier and Sarjeet Joha our take on that. We think 2023 does mark a pivot point as natural language processing really infiltrates enterprise tech just as Amazon turned the data center into an API. We think going forward, you're going to be interacting with technology through natural language, through English commands or other, you know, foreign language commands, and investors are lining up, all the VCs are getting excited about creating something competitive to ChatGPT, according to (indistinct) a hundred million dollars gets you a seat at the table, gets you into the game. (laughing) That's before you have to start doing promotion. But he thinks that's what it takes to actually create a clone or something equivalent. We've seen stuff from, you know, the head of Facebook's, you know, AI saying, "Oh, it's really not that sophisticated, ChatGPT, "it's kind of like IBM Watson, it's great engineering, "but you know, we've got more advanced technology." We know Google's working on some really interesting stuff. But here's the thing. ETR just launched this survey for the February survey. It's in the field now. We circle open AI in this category. They weren't even in the survey, Eric, last quarter. So 52% of the ETR survey respondents indicated a positive sentiment toward open AI. I added up all the sort of different bars, we could double click on that. And then I got this inbound from Scott Stevenson of Deep Graham. He said "AI is recession-proof." I don't know if that's the case, but it's a good quote. So bring this back up and take us through this. Explain this chart for us, if you would. >> First of all, I like Scott's quote better than the Facebook one. I think that's some sour grapes. Meta just spent an insane amount of money on the Metaverse and that's a dud. Microsoft just spent money on open AI and it is hot, undoubtedly hot. We've only been in the field with our current ETS survey for a week. So my caveat is it's preliminary data, but I don't care if it's preliminary data. (laughing) We're getting a sneak peek here at what is the number one net sentiment and mindshare leader in the entire machine-learning AI sector within a week. It's beating Data- >> 600. 600 in. >> It's beating Databricks. And we all know Databricks is a huge established enterprise company, not only in machine-learning AI, but it's in the top 10 in the entire survey. We have over 400 vendors in this survey. It's number eight overall, already. In a week. This is not hype. This is real. And I could go on the NLP stuff for a while. Not only here are we seeing it in open AI and machine-learning and AI, but we're seeing NLP in security. It's huge in email security. It's completely transforming that area. It's one of the reasons I thought Palo might take Abnormal out. They're doing such a great job with NLP in this email side, and also in the data prep tools. NLP is going to take out data prep tools. If we have time, I'll discuss that later. But yeah, this is, to me this is a no-brainer, and we're already seeing it in the data. >> Yeah, John Furrier called, you know, the ChatGPT introduction. He said it reminded him of the Netscape moment, when we all first saw Netscape Navigator and went, "Wow, it really could be transformative." All right, number six, the cloud expands to supercloud as edge computing accelerates and CloudFlare is a big winner in 2023. We've reported obviously on cloud, multi-cloud, supercloud and CloudFlare, basically saying what multi-cloud should have been. We pulled this quote from Atif Kahn, who is the founder and CTO of Alkira, thanks, one of the inbounds, thank you. "In 2023, highly distributed IT environments "will become more the norm "as organizations increasingly deploy hybrid cloud, "multi-cloud and edge settings..." Eric, from one of your round tables, "If my sources from edge computing are coming "from the cloud, that means I have my workloads "running in the cloud. "There is no one better than CloudFlare," That's a senior director of IT architecture at a huge financial firm. And then your analysis shows CloudFlare really growing in pervasion, that sort of market presence in the dataset, dramatically, to near 20%, leading, I think you had told me that they're even ahead of Google Cloud in terms of momentum right now. >> That was probably the biggest shock to me in our January 2023 tesis, which covers the public companies in the cloud computing sector. CloudFlare has now overtaken GCP in overall spending, and I was shocked by that. It's already extremely pervasive in networking, of course, for the edge networking side, and also in security. This is the number one leader in SaaSi, web access firewall, DDoS, bot protection, by your definition of supercloud, which we just did a couple of weeks ago, and I really enjoyed that by the way Dave, I think CloudFlare is the one that fits your definition best, because it's bringing all of these aspects together, and most importantly, it's cloud agnostic. It does not need to rely on Azure or AWS to do this. It has its own cloud. So I just think it's, when we look at your definition of supercloud, CloudFlare is the poster child. >> You know, what's interesting about that too, is a lot of people are poo-pooing CloudFlare, "Ah, it's, you know, really kind of not that sophisticated." "You don't have as many tools," but to your point, you're can have those tools in the cloud, Cloudflare's doing serverless on steroids, trying to keep things really simple, doing a phenomenal job at, you know, various locations around the world. And they're definitely one to watch. Somebody put them on my radar (laughing) a while ago and said, "Dave, you got to do a breaking analysis on CloudFlare." And so I want to thank that person. I can't really name them, 'cause they work inside of a giant hyperscaler. But- (Eric laughing) (Dave chuckling) >> Real quickly, if I can from a competitive perspective too, who else is there? They've already taken share from Akamai, and Fastly is their really only other direct comp, and they're not there. And these guys are in poll position and they're the only game in town right now. I just, I don't see it slowing down. >> I thought one of your comments from your roundtable I was reading, one of the folks said, you know, CloudFlare, if my workloads are in the cloud, they are, you know, dominant, they said not as strong with on-prem. And so Akamai is doing better there. I'm like, "Okay, where would you want to be?" (laughing) >> Yeah, which one of those two would you rather be? >> Right? Anyway, all right, let's move on. Number seven, blockchain continues to look for a home in the enterprise, but devs will slowly begin to adopt in 2023. You know, blockchains have got a lot of buzz, obviously crypto is, you know, the killer app for blockchain. Senior IT architect in financial services from your, one of your insight roundtables said quote, "For enterprises to adopt a new technology, "there have to be proven turnkey solutions. "My experience in talking with my peers are, "blockchain is still an open-source component "where you have to build around it." Now I want to thank Ravi Mayuram, who's the CTO of Couchbase sent in, you know, one of the predictions, he said, "DevOps will adopt blockchain, specifically Ethereum." And he referenced actually in his email to me, Solidity, which is the programming language for Ethereum, "will be in every DevOps pro's playbook, "mirroring the boom in machine-learning. "Newer programming languages like Solidity "will enter the toolkits of devs." His point there, you know, Solidity for those of you don't know, you know, Bitcoin is not programmable. Solidity, you know, came out and that was their whole shtick, and they've been improving that, and so forth. But it, Eric, it's true, it really hasn't found its home despite, you know, the potential for smart contracts. IBM's pushing it, VMware has had announcements, and others, really hasn't found its way in the enterprise yet. >> Yeah, and I got to be honest, I don't think it's going to, either. So when we did our top trends series, this was basically chosen as an anti-prediction, I would guess, that it just continues to not gain hold. And the reason why was that first comment, right? It's very much a niche solution that requires a ton of custom work around it. You can't just plug and play it. And at the end of the day, let's be very real what this technology is, it's a database ledger, and we already have database ledgers in the enterprise. So why is this a priority to move to a different database ledger? It's going to be very niche cases. I like the CTO comment from Couchbase about it being adopted by DevOps. I agree with that, but it has to be a DevOps in a very specific use case, and a very sophisticated use case in financial services, most likely. And that's not across the entire enterprise. So I just think it's still going to struggle to get its foothold for a little bit longer, if ever. >> Great, thanks. Okay, let's move on. Number eight, AWS Databricks, Google Snowflake lead the data charge with Microsoft. Keeping it simple. So let's unpack this a little bit. This is the shared accounts peer position for, I pulled data platforms in for analytics, machine-learning and AI and database. So I could grab all these accounts or these vendors and see how they compare in those three sectors. Analytics, machine-learning and database. Snowflake and Databricks, you know, they're on a crash course, as you and I have talked about. They're battling to be the single source of truth in analytics. They're, there's going to be a big focus. They're already started. It's going to be accelerated in 2023 on open formats. Iceberg, Python, you know, they're all the rage. We heard about Iceberg at Snowflake Summit, last summer or last June. Not a lot of people had heard of it, but of course the Databricks crowd, who knows it well. A lot of other open source tooling. There's a company called DBT Labs, which you're going to talk about in a minute. George Gilbert put them on our radar. We just had Tristan Handy, the CEO of DBT labs, on at supercloud last week. They are a new disruptor in data that's, they're essentially making, they're API-ifying, if you will, KPIs inside the data warehouse and dramatically simplifying that whole data pipeline. So really, you know, the ETL guys should be shaking in their boots with them. Coming back to the slide. Google really remains focused on BigQuery adoption. Customers have complained to me that they would like to use Snowflake with Google's AI tools, but they're being forced to go to BigQuery. I got to ask Google about that. AWS continues to stitch together its bespoke data stores, that's gone down that "Right tool for the right job" path. David Foyer two years ago said, "AWS absolutely is going to have to solve that problem." We saw them start to do it in, at Reinvent, bringing together NoETL between Aurora and Redshift, and really trying to simplify those worlds. There's going to be more of that. And then Microsoft, they're just making it cheap and easy to use their stuff, you know, despite some of the complaints that we hear in the community, you know, about things like Cosmos, but Eric, your take? >> Yeah, my concern here is that Snowflake and Databricks are fighting each other, and it's allowing AWS and Microsoft to kind of catch up against them, and I don't know if that's the right move for either of those two companies individually, Azure and AWS are building out functionality. Are they as good? No they're not. The other thing to remember too is that AWS and Azure get paid anyway, because both Databricks and Snowflake run on top of 'em. So (laughing) they're basically collecting their toll, while these two fight it out with each other, and they build out functionality. I think they need to stop focusing on each other, a little bit, and think about the overall strategy. Now for Databricks, we know they came out first as a machine-learning AI tool. They were known better for that spot, and now they're really trying to play catch-up on that data storage compute spot, and inversely for Snowflake, they were killing it with the compute separation from storage, and now they're trying to get into the MLAI spot. I actually wouldn't be surprised to see them make some sort of acquisition. Frank Slootman has been a little bit quiet, in my opinion there. The other thing to mention is your comment about DBT Labs. If we look at our emerging technology survey, last survey when this came out, DBT labs, number one leader in that data integration space, I'm going to just pull it up real quickly. It looks like they had a 33% overall net sentiment to lead data analytics integration. So they are clearly growing, it's fourth straight survey consecutively that they've grown. The other name we're seeing there a little bit is Cribl, but DBT labs is by far the number one player in this space. >> All right. Okay, cool. Moving on, let's go to number nine. With Automation mixer resurgence in 2023, we're showing again data. The x axis is overlap or presence in the dataset, and the vertical axis is shared net score. Net score is a measure of spending momentum. As always, you've seen UI path and Microsoft Power Automate up until the right, that red line, that 40% line is generally considered elevated. UI path is really separating, creating some distance from Automation Anywhere, they, you know, previous quarters they were much closer. Microsoft Power Automate came on the scene in a big way, they loom large with this "Good enough" approach. I will say this, I, somebody sent me a results of a (indistinct) survey, which showed UiPath actually had more mentions than Power Automate, which was surprising, but I think that's not been the case in the ETR data set. We're definitely seeing a shift from back office to front soft office kind of workloads. Having said that, software testing is emerging as a mainstream use case, we're seeing ML and AI become embedded in end-to-end automations, and low-code is serving the line of business. And so this, we think, is going to increasingly have appeal to organizations in the coming year, who want to automate as much as possible and not necessarily, we've seen a lot of layoffs in tech, and people... You're going to have to fill the gaps with automation. That's a trend that's going to continue. >> Yep, agreed. At first that comment about Microsoft Power Automate having less citations than UiPath, that's shocking to me. I'm looking at my chart right here where Microsoft Power Automate was cited by over 60% of our entire survey takers, and UiPath at around 38%. Now don't get me wrong, 38% pervasion's fantastic, but you know you're not going to beat an entrenched Microsoft. So I don't really know where that comment came from. So UiPath, looking at it alone, it's doing incredibly well. It had a huge rebound in its net score this last survey. It had dropped going through the back half of 2022, but we saw a big spike in the last one. So it's got a net score of over 55%. A lot of people citing adoption and increasing. So that's really what you want to see for a name like this. The problem is that just Microsoft is doing its playbook. At the end of the day, I'm going to do a POC, why am I going to pay more for UiPath, or even take on another separate bill, when we know everyone's consolidating vendors, if my license already includes Microsoft Power Automate? It might not be perfect, it might not be as good, but what I'm hearing all the time is it's good enough, and I really don't want another invoice. >> Right. So how does UiPath, you know, and Automation Anywhere, how do they compete with that? Well, the way they compete with it is they got to have a better product. They got a product that's 10 times better. You know, they- >> Right. >> they're not going to compete based on where the lowest cost, Microsoft's got that locked up, or where the easiest to, you know, Microsoft basically give it away for free, and that's their playbook. So that's, you know, up to UiPath. UiPath brought on Rob Ensslin, I've interviewed him. Very, very capable individual, is now Co-CEO. So he's kind of bringing that adult supervision in, and really tightening up the go to market. So, you know, we know this company has been a rocket ship, and so getting some control on that and really getting focused like a laser, you know, could be good things ahead there for that company. Okay. >> One of the problems, if I could real quick Dave, is what the use cases are. When we first came out with RPA, everyone was super excited about like, "No, UiPath is going to be great for super powerful "projects, use cases." That's not what RPA is being used for. As you mentioned, it's being used for mundane tasks, so it's not automating complex things, which I think UiPath was built for. So if you were going to get UiPath, and choose that over Microsoft, it's going to be 'cause you're doing it for more powerful use case, where it is better. But the problem is that's not where the enterprise is using it. The enterprise are using this for base rote tasks, and simply, Microsoft Power Automate can do that. >> Yeah, it's interesting. I've had people on theCube that are both Microsoft Power Automate customers and UiPath customers, and I've asked them, "Well you know, "how do you differentiate between the two?" And they've said to me, "Look, our users and personal productivity users, "they like Power Automate, "they can use it themselves, and you know, "it doesn't take a lot of, you know, support on our end." The flip side is you could do that with UiPath, but like you said, there's more of a focus now on end-to-end enterprise automation and building out those capabilities. So it's increasingly a value play, and that's going to be obviously the challenge going forward. Okay, my last one, and then I think you've got some bonus ones. Number 10, hybrid events are the new category. Look it, if I can get a thousand inbounds that are largely self-serving, I can do my own here, 'cause we're in the events business. (Eric chuckling) Here's the prediction though, and this is a trend we're seeing, the number of physical events is going to dramatically increase. That might surprise people, but most of the big giant events are going to get smaller. The exception is AWS with Reinvent, I think Snowflake's going to continue to grow. So there are examples of physical events that are growing, but generally, most of the big ones are getting smaller, and there's going to be many more smaller intimate regional events and road shows. These micro-events, they're going to be stitched together. Digital is becoming a first class citizen, so people really got to get their digital acts together, and brands are prioritizing earned media, and they're beginning to build their own news networks, going direct to their customers. And so that's a trend we see, and I, you know, we're right in the middle of it, Eric, so you know we're going to, you mentioned RSA, I think that's perhaps going to be one of those crazy ones that continues to grow. It's shrunk, and then it, you know, 'cause last year- >> Yeah, it did shrink. >> right, it was the last one before the pandemic, and then they sort of made another run at it last year. It was smaller but it was very vibrant, and I think this year's going to be huge. Global World Congress is another one, we're going to be there end of Feb. That's obviously a big big show, but in general, the brands and the technology vendors, even Oracle is going to scale down. I don't know about Salesforce. We'll see. You had a couple of bonus predictions. Quantum and maybe some others? Bring us home. >> Yeah, sure. I got a few more. I think we touched upon one, but I definitely think the data prep tools are facing extinction, unfortunately, you know, the Talons Informatica is some of those names. The problem there is that the BI tools are kind of including data prep into it already. You know, an example of that is Tableau Prep Builder, and then in addition, Advanced NLP is being worked in as well. ThoughtSpot, Intelius, both often say that as their selling point, Tableau has Ask Data, Click has Insight Bot, so you don't have to really be intelligent on data prep anymore. A regular business user can just self-query, using either the search bar, or even just speaking into what it needs, and these tools are kind of doing the data prep for it. I don't think that's a, you know, an out in left field type of prediction, but it's the time is nigh. The other one I would also state is that I think knowledge graphs are going to break through this year. Neo4j in our survey is growing in pervasion in Mindshare. So more and more people are citing it, AWS Neptune's getting its act together, and we're seeing that spending intentions are growing there. Tiger Graph is also growing in our survey sample. I just think that the time is now for knowledge graphs to break through, and if I had to do one more, I'd say real-time streaming analytics moves from the very, very rich big enterprises to downstream, to more people are actually going to be moving towards real-time streaming, again, because the data prep tools and the data pipelines have gotten easier to use, and I think the ROI on real-time streaming is obviously there. So those are three that didn't make the cut, but I thought deserved an honorable mention. >> Yeah, I'm glad you did. Several weeks ago, we did an analyst prediction roundtable, if you will, a cube session power panel with a number of data analysts and that, you know, streaming, real-time streaming was top of mind. So glad you brought that up. Eric, as always, thank you very much. I appreciate the time you put in beforehand. I know it's been crazy, because you guys are wrapping up, you know, the last quarter survey in- >> Been a nuts three weeks for us. (laughing) >> job. I love the fact that you're doing, you know, the ETS survey now, I think it's quarterly now, right? Is that right? >> Yep. >> Yep. So that's phenomenal. >> Four times a year. I'll be happy to jump on with you when we get that done. I know you were really impressed with that last time. >> It's unbelievable. This is so much data at ETR. Okay. Hey, that's a wrap. Thanks again. >> Take care Dave. Good seeing you. >> All right, many thanks to our team here, Alex Myerson as production, he manages the podcast force. Ken Schiffman as well is a critical component of our East Coast studio. Kristen Martin and Cheryl Knight help get the word out on social media and in our newsletters. And Rob Hoof is our editor-in-chief. He's at siliconangle.com. He's just a great editing for us. Thank you all. Remember all these episodes that are available as podcasts, wherever you listen, podcast is doing great. Just search "Breaking analysis podcast." Really appreciate you guys listening. I publish each week on wikibon.com and siliconangle.com, or you can email me directly if you want to get in touch, david.vellante@siliconangle.com. That's how I got all these. I really appreciate it. I went through every single one with a yellow highlighter. It took some time, (laughing) but I appreciate it. You could DM me at dvellante, or comment on our LinkedIn post and please check out etr.ai. Its data is amazing. Best survey data in the enterprise tech business. This is Dave Vellante for theCube Insights, powered by ETR. Thanks for watching, and we'll see you next time on "Breaking Analysis." (upbeat music beginning) (upbeat music ending)

(gentle music playing) >> For centuries, we've been captivated by the concept of machines doing the job of humans. And over the past decade or so, we've really focused on AI and the possibility of intelligent machines that can perform cognitive tasks. Now in the past few years, with the popularity of machine learning models ranging from recent ChatGPT to Bert, we're starting to see how AI is changing the way we interact with the world. How is AI transforming the way we do business? And what does the future hold for us there. At theCube, we've covered Oracle's AI and ML strategy for years, which has really been used to drive automation into Oracle's autonomous database. We've talked a lot about MySQL HeatWave in database machine learning, and AI pushed into Oracle's business apps. Oracle, it tends to lead in AI, but not competing as a direct AI player per se, but rather embedding AI and machine learning into its portfolio to enhance its existing products, and bring new services and offerings to the market. Now, last October at Cloud World in Las Vegas, Oracle partnered with Nvidia, which is the go-to AI silicon provider for vendors. And they announced an investment, a pretty significant investment to deploy tens of thousands more Nvidia GPUs to OCI, the Oracle Cloud Infrastructure and build out Oracle's infrastructure for enterprise scale AI. Now, Oracle CEO, Safra Catz said something to the effect of this alliance is going to help customers across industries from healthcare, manufacturing, telecoms, and financial services to overcome the multitude of challenges they face. Presumably she was talking about just driving more automation and more productivity. Now, to learn more about Oracle's plans for AI, we'd like to welcome in Elad Ziklik, who's the vice president of AI services at Oracle. Elad, great to see you. Welcome to the show. >> Thank you. Thanks for having me. >> You're very welcome. So first let's talk about Oracle's path to AI. I mean, it's the hottest topic going for years you've been incorporating machine learning into your products and services, you know, could you tell us what you've been working on, how you got here? >> So great question. So as you mentioned, I think most of the original four-way into AI was on embedding AI and using AI to make our applications, and databases better. So inside mySQL HeatWave, inside our autonomous database in power, we've been driving AI, all of course are SaaS apps. So Fusion, our large enterprise business suite for HR applications and CRM and ELP, and whatnot has built in AI inside it. Most recently, NetSuite, our small medium business SaaS suite started using AI for things like automated invoice processing and whatnot. And most recently, over the last, I would say two years, we've started exposing and bringing these capabilities into the broader OCI Oracle Cloud infrastructure. So the developers, and ISVs and customers can start using our AI capabilities to make their apps better and their experiences and business workflow better, and not just consume these as embedded inside Oracle. And this recent partnership that you mentioned with Nvidia is another step in bringing the best AI infrastructure capabilities into this platform so you can actually build any type of machine learning workflow or AI model that you want on Oracle Cloud. >> So when I look at the market, I see companies out there like DataRobot or C3 AI, there's maybe a half dozen that sort of pop up on my radar anyway. And my premise has always been that most customers, they don't want to become AI experts, they want to buy applications and have AI embedded or they want AI to manage their infrastructure. So my question to you is, how does Oracle help its OCI customers support their business with AI? >> So it's a great question. So I think what most customers want is business AI. They want AI that works for the business. They want AI that works for the enterprise. I call it the last mile of AI. And they want this thing to work. The majority of them don't want to hire a large and expensive data science teams to go and build everything from scratch. They just want the business problem solved by applying AI to it. My best analogy is Lego. So if you think of Lego, Lego has these millions Lego blocks that you can use to build anything that you want. But the majority of people like me or like my kids, they want the Lego death style kit or the Lego Eiffel Tower thing. They want a thing that just works, and it's very easy to use. And still Lego blocks, you still need to build some things together, which just works for the scenario that you're looking for. So that's our focus. Our focus is making it easy for customers to apply AI where they need to, in the right business context. So whether it's embedding it inside the business applications, like adding forecasting capabilities to your supply chain management or financial planning software, whether it's adding chat bots into the line of business applications, integrating these things into your analytics dashboard, even all the way to, we have a new platform piece we call ML applications that allows you to take a machine learning model, and scale it for the thousands of tenants that you would be. 'Cause this is a big problem for most of the ML use cases. It's very easy to build something for a proof of concept or a pilot or a demo. But then if you need to take this and then deploy it across your thousands of customers or your thousands of regions or facilities, then it becomes messy. So this is where we spend our time making it easy to take these things into production in the context of your business application or your business use case that you're interested in right now. >> So you mentioned chat bots, and I want to talk about ChatGPT, but my question here is different, we'll talk about that in a minute. So when you think about these chat bots, the ones that are conversational, my experience anyway is they're just meh, they're not that great. But the ones that actually work pretty well, they have a conditioned response. Now they're limited, but they say, which of the following is your problem? And then if that's one of the following is your problem, you can maybe solve your problem. But this is clearly a trend and it helps the line of business. How does Oracle think about these use cases for your customers? >> Yeah, so I think the key here is exactly what you said. It's about task completion. The general purpose bots are interesting, but as you said, like are still limited. They're getting much better, I'm sure we'll talk about ChatGPT. But I think what most enterprises want is around task completion. I want to automate my expense report processing. So today inside Oracle we have a chat bot where I submit my expenses the bot ask a couple of question, I answer them, and then I'm done. Like I don't need to go to our fancy application, and manually submit an expense report. I do this via Slack. And the key is around managing the right expectations of what this thing is capable of doing. Like, I have a story from I think five, six years ago when technology was much inferior than it is today. Well, one of the telco providers I was working with wanted to roll a chat bot that does realtime translation. So it was for a support center for of the call centers. And what they wanted do is, Hey, we have English speaking employees, whatever, 24/7, if somebody's calling, and the native tongue is different like Hebrew in my case, or Chinese or whatnot, then we'll give them a chat bot that they will interact with and will translate this on the fly and everything would work. And when they rolled it out, the feedback from customers was horrendous. Customers said, the technology sucks. It's not good. I hate it, I hate your company, I hate your support. And what they've done is they've changed the narrative. Instead of, you go to a support center, and you assume you're going to talk to a human, and instead you get a crappy chat bot, they're like, Hey, if you want to talk to a Hebrew speaking person, there's a four hour wait, please leave your phone and we'll call you back. Or you can try a new amazing Hebrew speaking AI powered bot and it may help your use case. Do you want to try it out? And some people said, yeah, let's try it out. Plus one to try it out. And the feedback, even though it was the exact same technology was amazing. People were like, oh my God, this is so innovative, this is great. Even though it was the exact same experience that they hated a few weeks earlier on. So I think the key lesson that I picked from this experience is it's all about setting the right expectations, and working around the right use case. If you are replacing a human, the level is different than if you are just helping or augmenting something that otherwise would take a lot of time. And I think this is the focus that we are doing, picking up the tasks that people want to accomplish or that enterprise want to accomplish for the customers, for the employees. And using chat bots to make those specific ones better rather than, hey, this is going to replace all humans everywhere, and just be better than that. >> Yeah, I mean, to the point you mentioned expense reports. I'm in a Twitter thread and one guy says, my favorite part of business travel is filling out expense reports. It's an hour of excitement to figure out which receipts won't scan. We can all relate to that. It's just the worst. When you think about companies that are building custom AI driven apps, what can they do on OCI? What are the best options for them? Do they need to hire an army of machine intelligence experts and AI specialists? Help us understand your point of view there. >> So over the last, I would say the two or three years we've developed a full suite of machine learning and AI services for, I would say probably much every use case that you would expect right now from applying natural language processing to understanding customer support tickets or social media, or whatnot to computer vision platforms or computer vision services that can understand and detect objects, and count objects on shelves or detect cracks in the pipe or defecting parts, all the way to speech services. It can actually transcribe human speech. And most recently we've launched a new document AI service. That can actually look at unstructured documents like receipts or invoices or government IDs or even proprietary documents, loan application, student application forms, patient ingestion and whatnot and completely automate them using AI. So if you want to do one of the things that are, I would say common bread and butter for any industry, whether it's financial services or healthcare or manufacturing, we have a suite of services that any developer can go, and use easily customized with their own data. You don't need to be an expert in deep learning or large language models. You could just use our automobile capabilities, and build your own version of the models. Just go ahead and use them. And if you do have proprietary complex scenarios that you need customer from scratch, we actually have the most cost effective platform for that. So we have the OCI data science as well as built-in machine learning platform inside the databases inside the Oracle database, and mySQL HeatWave that allow data scientists, python welding people that actually like to build and tweak and control and improve, have everything that they need to go and build the machine learning models from scratch, deploy them, monitor and manage them at scale in production environment. And most of it is brand new. So we did not have these technologies four or five years ago and we've started building them and they're now at enterprise scale over the last couple of years. >> So what are some of the state-of-the-art tools, that AI specialists and data scientists need if they're going to go out and develop these new models? >> So I think it's on three layers. I think there's an infrastructure layer where the Nvidia's of the world come into play. For some of these things, you want massively efficient, massively scaled infrastructure place. So we are the most cost effective and performant large scale GPU training environment today. We're going to be first to onboard the new Nvidia H100s. These are the new super powerful GPU's for large language model training. So we have that covered for you in case you need this 'cause you want to build these ginormous things. You need a data science platform, a platform where you can open a Python notebook, and just use all these fancy open source frameworks and create the models that you want, and then click on a button and deploy it. And it infinitely scales wherever you need it. And in many cases you just need the, what I call the applied AI services. You need the Lego sets, the Lego death style, Lego Eiffel Tower. So we have a suite of these sets for typical scenarios, whether it's cognitive services of like, again, understanding images, or documents all the way to solving particular business problems. So an anomaly detection service, demand focusing service that will be the equivalent of these Lego sets. So if this is the business problem that you're looking to solve, we have services out there where we can bring your data, call an API, train a model, get the model and use it in your production environment. So wherever you want to play, all the way into embedding this thing, inside this applications, obviously, wherever you want to play, we have the tools for you to go and engage from infrastructure to SaaS at the top, and everything in the middle. >> So when you think about the data pipeline, and the data life cycle, and the specialized roles that came out of kind of the (indistinct) era if you will. I want to focus on two developers and data scientists. So the developers, they hate dealing with infrastructure and they got to deal with infrastructure. Now they're being asked to secure the infrastructure, they just want to write code. And a data scientist, they're spending all their time trying to figure out, okay, what's the data quality? And they're wrangling data and they don't spend enough time doing what they want to do. So there's been a lack of collaboration. Have you seen that change, are these approaches allowing collaboration between data scientists and developers on a single platform? Can you talk about that a little bit? >> Yeah, that is a great question. One of the biggest set of scars that I have on my back from for building these platforms in other companies is exactly that. Every persona had a set of tools, and these tools didn't talk to each other and the handoff was painful. And most of the machine learning things evaporate or die on the floor because of this problem. It's very rarely that they are unsuccessful because the algorithm wasn't good enough. In most cases it's somebody builds something, and then you can't take it to production, you can't integrate it into your business application. You can't take the data out, train, create an endpoint and integrate it back like it's too painful. So the way we are approaching this is focused on this problem exactly. We have a single set of tools that if you publish a model as a data scientist and developers, and even business analysts that are seeing a inside of business application could be able to consume it. We have a single model store, a single feature store, a single management experience across the various personas that need to play in this. And we spend a lot of time building, and borrowing a word that cellular folks used, and I really liked it, building inside highways to make it easier to bring these insights into where you need them inside applications, both inside our applications, inside our SaaS applications, but also inside custom third party and even first party applications. And this is where a lot of our focus goes to just because we have dealt with so much pain doing this inside our own SaaS that we now have built the tools, and we're making them available for others to make this process of building a machine learning outcome driven insight in your app easier. And it's not just the model development, and it's not just the deployment, it's the entire journey of taking the data, building the model, training it, deploying it, looking at the real data that comes from the app, and creating this feedback loop in a more efficient way. And that's our focus area. Exactly this problem. >> Well thank you for that. So, last week we had our super cloud two event, and I had Juan Loza on and he spent a lot of time talking about how open Oracle is in its philosophy, and I got a lot of feedback. They were like, Oracle open, I don't really think, but the truth is if you think about database Oracle database, it never met a hardware platform that it didn't like. So in that sense it's open. So, but my point is, a big part of of machine learning and AI is driven by open source tools, frameworks, what's your open source strategy? What do you support from an open source standpoint? >> So I'm a strong believer that you don't actually know, nobody knows where the next slip fog or the next industry shifting innovation in AI is going to come from. If you look six months ago, nobody foreseen Dali, the magical text to image generation and the exploding brought into just art and design type of experiences. If you look six weeks ago, I don't think anybody's seen ChatGPT, and what it can do for a whole bunch of industries. So to me, assuming that a customer or partner or developer would want to lock themselves into only the tools that a specific vendor can produce is ridiculous. 'Cause nobody knows, if anybody claims that they know where the innovation is going to come from in a year or two, let alone in five or 10, they're just wrong or lying. So our strategy for Oracle is to, I call this the Netflix of AI. So if you think about Netflix, they produced a bunch of high quality shows on their own. A few years ago it was House of Cards. Last month my wife and I binge watched Ginny and Georgie, but they also curated a lot of shows that they found around the world and bought them to their customers. So it started with things like Seinfeld or Friends and most recently it was Squid games and those are famous Israeli TV series called Founder that Netflix bought in, and they bought it as is and they gave it the Netflix value. So you have captioning and you have the ability to speed the movie and you have it inside your app, and you can download it and watch it offline and everything, but nobody Netflix was involved in the production of these first seasons. Now if these things hunt and they're great, then the third season or the fourth season will get the full Netflix production value, high value budget, high value location shooting or whatever. But you as a customer, you don't care whether the producer and director, and screenplay writing is a Netflix employee or is somebody else's employee. It is fulfilled by Netflix. I believe that we will become, or we are looking to become the Netflix of AI. We are building a bunch of AI in a bunch of places where we think it's important and we have some competitive advantage like healthcare with Acellular partnership or whatnot. But I want to bring the best AI software and hardware to OCI and do a fulfillment by Oracle on that. So you'll get the Oracle security and identity and single bill and everything you'd expect from a company like Oracle. But we don't have to be building the data science, and the models for everything. So this means both open source recently announced a partnership with Anaconda, the leading provider of Python distribution in the data science ecosystem where we are are doing a joint strategic partnership of bringing all the goodness into Oracle customers as well as in the process of doing the same with Nvidia, and all those software libraries, not just the Hubble, both for other stuff like Triton, but also for healthcare specific stuff as well as other ISVs, other AI leading ISVs that we are in the process of partnering with to get their stuff into OCI and into Oracle so that you can truly consume the best AI hardware, and the best AI software in the world on Oracle. 'Cause that is what I believe our customers would want the ability to choose from any open source engine, and honestly from any ISV type of solution that is AI powered and they want to use it in their experiences. >> So you mentioned ChatGPT, I want to talk about some of the innovations that are coming. As an AI expert, you see ChatGPT on the one hand, I'm sure you weren't surprised. On the other hand, maybe the reaction in the market, and the hype is somewhat surprising. You know, they say that we tend to under or over-hype things in the early stages and under hype them long term, you kind of use the internet as example. What's your take on that premise? >> So. I think that this type of technology is going to be an inflection point in how software is being developed. I truly believe this. I think this is an internet style moment, and the way software interfaces, software applications are being developed will dramatically change over the next year two or three because of this type of technologies. I think there will be industries that will be shifted. I think education is a good example. I saw this thing opened on my son's laptop. So I think education is going to be transformed. Design industry like images or whatever, it's already been transformed. But I think that for mass adoption, like beyond the hype, beyond the peak of inflected expectations, if I'm using Gartner terminology, I think certain things need to go and happen. One is this thing needs to become more reliable. So right now it is a complete black box that sometimes produce magic, and sometimes produce just nonsense. And it needs to have better explainability and better lineage to, how did you get to this answer? 'Cause I think enterprises are going to really care about the things that they surface with the customers or use internally. So I think that is one thing that's going to come out. And the other thing that's going to come out is I think it's going to come industry specific large language models or industry specific ChatGPTs. Something like how OpenAI did co-pilot for writing code. I think we will start seeing this type of apps solving for specific business problems, understanding contracts, understanding healthcare, writing doctor's notes on behalf of doctors so they don't have to spend time manually recording and analyzing conversations. And I think that would become the sweet spot of this thing. There will be companies, whether it's OpenAI or Microsoft or Google or hopefully Oracle that will use this type of technology to solve for specific very high value business needs. And I think this will change how interfaces happen. So going back to your expense report, the world of, I'm going to go into an app, and I'm going to click on seven buttons in order to get some job done like this world is gone. Like I'm going to say, hey, please do this and that. And I expect an answer to come out. I've seen a recent demo about, marketing in sales. So a customer sends an email that is interested in something and then a ChatGPT powered thing just produces the answer. I think this is how the world is going to evolve. Like yes, there's a ton of hype, yes, it looks like magic and right now it is magic, but it's not yet productive for most enterprise scenarios. But in the next 6, 12, 24 months, this will start getting more dependable, and it's going to change how these industries are being managed. Like I think it's an internet level revolution. That's my take. >> It's very interesting. And it's going to change the way in which we have. Instead of accessing the data center through APIs, we're going to access it through natural language processing and that opens up technology to a huge audience. Last question, is a two part question. And the first part is what you guys are working on from the futures, but the second part of the question is, we got data scientists and developers in our audience. They love the new shiny toy. So give us a little glimpse of what you're working on in the future, and what would you say to them to persuade them to check out Oracle's AI services? >> Yep. So I think there's two main things that we're doing, one is around healthcare. With a new recent acquisition, we are spending a significant effort around revolutionizing healthcare with AI. Of course many scenarios from patient care using computer vision and cameras through automating, and making better insurance claims to research and pharma. We are making the best models from leading organizations, and internal available for hospitals and researchers, and insurance providers everywhere. And we truly are looking to become the leader in AI for healthcare. So I think that's a huge focus area. And the second part is, again, going back to the enterprise AI angle. Like we want to, if you have a business problem that you want to apply here to solve, we want to be your platform. Like you could use others if you want to build everything complicated and whatnot. We have a platform for that as well. But like, if you want to apply AI to solve a business problem, we want to be your platform. We want to be the, again, the Netflix of AI kind of a thing where we are the place for the greatest AI innovations accessible to any developer, any business analyst, any user, any data scientist on Oracle Cloud. And we're making a significant effort on these two fronts as well as developing a lot of the missing pieces, and building blocks that we see are needed in this space to make truly like a great experience for developers and data scientists. And what would I recommend? Get started, try it out. We actually have a shameless sales plug here. We have a free deal for all of our AI services. So it typically cost you nothing. I would highly recommend to just go, and try these things out. Go play with it. If you are a python welding developer, and you want to try a little bit of auto mail, go down that path. If you're not even there and you're just like, hey, I have these customer feedback things and I want to try out, if I can understand them and apply AI and visualize, and do some cool stuff, we have services for that. My recommendation is, and I think ChatGPT got us 'cause I see people that have nothing to do with AI, and can't even spell AI going and trying it out. I think this is the time. Go play with these things, go play with these technologies and find what AI can do to you or for you. And I think Oracle is a great place to start playing with these things. >> Elad, thank you. Appreciate you sharing your vision of making Oracle the Netflix of AI. Love that and really appreciate your time. >> Awesome. Thank you. Thank you for having me. >> Okay. Thanks for watching this Cube conversation. This is Dave Vellante. We'll see you next time. (gentle music playing)

>> TheCUBE presents Ignite 22 brought to you by Palo Alto Networks. >> Welcome back to Las Vegas, everyone. We're glad you're with us. This is theCUBE live at Palo Alto Ignite 22 at the MGM Grant in Las Vegas. Lisa Martin here with Dave Vellante, day one of our coverage. We've had great conversations. The cybersecurity landscape is so interesting Dave, it's such a challenging problem to solve but it's so diverse and dynamic at the same time. >> You know, Lisa theCUBE started in May of 2010 in Boston. We called it the chowder event, chowder and Lobster. It was a EMC world, 2010. BJ Jenkins, who's here, of course, was a longtime friend of theCUBE and made the, made the transition into from, well, it's still data, data to, to cyber. So >> True. And BJ is back with us. BJ Jenkins, president Palo Alto Networks great to have you back on theCUBE. >> It is great to be here in person on theCube >> Isn't it great? >> In Vegas. It's awesome. >> And we can tell by your voice will be, will be gentle. You, you've been in Vegas typical Vegas occupational hazard of losing the voice. >> Yeah. It was one of the benefits of Covid. I didn't lose my voice at home sitting talking to a TV. You lose it when you come to Vegas. >> Exactly. >> But it's a small price to pay. >> So things kick off yesterday with the partner summit. You had a keynote then, you had a customer, a CISO on stage. You had a keynote today, which we didn't get to see. But talk to us a little bit about the lay of the land. What are you hearing from CISOs, from CIOs as we know security is a board level conversation. >> Yeah, I, you know it's been an interesting three or four months here. Let me start with that. I think, cybersecurity in general is still front and center on CIOs and CISO's minds. It has to be, if you saw Wendy's presentation today and the threats out there companies have to have it front and center. I do think it's been interesting though with the macro uncertainty. We've taken to calling this year the revenge of the CFO and you know these deals in cybersecurity are still a top priority but they're getting finance and procurements, scrutiny which I think in this environment is a necessity but it's still a, you know, number one number two imperative no matter who you talked to, in my mind >> It was interesting what Nikesh was saying in the last conference call that, hey we just have to get more approvals. We know this. We're, we're bringing more go-to-market people on board. We, we have, we're filling the pipeline 'cause we know they're going to split up deals big deals go into smaller chunks. So the question I have for you is is how are you able to successfully integrate those people so that you can get ahead of that sort of macro transition? >> Yeah I, you know, I think there's two things I'd say about uncertain macro situations and Dave, you know how old I am. I'm pretty old. I've been through a lot of cycles. And in those cycles I've always found stronger companies with stronger value proposition separate themselves actually in uncertain, economic times. And so I think there's actually an opportunity here. The message tilts a little bit though where it's been about innovation and new threat vectors to one of you have 20, 30, 40 vendors you can consolidate become more effective in your security posture and save money on your TCOs. So one of the things as we bring people on board it's training them on that business value proposition. How do you take a customer who's got 20 or 30 tools take 'em down to 5 or 10 where Palo is more central and strategic and be able to demonstrate that value. So we do that through, we're making a huge investment in our people but macroeconomic times also puts some stronger people back on the market and we're able to incorporate them into the business. >> What are the conditions that are necessary for that consolidation? Like I would imagine if you're, if you're a big customer of a big, you know, competitor of yours that that migration is going to be harder than if you're dealing with lots of little point tools. Do those, do those point tools, are they sort of is it the end of the subscription? Is it just stuff that's off the books now? What's, the condition that is ripe for that kind of consolidation? >> Look, I think the challenge coming into this year was skills. And so customers had all of these point products. It required a lot more human intervention as Nikesh was talking about to integrate them or make them work. And as all of us know finding people with cybersecurity skills over the last 12 months has been incredibly hard. That drove, if you know, if you think about that a CIO and a CISO sitting there going, I have all all this investment in tools. I don't have the people to operate 'em. What do I need to do? What we tried to do is elevate that conversation because in a customer, everybody who's bought one of those, they they bought it to solve a problem. And there's people with affinity for that tool. They're not just going to say I want to get consolidated and give up my tool. They're going to wrap their arms around it. And so what we needed to do and this changed our ecosystem strategy too how we leverage partners. We needed to get into the CIO and CISO and say look at this chaos you have here and the challenges around people that it's, it's presenting you. We can help solve that by, by standardizing, consolidating taking that integration away from you as Nikesh talked about, and making it easier for your your high skill people to work on high skill, you know high challenges in there. >> Let chaos reign, and then reign in the chaos. >> Yes. >> Andy Grove. >> I was looking at some stats that there's 26 million developers but less than 3 million cybersecurity professionals. >> Talked about that skills gap and what CISOs and CIOs are facing is do you consider from a value prop perspective Palo Alto Networks to be a, a facilitator of helping organizations deal with that skills gap? >> I think there's a short term and a long term. I think Nikesh today talked about the long term that we'll never win this battle with human beings. We're going to have to win it with automation. That, that's the long term the short term right here and now is that people need people with cybersecurity skills. Now what we're trying to do, you know, is multifaceted. We work with universities to standardize programs to develop skills that people can come into the marketplace with. We run our own programs inside the company. We have a cloud academy program now where we take people high aptitude for sales and technical aptitude and we will put them through a six month boot camp on cloud and they'll come out of that ready to really work with the leading experts in cloud security. The third angle is partners, right, there are partners in the marketplace who want to drive their business into high services areas. They have people, they know how to train. We give them, we partner with them to give them training. Hopefully that helps solve some of the short-term gaps that are out there today. >> So you made the jump from data storage to security and >> Yeah. >> You know, network security, all kinds of security. What was that like? What you must have learned a lot in the last better part of a decade? >> Yeah. >> Take us through that. >> You know, so the first jump was from EMC. I was 15 years there to be CEO of Barracuda. And you know, it was interesting because EMC was, you know large enterprise for the most part. At Barracuda we had, you know 250,000 small and mid-size enterprises. And it was, it's interesting to get into security in small and mid-size businesses because, you know Wendy today was talking about nation states. For small and mid-size business, it's common thievery right? It's ransomware, it's, and, those customers don't have, you know, the human and financial resources to keep up with the threat factor. So, you know, Nikesh talked about how it's taken 'em four and a half years to get into cybersecurity. I remember my first week at Barracuda, I was talking with a customer who had, you know, breached data shut down. There wasn't much bitcoin back then so it was just a pure ransom. And I'm like, wow, this is, you know, incredible industry. So it's been a good, you know, transition for me. I still think data is at the heart of all of this. Right? And I have always believed there's a strong connection between the things I learned growing up at EMC and what I put into practice today at Palo Alto Networks. >> And how about a culture because I, you know I know have observed the EMC culture >> Yeah. >> And you were there in really the heyday. >> Yeah. >> Right? Which was an awesome place. And it seems like Palo Alto obviously, different times but you know, similar like laser focus on solving problems, you know, obviously great, you know value sellers, you know, you guys aren't the commodity >> Yeah. For Product. But there seemed to be some similarities from afar. I don't know Palo Alto as well as I know EMC. >> I think there's a lot. When I joined EMC, it was about, it was 2 billion in in revenue and I think when I left it was over 20, 20, 21. And, you know, we're at, you know hopefully 5, 5 5 in revenue. I feel like it's this very similar, there's a sense of urgency, there's an incredible focus on the customer. you know, Near and Moche are definitely different individuals but the both same kind of disruptive, Israeli force out there driving the business. There are a lot of similarities. I, you know, the passion, I feel privileged as a, you know go to market person that I have this incredible portfolio to go, you know, work with customers on. It's a lucky position to be in, but very I feel like it is a movie I've seen before. >> Yeah. And but, and the course, the challenges from the, the target that you're disrupting is different. It was, you know, EMC had a lot of big, you know IBM obviously was, you know, bigger target whereas you got thousands of, you know, smaller companies. >> Yes. >> And, and so that's a different dynamic but that's why the consolidation play is so important. >> Look at, that's why I joined Palo Alto Networks when I was at Barracuda for nine years. It just fascinated me, that there was 3000 plus players in security and why didn't security evolve like the storage market did or the server market or network where working >> Yeah, right. >> You know, two or three big gorillas came to, to dominate those markets. And it's, I think it's what Nikesh talked about today. There was a new problem in best of breed. It was always best of breed. You can never in security go in and, you know, say, Hey it's good I saved us some money but I got the third best product in the marketplace. And there was that kind of gap between products. I, believe in why I joined here I think this is my last gig is we have a chance to change that. And this is the first company as I look from the outside in that had best of breed as, you know Nikesh said 13 categories. >> Yeah. >> And you know, we're in the leaders quadrant and it's a conversation I have with customers. You don't have to sacrifice best of breed but get the benefits of a platform. And I, think that resonates today. I think we have a chance to change the industry from that viewpoint. >> Give us a little view of the voice of the customer. You had, was it Sabre? >> Yeah. >> That was on >> Scott Moser, The CISO from Sabre. >> Give us a view, what are you hearing from the voice of the customer? Obviously they're quite a successful customer but challenges, concerns, the partnership. >> Yeah. Look, I think security is similar to industries where we come up with magic marketing phrases and, you know, things to you know, make you want to procure our solutions. You know, zero trust is one. And you know, you'll talk to customers and they're like, okay, yes. And you know, the government, right? Joe, Joe Biden's putting out zero trust executive orders. And the, the problem is if you talk to customers, it's a journey. They have legacy infrastructure they have business drivers that you know they just don't deal with us. They've got to deal with the business side who's trying to make the money that keeps the, the company going. it's really helped them draw a map from where they're at today to zero trust or to a better security architecture. Or, you know, they're moving their apps into the cloud. How am I going to migrate? Right? Again, that discussion three years ago was around lift and shift, right? Today it's about, well, no I need cloud native developed apps to service the business the way I want to, I want to service it. How do I, so I, I think there's this element of a trusted partner and relationship. And again, I think this is why you can't have 40 or 50 of those. You got to start narrowing it down if you want to be able to meet and beat the threats that are out there for you. So I, you know, the customers, I see a lot of 'em. It's, here's where I'm at help me get here to a better position. And they know it's, you know Scott said in our keynote today, you don't just, you know have layer three firewall policies and decide, okay tomorrow I'm going to go to layer seven. That, that's not how it works. Right? There's, and, and by the way these things are a mission critical type areas. So there's got to be a game plan that you help customers go through to get there. >> Definitely. Last question, my last question for you is, is security being a board level conversation I was reading some stats from a survey I think it was the what's new in Cypress survey that that Palo Alto released today that showed that while significant numbers of organizations think they've got a cyber resiliency playbook, there's a lot of disconnect or lack of alignment at the boardroom. Are you in those conversations? How can you help facilitate that alignment between the executive team and the board when it comes to security being so foundational to any business? >> Yeah, it's, I've been on three, four public company boards. I'm on, I'm on two today. I would say four years ago, this was a almost a taboo topic. It was a, put your head in the sand and pray to God nothing happened. And you know, the world has changed significantly. And because of the number of breaches the impact it's had on brand, boards have to think about this in duty of care and their fiduciary duty. Okay. So then you start with a board that may not have the technical skills. The first problem the security industry had is how do I explain your risk profile in a way you can understand it. I'm, I'm on the board of Generac that makes home generators. It's a manufacturing, you know, company but they put Wifi modules in their boxes so that the dealers could help do the maintenance on 'em. And all of a sudden these things were getting attacked. Right? And they're being used for bot attacks. >> Yeah. >> Everybody on their board had a manufacturing background. >> Ah. >> So how do you help that board understand the risk they have that's what's changed over the last four years. It's a constant discussion. It's one I have with CISOs where they're like help us put it in layman's terms so they understand they know what we're doing and they feel confident but at the same time understand the marketplace better. And that's a journey for us. >> That Generac example is a great one because, you know, think about IOT Technologies. They've historically been air gaped >> Yes. >> By design. And all of a sudden the business comes in and says, "Hey we can put wifi in there", you know >> Connect it to a home Wifi system that >> Make our lives so much easier. Next thing you know, it's being used to attack. >> Yeah. >> So that's why, as you go around the world are you discerning, I know you were just in Japan are you discerning significant differences in sort of attitudes toward, towards cyber? Whether it's public policy, you know things like regulation where you, they don't want you sharing data, but as as a cyber company, you want to share that data with you know, public and private? >> Look it, I, I think around the world we see incredible government activity first of all. And I think given the position we're in we get to have some unique conversations there. I would say worldwide security is an imperative. I, no matter where I go, you know it's in front of everybody's mind. The, on the, the governance side, it's really what do we need to adapt to make sure we meet local regulations. And I, and I would just tell you Dave there's ways when you do that, and we talk with governments that because of how they want to do it reduce our ability to give them full insight into all the threats and how we can help them. And I do think over time governments understand that we can anonymize the data. There's, but that, that's a work in process. Definitely there is a balance. We need to have privacy, we need to have, you know personal security for people. But there's ways to collect that data in an anonymous way and give better security insight back into the architectures that are out there. >> All right. A little shift the gears here. A little sports question. We've had some great Boston's sports guests on theCUBE right? I mean, Randy Seidel, we were talking about him. Peter McKay, Snyk, I guess he's a competitor now but you know, there's no question got >> He got a little funding today. I saw that. >> Down round. But they still got a lot of money. Not of a down round, but they were, but yeah, but actually, you know, he was on several years ago and it was around the time they were talking about trading Brady. He said Never trade Brady. And he got that right. We, I think we can agree Brady's the goat. >> Yes. >> The big question I have for you is, Belichick. Do you ever question Has your belief in him as the greatest coach of all time wavered, you know, now that- No. Okay. >> Never. >> Weigh in on that. >> Never, he says >> Still the Goat. >> I'll give you my best. You know, never In Bill we trust. >> Okay. Still. >> All right >> I, you know, the NFL is a unique property that's designed for parody and is designed, I mean actively designed to not let Mr. Craft and Bill Belichick do what they do every year. I feel privileged as a Boston sports fan that in our worst years we're in the seventh playoff spot. And I have a lot of family in Chicago who would kill for that position, by the way. And you know, they're in perpetual rebuilding. And so look, and I think he, you know the way he's been able to manage the cap and the skill levels, I think we have a top five defense. There's different ways to win titles. And if I, you know, remember in Brady's last title with Boston, the defense won us that Super Bowl. >> Well thanks for weighing in on that because there's a lot of crazy talk going on. Like, 'Hey, if he doesn't beat Arizona, he's got to go.' I'm like, what? So, okay, I'm sometimes it takes a good good loyal fan who's maybe, you know, has >> The good news in Boston is we're emotional fans too so I understand you got to keep the long term long term in mind. And we're, we're in a privileged position in Boston. We've got Celtics, we've got Bruins we've got the Patriots right on the edge of the playoffs and we need the Red Sox to get to work. >> Yeah, no, you know they were last, last year so maybe they're going to win it all like they usually do. So >> Fingers crossed. >> Crazy worst to first. >> Exactly. Well you said, in Bill we trust it sounds like from our conversation in BJ we trust from the customers, the partners. >> I hope so. >> Thank you so much BJ, for coming back on theCUBE giving us the lay of the land, what's new, the voice of the customer and how Palo Alto was really differentiated in the market. We always appreciate your, coming on the show you >> Honor and privilege seeing you here. Thanks. >> You may be thinking that you were watching ESPN just now but you know, we call ourselves the ESPN at Tech News. This is Lisa Martin for Dave Vellante and our guest. You're watching theCUBE, the Leader and live emerging in enterprise tech coverage. (upbeat music)

>>Hello and run. Welcome back to the Cube's live coverage here. Day three of Cube's coverage, two sets, wall to wall coverage. Third set upstairs in the Executive Briefing Center. I'm John Furry, host of the Cube with Dave Alon. Two other hosts here. Lot of action. Dave. The cheer here is the CEO of MongoDB, exclusive post on Silicon Angle for your prior to the event. Thanks for doing that. Great to see >>You. Likewise. Nice to see you >>Coming on. See you David. So it's great to catch up. Prior to the event for that exclusive story on ecosystem, your perspective that resonated with a lot of the people. The traffic on that post and comments have been off the charts. I think we're seeing a ecosystem kind of surge and not change over, but like a an and ISV and new platform. So I really appreciate your perspective as a platform ISV for aws. What's it like? What's this event like? What's your learnings? What's your takeaway from your customers here this year? What's the most important story going on? >>First of all, I think being here is important for us because we have so many customers and partners here. In fact, if you look at the customers that Amazon themselves announced about two thirds of those customers or MongoDB customers. So we have a huge overlap in customers here. So just connecting with customers and partners has been important. Obviously a lot of them are thinking about their plans going to next year. So we're kind of meeting with them to think about what their priorities are and how we can help. And also we're sharing a little bit of our product roadmap in terms of where we're going and helping them think through like how they can best use Mongadi B as they think about their data strategy, you know, going to next year. So it's been a very productive end. We have a lot of people here, a lot of sales people, a lot of product people, and there's tons of customers here. So we can get a lot accomplished in a few days. >>Dave and I always talk on the cube. Well, Dave always goes to the TAM expansion question. Expanding your total stressful market, the market is changing and you guys have a great position growing positioned. How do you look at the total addressable market for Mongo changing? Where's the growth gonna come from? How do you see your role in the market and how does that impact your current business model? >>Yeah, our whole goal is to really enable developers to think about Mongo, to be first when they're building modern applications. So what we've done is first built a fir, a first class transactional platform and now we've kind expanding the platform to do things like search and analytics, right? And so we are really offering a broad set of capabilities. Now our primary focus is the developer and helping developers build these amazing applications and giving them tools to really do so in a very quick way. So if you think about customers like Intuit, customers like Canva, customers like, you know, Verizon, at and t, you know, who are just using us to really transform their business. It's either to build new applications quickly to do things at a certain level of performance of scale they've never done before. And so really enabling them to do so much more in building these next generation applications that they can build anywhere else. >>So I was listening to McDermott, bill McDermott this morning. Yeah. And you listen to Bill, you just wanna buy from the guy, right? He's amazing. But he was basically saying, look, companies like he was talking about ServiceNow that could help organizations digitally transform, et cetera, but make money or save money or in a good position. And I said, right, Mongo's definitely one of those companies. What are those conversations like here? I know you've been meeting with customers, it's a different environment right now. There's a lot of uncertainty. I, I was talking to one of your customers said, yeah, I'm up for renewal. I love Mongo. I'm gonna see if they can stage my payments a little bit. You know, things like that. Are those conversations? Yeah, you know, similar to what >>You having, we clearly customers are getting a little bit more prudent, but we haven't seen any kind of like slow down terms of deal cycles or, or elongated sales cycles. I mean, obviously different customers in different sectors are going through different issues. What we are seeing customers think about is like how can I, you know, either drive more efficiency in my business like and big part of that is modernization of my existing legacy tech stack. How can maybe consolidate to a fewer set of vendors? I think they like our broad platform story. You know, rather than using three or four different databases, they can use MongoDB to do everything. So that that resonates with customers and the fact that they can move fast, right? Developer productivity is a proxy for innovation. And so being able to move fast to either seize new opportunities or respond to new threats is really, you know, top of mind for still C level executive. >>So can your software, you're right, consolidation is the number one way in which people are save money. Can your software be deflationary? I mean, I mean that in a good way. So >>I was just meeting with a customer who was thinking about Mongo for their transactional platform, elastic for the search platform and like a graph database for a special use case. And, and we said you can do all that on MongoDB. And he is like, oh my goodness, I can consolidate everything. Have one elegant developer interface. I can keep all the data in one place. I can easily access that data. And that makes so much more sense than having to basically use a bunch of peace parts. And so that's, that's what we're seeing more and more interest from customers about. >>So one of the things I want to get your reaction to is, I was saying on the cube, now you can disagree with me if you want, but at, in the cloud native world at Cuban and Kubernetes was going through its hype cycle. The conversation went to it's getting boring. And that's good cause they want it to be boring. They don't want people to talk about the run time. They want it to be working. Working is boring. That's invisible. It's good, it's sticky, it's done. As you guys have such a great sticky business model, you got a great install base. Mongo works, people are happy, they like the product. So it's kind of working, I won't wanna say boring cuz that's, it's irrelevant. What's the exciting things that Mongo's bringing on top of the existing base of product that is gonna really get your clients and prospects enthused about the innovation from Mongo? What's what cuz it's, it's almost like electricity in a way. You guys are very utility in, in the way you do, but it's growing. But is there an exciting element coming that you see that they should pay attention to? What's, what's your >>Vision that, right, so if you look back over the last 10, 15 years, there's been big two big platform shifts, mobile and cloud. I think the next big platform shift is from what I call dumb apps to smart apps. So building more intelligence into applications. And what that means is automating human decision making and embedding that into applications. So we believe that to be a fundamentally a developer problem to solve, yes, you need data scientist to build the machine learning algorithms to train the models. Yeah. But ultimately you can't really deploy, deployed at scale unless you give developers the tools to build those smart applications that what we focused on. And a big part of that is what we call application driven analytics where people or can, can embed that intelligence into applications so that they can instead rather having humans involved, they can make decisions faster, drive to businesses more quickly, you know, shorten it's short and time to market, et cetera. >>And so your strategy to implement those smart apps is to keep targeting the developer Yes. And build on that >>Base. Correct. Exactly. So we wanna essentially democratize the ability for any customer to use our tools to build a smart applications where they don't have the resources of a Google or you know, a large tech company. And that's essentially resonating with our customer base. >>We, we were talking about this earlier after Swami's keynote, is most companies struggle to put data at the core of their business. And I don't mean centralizing it all in a single place as data's everywhere, but, but really organizing their company and democratizing data so people can make data decisions. So I think what you're saying, essentially Atlas is the platform that you're gonna inject intelligence into and allow developers to then build applications that are, you know, intelligent, smart with ai, machine intelligence, et cetera. And that's how the ones that don't have the resources of a Google or an Amazon become correct the, that kind of AI company if >>You, and that's, that's the whole purpose of a developer data platform is to enable them to have the tools, you know, to have very sophisticated analytics, to have the ability to do very sophisticated indexes, optimized for analytics, the ability to use data lakes for very efficient storage and retrieval of data to leverage, you know, edge devices to be able to capture and synchronize data. These are all critical elements to build these next generation applications. And you have to do that, but you don't want to stitch together a thousand primitives. You want to have a platform to do that. And that's where we really focus. >>You know, Dave, Dave and I, three, two days, Dave and I, Dave Ante and I have been talking a lot about developer productivity. And one observation that's now validated is that developers are setting the pace for innovation. Correct? And if you look at the how they, the language that they speak, it's not the same language as security departments, right? They speak almost like different languages, developer and security, and then you got data language. But the developers are making choices of self-service. They can accelerate, they're driving the behavior behavior into the organizations. And this is one of the things I wrote about on Friday last week was the organizational changes are changing cuz the developers set the pace. You can't force tooling down their throat. They're gonna go with what's easy, what's workable. If you believe that to be true, then all the security's gonna be in the developer pipeline. All the innovations we've driven off that high velocity developer site, we're seeing success of security being embedded there with the developers. What are you gonna bring up to that developer layer that's going to help with security, help with maybe even new things, >>Right? So, you know, it's, it's almost a cliche to say now software is in the world, right? Because every company's value props is driven by, it's either enabled to find or created through software. What that really means is that developers are eating all the work, right? And you're seeing, you saw in DevOps, right? Where developers basically enro encroach into the ops world and made infrastructure a programmable interface. You see developers, to your point, encroaching in security, embedding more and more security features into their applications. We believe the same thing's gonna happen with data scientists and business analysts where developers are gonna embed that functionality that was done by different domains in the Alex world and embed that capability into apps themselves. So these applications are just naturally smarter. So you don't need someone to look at a dashboard and say, aha, there's some insight here now I need to go make a decision. The application will do that for you and actually make that decision for you so you can move that much more quickly to run your business either more efficiently or to drive more, you know, revenue. >>Well the interesting thing about your business is cuz you know, you got a lot of transactional activity going on and the data, the way I would say what you just described is the data stack and the application stacks are coming together, right? And you're in a really good position, I think to really affect that. You think about we've, we've operationalized so many systems, we really haven't operationalized our data systems. And, and particularly as you guys get more into analytics, it becomes an interesting, you know, roadmap for Mongo and your customers. How do you see that? >>Yeah, so I wanna be clear, we're not trying to be a data warehouse, I get it. We're not trying to be like, you know, go compete. In fact, we have nice partnership with data bricks and so forth. What we are really trying to do is enable developers to instrument and build these applications that embed analytics. Like a good analogy I'd use is like Google Maps. You think about how sophisticated Google Maps has, and I use that because everyone has used Google Maps. Yeah. Like in the old, I was old enough to print out the directions, map quest exactly, put it on my lap and drive and look down. Now have this device that tells me, you know, if there's a traffic, if there's an accident, if there's something you know, going will reroute me automatically. And what that app is doing is embedding real time data into, into its decision making and making the decision for you so that you don't have to think about which road to take. Right? You, you're gonna see that happen across almost every application over the next X number of years where these applications are gonna become so much smarter and make these decisions for you. So you can just move so much more quickly. >>Yeah. Talk about the company, what status of the company, your growth plans. Obviously you're seeing a lot of news and Salesforce co CEO just resigned, layoffs at cnn, layoffs at DoorDash. You know, tech unfortunately is not impacted, thank God. I'm not that too bad. Certainly in cloud's not impacted it is impacting some of the buying behavior. We talked about that. What's going on with the company head count? What's your goals? How's the team doing? What are your priorities? >>Right? So we we're going after a big, big opportunity. You know, we recognize, obviously the market's a little choppy right now, but our long term, we're very bullish on the opportunity. We believe that we can be the modern developer data platform to build these next generation applications in terms of costs. We're obviously being a little bit more judicious about where we're investing, but we see big, big opportunities for us. And so our overall cost base will grow next year. But obviously we also recognize that there's ways to drive more efficiency. We're at a scale now. We're a 1.2 billion business. We're gonna announce our Q3 results next week. So we'll talk a little bit more about, you know, what we're seeing in the business next week. But we, we think we're a business that's growing fast. You know, we grew, you know, over 50, 50% and so, so we're pretty fast growing business. Yeah. You see? >>Yeah, Tuesday, December 6th you guys announce Exactly. Course is a big, we always watch and love it. So, so what I'm hearing is you're not, you're not stepping on the brakes, you're still accelerating growth, but not at all costs. >>Correct. The term we're using is profitable growth. We wanna, you know, you know, drive the business in a way that we think continues to seize the opportunity. But we also, we always exercise discipline. You know, I, I'm old enough where I had to deal with 2000 and 2008, so, you know, seen the movie before, I'm not 28 and have not seen these markets. And so obviously some are, you know, emerging leaders have not seen these kinds of markets before. So we're kind of helping them think about how to continue to be disciplined. And >>I like that reference to two thousand.com bubble and the financial crisis of 2008. I mentioned this to you when we chat, I'd love to get your thoughts. Now looking back for reinvent, Amazon wasn't a force in, in 2008. They weren't really that big debt yet. Know impact agility, wasn't it? They didn't hit that, they didn't hit that cruising altitude of the value pro cloud agility, time of value moving fast. Now they are. So this is the first time that they're a part of the economic equation. You're on, you're on in the middle of it with Amazon. They could be a catalyst to recover faster if plan properly. What's your CEO take on just that general and other CEOs might be watching and saying, Hey, you know, if I play this right, I could leverage the cloud. You know, Adams is leading into the cloud during a recession. Okay, I get that. But specifically there might be a tactic. What's your view on >>That? I mean, what, what we're seeing the, the hyperscalers do is really continue to kind of compete at the raw infrastructure level on storage, on compute, on network performance, on security to provide the, the kind of the building blocks for companies like Monga Beach really build on. So we're leveraging that price performance curve that they're pushing. You know, they obviously talk about Graviton three, they're talking about their training model chip sets and their inference model chip sets and their security chip sets. Which is great for us because we can leverage those capabilities to build upon that. And I think, you know, if you had asked me, you know, in 2008, would we be talking about chip sets in 2022? I'd probably say, oh, we're way beyond that. But what it really speaks to is those things are still so profoundly important. And I think that's where you can see Amazon and Google and Microsoft compete to provide the best underlying infrastructure where companies like mongadi we can build upon and we can help customers leverage that to really build the next generation. >>I'm not saying it's 2008 all over again, but we have data from 2008 that was the first major tailwind for the cloud. Yeah. When the CFO said we're going from CapEx to opex. So we saw that. Now it's a lot different now it's a lot more mature >>I think. I think there's a fine tuning trend going on where people are right sizing, fine tuning, whatever you wanna call it. But a craft is coming. A trade craft of cloud management, cloud optimization, managing the cost structures, tuning, it's a crafting, it's more of a craft. It's kind of seems like we're >>In that era, I call it cost optimization, that people are looking to say like, I know I'm gonna invest but I wanna be rational and more thoughtful about where I invest and why and with whom I invest with. Versus just like, you know, just, you know, everyone getting a 30% increase in their opex budgets every year. I don't think that's gonna happen. And so, and that's where we feel like it's gonna be an opportunity for us. We've kind of hit scap velocity. We've got the developer mind share. We have 37,000 customers of all shapes and sizes across the world. And that customer crown's only growing. So we feel like we're a place where people are gonna say, I wanna standardize among the >>Db. Yeah. And so let's get a great quote in his keynote, he said, if you wanna save money, the place to do it is in the cloud. >>You tighten the belt, which belt you tightening? The marketplace belt, the wire belt. We had a whole session on that. Tighten your belt thing. David Chair, CEO of a billion dollar company, MongoDB, continue to grow and grow and continue to innovate. Thanks for coming on the cube and thanks for participating in our stories. >>Thanks for having me. Great to >>Be here. Thank. Okay, I, Dave ante live on the show floor. We'll be right back with our final interview of the day after this short break, day three coming to close. Stay with us. We'll be right back.

>>Hey everyone, it's Vegas. Welcome back. We know you've been watching all day. We appreciate that. We always love being able to bring you some great content on the Cube Live from AWS Reinvented 22. Lisa Martin here with Paul Gill. And Paul, we've had such a great event. We've, I think we've done nearly 70 interviews since we started on the Cube on >>Monday night. I believe we just hit 70. Yeah, we just hit 70. You must feel like you've done half of >>Them. I really do. But we've been having great conversations. There's so much innovation going on at aws. Nothing slowed them down during the pandemic. We love also talking about the innovation, the flywheel that is their partner ecosystem. We're gonna have a great conversation about that >>Next. And as we've said, going back to day one, the energy of the show is remarkable. And here we are, we're getting late in the afternoon on day two, and there's just as much activity, just as much energy out there as, as the beginning of the first day. I have no doubt day three will be the >>Same. I agree. There's been no slowdown. We've got two guests here. We're gonna have a great conversation. Chuck Kubota joins us, senior Director of Cloud Services, GTM at Red Hat. Great to have you on the program. And Ted Stanton, global head of Sales, red Hat at IBM at aws. Welcome. >>Thanks for having us. >>How's the show going so far for you guys? >>It's a blur. Is it? Oh my gosh. >>Don't they all >>Blur? Well, yes, yes. I actually like last year a bit better. It was half the size. Yeah. And a lot easier to get around, but this is back to normal, so >>It is back to normal. Yeah. And and Ted, we're hearing north of 50,000 in-person attendees. I heard a, something I think was published. I heard the second hand over like 300,000 online attendees. This is maybe the biggest one we ever had. >>Yeah, yeah, I would agree. And frankly, it's my first time here, so I am massively impressed with the overall show, the meeting with partners, the meeting with customers, the announcements that were made, just fantastic. And >>If you remember back to two years ago, there were a lot of questions about whether in-person conferences would ever return and the volume that we used to see them. And that appears to be >>The case. I think we, I think we've answered, I think AWS has answered that for us, which I'm very pleased to see. Talk about some of those announcements. Ted. There's been so much that that's always one of the things we know and love about re men is there's slew of announcements. You were saying this morning, Paul, and then keynote, you lost, you stopped counting after I >>Lost 15, I lost count for 15. I think it was over 30 announcements this morning alone >>Where IBM and Red Hat are concern. What are some of the things that you are excited about in terms of some of the news, the innovation, and where the partnership is going? >>Well, definitely where the partnership is going, and I think even as we're speaking right now, is a keynote going on with Aruba, talking about some of the partners and the way in which we support partners and the new technologies and the new abilities for partners to take advantage of these technologies to frankly delight our customers is really what most excites me. >>Chuck, what about you? What's going on with Red Hat? You've been there a long time. Sales, everything, picking up customers, massively transforming. What are some of the things that you're seeing and that you're excited >>About? Yeah, I mean, first of all, you know, as customers have, you know, years ago discovered it's not competitively advantageous to manage their own data centers in most cases. So they would like to, you know, give that responsibility to Amazon. We're seeing them move further up the stack, right? So that would be more beyond the operating system, the application platforms like OpenShift. And now we have a managed application platform built on OpenShift called Red Out OpenShift service on AWS or Rosa. And then we're even further going up the stack with that with, we just announced this week that red out OpenShift data science is available in the AWS marketplace, runs on Rosa, helps break the land speed record to getting those data models out there that are so important to make, you know, help organizations become more, much more data driven to remain competitive themselves. >>So talk about Rosa and how it differs from previous iterations of, of OpenShift. I mean, you had, you had an online version of OpenShift several years ago. What's different about Rosa? >>Yeah, so the old OpenShift online that was several years old, right? For one thing, wasn't a joint partnership between Amazon and Red Hat. So we work together, right? Very closely on this, which is great. Also, the awesome thing about Rosa, you know, if you think about like OpenShift for, for, as a matter of fact, Amazon is the number one cloud that OpenShift runs on, right? So a lot of those customers want to take advantage of their committed spins, their EDPs, they want one bill. And so Rosa comes through the one bill comes through the marketplace, right? Which is, which is totally awesome. Not only that or financially backing OpenShift with a 99.95% financially backed sla, right? We didn't have that before either, right? >>When you say financially backed sla, >>What do you mean? That means that if we drop below 99.95% of availability, we're gonna give you some money back, right? So we're really, you know, for lack of better words, putting our money where our mouth is. Absolutely right. >>And, and some of the key reasons that we even work together to build Rosa was frankly we've had a mirror of customers and virtually every single region, every single industry been using OpenShift on AWS for years, right? And we listened to them, they wanted a more managed version of it and we worked very closely together. And what's really great about Rosa too is we built some really fantastic integrations with some of the AWS native services like API gateway, Amazon rds, private link, right? To make it very simple and easy for customers to get started. We talked a little bit about the marketplace, but it's also available just on the AWS console, right? So customers can get started in a pay as you go fashion start to use it. And if they wanna move into a more commitment, more of a set schedule of payments, they can move into a marketplace private offer. >>Chuck, talk about, how about Rosen? How is unlocking the power of technology like containers Kubernetes for customers while dialing down some of the complexity that's >>There? Yeah, I mean if you think about, you know, kind of what we did, you know, earlier on, right? If you think about like virtualization, how it dialed down the complexity of having to get something rack, get a blade rack, stack cable and cooled every time you wanted to deploy new application, right? So what we do is we, our message is this, we want developers to focus on what matters most. And that's build, deploy, and running applications. Most of our customers are not in the business of building app platforms. They're not in the business of building platforms like banks, I, you know, financials, right? Government, et cetera. Right? So what we do is we allow those developers that are, enable those developers that know Java and Node and springing and what have you, just to keep writing what they know. And then, you know, I don't wanna get too technical here, but get pushed through way and, and OpenShift takes care of the rest, builds it for them, runs it through a pipeline, a CICD pipeline, goes through all the testing and quality gates and things like that, deploys it, auto wires it up, you know, to monitoring which is what you need. >>And we have all kinds of other, you know, higher order services and an ecosystem around that. And oh, by the way, also plugging into and taking advantage of the services like rds, right? If you're gonna write an application, a tradition, a cloud native application on Amazon, you're probably going to wanna run it in Rosa and consuming one of those databases, right? Like RDS or Aurora, what have you. >>And I, and I would say it's not even just the customers. We have a variety of ecosystem partners, both of our partners leveraging it as well. We have solos built their executive management system that they go ahead and turn and sell to their customers, streamlines data and collects data from a variety of different sources. They decided, you know, it's better to run that on top of Rosa than manage OpenShift themselves. We've seen IBM restack a lot of their software, you know, to run on top of Rose, take advantage of that capabilities. So lots of partners as well as customers are taking advantage of fully managed stack of that OpenShift that that turnkey capabilities that it provides >>For, for OpenShift customers who wanna move to Rose, is that gonna be a one button migration? Is that gonna be, can they run both environments simultaneously and migrate over time? What kind of tools are you giving them? >>We have quite, we have quite a few migration tools such as conveyor, right? That's one of our projects, part of our migration application toolkit, right? And you know, with those, there's also partners like Trilio, right? Who can help move, you know, applications back 'em up. In fact, we're working on a pretty cool joint go to market with that right now. But generally speaking, the OpenShift experience that the customers that we have know and love and those who have never used OpenShift either are coming to it as well via Rosa, right? The experience is primarily the same. You don't have to really retrain your people, right? If anything, there's a reduction in operational cost. We increase developer productivity cuz we manage so much of the stack for you. We have SRE site reliability engineers that are backing the platform that proactively get ahead of anything that may go wrong. So maybe you don't even notice if something went wrong, wrong. And then also reactively fixing it if it comes to that, right? So, you know, all those kind of things that your customers are having to do on their own or hire a contractor, a consultant, what have to do Now we benefit from a managed offering in the cloud, right? In Amazon, right? And your developers still have that great experience too, like to say, you know, again, break the land speed record to prod. >>I >>Like that. And, and I would actually say migrations from OpenShift are on premise. OpenShift to Rosa maybe only represents about a third of the customers we have. About another third of the customers is frankly existing AWS customers. Maybe they're doing Kubernetes, do it, the, you know, do it themselves. We're struggling with some of the management of that. And so actually started to lean on top of using Rosa as a better platform to actually build upon their applications. And another third, we have quite a few customers that were frankly new OpenShift customers, new Red Hat customers and new AWS customers that were looking to build that next cloud native application. Lots of in the startup space that I've actually chosen to go with Rosa. >>It's funny you mention that because the largest Rosa consumer is new to OpenShift. Oh wow. Right. That's pretty, that's pretty powerful, right? It's not just for existing OpenShift customers, existing OpenShift. If you're running OpenShift, you know, on EC two, right. Self-managed, there's really no better way to run it than Rosa. You know, I think about whether this is the 10th year, 10 year anniversary of re right? Right. Yep. This is also the 10 year anniversary of OpenShift. Yeah, right. I think it one oh came out about sometime around a week, 10 years ago, right? When I came over to Red Hat in 2015. You know, if you, if you know your Kubernetes history was at July 25th, I think was when Kubernetes ga, July 25th, 2015 is when it g you have >>A good >>Memory. Well I remember those days back then, right? Those were fun, right? The, we had a, a large customer roll out on OpenShift three, which is our OpenShift RE based on Kubernetes. And where do you think they ran Amazon, right? Naturally. So, you know, as you move forward and, and, and OpenShift V four came out, the, reduces the operational complexity and becomes even more powerful through our operator framework and things like that. Now they revolved up to Rosa, right? And again, to help those customers focus on what matters most. And that's the applications, not the containers, not those underlying implementation and technical details while critically important, are not necessarily core to the business to most of our customers. >>Tremendous amount of innovation in OpenShift in a decade, >>Pardon me? >>Tremendous amount of innovation in OpenShift in the >>Last decade. Oh absolutely. And, and and tons more to come like every day. Right. I think what you're gonna see more of is, you know, as Kubernetes becomes more, more and more of the plumbing, you know, I call 'em productive abstractions on top of it, as you mentioned earlier, unlocking the power of these technologies while minimizing, even hiding the complexity of them so that you can just move fast Yeah. And safely move fast. >>I wanna be sure we get to, to marketplaces because you have been, red Hat has made, has really stepped up as commitment to the AWS marketplace. Why are you doing that now and how are, how are the marketplaces evolving as a channel for you? >>Well, cuz our customers want us to be there, right? I mean we, we, we are customer centric, customer first approach. Our customers want to buy through the marketplace. If you're an Amazon, if you're an Amazon customer, it's really easy for you to go procure software through the marketplace and have, instead of having to call up Red Hat and get on paper and write a second check, right? One stop shop one bill. Right? That is very, very attractive to our customers. Not only that, it opens up other ways to buy, you know, Ted mentioned earlier, you know, pay as you go buy the drink pricing using exactly what you need right now. Right? You know, AWS pioneered that, right? That provides that elasticity, you know, one of the core tenants at aws, AWS cloud, right? And we weren't able to get that with the traditional self-managed on Red Hat paper subscriptions. >>Talk a little bit about the go to market, what's, you talked about Ted, the kind of the three tenants of, of customer types. But talk a little bit about the gtm, the joint go to market, the joint engineering, so we get an understanding of how customers engage multiple options. >>Yeah, I mean, so if you think about go to market, you know, and the way I think of it is it's the intersection of a few areas, right? So the product and the product experience that we work together has to be so good that a customer or user, actually many start talk, talking about users now cuz it's self-service has a more than likely chance of getting their application to prod without ever talking to a person. Which is historically not what a lot of enterprise software companies are able to do, right? So that's one of those biggest things we do. We want customers to just be successful, turn it on, get going, be productive, right? At the same time we wanna to position the product in such a way that's differentiating that you can't get that experience anywhere else. And then part of that is ensuring that the education and enablement of our customers and our partners as such that they use the platform the right way to get as much value out of as possible. >>All backed by, you know, a very smart field that ensures that the customer get is making the right decision. A customer success org, this is attached to my org now that we can go on site and team with our customers to make sure that they get their first workloads up as quickly as possible, by the way, on our date, our, our dime. And then SRE and CEA backing that up with support and operational integrity to ensure that the service is always up and available so you can sleep, sleep, sleep well at night. Right? Right. One of our PMs of, of of Rosa, he says, what does he say? He says, Rosa allows organizations, enables organizations to go from 24 7 operations to nine to five innovation. Right? And that's powerful. That's how our customers remain more competitive running on Rosa with aws, >>When you're in customer conversations and you have 30 seconds, what are the key differentiators of the solution that you go boom, boom, boom, and they just go, I get it. >>Well, I mean, my 32nd elevator pitch, I think I've already said, I'll say it again. And that is OpenShift allows you to focus on your applications, build, deploy, and run applications while unlocking the power of the technologies like containers and Kubernetes and hiding or minimizing those complexities. So you can do as fast as possible. >>Mic drop Ted, question for you? Sure. Here we are at the, this is the, I leave the 11th reinvent, 10th anniversary, 11th event. You've been in the industry a long time. What is your biggest takeaway from what's been announced and discussed so far at Reinvent 22, where the AWS and and its partner ecosystem is concerned? If you had 30 seconds or if you had a bumper sticker to put on your DeLorean, what would you say? >>I would say we're continuing to innovate on behalf of our customers, but making sure we bring all of our partners and ecosystems along in that innovation. >>Yeah. I love the customer obsession on both sides there. Great work guides. Congrats on the 10th anniversary of OpenShift and so much evolution, the customer obsession is really clear for both of you guys. We appreciate your time. You're gonna have to come back now. Absolutely. Absolutely. Thank you. All right. Thank you so much for joining us. For our guests and for Paul Gillin. I'm Lisa Martin. You're watching The Cube, the leader in live enterprise and emerging tech coverage.

(soft techno upbeat music) >> Hi there. Welcome back to Las Vegas. This is Dave Villante with Paul Gillon. Reinvent day one and a half. We started last night, Monday, theCUBE after dark. Now we're going wall to wall. Today. Today was of course the big keynote, Adam Selipsky, kind of the baton now handing, you know, last year when he did his keynote, he was very new. He was sort of still getting his feet wet and finding his guru swing. Settling in a little bit more this year, learning a lot more, getting deeper into the tech, but of course, sharing the love with other leaders like Peter DeSantis. Tomorrow's going to be Swamy in the keynote. Adrian Cockcroft is here. Former AWS, former network Netflix CTO, currently an analyst. You got your own firm now. You're out there. Great to see you again. Thanks for coming on theCUBE. >> Yeah, thanks. >> We heard you on at Super Cloud, you gave some really good insights there back in August. So now as an outsider, you come in obviously, you got to be impressed with the size and the ecosystem and the energy. Of course. What were your thoughts on, you know what you've seen so far, today's keynotes, last night Peter DeSantis, what stood out to you? >> Yeah, I think it's great to be back at Reinvent again. We're kind of pretty much back to where we were before the pandemic sort of shut it down. This is a little, it's almost as big as the, the largest one that we had before. And everyone's turned up. It just feels like we're back. So that's really good to see. And it's a slightly different style. I think there were was more sort of video production things happening. I think in this keynote, more storytelling. I'm not sure it really all stitched together very well. Right. Some of the stories like, how does that follow that? So there were a few things there and some of there were spelling mistakes on the slides, you know that ELT instead of ETL and they spelled ZFS wrong and something. So it just seemed like there was, I'm not quite sure just maybe a few things were sort of rushed at the last minute. >> Not really AWS like, was it? It's kind of remind the Patriots Paul, you know Bill Belichick's teams are fumbling all over the place. >> That's right. That's right. >> Part of it may be, I mean the sort of the market. They have a leader in marketing right now but they're going to have a CMO. So that's sort of maybe as lack of a single threaded leader for this thing. Everything's being shared around a bit more. So maybe, I mean, it's all fixable and it's mine. This is minor stuff. I'm just sort of looking at it and going there's a few things that looked like they were not quite as good as they could have been in the way it was put together. Right? >> But I mean, you're taking a, you know a year of not doing Reinvent. Yeah. Being isolated. You know, we've certainly seen it with theCUBE. It's like, okay, it's not like riding a bike. You know, things that, you know you got to kind of relearn the muscle memories. It's more like golf than is bicycle riding. >> Well I've done AWS keynotes myself. And they are pretty much scrambled. It looks nice, but there's a lot of scrambling leading up to when it actually goes. Right? And sometimes you can, you sometimes see a little kind of the edges of that, and sometimes it's much more polished. But you know, overall it's pretty good. I think Peter DeSantis keynote yesterday was a lot of really good meat there. There was some nice presentations, and some great announcements there. And today I was, I thought I was a little disappointed with some of the, I thought they could have been more. I think the way Andy Jesse did it, he crammed more announcements into his keynote, and Adam seems to be taking sort of a bit more of a measured approach. There were a few things he picked up on and then I'm expecting more to be spread throughout the rest of the day. >> This was more poetic. Right? He took the universe as the analogy for data, the ocean for security. Right? The Antarctic was sort of. >> Yeah. It looked pretty, >> yeah. >> But I'm not sure that was like, we're not here really to watch nature videos >> As analysts and journalists, You're like, come on. >> Yeah, >> Give it the meat >> That was kind the thing, yeah, >> It has always been the AWS has always been Reinvent has always been a shock at our approach. 100, 150 announcements. And they're really, that kind of pressure seems to be off them now. Their position at the top of the market seems to be unshakeable. There's no clear competition that's creeping up behind them. So how does that affect the messaging you think that AWS brings to market when it doesn't really have to prove that it's a leader anymore? It can go after maybe more of the niche markets or fix the stuff that's a little broken more fine tuning than grandiose statements. >> I think so AWS for a long time was so far out that they basically said, "We don't think about the competition, we are listen to the customers." And that was always the statement that works as long as you're always in the lead, right? Because you are introducing the new idea to the customer. Nobody else got there first. So that was the case. But in a few areas they aren't leading. Right? You could argue in machine learning, not necessarily leading in sustainability. They're not leading and they don't want to talk about some of these areas and-- >> Database. I mean arguably, >> They're pretty strong there, but the areas when you are behind, it's like they kind of know how to play offense. But when you're playing defense, it's a different set of game. You're playing a different game and it's hard to be good at both. I think and I'm not sure that they're really used to following somebody into a market and making a success of that. So there's something, it's a little harder. Do you see what I mean? >> I get opinion on this. So when I say database, David Foyer was two years ago, predicted AWS is going to have to converge somehow. They have no choice. And they sort of touched on that today, right? Eliminating ETL, that's one thing. But Aurora to Redshift. >> Yeah. >> You know, end to end. I'm not sure it's totally, they're fully end to end >> That's a really good, that is an excellent piece of work, because there's a lot of work that it eliminates. There's are clear pain points, but then you've got sort of the competing thing, is like the MongoDB and it's like, it's just a way with one database keeps it simple. >> Snowflake, >> Or you've got on Snowflake maybe you've got all these 20 different things you're trying to integrate at AWS, but it's kind of like you have a bag of Lego bricks. It's my favorite analogy, right? You want a toy for Christmas, you want a toy formula one racing car since that seems to be the theme, right? >> Okay. Do you want the fully built model that you can play with right now? Or do you want the Lego version that you have to spend three days building. Right? And AWS is the Lego technique thing. You have to spend some time building it, but once you've built it, you can evolve it, and you'll still be playing those are still good bricks years later. Whereas that prebuilt to probably broken gathering dust, right? So there's something about having an vulnerable architecture which is harder to get into, but more durable in the long term. And so AWS tends to play the long game in many ways. And that's one of the elements that they do that and that's good, but it makes it hard to consume for enterprise buyers that are used to getting it with a bow on top. And here's the solution. You know? >> And Paul, that was always Andy Chassy's answer to when we would ask him, you know, all these primitives you're going to make it simpler. You see the primitives give us the advantage to turn on a dime in the marketplace. And that's true. >> Yeah. So you're saying, you know, you take all these things together and you wrap it up, and you put a snowflake on top, and now you've got a simple thing or a Mongo or Mongo atlas or whatever. So you've got these layered platforms now which are making it simpler to consume, but now you're kind of, you know, you're all stuck in that ecosystem, you know, so it's like what layer of abstractions do you want to tie yourself to, right? >> The data bricks coming at it from more of an open source approach. But it's similar. >> We're seeing Amazon direct more into vertical markets. They spotlighted what Goldman Sachs is doing on their platform. They've got a variety of platforms that are supposedly targeted custom built for vertical markets. How do successful do you see that play being? Is this something that the customers you think are looking for, a fully integrated Amazon solution? >> I think so. There's usually if you look at, you know the MongoDB or data stacks, or the other sort of or elastic, you know, they've got the specific solution with the people that really are developing the core technology, there's open source equivalent version. The AWS is running, and it's usually maybe they've got a price advantage or it's, you know there's some data integration in there or it's somehow easier to integrate but it's not stopping those companies from growing. And what it's doing is it's endorsing that platform. So if you look at the collection of databases that have been around over the last few years, now you've got basically Elastic Mongo and Cassandra, you know the data stacks as being endorsed by the cloud vendors. These are winners. They're going to be around for a very long time. You can build yourself on that architecture. But what happened to Couch base and you know, a few of the other ones, you know, they don't really fit. Like how you going to bait? If you are now becoming an also ran, because you didn't get cloned by the cloud vendor. So the customers are going is that a safe place to be, right? >> But isn't it, don't they want to encourage those partners though in the name of building the marketplace ecosystem? >> Yeah. >> This is huge. >> But certainly the platform, yeah, the platform encourages people to do more. And there's always room around the edge. But the mainstream customers like that really like spending the good money, are looking for something that's got a long term life to it. Right? They're looking for a long commitment to that technology and that it's going to be invested in and grow. And the fact that the cloud providers are adopting and particularly AWS is adopting some of these technologies means that is a very long term commitment. You can base, you know, you can bet your future architecture on that for a decade probably. >> So they have to pick winners. >> Yeah. So it's sort of picking winners. And then if you're the open source company that's now got AWS turning up, you have to then leverage it and use that as a way to grow the market. And I think Mongo have done an excellent job of that. I mean, they're top level sponsors of Reinvent, and they're out there messaging that and doing a good job of showing people how to layer on top of AWS and make it a win-win both sides. >> So ever since we've been in the business, you hear the narrative hardware's going to die. It's just, you know, it's commodity and there's some truth to that. But hardware's actually driving good gross margins for the Cisco's of the world. Storage companies have always made good margins. Servers maybe not so much, 'cause Intel sucked all the margin out of it. But let's face it, AWS makes most of its money. We know on compute, it's got 25 plus percent operating margins depending on the seasonality there. What do you think happens long term to the infrastructure layer discussion? Okay, commodity cloud, you know, we talk about super cloud. Do you think that AWS, and the other cloud vendors that infrastructure, IS gets commoditized and they have to go up market or you see that continuing I mean history would say that still good margins in hardware. What are your thoughts on that? >> It's not commoditizing, it's becoming more specific. We've got all these accelerators and custom chips now, and this is something, this almost goes back. I mean, I was with some micro systems 20,30 years ago and we developed our own chips and HP developed their own chips and SGI mips, right? We were like, the architectures were all squabbling of who had the best processor chips and it took years to get chips that worked. Now if you make a chip and it doesn't work immediately, you screwed up somewhere right? It's become the technology of building these immensely complicated powerful chips that has become commoditized. So the cost of building a custom chip, is now getting to the point where Apple and Amazon, your Apple laptop has got full custom chips your phone, your iPhone, whatever and you're getting Google making custom chips and we've got Nvidia now getting into CPUs as well as GPUs. So we're seeing that the ability to build a custom chip, is becoming something that everyone is leveraging. And the cost of doing that is coming down to startups are doing it. So we're going to see many, many more, much more innovation I think, and this is like Intel and AMD are, you know they've got the compatibility legacy, but of the most powerful, most interesting new things I think are going to be custom. And we're seeing that with Graviton three particular in the three E that was announced last night with like 30, 40% whatever it was, more performance for HPC workloads. And that's, you know, the HPC market is going to have to deal with cloud. I mean they are starting to, and I was at Supercomputing a few weeks ago and they are tiptoeing around the edge of cloud, but those supercomputers are water cold. They are monsters. I mean you go around supercomputing, there are plumbing vendors on the booth. >> Of course. Yeah. >> Right? And they're highly concentrated systems, and that's really the only difference, is like, is it water cooler or echo? The rest of the technology stack is pretty much off the shelf stuff with a few tweets software. >> You point about, you know, the chips and what AWS is doing. The Annapurna acquisition. >> Yeah. >> They're on a dramatically different curve now. I think it comes down to, again, David Floyd's premise, really comes down to volume. The arm wafer volumes are 10 x those of X 86, volume always wins. And the economics of semis. >> That kind of got us there. But now there's also a risk five coming along if you, in terms of licensing is becoming one of the bottlenecks. Like if the cost of building a chip is really low, then it comes down to licensing costs and do you want to pay the arm license And the risk five is an open source chip set which some people are starting to use for things. So your dis controller may have a risk five in it, for example, nowadays, those kinds of things. So I think that's kind of the the dynamic that's playing out. There's a lot of innovation in hardware to come in the next few years. There's a thing called CXL compute express link which is going to be really interesting. I think that's probably two years out, before we start seeing it for real. But it lets you put glue together entire rack in a very flexible way. So just, and that's the entire industry coming together around a single standard, the whole industry except for Amazon, in fact just about. >> Well, but maybe I think eventually they'll get there. Don't use system on a chip CXL. >> I have no idea whether I have no knowledge about whether going to do anything CXL. >> Presuming I'm not trying to tap anything confidential. It just makes sense that they would do a system on chip. It makes sense that they would do something like CXL. Why not adopt the standard, if it's going to be as the cost. >> Yeah. And so that was one of the things out of zip computing. The other thing is the low latency networking with the elastic fabric adapter EFA and the extensions to that that were announced last night. They doubled the throughput. So you get twice the capacity on the nitro chip. And then the other thing was this, this is a bit technical, but this scalable datagram protocol that they've got which basically says, if I want to send a message, a packet from one machine to another machine, instead of sending it over one wire, I consider it over 16 wires in parallel. And I will just flood the network with all the packets and they can arrive in any order. This is why it isn't done normally. TCP is in order, the packets come in order they're supposed to, but this is fully flooding them around with its own fast retry and then they get reassembled at the other end. So they're not just using this now for HPC workloads. They've turned it on for TCP for just without any change to your application. If you are trying to move a large piece of data between two machines, and you're just pushing it down a network, a single connection, it takes it from five gigabits per second to 25 gigabits per second. A five x speed up, with a protocol tweak that's run by the Nitro, this is super interesting. >> Probably want to get all that AIML that stuff is going on. >> Well, the AIML stuff is leveraging it underneath, but this is for everybody. Like you're just copying data around, right? And you're limited, "Hey this is going to get there five times faster, pushing a big enough chunk of data around." So this is turning on gradually as the nitro five comes out, and you have to enable it at the instance level. But it's a super interesting announcement from last night. >> So the bottom line bumper sticker on commoditization is what? >> I don't think so. I mean what's the APIs? Your arm compatible, your Intel X 86 compatible or your maybe risk five one day compatible in the cloud. And those are the APIs, right? That's the commodity level. And the software is now, the software ecosystem is super portable across those as we're seeing with Apple moving from Intel to it's really not an issue, right? The software and the tooling is all there to do that. But underneath that, we're going to see an arms race between the top providers as they all try and develop faster chips for doing more specific things. We've got cranium for training, that instance has they announced it last year with 800 gigabits going out of a single instance, 800 gigabits or no, but this year they doubled it. Yeah. So 1.6 terabytes out of a single machine, right? That's insane, right? But what you're doing is you're putting together hundreds or thousands of those to solve the big machine learning training problems. These super, these enormous clusters that they're being formed for doing these massive problems. And there is a market now, for these incredibly large supercomputer clusters built for doing AI. That's all bandwidth limited. >> And you think about the timeframe from design to tape out. >> Yeah. >> Is just getting compressed It's relative. >> It is. >> Six is going the other way >> The tooling is all there. Yeah. >> Fantastic. Adrian, always a pleasure to have you on. Thanks so much. >> Yeah. >> Really appreciate it. >> Yeah, thank you. >> Thank you Paul. >> Cheers. All right. Keep it right there everybody. Don't forget, go to thecube.net, you'll see all these videos. Go to siliconangle.com, We've got features with Adam Selipsky, we got my breaking analysis, we have another feature with MongoDB's, Dev Ittycheria, Ali Ghodsi, as well Frank Sluman tomorrow. So check that out. Keep it right there. You're watching theCUBE, the leader in enterprise and emerging tech, right back. (soft techno upbeat music)

>>Hello >>Everyone and welcome back to Dallas where we're live from, Super computing. My name is Savannah Peterson, joined with my co-host David, and we have a rocket of a show for you this afternoon. The doctors are in the house and we are joined by nasa, ladies and gentlemen. So excited. Please welcome Dr. Dan Duffy and Dr. Bill Putman. Thank you so much for being here, guys. I know this is kind of last minute. How's it to be on the show floor? What's it like being NASA here? >>What's exciting? We haven't, we haven't been here for three years, so this is actually really exciting to come back and see everybody, to see the showroom floor, see the innovations that have happened over the last three years. It's pretty exciting. >>Yeah, it's great. And, and so, because your jobs are so cool, and I don't wanna even remotely give even too little of the picture or, or not do it justice, could you give the audience a little bit of background on what you do as I think you have one of the coolest jobs ever. YouTube bill. >>I, I appreciate that. I, I, I run high Performance Computing Center at NASA Goddard for science. It's high performance information technology. So we do everything from networking to security, to high performance computing, to data sciences, artificial intelligence and machine learning is huge for us now. Yeah, large amounts of data, big data sets, but we also do scientific visualizations and then cloud and commercial cloud computing, as well as on premises cloud computing. And quite frankly, we support a lot of what Bill and his team does. >>Bill, why don't you tell us what your team >>Does? Yeah, so I'm a, I'm an earth scientist. I work as the associate chief at the global modeling assimilation office. And our job is to really, you know, maximize the use of all the observations that NASA takes from space and build that into a coherent, consistent physical system of the earth. Right? And we're focused on utilizing the HC that, that Dan and the folks at the nccs provide to us, to the best of our abilities to integrate those observations, you know, on time scales from hours, days to, to seasonal to to monthly time scales. That's, that's the essence of our focus at the GMA o >>Casual modeling, all of NASA's earth data. That, that in itself as a sentence is pretty wild. I imagine you're dealing with a ton of data. >>Oh, massive amounts of data. Yes, >>Probably, I mean, as much as one probably could, now that I'm thinking about it. I mean, and especially with how far things have to travel. Bill, sticking with you, just to open us up, what technology here excites you the most about the future and that will make your job easier? Let's put it that way. >>To me, it's the accelerator technologies, right? So there's the limited, the limiting factor for, for us as scientists is how fast we can get an answer. And if we can get our answer faster through accelerated technologies, you know, with the support of the, of the nccs and the computing centers, but also the software engineers enabling that for us, then we can do more, right. And push the questions even further, you know, so once we've gotten fast enough to do what we want to do, there's always something next that we wanna look for. So, >>I mean, at nasa you have to exercise such patience, whether that be data, coming back, images from a rover, doesn't matter what it is. Sometimes there's a lot of time, days, hours, years, depending on the situation. Right? I really, I really admire that. What about you, Dan? What's got you really excited about the future here? So >>Bill talked about the, the accelerated technology, which is absolutely true and, and, and is needed to get us not to only to the point where we have the compute resources to do the simulations that Bill wants to do, and also do it in a energy efficient way. But it's really the software frameworks that go around that and the software frameworks, the technology that dealing with how to use those in an energy efficient and and most efficient way is extremely important. And that's some of the, you know, that's what I'm really here to try to understand better about is how can I support these scientists with not just the hardware, but the software frameworks by which they can be successful. >>Yeah. We've, we've had a lot of kind of philosophical discussion about this, the difference between the quantitative increases in power in computing that we're seeing versus the question of whether or not we need truly qualitative changes moving forward. Where do you see the limits of, of, of, you know, if you, if you're looking at the ability to gather more data and process more data more quickly, what you can do with that data changes when you're getting updates every second versus every month seems pretty obvious. Is there a, is there, but is there, is there a near term target that you have specifically where once you reach that target, if you weren't thinking ahead of that target, you'd kind of be going, Okay, well we solved that problem, we're getting the data in so fast that you can, you can ask me, what is the temperature in this area? And you can go, Oh, well, huh, an hour ago the data said this. Beyond that, do you need a qualitative change in our ability to process information and tease insight into out of chaos? Or do you just need more quantity to be able to get to the point where you can do things like predict weather six months in advance? What are, what are your thoughts on that? Yeah, >>It's an interesting question, right? And, and you ended it with predicting whether six months in advance, and actually I was thinking the other way, right? I was thinking going to finer and finer scales and shorter time scales when you talk about having data more frequently, right? So one of the things that I'm excited about as a modeler is going to hire resolution and representing smaller scale processes at nasa, we're, we're interested in observations that are global. So our models are global and we'd like to push those to as fine a resolution as possible to do things like severe storm predictions and so forth. So the faster we can get the data, the more data we can have, and that area would improve our ability to do that as well. So, >>And your background is in meteorology, right? >>Yes, I'm a meteorologist. >>Excellent. Okay. Yeah, yeah, >>Yeah. So, so I have to ask a question, and I'm sure all the audience cares about this. And I went through this when I was talking about the ghost satellites as well. What, what is it about weather that makes it so hard to predict? >>Oh, it's the classic chaos problem. The, the butterfly effects problem, and it's just true. You know, you always hear the story of a butterfly in Africa flaps, its rings and wings, and the weather changes in, in New York City, and it's just, computers are an excellent example of that, right? So we have a model of the earth, we can run it two times in a row and get the exact same answer, but if we flip a bit somewhere, then the answer changes 10 days later significantly. So it's a, it's a really interesting problem. So, >>Yeah. So do you have any issue with the fact that your colleague believes that butterflies are responsible for weather? No, I does that, does that, is it responsible for climate? Does that bother you at all? >>No, it doesn't. As a matter of fact, they actually run those butterfly like experi experiments within the systems where they do actually flip some bits and see what the uncertainties are that happen out 7, 8, 9 days out in advance to understand exactly what he's saying, to understand the uncertainties, but also the sensitivity with respect to the observations that they're taking. So >>Yeah, it's fascinating. It is. >>That is fascinating. Sticking with you for a second, Dan. So you're at the Center for Climate Simulation. Is that the center that's gonna help us navigate what happens over the next decade? >>Okay, so I, no one center is gonna help us navigate what's gonna happen over the next decade or the next 50 or a hundred years, right. It's gonna be everybody together. And I think NASA's role in that is really to pioneer the, the, the models that that bill and others are doing to understand what's gonna happen in not just the seasonal sub, but we also work with G, which is the God Institute for Space Studies. Yeah. Which does the decatal and, and the century long studies. Our, our job is to really help that research, understand what's happening with the client, but then feed that back into what observations we need to make next in order to better understand and better quantify the risks that we have to better quantify the mitigations that we can make to understand how and, and, and affect how the climate is gonna go for the future. So that's really what we trying to do. We're trying to do that research to understand the climate, understand what mitigations we can have, but also feedback into what observations we can make for the future. >>Yeah. And and what's the partnership ecosystem around that? You mentioned that it's gonna take all of us, I assume you work with a lot of >>Partners, Probably both of you. I mean, obviously the, the, the federal agencies work huge amounts together. Nasa, Noah is our huge partnerships. Sgs, a huge partnerships doe we've talked to doe several times this, so this, this this week already. So there's huge partnerships that go across the federal agency. We, we work also with Europeans as much as we can given the, the, the, you know, sort of the barriers of the countries and the financials. But we do collaborate as much as we can with, And the nice thing about NASA, I would say is the, all the observations that we take are public, they're paid for by the public. They're public, everybody can down them, anybody can down around the world. So that's also, and they're global measurements as Bill said, they're not just regional. >>Do you have, do you have specific, when you think about improving your ability to gain insights from data that that's being gathered? Yeah. Do you set out specific milestones that you're looking for? Like, you know, I hope by June of next year we will have achieved a place where we are able to accomplish X. Yeah. Do you, do you, Yeah. Bill, do you put, what, >>What milestones do we have here? So, yeah, I mean, do you have >>Yeah. Are, are you, are you sort of kept track of that way? Do you think of things like that? Like very specific things? Or is it just so fluid that as long as you're making progress towards the future, you feel okay? >>No, I would say we absolutely have milestones that we like to keep in track, especially from the modeling side of things, right? So whether it's observations that exist now that we want to use in our system, milestones to getting those observations integrated in, but also thinking even further ahead to the observations that we don't have yet. So we can use the models that we have today to simulate those kind of observations that we might want in the future that can help us do things that we can do right now. So those missions are, are aided by the work that we do at the GBO and, and the nccs, but, >>Okay, so if we, if we extrapolate really to the, to the what if future is really trying to understand the entire earth system as best as we can. So all the observations coming in, like you said, in in near real time, feeding that into an earth system model and to be able to predict short term, midterm or even long term predictions with, with some degree of certainty. And that may be things like climate change or it may be even more important, shorter term effects of, of severe weather. Yeah. Which is very important. And so we are trying to work towards that high resolution, immediate impact model that we can, that we can, you know, really share with the world and share those results as best, as best we can. >>Yeah. I, I have a quick, I have a quick follow up on that. I I bet we both did. >>So, so if you think about AI and ml, artificial intelligence and machine learning, something that, you know, people, people talk about a lot. Yeah. There's the concept of teaching a machine to go look for things, call it machine learning. A lot of it's machine teaching we're saying, you know, hit, you know, hit the rack on this side with a stick or the other side with the stick to get it to, to kind of go back and forth. Do you think that humans will be able to guide these systems moving forward enough to tease out the insights that we want? Or do you think we're gonna have to rely on what people think of as artificial intelligence to be able to go in with this massive amount of information with an almost infinite amount of variables and have the AI figure out that, you know what, it was the butterfly, It really was the butterfly. We all did models with it, but, but you understand the nuance that I'm saying. It's like we, we, we think we know what all the variables are and that it's chaotic because there's so many variables and there's so much data, but maybe there's something we're not taking into >>A account. Yeah, I I, I'm, I'm, I'm sure that's absolutely the case. And I'll, I'll start and let Bill, Bill jump in here. Yeah, there's a lot of nuances with a aiml. And so the, the, the, the real approach to get to where we want to be with this earth system model approach is a combination of both AI ML train models as best as we can and as unbiased way as we can. And there's a, there's a big conversation we have around that, but also with a physics or physical based model as well, Those two combined with the humans or the experts in the loop, we're not just gonna ask the artificial intelligence to predict anything and everything. The experts need to be in the loop to guide the training in as best as we, as, as we can in an unbiased, equitable way, but also interpret the results and not just give over to the ai. But that's the combination of that earth system model that we really wanna see. The future's a combination of AI l with physics based, >>But there's, there's a, there's an obvious place for a AI and ML in the modeling world that is in the parameterizations of the estimations that we have to do in our systems, right? So when we think about the earth system and modeling the earth system, there are many things like the equations of motions and thermodynamics that have fixed equations that we know how to solve on a computer. But there's a lot of things that happen physically in the atmosphere that we don't have equations for, and we have to estimate them. And machine learning through the use of high resolution models or observations in training the models to understand and, and represent that, yeah, that that's the place where it's really useful >>For us. There's so many factors, but >>We have to, but we have to make sure that we have the physics in that machine learning in those, in those training. So physics informed training isn't very important. So we're not just gonna go and let a model go off and do whatever it wants. It has to be constrained within physical constraints that the, that the experts know. >>Yeah. And with the wild amount of variables that affect our, our earth, quite frankly. Yeah, yeah. Which is geez. Which is insane. My god. So what's, what, what technology or what advancement needs to happen for your jobs to get easier, faster for our ability to predict to be even more successful than it is currently? >>You know, I think for me, the vision that I have for the future is that at some point, you know, all data is centrally located, essentially shared. We have our applications are then services that sit around all that data. I don't have to sit as a user and worry about, oh, is this all this data in place before I run my application? It's already there, it's already ready for me. My service is prepared and I just launch it out on that service. But that coupled with the performance that I need to get the result that I want in time. And I don't know when that's gonna happen, but at some point it might, you know, I don't know rooting for you, but that's, >>So there are, there are a lot of technologies we can talk about. What I'd like to mention is, is open science. So NASA is really trying to make a push and transformation towards open science. 2023 is gonna be the year of open science for nasa. And what does that mean? It means a lot of what Bill just said is that we have equity and fairness and accessibility and you can find the data, it's findability, it's fair data, you know, a fair findability accessibility reproducibility, and I forget what the eye stands for, but these are, these are tools and, and, and things that we need to, as, as a computing centers and including all the HC centers here, as well as the scientists need to support, to be as transparent as possible with the data sets and the, and the research that we're doing. And that's where I think is gonna be the best thing is if we can get this data out there that anybody can use in an equitable way and as transparent as possible, that's gonna eliminate, in my opinion, the bias over time because mistakes will be found and mistakes will be corrected over time. >>I love that. Yeah. The open source science end of this. No, it's great. And the more people that have access people I find in the academic world, especially people don't know what's going on in the private sector and vice versa. And so I love that you just brought that up. Closing question for you, because I suspect there might be some members of our audience who maybe have fantasized about working at nasa. You've both been working there for over a decade. Is it as cool as we all think of it? It is on the outside. >>I mean, it's, it's definitely pretty cool. >>You don't have to be modest about it, you know, >>I mean, just being at Goddard and being at the center where they build the James web web telescope and you can go to that clean room and see it, it's just fascinating. So it, it's really an amazing opportunity. >>Yeah. So NASA Goddard as a, as a center has, you know, information technologist, It has engineers, it has scientists, it has support staff, support team members. We have built more things, more instruments that have flown in this space than any other place in the world. The James Lab, we were part of that, part of a huge group of people that worked on James. We and James, we came through and was assembled in our, our, our clean room. It's one of the biggest clean rooms in, in, in the world. And we all took opportunities to go over and take selfies with this as they put those loveness mirrors on them. Yeah, it was awesome. It was amazing. And to see what the James we has done in such a short amount of time, the successes that they've gone through is just incredible. Now, I'm not a, I'm not a part of the James web team, but to be a, to be at the same center, to to listen to scientists like Bill talk about their work, to listen to scientists that, that talk about James, we, that's what's inspiring. And, and we get that all the time. >>And to have the opportunity to work with the astronauts that service the, the Hubble Telescope, you know, these things are, >>That's literally giving me goosebumps right now. I'm sitting over >>Here just, just an amazing opportunity. And woo. >>Well, Dan, Bill, thank you both so much for being on the show. I know it was a bit last minute, but I can guarantee we all got a lot out of it. David and I both, I know I speak for us in the whole cube audience, so thank you. We'll have you, anytime you wanna come talk science on the cube. Thank you all for tuning into our supercomputing footage here, live in Dallas. My name is Savannah Peterson. I feel cooler having sat next to these two gentlemen for the last 15 minutes and I hope you did too. We'll see you again soon.

>>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) >> Hey everyone, welcome back to Chicago theCUBE is live on the floor at AnsibleFest 2022, the first in-person Ansible event that we've covered since 2019. Lisa Martin here with John Furrier. John, great to be here. There's about 1400 to 1500 people here in person, the partner ecosystem is growing and evolving, and that's going to be one of the themes of our next conversation. >> CloudScale is continuing to change the ecosystem, and this segment with AWS is going to be awesome. >> Exactly, we've got one of our alumni back with us, Stefanie Chiras joins us again, senior vice president, partner ecosystem success at Red Hat. and Manasi Jagannatha is also here Global Alliance Manager at AWS. Ladies, welcome to the program. >> Both: Thank you. >> Manasi: Nice to be here. >> Stefanie: Yeah. >> So some exciting news that came out. First of all was great to see you on stage. >> Thank you. >> In front of a live audience. The community is, you talked about this before we went live. The Ansible is nothing, if not the community. So I can only imagine how great that felt to be on stage in front of live bodies announcing the next step with Ansible and AWS. Tell us about that. >> I mean, you can't compete with the energy that comes from a live event. And I remember the first AnsibleFest I came to, it's just this electric feeling born out of the community, born out of collaboration and getting together feeds that collaboration in a way that like nothing else. >> Lisa: Can't do it by video alone. >> You cannot. And so it was so fun cuz today was big news. We announced that Ansible will be available through the AWS marketplace, the next step in our partnership journey. And we've been hearing like most of our announcements, we do these because customers ask for them. And that's really what is key. And the combination of what Red Hat brings to the table and what AWS brings to the table. That's what underpins this announcement this morning. >> Talk about it from a customer demand perspective and how you are not only meeting customers where they are, but you're speaking their language. >> Manasi: Yeah. >> Yeah, there's a couple of aspects and then I want to pass it to Manasi because nothing speaks better than a customer experience. But the specifics I think of what come together is this is where technology, procurement, experience, accessibility all come together. And it took both of us in order to do that. But we actually talked about a great example today, the TransUnion. >> So we have TransUnion, they are a credit reporting company and they're a giant customer. They use RHEL, they use AWS services. So while they were transitioning to the cloud, the first thing they wanted to know was compliance, right? Like, how do we have guardrails around compliance? That was a key feature for them. And then the other piece was how do we scale without increasing the complexity? And then the critical piece was being able to integrate with the depth of AWS services without having to do it over and over again. So what TransUnion did was they basically integrated Ansible automation platform with the AWS Cloud Control API that gave them the flexibility To basically integrate with what, 200 plus services? And it's amazing to see them grow over time. >> What's interesting is that Amazon, obviously cloud has been awesome. We've been covering it since the beginning. DevOps infrastructures code was the dream. Now it's app says code, you have configuration code before that. As cloud goes next level here, we're starting to see a lot more higher level services on AWS being adopted by customers. And so I want to get into how the marketplace deal works. So what's in it for the customer? Because as they bring Ansible across the enterprise and edge, now we're seeing that develop. If I'm the customer, am I buying it through the marketplace? What's the mechanics of the deal? Can I just tap into the bill, explain the marketplace workflow or how it works? >> Yeah, I'd love to do that. So customers come to the marketplace for three key benefits, right? Like one is the consumption based model, pay as you go, you can get hourly, annual, and spot instances. For some services you even get per second billing, right? Like, that's amazing, that's one. And then the other piece is John and Stefanie, as you know, customers would love to draw down on their EDPs, right? Like they want a single- >> EDPs, explain that with acronym. >> It's enterprise discount program. So they want a single bill where they can use third party services and AWS services and they don't have to go through the hustle of saying, "Hey, let me combine all these different pieces." So combining that, and of course the power of Ansible, right? Like customers love Ansible, they've built playbooks. The beauty of it is whatever you want to build on AWS, there is most likely a playbook or a module that already exists. So they can just tap into that and build into- >> Operationally it's a purchasing through marketplace. >> And you know, I mean, being an engineer myself, we always often get caught up in the technology aspect. Like what's the greatest technology? And everyone, as Manasi said, everyone loves the technology of Ansible, but the procurement aspect is also so important. And this is where I think this partnership really comes together. It is natively, Ansible is now, natively integrated into AWS billing. So one bill, you go and you log in. Now you have a Red Hat subscription, you get all the benefits from Red Hat that comes along with that subscription. But the like Ansible is all about simplicity. This brings simplicity to that procurement model and it allows you to scale within your AWS cloud environment that you have set up. And as Manasi mentioned, pull in those other native services from AWS. It's Great. >> It's interesting one of the things that buzzword Lisa and I were just talking as in the industry is the word multiplayer. I've heard people say that's multiplayer software, kind of a gaming analogy. But what you guys are doing is setting up, once they go with Ansible in the marketplace, they're just buying as things get more collaborative off the marketplace. So it kind of streamlines, if I get this right. >> Stefanie: Yep. >> The purchasing process. So they're already in, they just use it's on the bill. Is that kind of how it works? >> Yep. >> Absolutely done, yeah. >> So it the customer has a partnership with us more on the technology side and this particular case and with AWS and the procurement side, it brings that together. >> So multiplayer software, is it multiplayer software? >> We like to talk about multi-partner solutions and I think this provides a new grounding for other partners to come in and build upon that with their services capabilities, with their other technology capabilities. So well clearly in my world, we talk about multi-partner. (both laughs) >> Well, what you're doing is empowering the developers. I know that Red Hat is one of its goals is let's make things much more seamless, much smoother for the developers as the buyer's journey has changed. And John, you've talked about that quite a bit. You're empowering those buyers to actually have a much simpler, streamlined process and to be able to start seeing automation become democratized across organizations. >> Yeah, and one of the things I love about the announcement as well is it pulls in the other values of Ansible automation platform in that simplicity model that you mentioned with like things like certified collections, certified collections that have been built by partners. We have built certified collections, to go along with this offering as well as part of the AWS offering that pulls in these other partner engagements together. And as you said, democratizes not only what we've done together, but what we've done with other partners together. >> Lisa: Right. >> Yeah. >> Can you kind of talk kind of about the depths of the partnership, the co-engineering, and sort of the evolution and the customer involvement in the expansion of the partnership? >> Yeah, I'd love to walk you through that. So we've had a longstanding partnership coming up on 15 years now Stefanie, can you believe it? >> Stefanie: Yeah. (laughs) >> 15 years we've been building, to give you some historical context, right? In back in 2008 we launched RHEL and in 2015 we supported SAP workloads on RHEL. And then the list goes on, right? Like we've been launching Graviton instances, Arm instances, Nitro. The key to be noted here is that every new instance Launch, RHEL has always been supported on day one, right? Like that's been our motto. So that's one. And then in 2021, as you know, we launched Rosa Red Hat OpenShift service on AWS. And that's helped customers with their modernization journey to AWS. So that's been context historically around where we were and where we are today. And now with Ansible, it just gives customer another tool in their arsenal, right? And then the goal is to make sure we meet customers where they are, give them all the Red Hat products that they love using on their hybrid workloads. >> Sounds like a lot is coming maybe at re:Invent too, coming up. >> Yeah. >> What's next? >> This is the beginning, right? We'll continue to grow and based upon not only laying the building blocks for what customers can build with, and you mentioned Lisa, right? We follow this journey that Manasi talked about because of what customers ask for. So it's always a new adventure to determine what'll come next based upon what we hear from our joint customers. >> On that front though, Stefanie, talk about the impact of the broader ecosystem that this is just scratching the surface. >> One of the things, and we've been going through a whole transformation at Red Hat about how we engage with the ecosystem. We've done organizational shifts, we've done a complete revamp of how we engage with the ecosystem. One of our biggest focus is to make sure that the partnerships that we have with one partner bring value to the rest of our partners. No better example than something like this when we work with AWS to create accessibility and capability through a procurement model that we know is important to customers. But that then serves as a launch point for other partners to build certified collections around or now around validated content, which we talked about today at AnsibleFest, that allows other partners to engage. And we're seeing a huge amount in services partners, right? Automation is so pervasive now as customers want to go out and scale. We're seeing services partners really come in and help customers go from, it's always challenging when you have a broad set of IT. You have cloud native over here, you have bare metal over here, you have virtual, it's complex. >> John: Yeah. >> There's sometimes an energy activation barrier to get over that initial automation. We're seeing partners come in with really skilled services capabilities to help customers get over that hump to consolidate with an automation plan. It gets them better equipped to do day one automation and day two automation. And that's where Ansible automation platform is going. It's not just about configuration management, it's about day two management as well. >> Talk about those barriers a little bit more and how Ansible and AWS together are helping customers really knock those out of the park. Another baseball reference for you. We see that a lot of organizations, the skills gap, which we've talked about already on the conversation today, but Ansible as being a facilitator of helping organizations to attract talent, to retain talent, but also customers that maybe don't know where to start or don't know how to determine the ROI that automating processes will bring. How can this partnership help customers nock those out of the park? >> So I'll start and then I'll pass it to Manasi here. But I think one of the key things in this particular partnership is just plain old accessibility. Accessibility, which public cloud has taught the world a new way to get fast access that consumption based pricing. Right you can get your hands on it, you can test it out, you can have a team go in and test it out, and then you can see it's built for scale. So then you can scale it as far as you want to go forward. We clearly have an ecosystem of services partners, so does AWS to help people then sort of take it to the next level as they want to build upon it. But to me the first step is about accessibility, getting your hands dirty. You can build it into those committed spend programs that you may have with AWS as well to try new things. But it's a great test bed. >> Absolutely. And then to add to what Stefanie said, together Red Hat and AWS, we have about a hundred thousand partners combined, right? Like resellers, sis, GSI, distributors. So the reach the combined partnership has just amplifies. >> Yeah, it's huge news. I think it's a big deal because you operationalize the heavy lifting of procurement for all your joint customers and the scale piece is huge. So congratulations. I think it's going to make a lot of money for Ansible. So good call there. My question is, as we hear here, the next level's edge. So AWS has been doing a ton of hybrids since outpost announcement years ago. Now you got all kinds of regional expansions, you've got local zones, you've got all kinds of new edge activity. So are there dots connecting here with the edge with Red Hat Ansible? >> Do you want- >> Yeah, so I think we see two trends with our customers, right? Like mainly I'm specifically talking about our RHEL customer base on AWS. We have almost hundreds to thousands of customers using RHEL on AWS. These are 90% of fortune 500 companies use RHEL, right? So with that customer base, they are looking to expand your point into the edge. There's outposts, there are so many hybrid environments that they're trying to expand in. So just adding Ansible, RHEL, Rosa, OpenShift, that entire makes, just gives customers that the plethora of products they need to run their workloads everywhere, right? Like we have certifications outpost, we have certifications with OpenShift, right? So it just completes the puzzle, if you- >> So it's a nice fit. >> Yeah. >> It is a really nice fit. And I love Edge and Edge once you start going distributed, this automation aspect is key for all the reasons, for security reasons to make sure you do it the same way every single time. It's just pervasive in it. But things like the Cloud Control API allow it to bridge into things like Outpost. It allows a simple way, one clean way to do API and then you can expand it out and get the value. >> So this is why you are on stage and you said that Ansible's going to expand the scope to be more enterprise architecture. >> Stefanie: That's right. >> That's essentially what you're getting at. This is now a distributed computing fabric at cloud scale on AWS. >> Stefanie: That's right. >> Did I get that right? >> Yep, and it touches all the different deployments you may have, on-prem, virtual, cloud native, you name it. >> So how do the people turn into architects? Cuz this is, again, we had this earlier conversation with Tom, multi-tool players, a baseball analogy I used. It's like signifies the best player, your customers are becoming multiple tool players or operators. The new operator is now the top talent. They got to run Ansible, they got to automate, they got to provide services to the cloud native developers. So this new role is emerging, it's not a cloud architect but it's, if it's going to be system architecture wide, what's this new person look like that's going to run all this? >> I think it's an interesting question. We were talking yesterday, actually, Tom and I were talking with the partners. We had Partner Day, the first ever at AnsibleFest yesterday, which was great. We got a lot of insight. They talked a lot about this platform focus, right? Customers are looking to create that platform so that the developers can come in and build upon it without compromising what they want to do. So I do think there's a move in that direction to say how do you create these platforms at a company that no compromises, but it provides that consistency. I would say one thing in partnerships like this, I think customer expectations on the partner ecosystem to have it be trusted is increasing. They expect us as we've done to have our engineers roll up their sleeves together to come to the table together. That's going to show up in our curated content. It's going to show up in our validated content. Those are the places I think where we come up from the bottom through our partnership and we help bridge that gap. >> John: Awesome. >> And trust was brought up a number of times this morning during the keynote. We're almost out of time here, but I think it's one of those words that a lot of companies use. But I think what you're showing is really the value in it from Ansible's perspective from AWS's perspective and ultimately the value in it for the customer. >> Stefanie: Yes. >> So I got to ask you one final question. >> Stefanie: Absolutely. >> And maybe as as reinvent is around the corner, what's next for the partnership? Obviously big news today, Manasi, looking down down the pipe- >> Stefanie: Big news today. >> What are some of the things that you think are going to become next that you can share? >> I mean at this point, and I'll pass it to Manasi to close us out, but we are continuing to follow, to meet our customers where they want to be. We are looking across our portfolio for different ways that customers want to consume within AWS. We'll continue to look at the procurement models through the partner programs that Manasi and the team have had. And to me the next step is really bringing in the rest of the ecosystem. How do we use this as a grounding step? >> Yeah, absolutely. So we are always listening to customer feedback and they want more Red Hat products in the marketplace. So that's where we'll be. >> In the marketplace. >> Congratulations great deal. >> Yes great work there guys. And customers always want more. That's the thing. But that's what keeps us going. So we love it. >> Absolutely. >> Thank you so much for joining John and me on the program today. It's been great to have you. And congratulations again. >> It's a pleasure. >> Thank you. >> For our guests and for John Furrier, I'm Lisa Martin. You're watching theCUBE Live from Chicago at AnsibleFest 2022. This is only day one of our coverage. We'll be back after a short break for more. (upbeat music)

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

>>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 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.