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The Truth About MySQL HeatWave


 

>>When Oracle acquired my SQL via the Sun acquisition, nobody really thought the company would put much effort into the platform preferring to focus all the wood behind its leading Oracle database, Arrow pun intended. But two years ago, Oracle surprised many folks by announcing my SQL Heatwave a new database as a service with a massively parallel hybrid Columbia in Mary Mary architecture that brings together transactional and analytic data in a single platform. Welcome to our latest database, power panel on the cube. My name is Dave Ante, and today we're gonna discuss Oracle's MySQL Heat Wave with a who's who of cloud database industry analysts. Holgar Mueller is with Constellation Research. Mark Stammer is the Dragon Slayer and Wikibon contributor. And Ron Westfall is with Fu Chim Research. Gentlemen, welcome back to the Cube. Always a pleasure to have you on. Thanks for having us. Great to be here. >>So we've had a number of of deep dive interviews on the Cube with Nip and Aggarwal. You guys know him? He's a senior vice president of MySQL, Heatwave Development at Oracle. I think you just saw him at Oracle Cloud World and he's come on to describe this is gonna, I'll call it a shock and awe feature additions to to heatwave. You know, the company's clearly putting r and d into the platform and I think at at cloud world we saw like the fifth major release since 2020 when they first announced MySQL heat wave. So just listing a few, they, they got, they taken, brought in analytics machine learning, they got autopilot for machine learning, which is automation onto the basic o l TP functionality of the database. And it's been interesting to watch Oracle's converge database strategy. We've contrasted that amongst ourselves. Love to get your thoughts on Amazon's get the right tool for the right job approach. >>Are they gonna have to change that? You know, Amazon's got the specialized databases, it's just, you know, the both companies are doing well. It just shows there are a lot of ways to, to skin a cat cuz you see some traction in the market in, in both approaches. So today we're gonna focus on the latest heat wave announcements and we're gonna talk about multi-cloud with a native MySQL heat wave implementation, which is available on aws MySQL heat wave for Azure via the Oracle Microsoft interconnect. This kind of cool hybrid action that they got going. Sometimes we call it super cloud. And then we're gonna dive into my SQL Heatwave Lake house, which allows users to process and query data across MyQ databases as heatwave databases, as well as object stores. So, and then we've got, heatwave has been announced on AWS and, and, and Azure, they're available now and Lake House I believe is in beta and I think it's coming out the second half of next year. So again, all of our guests are fresh off of Oracle Cloud world in Las Vegas. So they got the latest scoop. Guys, I'm done talking. Let's get into it. Mark, maybe you could start us off, what's your opinion of my SQL Heatwaves competitive position? When you think about what AWS is doing, you know, Google is, you know, we heard Google Cloud next recently, we heard about all their data innovations. You got, obviously Azure's got a big portfolio, snowflakes doing well in the market. What's your take? >>Well, first let's look at it from the point of view that AWS is the market leader in cloud and cloud services. They own somewhere between 30 to 50% depending on who you read of the market. And then you have Azure as number two and after that it falls off. There's gcp, Google Cloud platform, which is further way down the list and then Oracle and IBM and Alibaba. So when you look at AWS and you and Azure saying, hey, these are the market leaders in the cloud, then you start looking at it and saying, if I am going to provide a service that competes with the service they have, if I can make it available in their cloud, it means that I can be more competitive. And if I'm compelling and compelling means at least twice the performance or functionality or both at half the price, I should be able to gain market share. >>And that's what Oracle's done. They've taken a superior product in my SQL heat wave, which is faster, lower cost does more for a lot less at the end of the day and they make it available to the users of those clouds. You avoid this little thing called egress fees, you avoid the issue of having to migrate from one cloud to another and suddenly you have a very compelling offer. So I look at what Oracle's doing with MyQ and it feels like, I'm gonna use a word term, a flanking maneuver to their competition. They're offering a better service on their platforms. >>All right, so thank you for that. Holger, we've seen this sort of cadence, I sort of referenced it up front a little bit and they sat on MySQL for a decade, then all of a sudden we see this rush of announcements. Why did it take so long? And and more importantly is Oracle, are they developing the right features that cloud database customers are looking for in your view? >>Yeah, great question, but first of all, in your interview you said it's the edit analytics, right? Analytics is kind of like a marketing buzzword. Reports can be analytics, right? The interesting thing, which they did, the first thing they, they, they crossed the chasm between OTP and all up, right? In the same database, right? So major engineering feed very much what customers want and it's all about creating Bellevue for customers, which, which I think is the part why they go into the multi-cloud and why they add these capabilities. And they certainly with the AI capabilities, it's kind of like getting it into an autonomous field, self-driving field now with the lake cost capabilities and meeting customers where they are, like Mark has talked about the e risk costs in the cloud. So that that's a significant advantage, creating value for customers and that's what at the end of the day matters. >>And I believe strongly that long term it's gonna be ones who create better value for customers who will get more of their money From that perspective, why then take them so long? I think it's a great question. I think largely he mentioned the gentleman Nial, it's largely to who leads a product. I used to build products too, so maybe I'm a little fooling myself here, but that made the difference in my view, right? So since he's been charged, he's been building things faster than the rest of the competition, than my SQL space, which in hindsight we thought was a hot and smoking innovation phase. It kind of like was a little self complacent when it comes to the traditional borders of where, where people think, where things are separated between OTP and ola or as an example of adjacent support, right? Structured documents, whereas unstructured documents or databases and all of that has been collapsed and brought together for building a more powerful database for customers. >>So I mean it's certainly, you know, when, when Oracle talks about the competitors, you know, the competitors are in the, I always say they're, if the Oracle talks about you and knows you're doing well, so they talk a lot about aws, talk a little bit about Snowflake, you know, sort of Google, they have partnerships with Azure, but, but in, so I'm presuming that the response in MySQL heatwave was really in, in response to what they were seeing from those big competitors. But then you had Maria DB coming out, you know, the day that that Oracle acquired Sun and, and launching and going after the MySQL base. So it's, I'm, I'm interested and we'll talk about this later and what you guys think AWS and Google and Azure and Snowflake and how they're gonna respond. But, but before I do that, Ron, I want to ask you, you, you, you can get, you know, pretty technical and you've probably seen the benchmarks. >>I know you have Oracle makes a big deal out of it, publishes its benchmarks, makes some transparent on on GI GitHub. Larry Ellison talked about this in his keynote at Cloud World. What are the benchmarks show in general? I mean, when you, when you're new to the market, you gotta have a story like Mark was saying, you gotta be two x you know, the performance at half the cost or you better be or you're not gonna get any market share. So, and, and you know, oftentimes companies don't publish market benchmarks when they're leading. They do it when they, they need to gain share. So what do you make of the benchmarks? Have their, any results that were surprising to you? Have, you know, they been challenged by the competitors. Is it just a bunch of kind of desperate bench marketing to make some noise in the market or you know, are they real? What's your view? >>Well, from my perspective, I think they have the validity. And to your point, I believe that when it comes to competitor responses, that has not really happened. Nobody has like pulled down the information that's on GitHub and said, Oh, here are our price performance results. And they counter oracles. In fact, I think part of the reason why that hasn't happened is that there's the risk if Oracle's coming out and saying, Hey, we can deliver 17 times better query performance using our capabilities versus say, Snowflake when it comes to, you know, the Lakehouse platform and Snowflake turns around and says it's actually only 15 times better during performance, that's not exactly an effective maneuver. And so I think this is really to oracle's credit and I think it's refreshing because these differentiators are significant. We're not talking, you know, like 1.2% differences. We're talking 17 fold differences, we're talking six fold differences depending on, you know, where the spotlight is being shined and so forth. >>And so I think this is actually something that is actually too good to believe initially at first blush. If I'm a cloud database decision maker, I really have to prioritize this. I really would know, pay a lot more attention to this. And that's why I posed the question to Oracle and others like, okay, if these differentiators are so significant, why isn't the needle moving a bit more? And it's for, you know, some of the usual reasons. One is really deep discounting coming from, you know, the other players that's really kind of, you know, marketing 1 0 1, this is something you need to do when there's a real competitive threat to keep, you know, a customer in your own customer base. Plus there is the usual fear and uncertainty about moving from one platform to another. But I think, you know, the traction, the momentum is, is shifting an Oracle's favor. I think we saw that in the Q1 efforts, for example, where Oracle cloud grew 44% and that it generated, you know, 4.8 billion and revenue if I recall correctly. And so, so all these are demonstrating that's Oracle is making, I think many of the right moves, publishing these figures for anybody to look at from their own perspective is something that is, I think, good for the market and I think it's just gonna continue to pay dividends for Oracle down the horizon as you know, competition intens plots. So if I were in, >>Dave, can I, Dave, can I interject something and, and what Ron just said there? Yeah, please go ahead. A couple things here, one discounting, which is a common practice when you have a real threat, as Ron pointed out, isn't going to help much in this situation simply because you can't discount to the point where you improve your performance and the performance is a huge differentiator. You may be able to get your price down, but the problem that most of them have is they don't have an integrated product service. They don't have an integrated O L T P O L A P M L N data lake. Even if you cut out two of them, they don't have any of them integrated. They have multiple services that are required separate integration and that can't be overcome with discounting. And the, they, you have to pay for each one of these. And oh, by the way, as you grow, the discounts go away. So that's a, it's a minor important detail. >>So, so that's a TCO question mark, right? And I know you look at this a lot, if I had that kind of price performance advantage, I would be pounding tco, especially if I need two separate databases to do the job. That one can do, that's gonna be, the TCO numbers are gonna be off the chart or maybe down the chart, which you want. Have you looked at this and how does it compare with, you know, the big cloud guys, for example, >>I've looked at it in depth, in fact, I'm working on another TCO on this arena, but you can find it on Wiki bod in which I compared TCO for MySEQ Heat wave versus Aurora plus Redshift plus ML plus Blue. I've compared it against gcps services, Azure services, Snowflake with other services. And there's just no comparison. The, the TCO differences are huge. More importantly, thefor, the, the TCO per performance is huge. We're talking in some cases multiple orders of magnitude, but at least an order of magnitude difference. So discounting isn't gonna help you much at the end of the day, it's only going to lower your cost a little, but it doesn't improve the automation, it doesn't improve the performance, it doesn't improve the time to insight, it doesn't improve all those things that you want out of a database or multiple databases because you >>Can't discount yourself to a higher value proposition. >>So what about, I wonder ho if you could chime in on the developer angle. You, you followed that, that market. How do these innovations from heatwave, I think you used the term developer velocity. I've heard you used that before. Yeah, I mean, look, Oracle owns Java, okay, so it, it's, you know, most popular, you know, programming language in the world, blah, blah blah. But it does it have the, the minds and hearts of, of developers and does, where does heatwave fit into that equation? >>I think heatwave is gaining quickly mindshare on the developer side, right? It's not the traditional no sequel database which grew up, there's a traditional mistrust of oracles to developers to what was happening to open source when gets acquired. Like in the case of Oracle versus Java and where my sql, right? And, but we know it's not a good competitive strategy to, to bank on Oracle screwing up because it hasn't worked not on Java known my sequel, right? And for developers, it's, once you get to know a technology product and you can do more, it becomes kind of like a Swiss army knife and you can build more use case, you can build more powerful applications. That's super, super important because you don't have to get certified in multiple databases. You, you are fast at getting things done, you achieve fire, develop velocity, and the managers are happy because they don't have to license more things, send you to more trainings, have more risk of something not being delivered, right? >>So it's really the, we see the suite where this best of breed play happening here, which in general was happening before already with Oracle's flagship database. Whereas those Amazon as an example, right? And now the interesting thing is every step away Oracle was always a one database company that can be only one and they're now generally talking about heat web and that two database company with different market spaces, but same value proposition of integrating more things very, very quickly to have a universal database that I call, they call the converge database for all the needs of an enterprise to run certain application use cases. And that's what's attractive to developers. >>It's, it's ironic isn't it? I mean I, you know, the rumor was the TK Thomas Curian left Oracle cuz he wanted to put Oracle database on other clouds and other places. And maybe that was the rift. Maybe there was, I'm sure there was other things, but, but Oracle clearly is now trying to expand its Tam Ron with, with heatwave into aws, into Azure. How do you think Oracle's gonna do, you were at a cloud world, what was the sentiment from customers and the independent analyst? Is this just Oracle trying to screw with the competition, create a little diversion? Or is this, you know, serious business for Oracle? What do you think? >>No, I think it has lakes. I think it's definitely, again, attriting to Oracle's overall ability to differentiate not only my SQL heat wave, but its overall portfolio. And I think the fact that they do have the alliance with the Azure in place, that this is definitely demonstrating their commitment to meeting the multi-cloud needs of its customers as well as what we pointed to in terms of the fact that they're now offering, you know, MySQL capabilities within AWS natively and that it can now perform AWS's own offering. And I think this is all demonstrating that Oracle is, you know, not letting up, they're not resting on its laurels. That's clearly we are living in a multi-cloud world, so why not just make it more easy for customers to be able to use cloud databases according to their own specific, specific needs. And I think, you know, to holder's point, I think that definitely lines with being able to bring on more application developers to leverage these capabilities. >>I think one important announcement that's related to all this was the JSON relational duality capabilities where now it's a lot easier for application developers to use a language that they're very familiar with a JS O and not have to worry about going into relational databases to store their J S O N application coding. So this is, I think an example of the innovation that's enhancing the overall Oracle portfolio and certainly all the work with machine learning is definitely paying dividends as well. And as a result, I see Oracle continue to make these inroads that we pointed to. But I agree with Mark, you know, the short term discounting is just a stall tag. This is not denying the fact that Oracle is being able to not only deliver price performance differentiators that are dramatic, but also meeting a wide range of needs for customers out there that aren't just limited device performance consideration. >>Being able to support multi-cloud according to customer needs. Being able to reach out to the application developer community and address a very specific challenge that has plagued them for many years now. So bring it all together. Yeah, I see this as just enabling Oracles who ring true with customers. That the customers that were there were basically all of them, even though not all of them are going to be saying the same things, they're all basically saying positive feedback. And likewise, I think the analyst community is seeing this. It's always refreshing to be able to talk to customers directly and at Oracle cloud there was a litany of them and so this is just a difference maker as well as being able to talk to strategic partners. The nvidia, I think partnerships also testament to Oracle's ongoing ability to, you know, make the ecosystem more user friendly for the customers out there. >>Yeah, it's interesting when you get these all in one tools, you know, the Swiss Army knife, you expect that it's not able to be best of breed. That's the kind of surprising thing that I'm hearing about, about heatwave. I want to, I want to talk about Lake House because when I think of Lake House, I think data bricks, and to my knowledge data bricks hasn't been in the sites of Oracle yet. Maybe they're next, but, but Oracle claims that MySQL, heatwave, Lakehouse is a breakthrough in terms of capacity and performance. Mark, what are your thoughts on that? Can you double click on, on Lakehouse Oracle's claims for things like query performance and data loading? What does it mean for the market? Is Oracle really leading in, in the lake house competitive landscape? What are your thoughts? >>Well, but name in the game is what are the problems you're solving for the customer? More importantly, are those problems urgent or important? If they're urgent, customers wanna solve 'em. Now if they're important, they might get around to them. So you look at what they're doing with Lake House or previous to that machine learning or previous to that automation or previous to that O L A with O ltp and they're merging all this capability together. If you look at Snowflake or data bricks, they're tacking one problem. You look at MyQ heat wave, they're tacking multiple problems. So when you say, yeah, their queries are much better against the lake house in combination with other analytics in combination with O ltp and the fact that there are no ETLs. So you're getting all this done in real time. So it's, it's doing the query cross, cross everything in real time. >>You're solving multiple user and developer problems, you're increasing their ability to get insight faster, you're having shorter response times. So yeah, they really are solving urgent problems for customers. And by putting it where the customer lives, this is the brilliance of actually being multicloud. And I know I'm backing up here a second, but by making it work in AWS and Azure where people already live, where they already have applications, what they're saying is, we're bringing it to you. You don't have to come to us to get these, these benefits, this value overall, I think it's a brilliant strategy. I give Nip and Argo wallet a huge, huge kudos for what he's doing there. So yes, what they're doing with the lake house is going to put notice on data bricks and Snowflake and everyone else for that matter. Well >>Those are guys that whole ago you, you and I have talked about this. Those are, those are the guys that are doing sort of the best of breed. You know, they're really focused and they, you know, tend to do well at least out of the gate. Now you got Oracle's converged philosophy, obviously with Oracle database. We've seen that now it's kicking in gear with, with heatwave, you know, this whole thing of sweets versus best of breed. I mean the long term, you know, customers tend to migrate towards suite, but the new shiny toy tends to get the growth. How do you think this is gonna play out in cloud database? >>Well, it's the forever never ending story, right? And in software right suite, whereas best of breed and so far in the long run suites have always won, right? So, and sometimes they struggle again because the inherent problem of sweets is you build something larger, it has more complexity and that means your cycles to get everything working together to integrate the test that roll it out, certify whatever it is, takes you longer, right? And that's not the case. It's a fascinating part of what the effort around my SQL heat wave is that the team is out executing the previous best of breed data, bringing us something together. Now if they can maintain that pace, that's something to to, to be seen. But it, the strategy, like what Mark was saying, bring the software to the data is of course interesting and unique and totally an Oracle issue in the past, right? >>Yeah. But it had to be in your database on oci. And but at, that's an interesting part. The interesting thing on the Lake health side is, right, there's three key benefits of a lakehouse. The first one is better reporting analytics, bring more rich information together, like make the, the, the case for silicon angle, right? We want to see engagements for this video, we want to know what's happening. That's a mixed transactional video media use case, right? Typical Lakehouse use case. The next one is to build more rich applications, transactional applications which have video and these elements in there, which are the engaging one. And the third one, and that's where I'm a little critical and concerned, is it's really the base platform for artificial intelligence, right? To run deep learning to run things automatically because they have all the data in one place can create in one way. >>And that's where Oracle, I know that Ron talked about Invidia for a moment, but that's where Oracle doesn't have the strongest best story. Nonetheless, the two other main use cases of the lake house are very strong, very well only concern is four 50 terabyte sounds long. It's an arbitrary limitation. Yeah, sounds as big. So for the start, and it's the first word, they can make that bigger. You don't want your lake house to be limited and the terabyte sizes or any even petabyte size because you want to have the certainty. I can put everything in there that I think it might be relevant without knowing what questions to ask and query those questions. >>Yeah. And you know, in the early days of no schema on right, it just became a mess. But now technology has evolved to allow us to actually get more value out of that data. Data lake. Data swamp is, you know, not much more, more, more, more logical. But, and I want to get in, in a moment, I want to come back to how you think the competitors are gonna respond. Are they gonna have to sort of do a more of a converged approach? AWS in particular? But before I do, Ron, I want to ask you a question about autopilot because I heard Larry Ellison's keynote and he was talking about how, you know, most security issues are human errors with autonomy and autonomous database and things like autopilot. We take care of that. It's like autonomous vehicles, they're gonna be safer. And I went, well maybe, maybe someday. So Oracle really tries to emphasize this, that every time you see an announcement from Oracle, they talk about new, you know, autonomous capabilities. It, how legit is it? Do people care? What about, you know, what's new for heatwave Lakehouse? How much of a differentiator, Ron, do you really think autopilot is in this cloud database space? >>Yeah, I think it will definitely enhance the overall proposition. I don't think people are gonna buy, you know, lake house exclusively cause of autopilot capabilities, but when they look at the overall picture, I think it will be an added capability bonus to Oracle's benefit. And yeah, I think it's kind of one of these age old questions, how much do you automate and what is the bounce to strike? And I think we all understand with the automatic car, autonomous car analogy that there are limitations to being able to use that. However, I think it's a tool that basically every organization out there needs to at least have or at least evaluate because it goes to the point of it helps with ease of use, it helps make automation more balanced in terms of, you know, being able to test, all right, let's automate this process and see if it works well, then we can go on and switch on on autopilot for other processes. >>And then, you know, that allows, for example, the specialists to spend more time on business use cases versus, you know, manual maintenance of, of the cloud database and so forth. So I think that actually is a, a legitimate value proposition. I think it's just gonna be a case by case basis. Some organizations are gonna be more aggressive with putting automation throughout their processes throughout their organization. Others are gonna be more cautious. But it's gonna be, again, something that will help the overall Oracle proposition. And something that I think will be used with caution by many organizations, but other organizations are gonna like, hey, great, this is something that is really answering a real problem. And that is just easing the use of these databases, but also being able to better handle the automation capabilities and benefits that come with it without having, you know, a major screwup happened and the process of transitioning to more automated capabilities. >>Now, I didn't attend cloud world, it's just too many red eyes, you know, recently, so I passed. But one of the things I like to do at those events is talk to customers, you know, in the spirit of the truth, you know, they, you know, you'd have the hallway, you know, track and to talk to customers and they say, Hey, you know, here's the good, the bad and the ugly. So did you guys, did you talk to any customers my SQL Heatwave customers at, at cloud world? And and what did you learn? I don't know, Mark, did you, did you have any luck and, and having some, some private conversations? >>Yeah, I had quite a few private conversations. The one thing before I get to that, I want disagree with one point Ron made, I do believe there are customers out there buying the heat wave service, the MySEQ heat wave server service because of autopilot. Because autopilot is really revolutionary in many ways in the sense for the MySEQ developer in that it, it auto provisions, it auto parallel loads, IT auto data places it auto shape predictions. It can tell you what machine learning models are going to tell you, gonna give you your best results. And, and candidly, I've yet to meet a DBA who didn't wanna give up pedantic tasks that are pain in the kahoo, which they'd rather not do and if it's long as it was done right for them. So yes, I do think people are buying it because of autopilot and that's based on some of the conversations I had with customers at Oracle Cloud World. >>In fact, it was like, yeah, that's great, yeah, we get fantastic performance, but this really makes my life easier and I've yet to meet a DBA who didn't want to make their life easier. And it does. So yeah, I've talked to a few of them. They were excited. I asked them if they ran into any bugs, were there any difficulties in moving to it? And the answer was no. In both cases, it's interesting to note, my sequel is the most popular database on the planet. Well, some will argue that it's neck and neck with SQL Server, but if you add in Mariah DB and ProCon db, which are forks of MySQL, then yeah, by far and away it's the most popular. And as a result of that, everybody for the most part has typically a my sequel database somewhere in their organization. So this is a brilliant situation for anybody going after MyQ, but especially for heat wave. And the customers I talk to love it. I didn't find anybody complaining about it. And >>What about the migration? We talked about TCO earlier. Did your t does your TCO analysis include the migration cost or do you kind of conveniently leave that out or what? >>Well, when you look at migration costs, there are different kinds of migration costs. By the way, the worst job in the data center is the data migration manager. Forget it, no other job is as bad as that one. You get no attaboys for doing it. Right? And then when you screw up, oh boy. So in real terms, anything that can limit data migration is a good thing. And when you look at Data Lake, that limits data migration. So if you're already a MySEQ user, this is a pure MySQL as far as you're concerned. It's just a, a simple transition from one to the other. You may wanna make sure nothing broke and every you, all your tables are correct and your schema's, okay, but it's all the same. So it's a simple migration. So it's pretty much a non-event, right? When you migrate data from an O LTP to an O L A P, that's an ETL and that's gonna take time. >>But you don't have to do that with my SQL heat wave. So that's gone when you start talking about machine learning, again, you may have an etl, you may not, depending on the circumstances, but again, with my SQL heat wave, you don't, and you don't have duplicate storage, you don't have to copy it from one storage container to another to be able to be used in a different database, which by the way, ultimately adds much more cost than just the other service. So yeah, I looked at the migration and again, the users I talked to said it was a non-event. It was literally moving from one physical machine to another. If they had a new version of MySEQ running on something else and just wanted to migrate it over or just hook it up or just connect it to the data, it worked just fine. >>Okay, so every day it sounds like you guys feel, and we've certainly heard this, my colleague David Foyer, the semi-retired David Foyer was always very high on heatwave. So I think you knows got some real legitimacy here coming from a standing start, but I wanna talk about the competition, how they're likely to respond. I mean, if your AWS and you got heatwave is now in your cloud, so there's some good aspects of that. The database guys might not like that, but the infrastructure guys probably love it. Hey, more ways to sell, you know, EC two and graviton, but you're gonna, the database guys in AWS are gonna respond. They're gonna say, Hey, we got Redshift, we got aqua. What's your thoughts on, on not only how that's gonna resonate with customers, but I'm interested in what you guys think will a, I never say never about aws, you know, and are they gonna try to build, in your view a converged Oola and o LTP database? You know, Snowflake is taking an ecosystem approach. They've added in transactional capabilities to the portfolio so they're not standing still. What do you guys see in the competitive landscape in that regard going forward? Maybe Holger, you could start us off and anybody else who wants to can chime in, >>Happy to, you mentioned Snowflake last, we'll start there. I think Snowflake is imitating that strategy, right? That building out original data warehouse and the clouds tasking project to really proposition to have other data available there because AI is relevant for everybody. Ultimately people keep data in the cloud for ultimately running ai. So you see the same suite kind of like level strategy, it's gonna be a little harder because of the original positioning. How much would people know that you're doing other stuff? And I just, as a former developer manager of developers, I just don't see the speed at the moment happening at Snowflake to become really competitive to Oracle. On the flip side, putting my Oracle hat on for a moment back to you, Mark and Iran, right? What could Oracle still add? Because the, the big big things, right? The traditional chasms in the database world, they have built everything, right? >>So I, I really scratched my hat and gave Nipon a hard time at Cloud world say like, what could you be building? Destiny was very conservative. Let's get the Lakehouse thing done, it's gonna spring next year, right? And the AWS is really hard because AWS value proposition is these small innovation teams, right? That they build two pizza teams, which can be fit by two pizzas, not large teams, right? And you need suites to large teams to build these suites with lots of functionalities to make sure they work together. They're consistent, they have the same UX on the administration side, they can consume the same way, they have the same API registry, can't even stop going where the synergy comes to play over suite. So, so it's gonna be really, really hard for them to change that. But AWS super pragmatic. They're always by themselves that they'll listen to customers if they learn from customers suite as a proposition. I would not be surprised if AWS trying to bring things closer together, being morely together. >>Yeah. Well how about, can we talk about multicloud if, if, again, Oracle is very on on Oracle as you said before, but let's look forward, you know, half a year or a year. What do you think about Oracle's moves in, in multicloud in terms of what kind of penetration they're gonna have in the marketplace? You saw a lot of presentations at at cloud world, you know, we've looked pretty closely at the, the Microsoft Azure deal. I think that's really interesting. I've, I've called it a little bit of early days of a super cloud. What impact do you think this is gonna have on, on the marketplace? But, but both. And think about it within Oracle's customer base, I have no doubt they'll do great there. But what about beyond its existing install base? What do you guys think? >>Ryan, do you wanna jump on that? Go ahead. Go ahead Ryan. No, no, no, >>That's an excellent point. I think it aligns with what we've been talking about in terms of Lakehouse. I think Lake House will enable Oracle to pull more customers, more bicycle customers onto the Oracle platforms. And I think we're seeing all the signs pointing toward Oracle being able to make more inroads into the overall market. And that includes garnishing customers from the leaders in, in other words, because they are, you know, coming in as a innovator, a an alternative to, you know, the AWS proposition, the Google cloud proposition that they have less to lose and there's a result they can really drive the multi-cloud messaging to resonate with not only their existing customers, but also to be able to, to that question, Dave's posing actually garnish customers onto their platform. And, and that includes naturally my sequel but also OCI and so forth. So that's how I'm seeing this playing out. I think, you know, again, Oracle's reporting is indicating that, and I think what we saw, Oracle Cloud world is definitely validating the idea that Oracle can make more waves in the overall market in this regard. >>You know, I, I've floated this idea of Super cloud, it's kind of tongue in cheek, but, but there, I think there is some merit to it in terms of building on top of hyperscale infrastructure and abstracting some of the, that complexity. And one of the things that I'm most interested in is industry clouds and an Oracle acquisition of Cerner. I was struck by Larry Ellison's keynote, it was like, I don't know, an hour and a half and an hour and 15 minutes was focused on healthcare transformation. Well, >>So vertical, >>Right? And so, yeah, so you got Oracle's, you know, got some industry chops and you, and then you think about what they're building with, with not only oci, but then you got, you know, MyQ, you can now run in dedicated regions. You got ADB on on Exadata cloud to customer, you can put that OnPrem in in your data center and you look at what the other hyperscalers are, are doing. I I say other hyperscalers, I've always said Oracle's not really a hyperscaler, but they got a cloud so they're in the game. But you can't get, you know, big query OnPrem, you look at outposts, it's very limited in terms of, you know, the database support and again, that that will will evolve. But now you got Oracle's got, they announced Alloy, we can white label their cloud. So I'm interested in what you guys think about these moves, especially the industry cloud. We see, you know, Walmart is doing sort of their own cloud. You got Goldman Sachs doing a cloud. Do you, you guys, what do you think about that and what role does Oracle play? Any thoughts? >>Yeah, let me lemme jump on that for a moment. Now, especially with the MyQ, by making that available in multiple clouds, what they're doing is this follows the philosophy they've had the past with doing cloud, a customer taking the application and the data and putting it where the customer lives. If it's on premise, it's on premise. If it's in the cloud, it's in the cloud. By making the mice equal heat wave, essentially a plug compatible with any other mice equal as far as your, your database is concern and then giving you that integration with O L A P and ML and Data Lake and everything else, then what you've got is a compelling offering. You're making it easier for the customer to use. So I look the difference between MyQ and the Oracle database, MyQ is going to capture market more market share for them. >>You're not gonna find a lot of new users for the Oracle debate database. Yeah, there are always gonna be new users, don't get me wrong, but it's not gonna be a huge growth. Whereas my SQL heatwave is probably gonna be a major growth engine for Oracle going forward. Not just in their own cloud, but in AWS and in Azure and on premise over time that eventually it'll get there. It's not there now, but it will, they're doing the right thing on that basis. They're taking the services and when you talk about multicloud and making them available where the customer wants them, not forcing them to go where you want them, if that makes sense. And as far as where they're going in the future, I think they're gonna take a page outta what they've done with the Oracle database. They'll add things like JSON and XML and time series and spatial over time they'll make it a, a complete converged database like they did with the Oracle database. The difference being Oracle database will scale bigger and will have more transactions and be somewhat faster. And my SQL will be, for anyone who's not on the Oracle database, they're, they're not stupid, that's for sure. >>They've done Jason already. Right. But I give you that they could add graph and time series, right. Since eat with, Right, Right. Yeah, that's something absolutely right. That's, that's >>A sort of a logical move, right? >>Right. But that's, that's some kid ourselves, right? I mean has worked in Oracle's favor, right? 10 x 20 x, the amount of r and d, which is in the MyQ space, has been poured at trying to snatch workloads away from Oracle by starting with IBM 30 years ago, 20 years ago, Microsoft and, and, and, and didn't work, right? Database applications are extremely sticky when they run, you don't want to touch SIM and grow them, right? So that doesn't mean that heat phase is not an attractive offering, but it will be net new things, right? And what works in my SQL heat wave heat phases favor a little bit is it's not the massive enterprise applications which have like we the nails like, like you might be only running 30% or Oracle, but the connections and the interfaces into that is, is like 70, 80% of your enterprise. >>You take it out and it's like the spaghetti ball where you say, ah, no I really don't, don't want to do all that. Right? You don't, don't have that massive part with the equals heat phase sequel kind of like database which are more smaller tactical in comparison, but still I, I don't see them taking so much share. They will be growing because of a attractive value proposition quickly on the, the multi-cloud, right? I think it's not really multi-cloud. If you give people the chance to run your offering on different clouds, right? You can run it there. The multi-cloud advantages when the Uber offering comes out, which allows you to do things across those installations, right? I can migrate data, I can create data across something like Google has done with B query Omni, I can run predictive models or even make iron models in different place and distribute them, right? And Oracle is paving the road for that, but being available on these clouds. But the multi-cloud capability of database which knows I'm running on different clouds that is still yet to be built there. >>Yeah. And >>That the problem with >>That, that's the super cloud concept that I flowed and I I've always said kinda snowflake with a single global instance is sort of, you know, headed in that direction and maybe has a league. What's the issue with that mark? >>Yeah, the problem with the, with that version, the multi-cloud is clouds to charge egress fees. As long as they charge egress fees to move data between clouds, it's gonna make it very difficult to do a real multi-cloud implementation. Even Snowflake, which runs multi-cloud, has to pass out on the egress fees of their customer when data moves between clouds. And that's really expensive. I mean there, there is one customer I talked to who is beta testing for them, the MySQL heatwave and aws. The only reason they didn't want to do that until it was running on AWS is the egress fees were so great to move it to OCI that they couldn't afford it. Yeah. Egress fees are the big issue but, >>But Mark the, the point might be you might wanna root query and only get the results set back, right was much more tinier, which been the answer before for low latency between the class A problem, which we sometimes still have but mostly don't have. Right? And I think in general this with fees coming down based on the Oracle general E with fee move and it's very hard to justify those, right? But, but it's, it's not about moving data as a multi-cloud high value use case. It's about doing intelligent things with that data, right? Putting into other places, replicating it, what I'm saying the same thing what you said before, running remote queries on that, analyzing it, running AI on it, running AI models on that. That's the interesting thing. Cross administered in the same way. Taking things out, making sure compliance happens. Making sure when Ron says I don't want to be American anymore, I want to be in the European cloud that is gets migrated, right? So tho those are the interesting value use case which are really, really hard for enterprise to program hand by hand by developers and they would love to have out of the box and that's yet the innovation to come to, we have to come to see. But the first step to get there is that your software runs in multiple clouds and that's what Oracle's doing so well with my SQL >>Guys. Amazing. >>Go ahead. Yeah. >>Yeah. >>For example, >>Amazing amount of data knowledge and, and brain power in this market. Guys, I really want to thank you for coming on to the cube. Ron Holger. Mark, always a pleasure to have you on. Really appreciate your time. >>Well all the last names we're very happy for Romanic last and moderator. Thanks Dave for moderating us. All right, >>We'll see. We'll see you guys around. Safe travels to all and thank you for watching this power panel, The Truth About My SQL Heat Wave on the cube. Your leader in enterprise and emerging tech coverage.

Published Date : Nov 1 2022

SUMMARY :

Always a pleasure to have you on. I think you just saw him at Oracle Cloud World and he's come on to describe this is doing, you know, Google is, you know, we heard Google Cloud next recently, They own somewhere between 30 to 50% depending on who you read migrate from one cloud to another and suddenly you have a very compelling offer. All right, so thank you for that. And they certainly with the AI capabilities, And I believe strongly that long term it's gonna be ones who create better value for So I mean it's certainly, you know, when, when Oracle talks about the competitors, So what do you make of the benchmarks? say, Snowflake when it comes to, you know, the Lakehouse platform and threat to keep, you know, a customer in your own customer base. And oh, by the way, as you grow, And I know you look at this a lot, to insight, it doesn't improve all those things that you want out of a database or multiple databases So what about, I wonder ho if you could chime in on the developer angle. they don't have to license more things, send you to more trainings, have more risk of something not being delivered, all the needs of an enterprise to run certain application use cases. I mean I, you know, the rumor was the TK Thomas Curian left Oracle And I think, you know, to holder's point, I think that definitely lines But I agree with Mark, you know, the short term discounting is just a stall tag. testament to Oracle's ongoing ability to, you know, make the ecosystem Yeah, it's interesting when you get these all in one tools, you know, the Swiss Army knife, you expect that it's not able So when you say, yeah, their queries are much better against the lake house in You don't have to come to us to get these, these benefits, I mean the long term, you know, customers tend to migrate towards suite, but the new shiny bring the software to the data is of course interesting and unique and totally an Oracle issue in And the third one, lake house to be limited and the terabyte sizes or any even petabyte size because you want keynote and he was talking about how, you know, most security issues are human I don't think people are gonna buy, you know, lake house exclusively cause of And then, you know, that allows, for example, the specialists to And and what did you learn? The one thing before I get to that, I want disagree with And the customers I talk to love it. the migration cost or do you kind of conveniently leave that out or what? And when you look at Data Lake, that limits data migration. So that's gone when you start talking about So I think you knows got some real legitimacy here coming from a standing start, So you see the same And you need suites to large teams to build these suites with lots of functionalities You saw a lot of presentations at at cloud world, you know, we've looked pretty closely at Ryan, do you wanna jump on that? I think, you know, again, Oracle's reporting I think there is some merit to it in terms of building on top of hyperscale infrastructure and to customer, you can put that OnPrem in in your data center and you look at what the So I look the difference between MyQ and the Oracle database, MyQ is going to capture market They're taking the services and when you talk about multicloud and But I give you that they could add graph and time series, right. like, like you might be only running 30% or Oracle, but the connections and the interfaces into You take it out and it's like the spaghetti ball where you say, ah, no I really don't, global instance is sort of, you know, headed in that direction and maybe has a league. Yeah, the problem with the, with that version, the multi-cloud is clouds And I think in general this with fees coming down based on the Oracle general E with fee move Yeah. Guys, I really want to thank you for coming on to the cube. Well all the last names we're very happy for Romanic last and moderator. We'll see you guys around.

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Ruchir Puri, IBM and Tom Anderson, Red Hat | AnsibleFest 2022


 

>>Good morning live from Chicago. It's the cube on the floor at Ansible Fast 2022. This is day two of our wall to wall coverage. Lisa Martin here with John Furrier. John, we're gonna be talking next in the segment with two alumni about what Red Hat and IBM are doing to give Ansible users AI superpowers. As one of our alumni guests said, just off the keynote stage, we're nearing an inflection point in ai. >>The power of AI with Ansible is really gonna be an innovative, I think an inflection point for a long time because Ansible does such great things. This segment's gonna explore that innovation, bringing AI and making people more productive and more importantly, you know, this whole low code, no code, kind of right in the sweet spot of the skills gap. So should be a great segment. >>Great segment. Please welcome back two of our alumni. Perry is here, the Chief scientist, IBM Research and IBM Fellow. And Tom Anderson joins us once again, VP and general manager at Red Hat. Gentlemen, great to have you on the program. We're gonna have you back. >>Thank you for having >>Us and thanks for joining us. Fresh off the keynote stage. Really enjoyed your keynote this morning. Very exciting news. You have a project called Project Wisdom. We're talking about this inflection point in ai. Tell the audience, the viewers, what is Project Wisdom And Wisdom differs from intelligence. How >>I think Project Wisdom is really about, as I said, sort of combining two major forces that are in many ways disrupting and, and really constructing many a aspects of our society, which are software and AI together. Yeah. And I truly believe it's gonna result in a se shift on how not just enterprises, but society carries forefront. And as I said, intelligence is, is, I would argue at least artificial intelligence is more, in some ways mechanical, if I may say it, it's about algorithms, it's about data, it's about compute. Wisdom is all about what is truly important to bring out. It's not just about when you bring out a, a insight, when you bring out a decision to be able to explain that decision as well. It's almost like humans have wisdom. Machines have intelligence and, and it's about project wisdom. That's why we called it wisdom. >>Because it is about being a, a assistant augmenting humans. Just like be there with the humans and, and almost think of it as behave and interact with them as another colleague will versus intelligence, which is, you know, as I said, more mechanical is about data. Computer algorithms crunch together and, and we wanna bring the power of project wisdom and artificial intelligence to developers to, as you said, close the skills gap to be able to really make them more productive and have wisdom for Ansible be their assistant. Yeah. To be able to get things for them that they would find many ways mundane, many ways hard to find and again, be an assistant and augmented, >>You know, you know what's interesting, I want to get into the origin, how it all happened, but interesting IBM research, well known for the deep tech, big engineering. And you guys have been doing this for a long time, so congratulations. But it's interesting here at this event, even on stage here event, you're starting to see the automation come in. So the question comes up, scale. So what happens, IBM buys Red Hat, you go raid the, the raid, the ip, Trevor Treasure trove of ai. I mean this cuz this is kind of like bringing two killer apps together. The Ansible configuration automation layer with ai just kind of a, >>Yeah, it's an amazing relationship. I was gonna say marriage, but I don't wanna say marriage cause I may be >>Last. I didn't mean say raid the Treasure Trobe, but the kind of >>Like, oh my God. An amazing relationship where we bring all this expertise around automation, obviously around IP and application infrastructure automation and IBM research, Richie and his team bring this amazing capacity and experience around ai. Bring those two things together and applying AI to automation for our teams is so incredibly fantastic. I just can't contain my enthusiasm about it. And you could feel it in the keynote this morning that Richie was doing the energy in the room and when folks saw that, it's just amazing. >>The geeks are gonna love it for sure. But here I wanna get into the whole evolution. Computers on computers, remember the old days thinking machines was a company generations ago that I think they've sold or went outta business, but self-learning, learning machines, computers, programming, computers was actually on your slide you kind of piece out this next wave of AI and machine learning, starting with expert systems really kind of, I'm almost say static, but like okay programs. Yeah, yeah. And then now with machine learning and that big debate was unsupervised, supervised, which is not really perfect. Deep learning, which now explores some things, but now we're at another wave. Take, take us through the thought there explaining what this transition looks like and why. >>I think we are, as I said, we are really at an inflection point in the journey of ai. And if ai, I think it's fair to say data is the pain of ai without data, AI doesn't exist. But if I were to train AI with what is known as supervised learning or or data that is labeled, you are almost sort of limited because there are only so many people who have that expertise. And interestingly, they all have day jobs. So they're not just gonna sit around and label this for you. Some people may be available, but you know, this is not, again, as I as Tom said, we are really trying to apply it to some very sort of key domains which require subject matter expertise. This is not like labeling cats and dogs that everybody else in the board knows there are, the community's very large, but still the skills to go around are not that many. >>And I truly believe to apply AI to the, to the word of, you know, enterprises information technology automation, you have to have unsupervised learning and that's the only way to skate. Yeah. And these two trends really about, you know, information technology percolating across every enterprise and unsupervised learning, which is learning on this very large amount of data with of course know very large compute with some very powerful algorithms like transformer architectures and others which have been disrupting the, the domain of natural language as well are coming together with what I described as foundation models. Yeah. Which anybody who plays with it, you'll be blown away. That's literally blown away. >>And you call that self supervision at scale, which is kind of the foundation. So I have to ask you, cuz this comes up a lot with cloud, cloud scale, everyone tells horizontally scalable cloud, but vertically specialized applications where domain expertise and data plays. So the better the data, the better the self supervision, better the learning. But if it's horizontally scalable is a lot to learn. So how do you create that data ops where it's where the machines are gonna be peaked to maximize what's addressable, but what's also in the domain too, you gotta have that kind of diversity. Can you share your thoughts on that? >>Absolutely. So in, in the domain of foundation models, there are two main stages I would say. One is what I'll describe as pre-training, which is think of it as the, the machine in this particular case is knowledgeable about the domain of code in general. It knows syntax of Python, Java script know, go see Java and so, so on actually, and, and also Yammel as well, which is obviously one would argue is the domain of information technology. And once you get to that level, it's a, it's almost like having a developer who knows all of this but may not be an expert at Ansible just yet. He or she can be an expert at Ansible but is not there yet. That's what I'll call background knowledge. And also in the, in the case of foundation models, they are very adept at natural language as well. So they can connect natural language to code, but they are not yet expert at the domain of Ansible. >>Now there's something called, the second stage of learning is called fine tuning, which is about this data ops where I take data, which is sort of the SME data in this particular case. And it's curated. So this is not just generic data, you pick off GitHub, you don't know what exists out there. This is the data which is governed, which we know is of high quality as well. And you think of it as you specialize the generic AI with pre-trained AI with that data. And those two stages, including the governance of that data that goes into it results in this sort of really breakthrough technology that we've been calling Project Wisdom for. Our first application is Ansible, but just watch out that area. There are many more to come and, and we are gonna really, I'm really excited about this partnership with Red Hat because across IBM and research, I think where wherever we, if there is one place where we can find excited, open source, open developer community, it is Right. That's, >>Yeah. >>Tom, talk about the, the role of open source and Project Wisdom, the involvement of the community and maybe Richard, any feedback that you've gotten since coming off stage? I'm sure you were mobbed. >>Yeah, so for us this is, it's called Project Wisdom, not Product Wisdom. Right? Sorry. Right. And so, no, you didn't say that but I wanna just emphasize that it is a project and for us that is a key word in the upstream community that this is where we're inviting the community to jump on board with us and bring their expertise. All these people that are here will start to participate. They're excited in it. They'll bring their expertise and experience and that fine tuning of the model will just get better and better. So we're really excited about introducing this now and involving the community because it's super nuts. Everything that Red Hat does is around the community and this is no different. And so we're really excited about Project Wisdom. >>That's interesting. The project piece because if you see in today's world the innovation strategy before where we are now, go back to say 15 years ago it was of standard, it's gotta have standard bodies. You can still innovate and differentiate, but yet with open source and community, it's a blending of research and practitioners. I think that to me is a big story here is that what you guys are demonstrating is the combination of research and practitioners in the project. Yes. So how does this play out? Cuz this is kind of like how things are gonna get done in the cloud cuz Amazon's not gonna just standardize their stack at at higher level services, nor is Azure and they might get some plumbing commonalities below, but for Project Project Wisdom to be successful, they can, it doesn't need to have standards. If I get this right, if I can my on point here, what do you guys think about that? React to that? Yeah, >>So I definitely, I think standardization in terms of what we will call ML ops pipeline for models to be deployed and managed and operated. It's like models, like any other code, there's standardization on DevOps ops pipeline, there's standardization on machine learning pipeline. And these models will be deployed in the cloud because they need to scale. The only way to scale to, you know, thousands of users is through cloud. And there is, there are standard pipelines that we are working and architecting together with the Red Hat community leveraging open source packages. Yeah. Is really to, to help scale out the AI models of wisdom together. And another point I wanted to pick up on just what Tom said, I've been sort of in the area of productizing AI for for long now having experience with Watson as well. The only scenario where I've seen AI being successful is in this scenario where, what I describe as it meets the criteria of flywheel of ai. >>What do I mean by flywheel of ai? It cannot be some research people build a model. It may be wowing, but you roll it out and there's no feedback. Yeah, exactly. Okay. We are duh. So what actually, the only way the more people use these models, the more they give you feedback, the better it gets because it knows what is right and what is not right. It will never be right the first time. Actually, you know, the data it is trained on is a depiction of reality. Yeah. It is not a reality in itself. Yeah. The reality is a constantly moving target and the only way to make AI successful is to close that loop with the community. And that's why I just wanted to reemphasize the point on why community is that important >>Actually. And what's interesting Tom is this is a difference between standards bodies, old school and communities. Because developers are very efficient in their feedback. Yes. They jump to patterns that serve their needs, whether it's self-service or whatever. You can kind of see what's going on. Yeah. It's either working or not. Yeah, yeah, >>Yeah. We get immediate feedback from the community and we know real fast when something isn't working, when something is working, there are no problems with the flow of data between the members of the community and, and the developers themselves. So yeah, it's, I'm it's great. It's gonna be fantastic. The energy around Project Wisdom already. I bet. We're gonna go down to the Project Wisdom session, the breakout session, and I bet you the room will be overflowed. >>How do people get involved real quick? Get, get a take a minute to explain how I would get involved. I'm a community member. Yep. I'm watching this video, I'm intrigued. This has got me enthusiastic. How do I get more confident with this opportunity? >>So you go to, first of all, you go to red hat.com/project Wisdom and you register your interests and you wanna participate. We're gonna start growing this process, bringing people in, getting ready to make the service available to people to start using and to experiment with. Start getting their feedback. So this is the beginning of, of a journey. This isn't the, you know, this isn't the midpoint of a journey, this is the begin. You know, even though the work has been going on for a year, this is the beginning of the community journey now. And so we're gonna start working together through channels like Discord and whatnot to be able to exchange information and bring people in. >>What are some of the key use cases, maybe Richie are starting with you that, that you think maybe dream use cases that you think the community will help to really uncover as we're looking at Project Wisdom really helping in this transformation of ai. >>So if I focus on let's say Ansible itself, there are much wider use cases, but Ansible itself and you know, I, I would say I had not realized, I've been working on AI for Good for long, but I had not realized the excitement and the power of Ansible community itself. It's very large, it's very bottom sum, which I love actually. But as I went to lot of like CTOs and CIOs of lot of our customers as well, it was becoming clear the use cases of, you know, I've got thousand Ansible developers or IT or automation experts. They write code all the time. I don't know what all of this code is about. So the, the system administrators, managers, they're trying to figure out sort of how to organize all of this together and think of it as Google for finding all of these automation code automation content. >>And I'm very excited about not just the use cases that we demonstrated today, that is beginning of the journey, but to be able to help enterprises in finding the right code through natural language interfaces, generating the code, helping Del us debug their code as well. Giving them predictive insights into this may happen. Just watch out for it when you deploy this. Something like that happened before, just watch out for it as well. So I'm, I'm excited about the entire life cycle of IT automation, Not just about at the build time, but also at the time of deployment. At the time of management. This is just a start of a journey, but there are many exciting use cases abound for Ansible and beyond. >>It's gonna be great to watch this as it unfolds. Obviously just announcing this today. We thank you both so much for joining us on the program, talking about Project wisdom and, and sharing how the community can get involved. So you're gonna have to come back next year. We're gonna have to talk about what's going on. Cause I imagine with the excitement of the community and the volume of the community, this is just the tip of the iceberg. Absolutely. >>This is absolutely exactly. You're excited about. >>Excellent. And you should be. Congratulations. Thank, thanks again for joining us. We really appreciate your insights. Thank you. Thank >>You for having >>Us. For our guests and John Furrier, I'm Lisa Barton and you're watching The Cube Lie from Chicago at Ansible Fest 22. This is day two of wall to wall coverage on the cube. Stick around. Our next guest joins us in just a minute.

Published Date : Oct 19 2022

SUMMARY :

It's the cube on the floor at Ansible Fast 2022. bringing AI and making people more productive and more importantly, you know, this whole low code, Gentlemen, great to have you on the program. Tell the audience, the viewers, what is Project Wisdom And Wisdom differs from intelligence. It's not just about when you bring out a, a insight, when you bring out a decision to to developers to, as you said, close the skills gap to And you guys have been doing this for a long time, I was gonna say marriage, And you could feel it in the keynote this morning And then now with machine learning and that big debate was unsupervised, This is not like labeling cats and dogs that everybody else in the board the domain of natural language as well are coming together with And you call that self supervision at scale, which is kind of the foundation. And once you So this is not just generic data, you pick off GitHub, of the community and maybe Richard, any feedback that you've gotten since coming off stage? Everything that Red Hat does is around the community and this is no different. story here is that what you guys are demonstrating is the combination of research and practitioners The only way to scale to, you know, thousands of users is through the only way to make AI successful is to close that loop with the community. They jump to patterns that serve the breakout session, and I bet you the room will be overflowed. Get, get a take a minute to explain how I would get involved. So you go to, first of all, you go to red hat.com/project Wisdom and you register your interests and you What are some of the key use cases, maybe Richie are starting with you that, that you think maybe dream use the use cases of, you know, I've got thousand Ansible developers So I'm, I'm excited about the entire life cycle of IT automation, and sharing how the community can get involved. This is absolutely exactly. And you should be. This is day two of wall to wall coverage on the cube.

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Druva Why Ransomware Isn't Your Only Problem


 

>> 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)

Published Date : Oct 13 2022

SUMMARY :

and prepared for the threats they face It's great to have you back on theCUBE. to be here with you. of the global IT landscape and it has the attention, all the way up the stack to the C-suite, and helping the organization has to be a data company in the context of IT computing. that organizations need to be aware of? and that is the area of ransomware. the demographics of the survey and kind of the aha moment of this is going to happen, and to take advantage of the key advantages and that extends the time to recover and not lose data in the that you articulated, the CIO, the CSO, you know, whoever it is, So all the way at the top, And the reason we say that is, you know, to have you on the program. Thank you, Lisa. and you are watching theCUBE, and to extract critical insights. and the Druva special presentation So it's great to have you here because the backup person often, you know, It's funny, you know. and the realities of how is that you pay blackmail. Yeah, so the fact that, you know, 60, and even the psychology Yeah, I hear where you coming from. or that the backup systems is that the attack vectors and then letting you know you have ransom. They all kind of have the same problem. is the best you can get I guess that's the question here. And that's the way that you Very much the future. So in the future, if you use Now it really is about the and they get to do a full test and thanks for the insight. Always happy to talk and Anjan Srinivas, the GM and VP none of the weaknesses This is the topic. and causes a lot of problems, disruption. and reads it is going to that they needed to do. that comes in the market, I'm desperate. Where does the logic need to reside? and let's face it, the disk-based and the cloud native of being a SaaS service in the cloud is We just reviewed the IDC with Phil. and they need to manage and operate, of the disruption side of it. And so the guarantee actually protects you I'd love to have you share So that is the second level of insights actually kind of the record really easy to consume, the scale to the table, and the future of cloud native Druva is the only 100% SaaS vendor is that in the scramble

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Druva Why Ransomware Isn't Your Only Problem Full Episode V3


 

>>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.

Published Date : Oct 6 2022

SUMMARY :

Now, the first major change was to recognize that the perimeter had suddenly And that new approaches to operational resilience were general manager of product management at the company. It's great to have you back on the cube. of the IT people, but of the business people alike, because it really does have a priority all the way up the stack to the C-suite. and helping the organization to extract value from their data to be a data company to be competitive, digital resilience, data resilience. But data resilience is really a part of digital resilience, if you think about the data itself 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 the fact Let, let's talk a little bit about the demographics of the survey and then talk about what was CTOs, VP of of infrastructure, you know, managers of data centers, the bad guys aren't, aren't necessarily to be trusted. And these people are smart people and, and they're professionals, but oftentimes you don't know what you don't know. in this situation across any industry can do to truly enable And the fact of the matter is a disaster recovery What are some of the advantages? And in the old days when we had disaster recoveries where So if they have those resources in place, then they can simply turn them on, Those are the kinds of things that organizations have to put into place really what do you recommend organizations? the c cso, you know, whoever it is, they're extremely concerned about these. So all the way at the top critically important, business critical for any industry. And the reason we say that is, you know, Phil, it's been a pleasure to have you on the program. Thank you, Lisa. I'm Lisa Martin and you are watching the Cube, the leader in live tech coverage. the answer often boils down to what flavor of complexity do you like best? the DR A platform automates and manages critical daily tasks giving you time I'm John Furrier, host of the Cube. So it's great to have you here for this special presentation. because the backup person often, you know, might say that it's great because maybe It's funny, you know, we're good boss, we got this covered. not only like they get hit once, so, you know, this is a constant chasing the tail on some the ransom, which as, as a person who, you know, the people that were attacked by ransomware paid the ransom. for the bad guys if they know you're paying up and if you're stupid enough not to change, I I think it's a, it's a litany of thing starting with the, that aspect that I mentioned before, Yeah, but I I I hear where you come from exactly. so that you can have SSO and things like that. So what you're saying is that the attack vectors and the attackers are getting smarter. the backups first and then deleting them and then letting you know you Okay, so you guys have a lot of customers, they all kind of have the same this problem. after doing many, many layers of defense on the other side and having to do all that work with I guess how do, how do you break the laws of physics? And that's the, i that's the way that you break the laws So in the future, if you use a SAS data protection system seen that been in the ways of innovation now it's really is about the recovery and real time. all of our competitors have to do to, you know, to, to break, to try to break the laws Great stuff Chris, great to have you on, bring that perspective and thanks for the insight. Always happy to talk about my favorite subject. the GM and VP of Product Manage will join me. The good news is that you can keep your data safe and recover faster with in the event of an attack. the IDC white paper that you guys put together with IDC really kind Ransomware is continues to thunder away at businesses and causes a lot of So I'll say the, the thing that pops out to me is, is on the one hand, And I think the other important thing to note, John, is that people are grappling So it seems to be that there's a confidence problem you know, driven at a data insight level where we have people even monitoring our service finish the story so to say, right? And you scratch your head and you think, well if your backup environment I wanna get to in second, you know, I interviewed Jare, the the founder CEO many years ago, but the most obvious one that always comes up is every single backup you do with DVA And one of the nice parts of being a SA service in the cloud is How are you guys responding to your customer's needs? overall security operating model that they are really owning and they need to manage and operate And that has been this age old problem, do more with less. of this mindset of kind of being able to look at where each of those functionalities need to lie. And you guys have this guarantee, And so the guarantee actually protects you against multiple types of risks all with SLAs. this to work is to have a service that can provide you SLAs across all of the risks because You mentioned the new workloads on John, you mentioned this new security hearing shift left DevOps is now the and analytics on that data to protect themselves and secure themselves and do interesting things with So that is the second level of insights and And so, you know, what engine said is, you know, one of the great things of being a SaaS provider is I have metadata That's great stuff. a service simplicity to kind of continue on amongst kind of keeping these complex But the end of the day automation, cross cloud protection and security to protect and It's not just ransomware they have to worry about. and control can leave you exposed to security vulnerabilities, including ransomware that frequency of attacks is on the rise and the severity of

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Phil Goodwin, Druva, Why Ransomware Isn't Your Only Problem


 

>>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.

Published Date : Oct 6 2022

SUMMARY :

Now, the first major change was to recognize that the perimeter had suddenly And that new approaches to operational resilience were general manager of product management at the company. It's great to have you back on the cube. of the IT people, but of the business people alike, because it really does have a priority all the way up the stack to the C-suite. and helping the organization to extract value from their data to be a data company to be competitive, digital resilience, data resilience. and the context of of IT computing. 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 the fact Let, let's talk a little bit about the demographics of the survey and then talk about what was CTOs, VP of of infrastructure, you know, managers of data centers, the bad guys aren't, aren't necessarily to be trusted. And like I say, the bad guys are always dreaming up new ways to attack us. this situation across any industry can do to truly enable And the fact of the matter is a disaster recovery What are some of the advantages? And in the old days when we had disaster recoveries where So if they have those resources in place, then they can simply turn them on, Those are the kinds of things that organizations have to put into place really the landscape threat landscape just gets more and more amorphous. the c cso, you know, whoever it is, they're extremely concerned about these. So all the way at the top critically important, business critical for any industry. And the reason we say that is, you know, Phil, it's been a pleasure to have you on the program. Thank you, Lisa. I'm Lisa Martin and you are watching The Cube, the leader in live tech coverage.

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Data Power Panel V3


 

(upbeat music) >> The stampede to cloud and massive VC investments has led to the emergence of a new generation of object store based data lakes. And with them two important trends, actually three important trends. First, a new category that combines data lakes and data warehouses aka the lakehouse is emerged as a leading contender to be the data platform of the future. And this novelty touts the ability to address data engineering, data science, and data warehouse workloads on a single shared data platform. The other major trend we've seen is query engines and broader data fabric virtualization platforms have embraced NextGen data lakes as platforms for SQL centric business intelligence workloads, reducing, or somebody even claim eliminating the need for separate data warehouses. Pretty bold. However, cloud data warehouses have added complimentary technologies to bridge the gaps with lakehouses. And the third is many, if not most customers that are embracing the so-called data fabric or data mesh architectures. They're looking at data lakes as a fundamental component of their strategies, and they're trying to evolve them to be more capable, hence the interest in lakehouse, but at the same time, they don't want to, or can't abandon their data warehouse estate. As such we see a battle royale is brewing between cloud data warehouses and cloud lakehouses. Is it possible to do it all with one cloud center analytical data platform? Well, we're going to find out. My name is Dave Vellante and welcome to the data platform's power panel on theCUBE. Our next episode in a series where we gather some of the industry's top analysts to talk about one of our favorite topics, data. In today's session, we'll discuss trends, emerging options, and the trade offs of various approaches and we'll name names. Joining us today are Sanjeev Mohan, who's the principal at SanjMo, Tony Baers, principal at dbInsight. And Doug Henschen is the vice president and principal analyst at Constellation Research. Guys, welcome back to theCUBE. Great to see you again. >> Thank guys. Thank you. >> Thank you. >> So it's early June and we're gearing up with two major conferences, there's several database conferences, but two in particular that were very interested in, Snowflake Summit and Databricks Data and AI Summit. Doug let's start off with you and then Tony and Sanjeev, if you could kindly weigh in. Where did this all start, Doug? The notion of lakehouse. And let's talk about what exactly we mean by lakehouse. Go ahead. >> Yeah, well you nailed it in your intro. One platform to address BI data science, data engineering, fewer platforms, less cost, less complexity, very compelling. You can credit Databricks for coining the term lakehouse back in 2020, but it's really a much older idea. You can go back to Cloudera introducing their Impala database in 2012. That was a database on top of Hadoop. And indeed in that last decade, by the middle of that last decade, there were several SQL on Hadoop products, open standards like Apache Drill. And at the same time, the database vendors were trying to respond to this interest in machine learning and the data science. So they were adding SQL extensions, the likes Hudi and Vertical we're adding SQL extensions to support the data science. But then later in that decade with the shift to cloud and object storage, you saw the vendor shift to this whole cloud, and object storage idea. So you have in the database camp Snowflake introduce Snowpark to try to address the data science needs. They introduced that in 2020 and last year they announced support for Python. You also had Oracle, SAP jumped on this lakehouse idea last year, supporting both the lake and warehouse single vendor, not necessarily quite single platform. Google very recently also jumped on the bandwagon. And then you also mentioned, the SQL engine camp, the Dremios, the Ahanas, the Starbursts, really doing two things, a fabric for distributed access to many data sources, but also very firmly planning that idea that you can just have the lake and we'll help you do the BI workloads on that. And then of course, the data lake camp with the Databricks and Clouderas providing a warehouse style deployments on top of their lake platforms. >> Okay, thanks, Doug. I'd be remiss those of you who me know that I typically write my own intros. This time my colleagues fed me a lot of that material. So thank you. You guys make it easy. But Tony, give us your thoughts on this intro. >> Right. Well, I very much agree with both of you, which may not make for the most exciting television in terms of that it has been an evolution just like Doug said. I mean, for instance, just to give an example when Teradata bought AfterData was initially seen as a hardware platform play. In the end, it was basically, it was all those after functions that made a lot of sort of big data analytics accessible to SQL. (clears throat) And so what I really see just in a more simpler definition or functional definition, the data lakehouse is really an attempt by the data lake folks to make the data lake friendlier territory to the SQL folks, and also to get into friendly territory, to all the data stewards, who are basically concerned about the sprawl and the lack of control in governance in the data lake. So it's really kind of a continuing of an ongoing trend that being said, there's no action without counter action. And of course, at the other end of the spectrum, we also see a lot of the data warehouses starting to edit things like in database machine learning. So they're certainly not surrendering without a fight. Again, as Doug was mentioning, this has been part of a continual blending of platforms that we've seen over the years that we first saw in the Hadoop years with SQL on Hadoop and data warehouses starting to reach out to cloud storage or should say the HDFS and then with the cloud then going cloud native and therefore trying to break the silos down even further. >> Now, thank you. And Sanjeev, data lakes, when we first heard about them, there were such a compelling name, and then we realized all the problems associated with them. So pick it up from there. What would you add to Doug and Tony? >> I would say, these are excellent points that Doug and Tony have brought to light. The concept of lakehouse was going on to your point, Dave, a long time ago, long before the tone was invented. For example, in Uber, Uber was trying to do a mix of Hadoop and Vertical because what they really needed were transactional capabilities that Hadoop did not have. So they weren't calling it the lakehouse, they were using multiple technologies, but now they're able to collapse it into a single data store that we call lakehouse. Data lakes, excellent at batch processing large volumes of data, but they don't have the real time capabilities such as change data capture, doing inserts and updates. So this is why lakehouse has become so important because they give us these transactional capabilities. >> Great. So I'm interested, the name is great, lakehouse. The concept is powerful, but I get concerned that it's a lot of marketing hype behind it. So I want to examine that a bit deeper. How mature is the concept of lakehouse? Are there practical examples that really exist in the real world that are driving business results for practitioners? Tony, maybe you could kick that off. >> Well, put it this way. I think what's interesting is that both data lakes and data warehouse that each had to extend themselves. To believe the Databricks hype it's that this was just a natural extension of the data lake. In point of fact, Databricks had to go outside its core technology of Spark to make the lakehouse possible. And it's a very similar type of thing on the part with data warehouse folks, in terms of that they've had to go beyond SQL, In the case of Databricks. There have been a number of incremental improvements to Delta lake, to basically make the table format more performative, for instance. But the other thing, I think the most dramatic change in all that is in their SQL engine and they had to essentially pretty much abandon Spark SQL because it really, in off itself Spark SQL is essentially stop gap solution. And if they wanted to really address that crowd, they had to totally reinvent SQL or at least their SQL engine. And so Databricks SQL is not Spark SQL, it is not Spark, it's basically SQL that it's adapted to run in a Spark environment, but the underlying engine is C++, it's not scale or anything like that. So Databricks had to take a major detour outside of its core platform to do this. So to answer your question, this is not mature because these are all basically kind of, even though the idea of blending platforms has been going on for well over a decade, I would say that the current iteration is still fairly immature. And in the cloud, I could see a further evolution of this because if you think through cloud native architecture where you're essentially abstracting compute from data, there is no reason why, if let's say you are dealing with say, the same basically data targets say cloud storage, cloud object storage that you might not apportion the task to different compute engines. And so therefore you could have, for instance, let's say you're Google, you could have BigQuery, perform basically the types of the analytics, the SQL analytics that would be associated with the data warehouse and you could have BigQuery ML that does some in database machine learning, but at the same time for another part of the query, which might involve, let's say some deep learning, just for example, you might go out to let's say the serverless spark service or the data proc. And there's no reason why Google could not blend all those into a coherent offering that's basically all triggered through microservices. And I just gave Google as an example, if you could generalize that with all the other cloud or all the other third party vendors. So I think we're still very early in the game in terms of maturity of data lakehouses. >> Thanks, Tony. So Sanjeev, is this all hype? What are your thoughts? >> It's not hype, but completely agree. It's not mature yet. Lakehouses have still a lot of work to do, so what I'm now starting to see is that the world is dividing into two camps. On one hand, there are people who don't want to deal with the operational aspects of vast amounts of data. They are the ones who are going for BigQuery, Redshift, Snowflake, Synapse, and so on because they want the platform to handle all the data modeling, access control, performance enhancements, but these are trade off. If you go with these platforms, then you are giving up on vendor neutrality. On the other side are those who have engineering skills. They want the independence. In other words, they don't want vendor lock in. They want to transform their data into any number of use cases, especially data science, machine learning use case. What they want is agility via open file formats using any compute engine. So why do I say lakehouses are not mature? Well, cloud data warehouses they provide you an excellent user experience. That is the main reason why Snowflake took off. If you have thousands of cables, it takes minutes to get them started, uploaded into your warehouse and start experimentation. Table formats are far more resonating with the community than file formats. But once the cost goes up of cloud data warehouse, then the organization start exploring lakehouses. But the problem is lakehouses still need to do a lot of work on metadata. Apache Hive was a fantastic first attempt at it. Even today Apache Hive is still very strong, but it's all technical metadata and it has so many different restrictions. That's why we see Databricks is investing into something called Unity Catalog. Hopefully we'll hear more about Unity Catalog at the end of the month. But there's a second problem. I just want to mention, and that is lack of standards. All these open source vendors, they're running, what I call ego projects. You see on LinkedIn, they're constantly battling with each other, but end user doesn't care. End user wants a problem to be solved. They want to use Trino, Dremio, Spark from EMR, Databricks, Ahana, DaaS, Frink, Athena. But the problem is that we don't have common standards. >> Right. Thanks. So Doug, I worry sometimes. I mean, I look at the space, we've debated for years, best of breed versus the full suite. You see AWS with whatever, 12 different plus data stores and different APIs and primitives. You got Oracle putting everything into its database. It's actually done some interesting things with MySQL HeatWave, so maybe there's proof points there, but Snowflake really good at data warehouse, simplifying data warehouse. Databricks, really good at making lakehouses actually more functional. Can one platform do it all? >> Well in a word, I can't be best at breed at all things. I think the upshot of and cogen analysis from Sanjeev there, the database, the vendors coming out of the database tradition, they excel at the SQL. They're extending it into data science, but when it comes to unstructured data, data science, ML AI often a compromise, the data lake crowd, the Databricks and such. They've struggled to completely displace the data warehouse when it really gets to the tough SLAs, they acknowledge that there's still a role for the warehouse. Maybe you can size down the warehouse and offload some of the BI workloads and maybe and some of these SQL engines, good for ad hoc, minimize data movement. But really when you get to the deep service level, a requirement, the high concurrency, the high query workloads, you end up creating something that's warehouse like. >> Where do you guys think this market is headed? What's going to take hold? Which projects are going to fade away? You got some things in Apache projects like Hudi and Iceberg, where do they fit Sanjeev? Do you have any thoughts on that? >> So thank you, Dave. So I feel that table formats are starting to mature. There is a lot of work that's being done. We will not have a single product or single platform. We'll have a mixture. So I see a lot of Apache Iceberg in the news. Apache Iceberg is really innovating. Their focus is on a table format, but then Delta and Apache Hudi are doing a lot of deep engineering work. For example, how do you handle high concurrency when there are multiple rights going on? Do you version your Parquet files or how do you do your upcerts basically? So different focus, at the end of the day, the end user will decide what is the right platform, but we are going to have multiple formats living with us for a long time. >> Doug is Iceberg in your view, something that's going to address some of those gaps in standards that Sanjeev was talking about earlier? >> Yeah, Delta lake, Hudi, Iceberg, they all address this need for consistency and scalability, Delta lake open technically, but open for access. I don't hear about Delta lakes in any worlds, but Databricks, hearing a lot of buzz about Apache Iceberg. End users want an open performance standard. And most recently Google embraced Iceberg for its recent a big lake, their stab at having supporting both lakes and warehouses on one conjoined platform. >> And Tony, of course, you remember the early days of the sort of big data movement you had MapR was the most closed. You had Horton works the most open. You had Cloudera in between. There was always this kind of contest as to who's the most open. Does that matter? Are we going to see a repeat of that here? >> I think it's spheres of influence, I think, and Doug very much was kind of referring to this. I would call it kind of like the MongoDB syndrome, which is that you have... and I'm talking about MongoDB before they changed their license, open source project, but very much associated with MongoDB, which basically, pretty much controlled most of the contributions made decisions. And I think Databricks has the same iron cloud hold on Delta lake, but still the market is pretty much associated Delta lake as the Databricks, open source project. I mean, Iceberg is probably further advanced than Hudi in terms of mind share. And so what I see that's breaking down to is essentially, basically the Databricks open source versus the everything else open source, the community open source. So I see it's a very similar type of breakdown that I see repeating itself here. >> So by the way, Mongo has a conference next week, another data platform is kind of not really relevant to this discussion totally. But in the sense it is because there's a lot of discussion on earnings calls these last couple of weeks about consumption and who's exposed, obviously people are concerned about Snowflake's consumption model. Mongo is maybe less exposed because Atlas is prominent in the portfolio, blah, blah, blah. But I wanted to bring up the little bit of controversy that we saw come out of the Snowflake earnings call, where the ever core analyst asked Frank Klutman about discretionary spend. And Frank basically said, look, we're not discretionary. We are deeply operationalized. Whereas he kind of poo-pooed the lakehouse or the data lake, et cetera, saying, oh yeah, data scientists will pull files out and play with them. That's really not our business. Do any of you have comments on that? Help us swing through that controversy. Who wants to take that one? >> Let's put it this way. The SQL folks are from Venus and the data scientists are from Mars. So it means it really comes down to it, sort that type of perception. The fact is, is that, traditionally with analytics, it was very SQL oriented and that basically the quants were kind of off in their corner, where they're using SaaS or where they're using Teradata. It's really a great leveler today, which is that, I mean basic Python it's become arguably one of the most popular programming languages, depending on what month you're looking at, at the title index. And of course, obviously SQL is, as I tell the MongoDB folks, SQL is not going away. You have a large skills base out there. And so basically I see this breaking down to essentially, you're going to have each group that's going to have its own natural preferences for its home turf. And the fact that basically, let's say the Python and scale of folks are using Databricks does not make them any less operational or machine critical than the SQL folks. >> Anybody else want to chime in on that one? >> Yeah, I totally agree with that. Python support in Snowflake is very nascent with all of Snowpark, all of the things outside of SQL, they're very much relying on partners too and make things possible and make data science possible. And it's very early days. I think the bottom line, what we're going to see is each of these camps is going to keep working on doing better at the thing that they don't do today, or they're new to, but they're not going to nail it. They're not going to be best of breed on both sides. So the SQL centric companies and shops are going to do more data science on their database centric platform. That data science driven companies might be doing more BI on their leagues with those vendors and the companies that have highly distributed data, they're going to add fabrics, and maybe offload more of their BI onto those engines, like Dremio and Starburst. >> So I've asked you this before, but I'll ask you Sanjeev. 'Cause Snowflake and Databricks are such great examples 'cause you have the data engineering crowd trying to go into data warehousing and you have the data warehousing guys trying to go into the lake territory. Snowflake has $5 billion in the balance sheet and I've asked you before, I ask you again, doesn't there has to be a semantic layer between these two worlds? Does Snowflake go out and do M&A and maybe buy ad scale or a data mirror? Or is that just sort of a bandaid? What are your thoughts on that Sanjeev? >> I think semantic layer is the metadata. The business metadata is extremely important. At the end of the day, the business folks, they'd rather go to the business metadata than have to figure out, for example, like let's say, I want to update somebody's email address and we have a lot of overhead with data residency laws and all that. I want my platform to give me the business metadata so I can write my business logic without having to worry about which database, which location. So having that semantic layer is extremely important. In fact, now we are taking it to the next level. Now we are saying that it's not just a semantic layer, it's all my KPIs, all my calculations. So how can I make those calculations independent of the compute engine, independent of the BI tool and make them fungible. So more disaggregation of the stack, but it gives us more best of breed products that the customers have to worry about. >> So I want to ask you about the stack, the modern data stack, if you will. And we always talk about injecting machine intelligence, AI into applications, making them more data driven. But when you look at the application development stack, it's separate, the database is tends to be separate from the data and analytics stack. Do those two worlds have to come together in the modern data world? And what does that look like organizationally? >> So organizationally even technically I think it is starting to happen. Microservices architecture was a first attempt to bring the application and the data world together, but they are fundamentally different things. For example, if an application crashes, that's horrible, but Kubernetes will self heal and it'll bring the application back up. But if a database crashes and corrupts your data, we have a huge problem. So that's why they have traditionally been two different stacks. They are starting to come together, especially with data ops, for instance, versioning of the way we write business logic. It used to be, a business logic was highly embedded into our database of choice, but now we are disaggregating that using GitHub, CICD the whole DevOps tool chain. So data is catching up to the way applications are. >> We also have databases, that trans analytical databases that's a little bit of what the story is with MongoDB next week with adding more analytical capabilities. But I think companies that talk about that are always careful to couch it as operational analytics, not the warehouse level workloads. So we're making progress, but I think there's always going to be, or there will long be a separate analytical data platform. >> Until data mesh takes over. (all laughing) Not opening a can of worms. >> Well, but wait, I know it's out of scope here, but wouldn't data mesh say, hey, do take your best of breed to Doug's earlier point. You can't be best of breed at everything, wouldn't data mesh advocate, data lakes do your data lake thing, data warehouse, do your data lake, then you're just a node on the mesh. (Tony laughs) Now you need separate data stores and you need separate teams. >> To my point. >> I think, I mean, put it this way. (laughs) Data mesh itself is a logical view of the world. The data mesh is not necessarily on the lake or on the warehouse. I think for me, the fear there is more in terms of, the silos of governance that could happen and the silo views of the world, how we redefine. And that's why and I want to go back to something what Sanjeev said, which is that it's going to be raising the importance of the semantic layer. Now does Snowflake that opens a couple of Pandora's boxes here, which is one, does Snowflake dare go into that space or do they risk basically alienating basically their partner ecosystem, which is a key part of their whole appeal, which is best of breed. They're kind of the same situation that Informatica was where in the early 2000s, when Informatica briefly flirted with analytic applications and realized that was not a good idea, need to redouble down on their core, which was data integration. The other thing though, that raises the importance of and this is where the best of breed comes in, is the data fabric. My contention is that and whether you use employee data mesh practice or not, if you do employee data mesh, you need data fabric. If you deploy data fabric, you don't necessarily need to practice data mesh. But data fabric at its core and admittedly it's a category that's still very poorly defined and evolving, but at its core, we're talking about a common meta data back plane, something that we used to talk about with master data management, this would be something that would be more what I would say basically, mutable, that would be more evolving, basically using, let's say, machine learning to kind of, so that we don't have to predefine rules or predefine what the world looks like. But so I think in the long run, what this really means is that whichever way we implement on whichever physical platform we implement, we need to all be speaking the same metadata language. And I think at the end of the day, regardless of whether it's a lake, warehouse or a lakehouse, we need common metadata. >> Doug, can I come back to something you pointed out? That those talking about bringing analytic and transaction databases together, you had talked about operationalizing those and the caution there. Educate me on MySQL HeatWave. I was surprised when Oracle put so much effort in that, and you may or may not be familiar with it, but a lot of folks have talked about that. Now it's got nowhere in the market, that no market share, but a lot of we've seen these benchmarks from Oracle. How real is that bringing together those two worlds and eliminating ETL? >> Yeah, I have to defer on that one. That's my colleague, Holger Mueller. He wrote the report on that. He's way deep on it and I'm not going to mock him. >> I wonder if that is something, how real that is or if it's just Oracle marketing, anybody have any thoughts on that? >> I'm pretty familiar with HeatWave. It's essentially Oracle doing what, I mean, there's kind of a parallel with what Google's doing with AlloyDB. It's an operational database that will have some embedded analytics. And it's also something which I expect to start seeing with MongoDB. And I think basically, Doug and Sanjeev were kind of referring to this before about basically kind of like the operational analytics, that are basically embedded within an operational database. The idea here is that the last thing you want to do with an operational database is slow it down. So you're not going to be doing very complex deep learning or anything like that, but you might be doing things like classification, you might be doing some predictives. In other words, we've just concluded a transaction with this customer, but was it less than what we were expecting? What does that mean in terms of, is this customer likely to turn? I think we're going to be seeing a lot of that. And I think that's what a lot of what MySQL HeatWave is all about. Whether Oracle has any presence in the market now it's still a pretty new announcement, but the other thing that kind of goes against Oracle, (laughs) that they had to battle against is that even though they own MySQL and run the open source project, everybody else, in terms of the actual commercial implementation it's associated with everybody else. And the popular perception has been that MySQL has been basically kind of like a sidelight for Oracle. And so it's on Oracles shoulders to prove that they're damn serious about it. >> There's no coincidence that MariaDB was launched the day that Oracle acquired Sun. Sanjeev, I wonder if we could come back to a topic that we discussed earlier, which is this notion of consumption, obviously Wall Street's very concerned about it. Snowflake dropped prices last week. I've always felt like, hey, the consumption model is the right model. I can dial it down in when I need to, of course, the street freaks out. What are your thoughts on just pricing, the consumption model? What's the right model for companies, for customers? >> Consumption model is here to stay. What I would like to see, and I think is an ideal situation and actually plays into the lakehouse concept is that, I have my data in some open format, maybe it's Parquet or CSV or JSON, Avro, and I can bring whatever engine is the best engine for my workloads, bring it on, pay for consumption, and then shut it down. And by the way, that could be Cloudera. We don't talk about Cloudera very much, but it could be one business unit wants to use Athena. Another business unit wants to use some other Trino let's say or Dremio. So every business unit is working on the same data set, see that's critical, but that data set is maybe in their VPC and they bring any compute engine, you pay for the use, shut it down. That then you're getting value and you're only paying for consumption. It's not like, I left a cluster running by mistake, so there have to be guardrails. The reason FinOps is so big is because it's very easy for me to run a Cartesian joint in the cloud and get a $10,000 bill. >> This looks like it's been a sort of a victim of its own success in some ways, they made it so easy to spin up single note instances, multi note instances. And back in the day when compute was scarce and costly, those database engines optimized every last bit so they could get as much workload as possible out of every instance. Today, it's really easy to spin up a new node, a new multi node cluster. So that freedom has meant many more nodes that aren't necessarily getting that utilization. So Snowflake has been doing a lot to add reporting, monitoring, dashboards around the utilization of all the nodes and multi node instances that have spun up. And meanwhile, we're seeing some of the traditional on-prem databases that are moving into the cloud, trying to offer that freedom. And I think they're going to have that same discovery that the cost surprises are going to follow as they make it easy to spin up new instances. >> Yeah, a lot of money went into this market over the last decade, separating compute from storage, moving to the cloud. I'm glad you mentioned Cloudera Sanjeev, 'cause they got it all started, the kind of big data movement. We don't talk about them that much. Sometimes I wonder if it's because when they merged Hortonworks and Cloudera, they dead ended both platforms, but then they did invest in a more modern platform. But what's the future of Cloudera? What are you seeing out there? >> Cloudera has a good product. I have to say the problem in our space is that there're way too many companies, there's way too much noise. We are expecting the end users to parse it out or we expecting analyst firms to boil it down. So I think marketing becomes a big problem. As far as technology is concerned, I think Cloudera did turn their selves around and Tony, I know you, you talked to them quite frequently. I think they have quite a comprehensive offering for a long time actually. They've created Kudu, so they got operational, they have Hadoop, they have an operational data warehouse, they're migrated to the cloud. They are in hybrid multi-cloud environment. Lot of cloud data warehouses are not hybrid. They're only in the cloud. >> Right. I think what Cloudera has done the most successful has been in the transition to the cloud and the fact that they're giving their customers more OnRamps to it, more hybrid OnRamps. So I give them a lot of credit there. They're also have been trying to position themselves as being the most price friendly in terms of that we will put more guardrails and governors on it. I mean, part of that could be spin. But on the other hand, they don't have the same vested interest in compute cycles as say, AWS would have with EMR. That being said, yes, Cloudera does it, I think its most powerful appeal so of that, it almost sounds in a way, I don't want to cast them as a legacy system. But the fact is they do have a huge landed legacy on-prem and still significant potential to land and expand that to the cloud. That being said, even though Cloudera is multifunction, I think it certainly has its strengths and weaknesses. And the fact this is that yes, Cloudera has an operational database or an operational data store with a kind of like the outgrowth of age base, but Cloudera is still based, primarily known for the deep analytics, the operational database nobody's going to buy Cloudera or Cloudera data platform strictly for the operational database. They may use it as an add-on, just in the same way that a lot of customers have used let's say Teradata basically to do some machine learning or let's say, Snowflake to parse through JSON. Again, it's not an indictment or anything like that, but the fact is obviously they do have their strengths and their weaknesses. I think their greatest opportunity is with their existing base because that base has a lot invested and vested. And the fact is they do have a hybrid path that a lot of the others lack. >> And of course being on the quarterly shock clock was not a good place to be under the microscope for Cloudera and now they at least can refactor the business accordingly. I'm glad you mentioned hybrid too. We saw Snowflake last month, did a deal with Dell whereby non-native Snowflake data could access on-prem object store from Dell. They announced a similar thing with pure storage. What do you guys make of that? Is that just... How significant will that be? Will customers actually do that? I think they're using either materialized views or extended tables. >> There are data rated and residency requirements. There are desires to have these platforms in your own data center. And finally they capitulated, I mean, Frank Klutman is famous for saying to be very focused and earlier, not many months ago, they called the going on-prem as a distraction, but clearly there's enough demand and certainly government contracts any company that has data residency requirements, it's a real need. So they finally addressed it. >> Yeah, I'll bet dollars to donuts, there was an EBC session and some big customer said, if you don't do this, we ain't doing business with you. And that was like, okay, we'll do it. >> So Dave, I have to say, earlier on you had brought this point, how Frank Klutman was poo-pooing data science workloads. On your show, about a year or so ago, he said, we are never going to on-prem. He burnt that bridge. (Tony laughs) That was on your show. >> I remember exactly the statement because it was interesting. He said, we're never going to do the halfway house. And I think what he meant is we're not going to bring the Snowflake architecture to run on-prem because it defeats the elasticity of the cloud. So this was kind of a capitulation in a way. But I think it still preserves his original intent sort of, I don't know. >> The point here is that every vendor will poo-poo whatever they don't have until they do have it. >> Yes. >> And then it'd be like, oh, we are all in, we've always been doing this. We have always supported this and now we are doing it better than others. >> Look, it was the same type of shock wave that we felt basically when AWS at the last moment at one of their reinvents, oh, by the way, we're going to introduce outposts. And the analyst group is typically pre briefed about a week or two ahead under NDA and that was not part of it. And when they dropped, they just casually dropped that in the analyst session. It's like, you could have heard the sound of lots of analysts changing their diapers at that point. >> (laughs) I remember that. And a props to Andy Jassy who once, many times actually told us, never say never when it comes to AWS. So guys, I know we got to run. We got some hard stops. Maybe you could each give us your final thoughts, Doug start us off and then-- >> Sure. Well, we've got the Snowflake Summit coming up. I'll be looking for customers that are really doing data science, that are really employing Python through Snowflake, through Snowpark. And then a couple weeks later, we've got Databricks with their Data and AI Summit in San Francisco. I'll be looking for customers that are really doing considerable BI workloads. Last year I did a market overview of this analytical data platform space, 14 vendors, eight of them claim to support lakehouse, both sides of the camp, Databricks customer had 32, their top customer that they could site was unnamed. It had 32 concurrent users doing 15,000 queries per hour. That's good but it's not up to the most demanding BI SQL workloads. And they acknowledged that and said, they need to keep working that. Snowflake asked for their biggest data science customer, they cited Kabura, 400 terabytes, 8,500 users, 400,000 data engineering jobs per day. I took the data engineering job to be probably SQL centric, ETL style transformation work. So I want to see the real use of the Python, how much Snowpark has grown as a way to support data science. >> Great. Tony. >> Actually of all things. And certainly, I'll also be looking for similar things in what Doug is saying, but I think sort of like, kind of out of left field, I'm interested to see what MongoDB is going to start to say about operational analytics, 'cause I mean, they're into this conquer the world strategy. We can be all things to all people. Okay, if that's the case, what's going to be a case with basically, putting in some inline analytics, what are you going to be doing with your query engine? So that's actually kind of an interesting thing we're looking for next week. >> Great. Sanjeev. >> So I'll be at MongoDB world, Snowflake and Databricks and very interested in seeing, but since Tony brought up MongoDB, I see that even the databases are shifting tremendously. They are addressing both the hashtag use case online, transactional and analytical. I'm also seeing that these databases started in, let's say in case of MySQL HeatWave, as relational or in MongoDB as document, but now they've added graph, they've added time series, they've added geospatial and they just keep adding more and more data structures and really making these databases multifunctional. So very interesting. >> It gets back to our discussion of best of breed, versus all in one. And it's likely Mongo's path or part of their strategy of course, is through developers. They're very developer focused. So we'll be looking for that. And guys, I'll be there as well. I'm hoping that we maybe have some extra time on theCUBE, so please stop by and we can maybe chat a little bit. Guys as always, fantastic. Thank you so much, Doug, Tony, Sanjeev, and let's do this again. >> It's been a pleasure. >> All right and thank you for watching. This is Dave Vellante for theCUBE and the excellent analyst. We'll see you next time. (upbeat music)

Published Date : Jun 2 2022

SUMMARY :

And Doug Henschen is the vice president Thank you. Doug let's start off with you And at the same time, me a lot of that material. And of course, at the and then we realized all the and Tony have brought to light. So I'm interested, the And in the cloud, So Sanjeev, is this all hype? But the problem is that we I mean, I look at the space, and offload some of the So different focus, at the end of the day, and warehouses on one conjoined platform. of the sort of big data movement most of the contributions made decisions. Whereas he kind of poo-pooed the lakehouse and the data scientists are from Mars. and the companies that have in the balance sheet that the customers have to worry about. the modern data stack, if you will. and the data world together, the story is with MongoDB Until data mesh takes over. and you need separate teams. that raises the importance of and the caution there. Yeah, I have to defer on that one. The idea here is that the of course, the street freaks out. and actually plays into the And back in the day when the kind of big data movement. We are expecting the end And the fact is they do have a hybrid path refactor the business accordingly. saying to be very focused And that was like, okay, we'll do it. So Dave, I have to say, the Snowflake architecture to run on-prem The point here is that and now we are doing that in the analyst session. And a props to Andy Jassy and said, they need to keep working that. Great. Okay, if that's the case, Great. I see that even the databases I'm hoping that we maybe have and the excellent analyst.

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Keynote Analysis with Zeus Kerravala | VeeamON 2022


 

>>Hello, everybody. Welcome to Von 2022, the live version. Yes, we're finally back live. Last time we did Von was 2019 live. Of course we did two subsequent years, uh, virtual. My name is Dave Valante and we've got two days of wall to wall coverage of VEON. As usual Veeam has brought together a number of customers, but it's really doing something different this year. Like many, uh, companies that you see, they have a big hybrid event. It's close to 40,000 people online and that's sort of driving the actual program where the content is actually different for the, the, the virtual viewers versus the onsite onsite. There's the, the V I P event going on, they got the keynotes. VM is a company who's a ancy occurred during the, the VMware rise. They brought in a new way of doing data protection. They didn't use agents. They, they protected at the hypervisor level. >>That changed the way that people did things. They're now doing it again in cloud, in SAS, in containers and ransomware. And so we're gonna dig into that. My cohost is Dave Nicholson this week, and we've got a special guest Zs Carava who is the principal at ZK research. He's an extraordinary analyst Zs. Great to see you, David. Thanks for coming out. Absolutely good to see you Beon. Great to be here. Yeah, we've done. Von act, live things have changed so dramatically. Uh, I mean the focus ransomware, it's now a whole new Tam, uh, the adjacency to security data protection. It's just a Zs. It's a whole new ballgame, isn't it? >>Well, it is. And, and in fact, um, during the keynote, they, they mentioned that they've, they're now tied at number one in, for, you know, back of a recovery, which is, I think it's safe to say Veeam. Does that really well? >>I think from a that's tied with Dell. Yes. Right. They didn't, I don't think they met Dell as >>Keto. And, uh, but I, you know, they've been rising Dell, EMC's been falling. And so I think >>It's somebody said 10 points that Dell lost and sharing the I data. >>It's not a big surprise. I mean, they haven't really invested a whole lot, >>I think anyway, >>Anyways, but I think from a Veeam perspective, the question is now that they've kind of hit that number one spot or close to it, what do they do next? This company, they mentioned, I was talking the CTO yesterday. You mentioned they're holding X bite of customer data. That is a lot of data. Right. And so they, they do back recovery really well. They do it arguably better than anybody. And so how do they take that data and then move into other adjacent markets to go create, not just a back recovery company, but a true data management platform company that has relevancy in cyber and analytics and artificial intelligence and data warehousing. Right? All those other areas I think are, are really open territory for this company right now. >>You know, Dave, you were a CTO at, at EMC when you, when you saw a lot of the acquisitions that the company made, uh, you, you know, they really never had a singular focus on data protection. They had a big data protection business, but that's the differentiator with Veeam. That's all it does. And you see that shine through from a, from a CTO's perspective. How do you see this market changing, evolving? And what's your sense as to how Vema is doing here? >>I think a lot of it's being driven by kind of, uh, unfortunately evil genius, uh, out in the market space. Yeah. I know we're gonna be hearing a lot about ransomware, uh, a lot about some concepts that we didn't really talk about outside of maybe the defense industry, air gaping, logical air gaping, um, Zs, you mentioned, you know, this, this, this question of what do you do when you have so many petabytes of data under management exabytes now exabytes, I'm sorry. Yeah, I see there I'm I'm already falling behind. One thing you could do is you could encrypt it all and then ask for Bitcoin in exchange for access to that data. >>Yes. That is what happens a >>Lot of them. So we're, we're getting, we're getting so much of the evil genius stuff headed our way. You start, you start thinking in those ways, but yet to, to your point, uh, dedicated backup products, don't address the scale and scope and variety of threats, not just from operational, uh, uh, you know, mishaps, uh, but now from so many bad actors coming in from the outside, it it's a whole new world. >>See us as analysts. We get inundated with ransomware solutions. Everybody's talking about it across the spectrum. The thing that interested me about what's happening here at VEON is they're, they're sort of trotting out this study that they do Veeam does some serious research, you know, thousands of customers that got hit by ransomware that they dug into. And then a, a larger study of all companies, many of whom didn't realize or said they hadn't been hit by ransomware, but they're really trying to inject thought leadership into the equation. You saw some of that in the analyst session this morning, it's now public. Uh, so we could talk about it. What were your thoughts on that data? >>Yeah, that was, uh, really fascinating data cuz it shows the ransomware industry, the response to it is largely reactive, right? We wait to get breach. We wait to, to uh, to get held at ransom I suppose. And then we, a lot of companies paid out. In fact, I thought there's one hospital in Florida, they're buying lots and lots of Bitcoin simply to pay out ransomware attacks. They didn't even really argue with them. They just pay it out. And I think Veeam's trying to change that mentality a little bit. You know, if you have the right strategy in place to be more preventative, you can do that. You can protect your data and then restore it right when you want to. So you don't have to be in that big bucket of companies that frankly pay and actually don't get their data back. Right. >>And like a third, I think roughly >>It's shocking amount of companies that get hit by that. And for a lot of companies, that's the end of their business. >>You know, a lot of the recovery process is manual is again a technologist. You understand that that's not the ideal way to go. In fact, it's probably a, a way to fail. >>Well, recovery's always the problem when I was in corporate, it used to joke that we were the best at backup, terrible at recovery. Well, you know, that's not atypical. >>My Fred Fred Moore, who was the vice president of strategy at a company called storage tech storage technology, corpor of storage tech. He had a great, uh, saying, he said, backup is one thing. Recovery is everything. And he started, he said that 30 years ago, but, but orchestration and automating that orchestration is, is really vital. We saw in the study, a lot of organizations are using scripts and scripts are fragile here they break. Right? >>Yeah, no, absolutely. Absolutely. Um, unfortunately the idea of the red run book on the shelf is still with us. Uh, uh, you know, scripting does not equal automation necessarily in every case, there's still gonna be a lot of manual steps in the process. Um, but you know, what I hope we get to talk about during the next couple of days is, you know, some of the factors that go into this, we've got day zero exploits that have already been uncovered that are stockpiled, uh, and tucked away. And it's inevitable that they're gonna hit. Yeah. So whether it's a manual recovery process or some level of automation, um, if you don't have something that is air gapped and cut off from the rest of the world in a physical or logical way, you can't guarantee >>That the, the problem with manual processes and scripting is even if you can set it up today, the environment changes so fast, right? With shadow it and business units buying their own services and users storing things and you know, wherever, um, you, you can't keep up with scripts in manual. Automation must be the way and I've been, and I don't care what part of it. You work in, whether it's this area in networking, communications, whatever automation must be the way I think prior to the pandemic, I saw a lot of resistance from it pros in the area of mission. Since the pandemic, I've seen a lot of warming up to it because I think it pros, I just realized they can't do their job without it. So, so you >>Don't, you don't think that edge devices, uh, lend themselves to manual >>Recovery, no process. In fact, I think that's one of the things they didn't talk about. What's that is, is edge. Edge is gonna be huge. More, every retailer, I talk to oil and gas, company's been using it for a long time. I've, you know, manufacturing organizations are looking at edge as a way to put more data in more places to improve experiences. Cuz you're moving the data closer, but we're creating a world where the fragmentation of data, you think it's bad now just wait a couple of years until the edge is a little more, you know, uh, to life here. And I think you ain't see nothing yet. This is this world of data. Everywhere is truly becoming that. And the thing with edge is there's no one definition, edge, you got IOT edge cellular edge, campus edge, right? Um, you know, you look at hotels, they have their own edge. I talked to major league baseball, right? They have every, stadium's got its own edge server in it. So we're moving into a world. We're putting more data in more places it's more fragmented than ever. And we need better ways of managing Of securing that data. But then also being able to recover for when >>Things happen. I was having that Danny Allen, he used the term that we coined called super cloud. He used that in the analyst meeting today. And, and that's a metaphor for this new layer of cloud. That's developing to your point, whether it's on-prem in a hybrid across clouds, not just running on the cloud, but actually abstracting away the complexity of the underlying primitives and APIs. And then eventually to your point, going out to the edge, I don't know if anyone who has an aggressive edge strategy Veeam to its credit, you know, has gone well beyond just virtualization and gone to bare metal into cloud. They were the containers. There was first at SAS. They acquired Caston who was a partner of theirs and they tried to acquire them earlier, but there was some government things and you know, that whole thing that got cleaned up and now they've, they own Caston. And I think the edge is next. I mean, it's gotta be, there's gonna be so much data at the edge. I guess the question is where is it today? How much of that is actually persisted? How much goes back to the cloud? I don't think people really have a good answer for that yet. >>No. In fact, a lot of edge services will be very ephemeral in nature. So it's not like with cloud where we'll take data and we'll store it there forever with the edge, we're gonna take data, we'll store it there for the time, point in time we need it. But I think one of the interesting things about Veeam is because they're decoupled from the airline hardware, they can run virtual machines and containers, porting Veeam to whatever platform you have next actually isn't all that difficult. Right? And so then if you need to be able to go back to a certain point in time, they can do that instantly. It's, it's a fascinating way to do backup. Are >>You you' point about it? I mean, you remember the signs up and down, you know, near the EMC facility, right outside of Southborough no hardware agenda that that was Jeremy Burton when he was running Verto of course they've got a little hardware agenda. So, but Veeam doesn't Veeam is, you know, they they're friendly with all the hardware players of pure play software, couple other stats on them. So they're a billion dollar company. They've now started to talk about their ARR growth. They grew, uh, 27% last year in, in, in annual recurring revenue, uh, 25%, uh, in the most recent quarter. And so they're in, in the vast majority of their business is subscription. I think they said, uh, 73% is now subscription based. So they really trans transitioned that business. The other thing about vem is they they've come up with a licensing model that's very friendly. >>Um, and they sort of removed that friction early on in the process. I remember talking to TIR about this. He said, we are gonna incent our partners and make it transparent to them, whether it's, you know, that when we shift from, you know, the, the, the, the crack of, of perpetual license to a subscription model, we're gonna make that transparent to partners. We'll take care of that. Essentially. They funded that transition. So that's worked very well. So they do stand out, I think from some of the larger companies at these big portfolios, although the big portfolio companies, you know, they get board level contacts and they can elbow their ways in your thoughts on that sort of selling dynamic. >>So navigating that transition to a subscription model is always fraught with danger. Everybody wants you to be there, but they want you to be there now. Mm-hmm <affirmative>, they don't like the transition that happens over 1824 months to get there. Um, >>As a private company, they're somewhat shielded from what they would've been if they were appli. Sure, >>Exactly. But, but that, but that bodes well from a, from a, a Veeam perspective. Um, the other interesting thing is that they sit where customers sit today in the real world, a hybrid world, not everything is in the cloud or a single cloud, uh, still a lot of on-prem things to take care of. And, >>And there will be for >>A long time exactly. Back to this idea. Yeah. There's a very long tail on that. So it's, it's, it's well enough to have a niche product that addresses a certain segment of the market, but to be able to go in and say all data everywhere, it doesn't matter where it lives. We have you covered. Um, that's a powerful message. And we were talking earlier. I think they, they stand a really good shot at taking market share, you know, on an ongoing basis. >>Yeah. The interesting thing about this market, Dave is they're, you know, although, you know, they're tied to number one with Dell now, they're, it's 12%, right? This reminds me of the security industry five, six years ago, where it's so fragmented. There's so many vendors, no one really stood out right. Then what happened in security? It's a little company called Palo Alto networks came around, they created a platform story. They moved into adjacent markets like SDWAN, they did a lot of smart acquisitions and they took off. I think vem is at that similar point where they've now, you know, that 12% number they've got some capital. Now they could go do some acquisitions that they want do. There's lots of adjacent markets as they talk about this company could be the Palo Alto of the data management market, if you know, and based on good execution. But there's certainly the opportunities there with all the data that they're holding. >>That's a really interesting point. I wanna stay that in a second. So there's obviously, there's, there's backup, there's recovery, there's data protection, there's ransomware protection, there's SAS data protection. And now all of a sudden you're seeing even a company like Rubrik is kind of repositioning as a security play. Yeah. Which I'm not sure that's the right move for a company that's really been focused on, on backup to really dive into that fragmented market. But it's clearly an adjacency and we heard Anan the new CEO today in the analyst segment, you know, we asked him, what's your kinda legacy gonna look like? And he said, I want to, I want to, defragment this market he's looking at. Yeah. He wants 25 to 45% of the market, which I think is really ambitious. I love that goal now to your point, agree, he, he sure. But that doubles yeah. >>From today or more, and he gets there to your point, possibly through acquisitions, they've made some really interesting tuck-ins with Castin. They certainly bought an AWS, uh, cloud play years ago. But my, my so, uh, Veeam was purchased by, uh, private equity inside capital inside capital in January of 2020, just before COVID for 5 billion. And at the time, then COVID hit right after you were like uhoh. And then of course the market took off so great acquisition by insight. But I think an IPO is in their future and that's, uh, Zs when they can start picking up some of these adjacent markets through every day. >>And I think one of the challenges for them is now that the Holden XAB bited data, they need to be able to tell customers things they, the customer doesn't know. Right. And that's where a lot of the work they're doing in artificial intelligence machine learning comes into play. Right. And, and nobody does that better than AWS, right? AWS is always looking at your data and telling you things you don't know, which makes you buy more. And so I think from a Veeam perspective, they need to now take all this, this huge asset they have and, and find a way to monetize it. And that's by revealing these key insights to customers that the customers don't even know they have. And >>They've got that monitor monitoring layer. Um, it's if you called it, Danny, didn't like to use the term, but he called it an AI. It's really machine learning that monitors. And then I think makes recommendations. I want to dig into that a little bit with it. >>Well, you can see the platform story starting to build here. Right. And >>Here's a really good point. Yeah. Because they really have been historically a point product company. This notion of super cloud is really a platform play. >>Right. And if you look in the software industry, look across any, any segment of the software industry, those companies that were niche that became big became platforms, Salesforce, SAP, Oracle. Right. And, and they find a way to allow others to build on their platform. You know, companies, they think like a Citrix, they never did that. Yeah. And they kind of taped, you know, petered out at a certain level of growth and had to, you know, change. They're still changing their business model, in fact. But I think that's Veeam's at that inflection point, right. They either build a platform story, enable others to do more on their platform or they stagnate >>HP software is another good example. They never were able to get that platform. And we're not able bunch of spoke with it, a non used to work there. Why is it so important Dave, to have a platform over a product? >>Well, cynical, Dave says, uh, you have a platform because it attracts investment and it makes you look cooler than maybe you really are. Um, but, uh, but really for longevity, you have, you, you, you have to be a platform. So what's >>The difference. How do you know when you have platform versus it? APIs? Is it, yeah. Brett, is it ecosystem? >>Some of it is. Some of it is semantics. Look at when, when I'm worried about my critical assets, my data, um, I think of a platform, a portfolio of point solutions for backing up edge data stuff. That's in the cloud stuff that exists in SAS. I see that holistically. And I think guys, you're doing enough. This is good. Don't, don't dilute your efforts. Just keep focusing on making sure that you can back up my data wherever it lives and we'll both win together. So whenever I hear a platform, I get a little bit, a little bit sketchy, >>Well platform, beats products, doesn't >>It? Yeah. To me, it's a last word. You said ecosystem. Yes. When you think of the big platform players, everybody B in the customer, uh, experience space builds to build for Salesforce. First, if you're a small security vendor, you build for Palo Alto first, right? Right. If you're in the database, you build for Oracle first and when you're that de facto platform, you create an ecosystem around you that you no longer have to fund and build yourself. It just becomes self-fulfilling. And that drives a level of stickiness that can't be replicated through product. >>Well, look at the ecosystem that, that these guys are forming. I mean, it's clear. Yeah. So are they becoming in your view >>Of platform? I think they are becoming a platform and I think that's one of the reasons they brought on and in, I think he's got some good experience doing that. You could argue that ring kind of became that. Right. The, when, you know, when he was ring central. >>Yeah. >>Yeah. And, uh, so I think some, some of his experiences and then moving into adjacencies, I think is really the reason they brought him in to lead this company to the next level. >>Excellent guys, thanks so much for setting up VEON 20, 22, 2 days of coverage on the cube. We're here at the area. It's a, it's a great venue. I >>Love the area. >>Yeah. It's nice. It's a nice intimate spot. A lot of customers here. Of course, there's gonna be a big Veeam party. They're famous for their parties, but, uh, we'll, we'll be here to cover it and, uh, keep it right there. We'll be back with the next segment. You're watching the cube VEON 20, 22 from Las Vegas.

Published Date : May 17 2022

SUMMARY :

Like many, uh, companies that you see, Absolutely good to see you Beon. one in, for, you know, back of a recovery, which is, I think it's safe to say Veeam. I think from a that's tied with Dell. And so I think I mean, they haven't really invested a whole lot, And so how do they take that data and then move into other adjacent markets to And you see that shine through from I think a lot of it's being driven by kind of, uh, unfortunately evil genius, uh, uh, you know, mishaps, uh, but now from so many bad actors coming in from the outside, does some serious research, you know, thousands of customers that got hit by ransomware that they dug You know, if you have the right strategy in place to be more preventative, you can do that. And for a lot of companies, that's the end of their business. You know, a lot of the recovery process is manual is again a technologist. Well, you know, that's not atypical. And he started, he said that 30 years ago, but, but orchestration and automating that orchestration and cut off from the rest of the world in a physical or logical way, you can't guarantee services and users storing things and you know, wherever, um, you, And I think you ain't see nothing yet. they tried to acquire them earlier, but there was some government things and you know, that whole thing that got cleaned up and And so then if you need to be able to go back I mean, you remember the signs up and down, you know, near the EMC facility, although the big portfolio companies, you know, they get board level contacts and they can elbow their ways in your Everybody wants you to be there, but they want you to be there now. As a private company, they're somewhat shielded from what they would've been if they were appli. the other interesting thing is that they sit where customers sit market share, you know, on an ongoing basis. I think vem is at that similar point where they've now, you know, Anan the new CEO today in the analyst segment, you know, And at the time, then COVID hit right after you were like And I think one of the challenges for them is now that the Holden XAB bited data, they need to be able to tell Um, it's if you called it, Well, you can see the platform story starting to build here. Because they really have been historically a point product company. And they kind of taped, you know, Why is it so important Dave, to have a platform over a Well, cynical, Dave says, uh, you have a platform because it attracts investment and it makes you How do you know when you have platform versus it? sure that you can back up my data wherever it lives and we'll both win together. facto platform, you create an ecosystem around you that you no longer have to fund and build yourself. So are they becoming in your The, when, you know, when he was ring central. I think is really the reason they brought him in to lead this company to the next level. We're here at the area. They're famous for their parties, but, uh, we'll, we'll be here to cover it and,

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Analyst Power Panel: Future of Database Platforms


 

(upbeat music) >> Once a staid and boring business dominated by IBM, Oracle, and at the time newcomer Microsoft, along with a handful of wannabes, the database business has exploded in the past decade and has become a staple of financial excellence, customer experience, analytic advantage, competitive strategy, growth initiatives, visualizations, not to mention compliance, security, privacy and dozens of other important use cases and initiatives. And on the vendor's side of the house, we've seen the rapid ascendancy of cloud databases. Most notably from Snowflake, whose massive raises leading up to its IPO in late 2020 sparked a spate of interest and VC investment in the separation of compute and storage and all that elastic resource stuff in the cloud. The company joined AWS, Azure and Google to popularize cloud databases, which have become a linchpin of competitive strategies for technology suppliers. And if I get you to put your data in my database and in my cloud, and I keep innovating, I'm going to build a moat and achieve a hugely attractive lifetime customer value in a really amazing marginal economics dynamic that is going to fund my future. And I'll be able to sell other adjacent services, not just compute and storage, but machine learning and inference and training and all kinds of stuff, dozens of lucrative cloud offerings. Meanwhile, the database leader, Oracle has invested massive amounts of money to maintain its lead. It's building on its position as the king of mission critical workloads and making typical Oracle like claims against the competition. Most were recently just yesterday with another announcement around MySQL HeatWave. An extension of MySQL that is compatible with on-premises MySQLs and is setting new standards in price performance. We're seeing a dramatic divergence in strategies across the database spectrum. On the far left, we see Amazon with more than a dozen database offerings each with its own API and primitives. AWS is taking a right tool for the right job approach, often building on open source platforms and creating services that it offers to customers to solve very specific problems for developers. And on the other side of the line, we see Oracle, which is taking the Swiss Army Knife approach, converging database functionality, enabling analytic and transactional workloads to run in the same data store, eliminating the need to ETL, at the same time adding capabilities into its platform like automation and machine learning. Welcome to this database Power Panel. My name is Dave Vellante, and I'm so excited to bring together some of the most respected industry analyst in the community. Today we're going to assess what's happening in the market. We're going to dig into the competitive landscape and explore the future of database and database platforms and decode what it means to customers. Let me take a moment to welcome our guest analyst today. Matt Kimball is a vice president and principal analysts at Moor Insights and Strategy, Matt. He knows products, he knows industry, he's got real world IT expertise, and he's got all the angles 25 plus years of experience in all kinds of great background. Matt, welcome. Thanks very much for coming on theCUBE. Holgar Mueller, friend of theCUBE, vice president and principal analyst at Constellation Research in depth knowledge on applications, application development, knows developers. He's worked at SAP and Oracle. And then Bob Evans is Chief Content Officer and co-founder of the Acceleration Economy, founder and principle of Cloud Wars. Covers all kinds of industry topics and great insights. He's got awesome videos, these three minute hits. If you haven't seen 'em, checking them out, knows cloud companies, his Cloud Wars minutes are fantastic. And then of course, Marc Staimer is the founder of Dragon Slayer Research. A frequent contributor and guest analyst at Wikibon. He's got a wide ranging knowledge across IT products, knows technology really well, can go deep. And then of course, Ron Westfall, Senior Analyst and Director Research Director at Futurum Research, great all around product trends knowledge. Can take, you know, technical dives and really understands competitive angles, knows Redshift, Snowflake, and many others. Gents, thanks so much for taking the time to join us in theCube today. It's great to have you on, good to see you. >> Good to be here, thanks for having us. >> Thanks, Dave. >> All right, let's start with an around the horn and briefly, if each of you would describe, you know, anything I missed in your areas of expertise and then you answer the following question, how would you describe the state of the database, state of platform market today? Matt Kimball, please start. >> Oh, I hate going first, but that it's okay. How would I describe the world today? I would just in one sentence, I would say, I'm glad I'm not in IT anymore, right? So, you know, it is a complex and dangerous world out there. And I don't envy IT folks I'd have to support, you know, these modernization and transformation efforts that are going on within the enterprise. It used to be, you mentioned it, Dave, you would argue about IBM versus Oracle versus this newcomer in the database space called Microsoft. And don't forget Sybase back in the day, but you know, now it's not just, which SQL vendor am I going to go with? It's all of these different, divergent data types that have to be taken, they have to be merged together, synthesized. And somehow I have to do that cleanly and use this to drive strategic decisions for my business. That is not easy. So, you know, you have to look at it from the perspective of the business user. It's great for them because as a DevOps person, or as an analyst, I have so much flexibility and I have this thing called the cloud now where I can go get services immediately. As an IT person or a DBA, I am calling up prevention hotlines 24 hours a day, because I don't know how I'm going to be able to support the business. And as an Oracle or as an Oracle or a Microsoft or some of the cloud providers and cloud databases out there, I'm licking my chops because, you know, my market is expanding and expanding every day. >> Great, thank you for that, Matt. Holgar, how do you see the world these days? You always have a good perspective on things, share with us. >> Well, I think it's the best time to be in IT, I'm not sure what Matt is talking about. (laughing) It's easier than ever, right? The direction is going to cloud. Kubernetes has won, Google has the best AI for now, right? So things are easier than ever before. You made commitments for five plus years on hardware, networking and so on premise, and I got gray hair about worrying it was the wrong decision. No, just kidding. But you kind of both sides, just to be controversial, make it interesting, right. So yeah, no, I think the interesting thing specifically with databases, right? We have this big suite versus best of breed, right? Obviously innovation, like you mentioned with Snowflake and others happening in the cloud, the cloud vendors server, where to save of their databases. And then we have one of the few survivors of the old guard as Evans likes to call them is Oracle who's doing well, both their traditional database. And now, which is really interesting, remarkable from that because Oracle it was always the power of one, have one database, add more to it, make it what I call the universal database. And now this new HeatWave offering is coming and MySQL open source side. So they're getting the second (indistinct) right? So it's interesting that older players, traditional players who still are in the market are diversifying their offerings. Something we don't see so much from the traditional tools from Oracle on the Microsoft side or the IBM side these days. >> Great, thank you Holgar. Bob Evans, you've covered this business for a while. You've worked at, you know, a number of different outlets and companies and you cover the competition, how do you see things? >> Dave, you know, the other angle to look at this from is from the customer side, right? You got now CEOs who are any sort of business across all sorts of industries, and they understand that their future success is going to be dependent on their ability to become a digital company, to understand data, to use it the right way. So as you outline Dave, I think in your intro there, it is a fantastic time to be in the database business. And I think we've got a lot of new buyers and influencers coming in. They don't know all this history about IBM and Microsoft and Oracle and you know, whoever else. So I think they're going to take a long, hard look, Dave, at some of these results and who is able to help these companies not serve up the best technology, but who's going to be able to help their business move into the digital future. So it's a fascinating time now from every perspective. >> Great points, Bob. I mean, digital transformation has gone from buzzword to imperative. Mr. Staimer, how do you see things? >> I see things a little bit differently than my peers here in that I see the database market being segmented. There's all the different kinds of databases that people are looking at for different kinds of data, and then there is databases in the cloud. And so database as cloud service, I view very differently than databases because the traditional way of implementing a database is changing and it's changing rapidly. So one of the premises that you stated earlier on was that you viewed Oracle as a database company. I don't view Oracle as a database company anymore. I view Oracle as a cloud company that happens to have a significant expertise and specialty in databases, and they still sell database software in the traditional way, but ultimately they're a cloud company. So database cloud services from my point of view is a very distinct market from databases. >> Okay, well, you gave us some good meat on the bone to talk about that. Last but not least-- >> Dave did Marc, just say Oracle's a cloud company? >> Yeah. (laughing) Take away the database, it would be interesting to have that discussion, but let's let Ron jump in here. Ron, give us your take. >> That's a great segue. I think it's truly the era of the cloud database, that's something that's rising. And the key trends that come with it include for example, elastic scaling. That is the ability to scale on demand, to right size workloads according to customer requirements. And also I think it's going to increase the prioritization for high availability. That is the player who can provide the highest availability is going to have, I think, a great deal of success in this emerging market. And also I anticipate that there will be more consolidation across platforms in order to enable cost savings for customers, and that's something that's always going to be important. And I think we'll see more of that over the horizon. And then finally security, security will be more important than ever. We've seen a spike (indistinct), we certainly have seen geopolitical originated cybersecurity concerns. And as a result, I see database security becoming all the more important. >> Great, thank you. Okay, let me share some data with you guys. I'm going to throw this at you and see what you think. We have this awesome data partner called Enterprise Technology Research, ETR. They do these quarterly surveys and each period with dozens of industry segments, they track clients spending, customer spending. And this is the database, data warehouse sector okay so it's taxonomy, so it's not perfect, but it's a big kind of chunk. They essentially ask customers within a category and buy a specific vendor, you're spending more or less on the platform? And then they subtract the lesses from the mores and they derive a metric called net score. It's like NPS, it's a measure of spending velocity. It's more complicated and granular than that, but that's the basis and that's the vertical axis. The horizontal axis is what they call market share, it's not like IDC market share, it's just pervasiveness in the data set. And so there are a couple of things that stand out here and that we can use as reference point. The first is the momentum of Snowflake. They've been off the charts for many, many, for over two years now, anything above that dotted red line, that 40%, is considered by ETR to be highly elevated and Snowflake's even way above that. And I think it's probably not sustainable. We're going to see in the next April survey, next month from those guys, when it comes out. And then you see AWS and Microsoft, they're really pervasive on the horizontal axis and highly elevated, Google falls behind them. And then you got a number of well funded players. You got Cockroach Labs, Mongo, Redis, MariaDB, which of course is a fork on MySQL started almost as protest at Oracle when they acquired Sun and they got MySQL and you can see the number of others. Now Oracle who's the leading database player, despite what Marc Staimer says, we know, (laughs) and they're a cloud player (laughing) who happens to be a leading database player. They dominate in the mission critical space, we know that they're the king of that sector, but you can see here that they're kind of legacy, right? They've been around a long time, they get a big install base. So they don't have the spending momentum on the vertical axis. Now remember this is, just really this doesn't capture spending levels, so that understates Oracle but nonetheless. So it's not a complete picture like SAP for instance is not in here, no Hana. I think people are actually buying it, but it doesn't show up here, (laughs) but it does give an indication of momentum and presence. So Bob Evans, I'm going to start with you. You've commented on many of these companies, you know, what does this data tell you? >> Yeah, you know, Dave, I think all these compilations of things like that are interesting, and that folks at ETR do some good work, but I think as you said, it's a snapshot sort of a two-dimensional thing of a rapidly changing, three dimensional world. You know, the incidents at which some of these companies are mentioned versus the volume that happens. I think it's, you know, with Oracle and I'm not going to declare my religious affiliation, either as cloud company or database company, you know, they're all of those things and more, and I think some of our old language of how we classify companies is just not relevant anymore. But I want to ask too something in here, the autonomous database from Oracle, nobody else has done that. So either Oracle is crazy, they've tried out a technology that nobody other than them is interested in, or they're onto something that nobody else can match. So to me, Dave, within Oracle, trying to identify how they're doing there, I would watch autonomous database growth too, because right, it's either going to be a big plan and it breaks through, or it's going to be caught behind. And the Snowflake phenomenon as you mentioned, that is a rare, rare bird who comes up and can grow 100% at a billion dollar revenue level like that. So now they've had a chance to come in, scare the crap out of everybody, rock the market with something totally new, the data cloud. Will the bigger companies be able to catch up and offer a compelling alternative, or is Snowflake going to continue to be this outlier. It's a fascinating time. >> Really, interesting points there. Holgar, I want to ask you, I mean, I've talked to certainly I'm sure you guys have too, the founders of Snowflake that came out of Oracle and they actually, they don't apologize. They say, "Hey, we not going to do all that complicated stuff that Oracle does, we were trying to keep it real simple." But at the same time, you know, they don't do sophisticated workload management. They don't do complex joints. They're kind of relying on the ecosystems. So when you look at the data like this and the various momentums, and we talked about the diverging strategies, what does this say to you? >> Well, it is a great point. And I think Snowflake is an example how the cloud can turbo charge a well understood concept in this case, the data warehouse, right? You move that and you find steroids and you see like for some players who've been big in data warehouse, like Sentara Data, as an example, here in San Diego, what could have been for them right in that part. The interesting thing, the problem though is the cloud hides a lot of complexity too, which you can scale really well as you attract lots of customers to go there. And you don't have to build things like what Bob said, right? One of the fascinating things, right, nobody's answering Oracle on the autonomous database. I don't think is that they cannot, they just have different priorities or the database is not such a priority. I would dare to say that it's for IBM and Microsoft right now at the moment. And the cloud vendors, you just hide that right through scripts and through scale because you support thousands of customers and you can deal with a little more complexity, right? It's not against them. Whereas if you have to run it yourself, very different story, right? You want to have the autonomous parts, you want to have the powerful tools to do things. >> Thank you. And so Matt, I want to go to you, you've set up front, you know, it's just complicated if you're in IT, it's a complicated situation and you've been on the customer side. And if you're a buyer, it's obviously, it's like Holgar said, "Cloud's supposed to make this stuff easier, but the simpler it gets the more complicated gets." So where do you place your bets? Or I guess more importantly, how do you decide where to place your bets? >> Yeah, it's a good question. And to what Bob and Holgar said, you know, the around autonomous database, I think, you know, part of, as I, you know, play kind of armchair psychologist, if you will, corporate psychologists, I look at what Oracle is doing and, you know, databases where they've made their mark and it's kind of, that's their strong position, right? So it makes sense if you're making an entry into this cloud and you really want to kind of build momentum, you go with what you're good at, right? So that's kind of the strength of Oracle. Let's put a lot of focus on that. They do a lot more than database, don't get me wrong, but you know, I'm going to short my strength and then kind of pivot from there. With regards to, you know, what IT looks at and what I would look at you know as an IT director or somebody who is, you know, trying to consume services from these different cloud providers. First and foremost, I go with what I know, right? Let's not forget IT is a conservative group. And when we look at, you know, all the different permutations of database types out there, SQL, NoSQL, all the different types of NoSQL, those are largely being deployed by business users that are looking for agility or businesses that are looking for agility. You know, the reason why MongoDB is so popular is because of DevOps, right? It's a great platform to develop on and that's where it kind of gained its traction. But as an IT person, I want to go with what I know, where my muscle memory is, and that's my first position. And so as I evaluate different cloud service providers and cloud databases, I look for, you know, what I know and what I've invested in and where my muscle memory is. Is there enough there and do I have enough belief that that company or that service is going to be able to take me to, you know, where I see my organization in five years from a data management perspective, from a business perspective, are they going to be there? And if they are, then I'm a little bit more willing to make that investment, but it is, you know, if I'm kind of going in this blind or if I'm cloud native, you know, that's where the Snowflakes of the world become very attractive to me. >> Thank you. So Marc, I asked Andy Jackson in theCube one time, you have all these, you know, data stores and different APIs and primitives and you know, very granular, what's the strategy there? And he said, "Hey, that allows us as the market changes, it allows us to be more flexible. If we start building abstractions layers, it's harder for us." I think also it was not a good time to market advantage, but let me ask you, I described earlier on that spectrum from AWS to Oracle. We just saw yesterday, Oracle announced, I think the third major enhancement in like 15 months to MySQL HeatWave, what do you make of that announcement? How do you think it impacts the competitive landscape, particularly as it relates to, you know, converging transaction and analytics, eliminating ELT, I know you have some thoughts on this. >> So let me back up for a second and defend my cloud statement about Oracle for a moment. (laughing) AWS did a great job in developing the cloud market in general and everything in the cloud market. I mean, I give them lots of kudos on that. And a lot of what they did is they took open source software and they rent it to people who use their cloud. So I give 'em lots of credit, they dominate the market. Oracle was late to the cloud market. In fact, they actually poo-pooed it initially, if you look at some of Larry Ellison's statements, they said, "Oh, it's never going to take off." And then they did 180 turn, and they said, "Oh, we're going to embrace the cloud." And they really have, but when you're late to a market, you've got to be compelling. And this ties into the announcement yesterday, but let's deal with this compelling. To be compelling from a user point of view, you got to be twice as fast, offer twice as much functionality, at half the cost. That's generally what compelling is that you're going to capture market share from the leaders who established the market. It's very difficult to capture market share in a new market for yourself. And you're right. I mean, Bob was correct on this and Holgar and Matt in which you look at Oracle, and they did a great job of leveraging their database to move into this market, give 'em lots of kudos for that too. But yesterday they announced, as you said, the third innovation release and the pace is just amazing of what they're doing on these releases on HeatWave that ties together initially MySQL with an integrated builtin analytics engine, so a data warehouse built in. And then they added automation with autopilot, and now they've added machine learning to it, and it's all in the same service. It's not something you can buy and put on your premise unless you buy their cloud customers stuff. But generally it's a cloud offering, so it's compellingly better as far as the integration. You don't buy multiple services, you buy one and it's lower cost than any of the other services, but more importantly, it's faster, which again, give 'em credit for, they have more integration of a product. They can tie things together in a way that nobody else does. There's no additional services, ETL services like Glue and AWS. So from that perspective, they're getting better performance, fewer services, lower cost. Hmm, they're aiming at the compelling side again. So from a customer point of view it's compelling. Matt, you wanted to say something there. >> Yeah, I want to kind of, on what you just said there Marc, and this is something I've found really interesting, you know. The traditional way that you look at software and, you know, purchasing software and IT is, you look at either best of breed solutions and you have to work on the backend to integrate them all and make them all work well. And generally, you know, the big hit against the, you know, we have one integrated offering is that, you lose capability or you lose depth of features, right. And to what you were saying, you know, that's the thing I found interesting about what Oracle is doing is they're building in depth as they kind of, you know, build that service. It's not like you're losing a lot of capabilities, because you're going to one integrated service versus having to use A versus B versus C, and I love that idea. >> You're right. Yeah, not only you're not losing, but you're gaining functionality that you can't get by integrating a lot of these. I mean, I can take Snowflake and integrate it in with machine learning, but I also have to integrate in with a transactional database. So I've got to have connectors between all of this, which means I'm adding time. And what it comes down to at the end of the day is expertise, effort, time, and cost. And so what I see the difference from the Oracle announcements is they're aiming at reducing all of that by increasing performance as well. Correct me if I'm wrong on that but that's what I saw at the announcement yesterday. >> You know, Marc, one thing though Marc, it's funny you say that because I started out saying, you know, I'm glad I'm not 19 anymore. And the reason is because of exactly what you said, it's almost like there's a pseudo level of witchcraft that's required to support the modern data environment right in the enterprise. And I need simpler faster, better. That's what I need, you know, I am no longer wearing pocket protectors. I have turned from, you know, break, fix kind of person, to you know, business consultant. And I need that point and click simplicity, but I can't sacrifice, you know, a depth of features of functionality on the backend as I play that consultancy role. >> So, Ron, I want to bring in Ron, you know, it's funny. So Matt, you mentioned Mongo, I often and say, if Oracle mentions you, you're on the map. We saw them yesterday Ron, (laughing) they hammered RedShifts auto ML, they took swipes at Snowflake, a little bit of BigQuery. What were your thoughts on that? Do you agree with what these guys are saying in terms of HeatWaves capabilities? >> Yes, Dave, I think that's an excellent question. And fundamentally I do agree. And the question is why, and I think it's important to know that all of the Oracle data is backed by the fact that they're using benchmarks. For example, all of the ML and all of the TPC benchmarks, including all the scripts, all the configs and all the detail are posted on GitHub. So anybody can look at these results and they're fully transparent and replicate themselves. If you don't agree with this data, then by all means challenge it. And we have not really seen that in all of the new updates in HeatWave over the last 15 months. And as a result, when it comes to these, you know, fundamentals in looking at the competitive landscape, which I think gives validity to outcomes such as Oracle being able to deliver 4.8 times better price performance than Redshift. As well as for example, 14.4 better price performance than Snowflake, and also 12.9 better price performance than BigQuery. And so that is, you know, looking at the quantitative side of things. But again, I think, you know, to Marc's point and to Matt's point, there are also qualitative aspects that clearly differentiate the Oracle proposition, from my perspective. For example now the MySQL HeatWave ML capabilities are native, they're built in, and they also support things such as completion criteria. And as a result, that enables them to show that hey, when you're using Redshift ML for example, you're having to also use their SageMaker tool and it's running on a meter. And so, you know, nobody really wants to be running on a meter when, you know, executing these incredibly complex tasks. And likewise, when it comes to Snowflake, they have to use a third party capability. They don't have the built in, it's not native. So the user, to the point that he's having to spend more time and it increases complexity to use auto ML capabilities across the Snowflake platform. And also, I think it also applies to other important features such as data sampling, for example, with the HeatWave ML, it's intelligent sampling that's being implemented. Whereas in contrast, we're seeing Redshift using random sampling. And again, Snowflake, you're having to use a third party library in order to achieve the same capabilities. So I think the differentiation is crystal clear. I think it definitely is refreshing. It's showing that this is where true value can be assigned. And if you don't agree with it, by all means challenge the data. >> Yeah, I want to come to the benchmarks in a minute. By the way, you know, the gentleman who's the Oracle's architect, he did a great job on the call yesterday explaining what you have to do. I thought that was quite impressive. But Bob, I know you follow the financials pretty closely and on the earnings call earlier this month, Ellison said that, "We're going to see HeatWave on AWS." And the skeptic in me said, oh, they must not be getting people to come to OCI. And then they, you remember this chart they showed yesterday that showed the growth of HeatWave on OCI. But of course there was no data on there, it was just sort of, you know, lines up and to the right. So what do you guys think of that? (Marc laughs) Does it signal Bob, desperation by Oracle that they can't get traction on OCI, or is it just really a smart tame expansion move? What do you think? >> Yeah, Dave, that's a great question. You know, along the way there, and you know, just inside of that was something that said Ellison said on earnings call that spoke to a different sort of philosophy or mindset, almost Marc, where he said, "We're going to make this multicloud," right? With a lot of their other cloud stuff, if you wanted to use any of Oracle's cloud software, you had to use Oracle's infrastructure, OCI, there was no other way out of it. But this one, but I thought it was a classic Ellison line. He said, "Well, we're making this available on AWS. We're making this available, you know, on Snowflake because we're going after those users. And once they see what can be done here." So he's looking at it, I guess you could say, it's a concession to customers because they want multi-cloud. The other way to look at it, it's a hunting expedition and it's one of those uniquely I think Oracle ways. He said up front, right, he doesn't say, "Well, there's a big market, there's a lot for everybody, we just want on our slice." Said, "No, we are going after Amazon, we're going after Redshift, we're going after Aurora. We're going after these users of Snowflake and so on." And I think it's really fairly refreshing these days to hear somebody say that, because now if I'm a buyer, I can look at that and say, you know, to Marc's point, "Do they measure up, do they crack that threshold ceiling? Or is this just going to be more pain than a few dollars savings is worth?" But you look at those numbers that Ron pointed out and that we all saw in that chart. I've never seen Dave, anything like that. In a substantive market, a new player coming in here, and being able to establish differences that are four, seven, eight, 10, 12 times better than competition. And as new buyers look at that, they're going to say, "What the hell are we doing paying, you know, five times more to get a poor result? What's going on here?" So I think this is going to rattle people and force a harder, closer look at what these alternatives are. >> I wonder if the guy, thank you. Let's just skip ahead of the benchmarks guys, bring up the next slide, let's skip ahead a little bit here, which talks to the benchmarks and the benchmarking if we can. You know, David Floyer, the sort of semiretired, you know, Wikibon analyst said, "Dave, this is going to force Amazon and others, Snowflake," he said, "To rethink actually how they architect databases." And this is kind of a compilation of some of the data that they shared. They went after Redshift mostly, (laughs) but also, you know, as I say, Snowflake, BigQuery. And, like I said, you can always tell which companies are doing well, 'cause Oracle will come after you, but they're on the radar here. (laughing) Holgar should we take this stuff seriously? I mean, or is it, you know, a grain salt? What are your thoughts here? >> I think you have to take it seriously. I mean, that's a great question, great point on that. Because like Ron said, "If there's a flaw in a benchmark, we know this database traditionally, right?" If anybody came up that, everybody will be, "Oh, you put the wrong benchmark, it wasn't audited right, let us do it again," and so on. We don't see this happening, right? So kudos to Oracle to be aggressive, differentiated, and seem to having impeccable benchmarks. But what we really see, I think in my view is that the classic and we can talk about this in 100 years, right? Is the suite versus best of breed, right? And the key question of the suite, because the suite's always slower, right? No matter at which level of the stack, you have the suite, then the best of breed that will come up with something new, use a cloud, put the data warehouse on steroids and so on. The important thing is that you have to assess as a buyer what is the speed of my suite vendor. And that's what you guys mentioned before as well, right? Marc said that and so on, "Like, this is a third release in one year of the HeatWave team, right?" So everybody in the database open source Marc, and there's so many MySQL spinoffs to certain point is put on shine on the speed of (indistinct) team, putting out fundamental changes. And the beauty of that is right, is so inherent to the Oracle value proposition. Larry's vision of building the IBM of the 21st century, right from the Silicon, from the chip all the way across the seven stacks to the click of the user. And that what makes the database what Rob was saying, "Tied to the OCI infrastructure," because designed for that, it runs uniquely better for that, that's why we see the cross connect to Microsoft. HeatWave so it's different, right? Because HeatWave runs on cheap hardware, right? Which is the breadth and butter 886 scale of any cloud provider, right? So Oracle probably needs it to scale OCI in a different category, not the expensive side, but also allow us to do what we said before, the multicloud capability, which ultimately CIOs really want, because data gravity is real, you want to operate where that is. If you have a fast, innovative offering, which gives you more functionality and the R and D speed is really impressive for the space, puts away bad results, then it's a good bet to look at. >> Yeah, so you're saying, that we versus best of breed. I just want to sort of play back then Marc a comment. That suite versus best of breed, there's always been that trade off. If I understand you Holgar you're saying that somehow Oracle has magically cut through that trade off and they're giving you the best of both. >> It's the developing velocity, right? The provision of important features, which matter to buyers of the suite vendor, eclipses the best of breed vendor, then the best of breed vendor is in the hell of a potential job. >> Yeah, go ahead Marc. >> Yeah and I want to add on what Holgar just said there. I mean the worst job in the data center is data movement, moving the data sucks. I don't care who you are, nobody likes it. You never get any kudos for doing it well, and you always get the ah craps, when things go wrong. So it's in- >> In the data center Marc all the time across data centers, across cloud. That's where the bleeding comes. >> It's right, you get beat up all the time. So nobody likes to move data, ever. So what you're looking at with what they announce with HeatWave and what I love about HeatWave is it doesn't matter when you started with it, you get all the additional features they announce it's part of the service, all the time. But they don't have to move any of the data. You want to analyze the data that's in your transactional, MySQL database, it's there. You want to do machine learning models, it's there, there's no data movement. The data movement is the key thing, and they just eliminate that, in so many ways. And the other thing I wanted to talk about is on the benchmarks. As great as those benchmarks are, they're really conservative 'cause they're underestimating the cost of that data movement. The ETLs, the other services, everything's left out. It's just comparing HeatWave, MySQL cloud service with HeatWave versus Redshift, not Redshift and Aurora and Glue, Redshift and Redshift ML and SageMaker, it's just Redshift. >> Yeah, so what you're saying is what Oracle's doing is saying, "Okay, we're going to run MySQL HeatWave benchmarks on analytics against Redshift, and then we're going to run 'em in transaction against Aurora." >> Right. >> But if you really had to look at what you would have to do with the ETL, you'd have to buy two different data stores and all the infrastructure around that, and that goes away so. >> Due to the nature of the competition, they're running narrow best of breed benchmarks. There is no suite level benchmark (Dave laughs) because they created something new. >> Well that's you're the earlier point they're beating best of breed with a suite. So that's, I guess to Floyer's earlier point, "That's going to shake things up." But I want to come back to Bob Evans, 'cause I want to tap your Cloud Wars mojo before we wrap. And line up the horses, you got AWS, you got Microsoft, Google and Oracle. Now they all own their own cloud. Snowflake, Mongo, Couchbase, Redis, Cockroach by the way they're all doing very well. They run in the cloud as do many others. I think you guys all saw the Andreessen, you know, commentary from Sarah Wang and company, to talk about the cost of goods sold impact of cloud. So owning your own cloud has to be an advantage because other guys like Snowflake have to pay cloud vendors and negotiate down versus having the whole enchilada, Safra Catz's dream. Bob, how do you think this is going to impact the market long term? >> Well, Dave, that's a great question about, you know, how this is all going to play out. If I could mention three things, one, Frank Slootman has done a fantastic job with Snowflake. Really good company before he got there, but since he's been there, the growth mindset, the discipline, the rigor and the phenomenon of what Snowflake has done has forced all these bigger companies to really accelerate what they're doing. And again, it's an example of how this intense competition makes all the different cloud vendors better and it provides enormous value to customers. Second thing I wanted to mention here was look at the Adam Selipsky effect at AWS, took over in the middle of May, and in Q2, Q3, Q4, AWS's growth rate accelerated. And in each of those three quotas, they grew faster than Microsoft's cloud, which has not happened in two or three years, so they're closing the gap on Microsoft. The third thing, Dave, in this, you know, incredibly intense competitive nature here, look at Larry Ellison, right? He's got his, you know, the product that for the last two or three years, he said, "It's going to help determine the future of the company, autonomous database." You would think he's the last person in the world who's going to bring in, you know, in some ways another database to think about there, but he has put, you know, his whole effort and energy behind this. The investments Oracle's made, he's riding this horse really hard. So it's not just a technology achievement, but it's also an investment priority for Oracle going forward. And I think it's going to form a lot of how they position themselves to this new breed of buyer with a new type of need and expectations from IT. So I just think the next two or three years are going to be fantastic for people who are lucky enough to get to do the sorts of things that we do. >> You know, it's a great point you made about AWS. Back in 2018 Q3, they were doing about 7.4 billion a quarter and they were growing in the mid forties. They dropped down to like 29% Q4, 2020, I'm looking at the data now. They popped back up last quarter, last reported quarter to 40%, that is 17.8 billion, so they more doubled and they accelerated their growth rate. (laughs) So maybe that pretends, people are concerned about Snowflake right now decelerating growth. You know, maybe that's going to be different. By the way, I think Snowflake has a different strategy, the whole data cloud thing, data sharing. They're not trying to necessarily take Oracle head on, which is going to make this next 10 years, really interesting. All right, we got to go, last question. 30 seconds or less, what can we expect from the future of data platforms? Matt, please start. >> I have to go first again? You're killing me, Dave. (laughing) In the next few years, I think you're going to see the major players continue to meet customers where they are, right. Every organization, every environment is, you know, kind of, we use these words bespoke in Snowflake, pardon the pun, but Snowflakes, right. But you know, they're all opinionated and unique and what's great as an IT person is, you know, there is a service for me regardless of where I am on my journey, in my data management journey. I think you're going to continue to see with regards specifically to Oracle, I think you're going to see the company continue along this path of being all things to all people, if you will, or all organizations without sacrificing, you know, kind of richness of features and sacrificing who they are, right. Look, they are the data kings, right? I mean, they've been a database leader for an awful long time. I don't see that going away any time soon and I love the innovative spirit they've brought in with HeatWave. >> All right, great thank you. Okay, 30 seconds, Holgar go. >> Yeah, I mean, the interesting thing that we see is really that trend to autonomous as Oracle calls or self-driving software, right? So the database will have to do more things than just store the data and support the DVA. It will have to show it can wide insights, the whole upside, it will be able to show to one machine learning. We haven't really talked about that. How in just exciting what kind of use case we can get of machine learning running real time on data as it changes, right? So, which is part of the E5 announcement, right? So we'll see more of that self-driving nature in the database space. And because you said we can promote it, right. Check out my report about HeatWave latest release where I post in oracle.com. >> Great, thank you for that. And Bob Evans, please. You're great at quick hits, hit us. >> Dave, thanks. I really enjoyed getting to hear everybody's opinion here today and I think what's going to happen too. I think there's a new generation of buyers, a new set of CXO influencers in here. And I think what Oracle's done with this, MySQL HeatWave, those benchmarks that Ron talked about so eloquently here that is going to become something that forces other companies, not just try to get incrementally better. I think we're going to see a massive new wave of innovation to try to play catch up. So I really take my hat off to Oracle's achievement from going to, push everybody to be better. >> Excellent. Marc Staimer, what do you say? >> Sure, I'm going to leverage off of something Matt said earlier, "Those companies that are going to develop faster, cheaper, simpler products that are going to solve customer problems, IT problems are the ones that are going to succeed, or the ones who are going to grow. The one who are just focused on the technology are going to fall by the wayside." So those who can solve more problems, do it more elegantly and do it for less money are going to do great. So Oracle's going down that path today, Snowflake's going down that path. They're trying to do more integration with third party, but as a result, aiming at that simpler, faster, cheaper mentality is where you're going to continue to see this market go. >> Amen brother Marc. >> Thank you, Ron Westfall, we'll give you the last word, bring us home. >> Well, thank you. And I'm loving it. I see a wave of innovation across the entire cloud database ecosystem and Oracle is fueling it. We are seeing it, with the native integration of auto ML capabilities, elastic scaling, lower entry price points, et cetera. And this is just going to be great news for buyers, but also developers and increased use of open APIs. And so I think that is really the key takeaways. Just we're going to see a lot of great innovation on the horizon here. >> Guys, fantastic insights, one of the best power panel as I've ever done. Love to have you back. Thanks so much for coming on today. >> Great job, Dave, thank you. >> All right, and thank you for watching. This is Dave Vellante for theCube and we'll see you next time. (soft music)

Published Date : Mar 31 2022

SUMMARY :

and co-founder of the and then you answer And don't forget Sybase back in the day, the world these days? and others happening in the cloud, and you cover the competition, and Oracle and you know, whoever else. Mr. Staimer, how do you see things? in that I see the database some good meat on the bone Take away the database, That is the ability to scale on demand, and they got MySQL and you I think it's, you know, and the various momentums, and Microsoft right now at the moment. So where do you place your bets? And to what Bob and Holgar said, you know, and you know, very granular, and everything in the cloud market. And to what you were saying, you know, functionality that you can't get to you know, business consultant. you know, it's funny. and all of the TPC benchmarks, By the way, you know, and you know, just inside of that was of some of the data that they shared. the stack, you have the suite, and they're giving you the best of both. of the suite vendor, and you always get the ah In the data center Marc all the time And the other thing I wanted to talk about and then we're going to run 'em and all the infrastructure around that, Due to the nature of the competition, I think you guys all saw the Andreessen, And I think it's going to form I'm looking at the data now. and I love the innovative All right, great thank you. and support the DVA. Great, thank you for that. And I think what Oracle's done Marc Staimer, what do you say? or the ones who are going to grow. we'll give you the last And this is just going to Love to have you back. and we'll see you next time.

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Shruthi Murthy, St. Louis University & Venkat Krishnamachari, MontyCloud | AWS Startup Showcase


 

(gentle music) >> Hello and welcome today's session theCUBE presentation of AWS Startup Showcase powered by theCUBE, I'm John Furrier, for your host of theCUBE. This is a session on breaking through with DevOps data analytics tools, cloud management tools with MontyCloud and cloud management migration, I'm your host. Thanks for joining me, I've got two great guests. Venkat Krishnamachari who's the co-founder and CEO of MontyCloud and Shruthi Sreenivasa Murthy, solution architect research computing group St. Louis University. Thanks for coming on to talk about transforming IT, day one day two operations. Venkat, great to see you. >> Great to see you again, John. So in this session, I really want to get into this cloud powerhouse theme you guys were talking about before on our previous Cube Conversations and what it means for customers, because there is a real market shift happening here. And I want to get your thoughts on what solution to the problem is basically, that you guys are targeting. >> Yeah, John, cloud migration is happening rapidly. Not an option. It is the current and the immediate future of many IT departments and any type of computing workloads. And applications and services these days are better served by cloud adoption. This rapid acceleration is where we are seeing a lot of challenges and we've been helping customers with our platform so they can go focus on their business. So happy to talk more about this. >> Yeah and Shruthi if you can just explain your relationship with these guys, because you're a cloud architect, you can try to put this together. MontyCloud is your customer, talk about your solution. >> Yeah I work at the St. Louis University as the solutions architect for the office of Vice President of Research. We can address St. Louis University as SLU, just to keep it easy. SLU is a 200-year-old university with more focus on research. And our goal at the Research Computing Group is to help researchers by providing the right infrastructure and computing capabilities that help them to advance their research. So here in SLU research portfolio, it's quite diverse, right? So we do research on vaccines, economics, geospatial intelligence, and many other really interesting areas, and you know, it involves really large data sets. So one of the research computing groups' ambitious plan is to move as many high-end computation applications from on-prem to the AWS. And I lead all the cloud initiatives for the St. Louis university. >> Yeah Venkat and I, we've been talking, many times on theCUBE, previous interviews about, you know, the rapid agility that's happening with serverless and functions, and, you know, microservices start to see massive acceleration of how fast cloud apps are being built. It's put a lot of pressure on companies to hang on and manage all this. And whether you're a security group was trying to lock down something, or it's just, it's so fast, the cloud development scene is really fun and you're implementing it at a large scale. What's it like these days from a development standpoint? You've got all this greatness in the cloud. What's the DevOps mindset right now? >> SLU is slowly evolving itself as the AWS Center of Excellence here in St. Louis. And most of the workflows that we are trying to implement on AWS and DevOps and, you know, CICD Pipelines. And basically we want it ready and updated for the researchers where they can use it and not have to wait on any of the resources. So it has a lot of importance. >> Research as code, it's like the internet, infrastructure as code is DevOps' ethos. Venkat, let's get into where this all leads to because you're seeing a culture shift in companies as they start to realize if they don't move fast, and the blockers that get in the way of the innovation, you really can't get your arms around this growth as an opportunity to operationalize all the new technology, could you talk about the transformation goals that are going on with your customer base. What's going on in the market? Can you explain and unpack the high level market around what you guys are doing? >> Sure thing, John. Let's bring up the slide one. So they have some content that Act-On tabs. John, every legal application, commercial application, even internal IT departments, they're all transforming fast. Speed has never been more important in the era we are today. For example, COVID research, you know, analyzing massive data sets to come up with some recommendations. They don't demand a lot from the IT departments so that researchers and developers can move fast. And I need departments that are not only moving current workloads to the cloud they're also ensuring the cloud is being consumed the right way. So researchers can focus on what they do best, what we win, learning and working closely with customers and gathering is that there are three steps or three major, you know, milestone that we like to achieve. I would start the outcome, right? That the important milestone IT departments are trying to get to is transforming such that they're directly tied to the key business objectives. Everything they do has to be connected to the business objective, which means the time and you know, budget and everything's aligned towards what they want to deliver. IT departments we talk with have one common goal. They want to be experts in cloud operations. They want to deliver cloud operations excellence so that researchers and developers can move fast. But they're almost always under the, you know, they're time poor, right? And there is budget gaps and that is talent and tooling gap. A lot of that is what's causing the, you know, challenges on their path to journey. And we have taken a methodical and deliberate position in helping them get there. >> Shruthi hows your reaction to that? Because, I mean, you want it faster, cheaper, better than before. You don't want to have all the operational management hassles. You mentioned that you guys want to do this turnkey. Is that the use case that you're going after? Just research kind of being researchers having the access at their fingertips, all these resources? What's the mindset there, what's your expectation? >> Well, one of the main expectations is to be able to deliver it to the researchers as demand and need and, you know, moving from a traditional on-prem HBC to cloud would definitely help because, you know, we are able to give the right resources to the researchers and able to deliver projects in a timely manner, and, you know, with some additional help from MontyCloud data platform, we are able to do it even better. >> Yeah I like the onboarding thing and to get an easy and you get value quickly, that's the cloud business model. Let's unpack the platform, let's go into the hood. Venkat let's, if you can take us through the, some of the moving parts under the platform, then as you guys have it's up at the high level, the market's obvious for everyone out there watching Cloud ops, speed, stablism. But let's go look at the platform. Let's unpack that, do you mind pick up on slide two and let's go look at the what's going on in the platform. >> Sure. Let's talk about what comes out of the platform, right? They are directly tied to what the customers would like to have, right? Customers would like to fast track their day one activities. Solution architects, such as Shruthi, their role is to try and help get out of the way of the researchers, but we ubiquitous around delegating cloud solutions, right? Our platform acts like a seasoned cloud architect. It's as if you've instantly turned on a cloud solution architect that should, they can bring online and say, Hey, I want help here to go faster. Our lab then has capabilities that help customers provision a set of governance contracts, drive consumption in the right way. One of the key things about driving consumption the right way is to ensure that we prevent a security cost or compliance issues from happening in the first place, which means you're shifting a lot of the operational burden to left and make sure that when provisioning happens, you have a guard rails in place, we help with that, the platform solves a problem without writing code. And an important takeaway here, John is that a was built for architects and administrators who want to move fast without having to write a ton of code. And it is also a platform that they can bring online, autonomous bots that can solve problems. For example, when it comes to post provisioning, everybody is in the business of ensuring security because it's a shared model. Everybody has to keep an eye on compliance, that is also a shared responsibility, so is cost optimization. So we thought wouldn't it be awesome to have architects such as Shruthi turn on a compliance bot on the platform that gives them the peace of mind that somebody else and an autonomous bot is watching our 24 by 7 and make sure that these day two operations don't throw curve balls at them, right? That's important for agility. So platform solves that problem with an automation approach. Going forward on an ongoing basis, right, the operation burden is what gets IT departments. We've seen that happen repeatedly. Like IT department, you know, you know this, John, maybe you have some thoughts on this. You know, you know, if you have some comments on how IT can face this, then maybe that's better to hear from you. >> No, well first I want to unpack that platform because I think one of the advantages I see here and that people are talking about in the industry is not only is the technology's collision colliding between the security postures and rapid cloud development, because DevOps and cloud, folks, are moving super fast. They want things done at the point of coding and CICB pipeline, as well as any kind of changes, they want it fast, not weeks. They don't want to have someone blocking it like a security team, so automation with the compliance is beautiful because now the security teams can provide policies. Those policies can then go right into your platform. And then everyone's got the rules of the road and then anything that comes up gets managed through the policy. So I think this is a big trend that nobody's talking about because this allows the cloud to go faster. What's your reaction to that? Do you agree? >> No, precisely right. I'll let Shurthi jump on that, yeah. >> Yeah, you know, I just wanted to bring up one of the case studies that we read on cloud and use their compliance bot. So REDCap, the Research Electronic Data Capture also known as REDCap is a web application. It's a HIPAA web application. And while the flagship projects for the research group at SLU. REDCap was running on traditional on-prem infrastructure, so maintaining the servers and updating the application to its latest version was definitely a challenge. And also granting access to the researchers had long lead times because of the rules and security protocols in place. So we wanted to be able to build a secure and reliable enrollment on the cloud where we could just provision on demand and in turn ease the job of updating the application to its latest version without disturbing the production environment. Because this is a really important application, most of the doctors and researchers at St. Louis University and the School of Medicine and St. Louis University Hospital users. So given this challenge, we wanted to bring in MontyCloud's cloud ops and, you know, security expertise to simplify the provisioning. And that's when we implemented this compliance bot. Once it is implemented, it's pretty easy to understand, you know, what is compliant, what is noncompliant with the HIPAA standards and where it needs an remediation efforts and what we need to do. And again, that can also be automated. It's nice and simple, and you don't need a lot of cloud expertise to go through the compliance bot and come up with your remediation plan. >> What's the change in the outcome in terms of the speed turnaround time, the before and after? So before you're dealing with obviously provisioning stuff and lead time, but just a compliance closed loop, just to ask a question, do we have, you know, just, I mean, there's a lot of manual and also some, maybe some workflows in there, but not as not as cool as an instant bot that solve yes or no decision. And after MontyCloud, what are some of the times, can you share any data there just doing an order of magnitude. >> Yeah, definitely. So the provisioning was never simpler, I mean, we are able to provision with just one or two clicks, and then we have a better governance guardrail, like Venkat says, and I think, you know, to give you a specific data, it, the compliance bot does about more than 160 checks and it's all automated, so when it comes to security, definitely we have been able to save a lot of effort on that. And I can tell you that our researchers are able to be 40% more productive with the infrastructure. And our research computing group is able to kind of save the time and, you know, the security measures and the remediation efforts, because we get customized alerts and notifications and you just need to go in and, you know. >> So people are happier, right? People are getting along at the office or virtually, you know, no one is yelling at each other on Slack, hey, where's? Cause that's really the harmony here then, okay. This is like a, I'm joking aside. This is a real cultural issue between speed of innovation and the, what could be viewed as a block, or just the time that say security teams or other teams might want to get back to you, make sure things are compliant. So that could slow things down, that tension is real and there's some disconnects within companies. >> Yeah John, that's spot on, and that means we have to do a better job, not only solving the traditional problems and make them simple, but for the modern work culture of integrations. You know, it's not uncommon like you cut out for researchers and architects to talk in a Slack channel often. You say, Hey, I need this resource, or I want to reconfigure this. How do we make that collaboration better? How do you make the platform intelligent so that the platform can take off some of the burden off of people so that the platform can monitor, react, notify in a Slack channel, or if you should, the administrator say, Hey, next time, this happens automatically go create a ticket for me. If it happens next time in this environment automatically go run a playbook, that remediates it. That gives a lot of time back that puts a peace of mind and the process that an operating model that you have inherited and you're trying to deliver excellence and has more help, particularly because it is very dynamic footprint. >> Yeah, I think this whole guard rail thing is a really big deal, I think it's like a feature, but it's a super important outcome because if you can have policies that map into these bots that can check rules really fast, then developers will have the freedom to drive as fast as they want, and literally go hard and then shift left and do the coding and do all their stuff on the hygiene side from the day, one on security is really a big deal. Can we go back to this slide again for the other project? There's another project on that slide. You talked about RED, was it REDCap, was that one? >> Yeah. Yeah, so REDCap, what's the other project. >> So SCAER, the Sinfield Center for Applied Economic Research at SLU is also known as SCAER. They're pretty data intensive, and they're into some really sophisticated research. The Center gets daily dumps of sensitive geo data sensitive de-identified geo data from various sources, and it's a terabyte so every day, becomes petabytes. So you know, we don't get the data in workable formats for the researchers to analyze. So the first process is to convert this data into a workable format and keep an analysis ready and doing this at a large scale has many challenges. So we had to make this data available to a group of users too, and some external collaborators with ads, you know, more challenges again, because we also have to do this without compromising on the security. So to handle these large size data, we had to deploy compute heavy instances, such as, you know, R5, 12xLarge, multiple 12xLarge instances, and optimizing the cost and the resources deployed on the cloud again was a huge challenge. So that's when we had to take MontyCloud help in automating the whole process of ingesting the data into the infrastructure and then converting them into a workable format. And this was all automated. And after automating most of the efforts, we were able to bring down the data processing time from two weeks or more to three days, which really helped the researchers. So MontyCloud's data platform also helped us with automating the risk, you know, the resource optimization process and that in turn helped bring the costs down, so it's been pretty helpful then. >> That's impressive weeks to days, I mean, this is the theme Venkat speed, speed, speed, hybrid, hybrid. A lot of stuff happening. I mean, this is the new normal, this is going to make companies more productive if they can get the apps built faster. What do you see as the CEO and founder of the company you're out there, you know, you're forging new ground with this great product. What do you see as the blockers from customers? Is it cultural, is it lack of awareness? Why aren't people jumping all over this? >> Only people aren't, right. They go at it in so many different ways that, you know, ultimately be the one person IT team or massively well-funded IT team. Everybody wants to Excel at what they're delivering in cloud operations, the path to that as what, the challenging part, right? What are you seeing as customers are trying to build their own operating model and they're writing custom code, then that's a lot of need for provisioning, governance, security, compliance, and monitoring. So they start integrating point tools, then suddenly IT department is now having a, what they call a tax, right? They have to maintain the technical debt while cloud service moving fast. It's not uncommon for one of the developers or one of the projects to suddenly consume a brand new resource. And as you know, AWS throws up a lot more services every month, right? So suddenly you're not keeping up with that service. So what we've been able to look at this from a point of view of how do we get customers to focus on what they want to do and automate things that we can help them with? >> Let me, let me rephrase the question if you don't mind. Cause I I didn't want to give the impression that you guys aren't, you guys have a great solution, but I think when I see enterprises, you know, they're transforming, right? So it's not so much the cloud innovators, like you guys, it's really that it's like the mainstream enterprise, so I have to ask you from a customer standpoint, what's some of the cultural things are technical reasons why they're not going faster? Cause everyone's, maybe it's the pandemic's forcing projects to be double down on, or some are going to be cut, this common theme of making things available faster, cheaper, stronger, more secure is what cloud does. What are some of the enterprise challenges that they have? >> Yeah, you know, it might be money for right, there's some cultural challenges like Andy Jassy or sometimes it's leadership, right? You want top down leadership that takes a deterministic step towards transformation, then adequately funding the team with the right skills and the tools, a lot of that plays into it. And there's inertia typically in an existing process. And when you go to cloud, you can do 10X better, people see that it doesn't always percolate down to how you get there. So those challenges are compounded and digital transformation leaders have to, you know, make that deliberate back there, be more KPI-driven. One of the things we are seeing in companies that do well is that the leadership decides that here are our top business objectives and KPIs. Now if we want the software and the services and the cloud division to support those objectives when they take that approach, transformation happens. But that is a lot more easier said than done. >> Well you're making it really easy with your solution. And we've done multiple interviews. I've got to say you're really onto something really with this provisioning and the compliance bots. That's really strong, that the only goes stronger from there, with the trends with security being built in. Shruthi, got to ask you since you're the customer, what's it like working with MontyCloud? It sounds so awesome, you're customer, you're using it. What's your review, what's your- What's your, what's your take on them? >> Yeah they are doing a pretty good job in helping us automate most of our workflows. And when it comes to keeping a tab on the resources, the utilization of the resources, so we can keep a tab on the cost in turn, you know, their compliance bots, their cost optimization tab. It's pretty helpful. >> Yeah well you're knocking projects down from three weeks to days, looking good, I mean, looking real strong. Venkat this is the track record you want to see with successful projects. Take a minute to explain what else is going on with MontyCloud. Other use cases that you see that are really primed for MontyCloud's platform. >> Yeah, John, quick minute there. Autonomous cloud operations is the goal. It's never done, right? It there's always some work that you hands-on do. But if you set a goal such that customers need to have a solution that automates most of the routine operations, then they can focus on the business. So we are going to relentlessly focused on the fact that autonomous operations will have the digital transformation happen faster, and we can create a lot more value for customers if they deliver to their KPIs and objectives. So our investments in the platform are going more towards that. Today we already have a fully automated compliance bot, a security bot, a cost optimization recommendation engine, a provisioning and governance engine, where we're going is we are enhancing all of this and providing customers lot more fluidity in how they can use our platform Click to perform your routine operations, Click to set up rules based automatic escalation or remediation. Cut down the number of hops a particular process will take and foster collaboration. All of this is what our platform is going and enhancing more and more. We intend to learn more from our customers and deliver better for them as we move forward. >> That's a good business model, make things easier, reduce the steps it takes to do something, and save money. And you're doing all those things with the cloud and awesome stuff. It's really great to hear your success stories and the work you're doing over there. Great to see resources getting and doing their job faster. And it's good and tons of data. You've got petabytes of that's coming in. It's it's pretty impressive, thanks for sharing your story. >> Sounds good, and you know, one quick call out is customers can go to MontyCloud.com today. Within 10 minutes, they can get an account. They get a very actionable and valuable recommendations on where they can save costs, what is the security compliance issues they can fix. There's a ton of out-of-the-box reports. One click to find out whether you are having some data that is not encrypted, or if any of your servers are open to the world. A lot of value that customers can get in under 10 minutes. And we believe in that model, give the value to customers. They know what to do with that, right? So customers can go sign up for a free trial at MontyCloud.com today and get the value. >> Congratulations on your success and great innovation. A startup showcase here with theCUBE coverage of AWS Startup Showcase breakthrough in DevOps, Data Analytics and Cloud Management with MontyCloud. I'm John Furrier, thanks for watching. (gentle music)

Published Date : Sep 22 2021

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the co-founder and CEO Great to see you again, John. It is the current and the immediate future you can just explain And I lead all the cloud initiatives greatness in the cloud. And most of the workflows that and the blockers that get in important in the era we are today. Is that the use case and need and, you know, and to get an easy and you get of the researchers, but we ubiquitous the cloud to go faster. I'll let Shurthi jump on that, yeah. and reliable enrollment on the cloud of the speed turnaround to kind of save the time and, you know, as a block, or just the off of people so that the and do the coding and do all Yeah, so REDCap, what's the other project. the researchers to analyze. of the company you're out there, of the projects to suddenly So it's not so much the cloud innovators, and the cloud division to and the compliance bots. the cost in turn, you know, to see with successful projects. So our investments in the platform reduce the steps it takes to give the value to customers. Data Analytics and Cloud

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VeeamON Power Panel | VeeamON 2021


 

>>President. >>Hello everyone and welcome to wien on 2021. My name is Dave Volonte and you're watching the cubes continuous coverage of the event. You know, VM is a company that made its mark riding the virtualization wave, but quite amazingly has continued to extend its product portfolio and catch the other major waves of the industry. Of course, we're talking about cloud backup. SaS data protection was one of the early players there making moves and containers. And this is the VM on power panel with me or Danny Allen, who is the Ceo and Senior vice president of product strategy at VM. Dave Russell is the vice President of enterprise Strategy, of course, said Vin and Rick Vanover, senior director of product strategy at VM. It's great to see you again. Welcome back to the cube. >>Good to be here. >>Well, it had to be here. >>Yeah, let's do it. >>Let's do this. So Danny, you know, we heard you kind of your keynotes and we saw the general sessions and uh sort of diving into the breakouts. But the thing that jumps out to me is this growth rate that you're on. Uh you know, many companies and we've seen this throughout the industry have really struggled, you know, moving from the traditional on prem model to an an A. R. R. Model. Uh they've had challenges doing so the, I mean, you're not a public company, but you're quite transparent and a lot of your numbers 25% a our our growth year of a year in the last quarter, You know, 400,000 plus customers. You're talking about huge numbers of downloads of backup and replication Danny. So what are your big takeaways from the last, You know, 6-12 months? I know it was a strange year obviously, but you guys just keep cranking. >>Yeah, so we're obviously hugely excited by this and it really is a confluence of various things. It's our, it's our partners, it's the channel. Um, it's our customers frankly that that guide us and give us direction on what to do. But I always focus in on the product because I, you know, we run product strategy here, this group and we're very focused on building good products and I would say there's three product areas that are on maximum thrust right now. One is in the data center. So we built a billion dollar business on being the very best in the data center for V sphere, hyper V, um, for Nutanix, HV and as we announced also with red hat virtualization. So data center obviously a huge thrust for us going forward. The second assess Office 3 65 is exploding. We already announced we're protecting 5.8 million users right now with being back up for Office 3 65 and there's a lot of room to grow there. There's 145 million daily users of Microsoft teams. So a lot of room to grow. And then the third areas cloud, we moved over 100 petabytes of data into the public cloud in Q one and there's a lot of opportunity there as well. So those three things are driving the growth, the data center SaAS and cloud >>Davis. I want to get your kind of former analyst perspective on this. Uh you know, I know, you know, it's kind of become cliche but you still got that D. N. A. And I'm gonna tap it. So when you think about and you were following beam, of course very closely during its ascendancy with virtualization. And back then you wouldn't just take your existing, you know, approaches to back up in your processes and just slap them on to virtualization. That that wouldn't have worked. You had to rethink your backup. And it seems like I want to ask you about cloud because people talk about lift and shift and what I hear from customers is, you know, if I just lift and shift to cloud, it's okay, but if I don't have a plan to change my operating model, you know, I don't get the real benefit out of it. And so I would think back up data protection, data management etcetera is a key part of that. So how are you thinking about cloud and the opportunity there? >>Yeah, that's a good point, David. You know, I think the key area right there is it's important to protect the workload of the environment. The way that that environment is naturally is best suited to be protected and also to interact in a way that the administrator doesn't have to rethink, doesn't have to change their process so early on. Um I think it was very successful because the interface is the work experience looked like what an active directory administrator was used to, seeing if they went to go and protect something with me where to go recover an item. Same is true in the cloud, You don't want to just take what's working well in one area and just force it, you know, around round peg into a square hole. This doesn't work well. So you've got to think about the environment and you've got to think about what's gonna be the real use case for getting access to this data. So you want to really tune things and there's obviously commonality involved, but from a workflow perspective, from an application perspective and then a delivery model perspective, Now, when it comes to hybrid cloud multi cloud, it's important to look like that you belong there, not a fish out of water. >>Well, so of course, Danny you were talking to talking about you guys have product first, Right? And so rick your your key product guy here. What's interesting to me is when you look at the history of the technology industry and disruption, it's it's so often that the the incumbent, which you knew now an incumbent, you know, you're not the startup anymore, but the incumbent has challenges riding these these new waves because you've got to serve the existing customer base, but you gotta ride the new momentum as well. So how rick do you approach that from a product standpoint? Because based on the numbers that we see it doesn't you seem to be winning in both the traditional business and the new business. So how do you adapt from a product standpoint? >>Well, Dave, that's a good question. And Danny set it up? Well, it's really the birth of the Wien platform and its relevance in the market. In my 11th year here at Wien, I've had all kinds of conversations. Right. You know, the perception was that, you know, this smb toy for one hyper Advisor those days are long gone. We can check the boxes across the data center and cloud and even cloud native apps. You know, one of the things that my team has done is invest heavily in both people and staff on kubernetes, which aligns to our casting acquisition, which was featured heavily here at V Mon. So I think that being able to have that complete platform conversation Dave has really given us incredible momentum but also credibility with the customers because more than ever, this fundamental promise of having data backed up and being able to drive a recovery for whatever may happen to data nowadays. You know, that's a real emotional, important thing for people and to be able to bring that kind of outcome across the data center, across the cloud, across changes in what they do kubernetes that's really aligned well to our success and you know, I love talking to customers now. It's a heck of a lot easier when you can say yes to so many things and get the technical win. So that kind of drives a lot of the momentum Dave, but it's really the platform. >>So let's talk about the future of it and I want all you guys to chime in here and Danny, you start up, How do you see it? I mean, I always say the last 10 years, the next 10 years ain't gonna be like the last 10 years whether it's in cloud or hybrid et cetera. But so how Danny do you see I. T. In the future of I. T. Where do you see VM fitting in, how does that inform your roadmap, your product strategy? Maybe you could kick that segment off? >>Yeah. I think of the kind of the two past decades that we've gone through starting back in 2000 we had a lot of digital services built for end users and it was built on physical infrastructure and that was fantastic. Obviously we could buy things online, we could order close we could order food, we we could do things interact with end users. The second era about a decade later was based on virtualization. Now that wasn't a benefit so much to the end user is a benefit to the business. The Y because you could put 10 servers on a single physical server and you could be a lot more flexible in terms of delivery. I really think this next era that we're going into is actually based on containers. That's why the cost of acquisition is so strategic to us. Because the unique thing about containers is they're designed for to be consumption friendly. You spin them up, you spin them down, you provision them, you d provisions and they're completely portable. You can move it >>from on >>premises if you're running open shift to e k s a k s G k E. And so I think the next big era that we're going to go through is this movement towards containerized infrastructure. Now, if you ask me who's running that, I still think there's going to be a data center operations team, platform ups is the way that I think about them who run that because who's going to take the call in the middle of the night. But it is interesting that we're going through this transformation and I think we're in the very early stages of this radical transformation to a more consumption based model. Dave. I don't know what you think about that. >>Yeah, I would say something pretty similar Danny. It sounds cliche day valenti, but I take everything back to digital transformation. And the reason I say that is to me, digital transformation is about improving customer intimacy and so that you can deliver goods and services that better resonate and you can deliver them in better time frame. So exactly what Danny said, you know, I think that the siloed approaches of the past where we built very hard in environments and we were willing to take a long time to stand those up and then we have very tight change control. I feel like 2020 sort of a metaphor for where the data center is going to throw all that out the window we're compiling today. We're shipping today and we're going to get experience today and we're going to refine it and do it again tomorrow. But that's the environment we live in. And to Danny's point why containers are so important. That notion of shift left meaning experience things earlier in the cycle. That is going to be the reality of the data center regardless of whether the data center is on prem hybrid cloud, multi cloud or for some of us potentially completely in the cloud. >>So rick when you think about some of your peeps like the backup admit right and how that role is changing in a big discussion in the economy now about the sort of skills gap we got all these jobs and and yet there's still all this unemployment now, you know the debate about the reasons why, but there's a there's a transition enrolls in terms of how people are using products and obviously containers brings that, what what are you seeing when you talk to like a guy called him your peeps? Yeah, it's >>an evolving conversation. Dave the audience, right. It has to be relevant. Uh you know, we were afforded good luxury in that data center wheelhouse that Danny mentioned. So virtualization platform storage, physical servers, that's a pretty good start. But in the software as a service wheelhouse, it's a different persona now, they used to talk to those types of people, there's a little bit of connection, but as we go farther to the cloud, native apps, kubernetes and some of the other SAAS platforms, it is absolutely an audience journey. So I've actually worked really hard on that in my team, right? Everything from what I would say, parachuting into a community, right? And you have to speak their language. Number one reason is just number one outcomes just be present. And if you're in these communities you can find these individuals, you can talk their language, you can resonate with their needs, right? So that's something uh you know, everything from Levin marketing strategy to the community strategy to even just seating products in the market, That's a recipe that beam does really well. So yeah, it's a moving target for sure. >>Dave you were talking about the cliche of digital transformation and I'll say this may be pre Covid, I really felt like it was a cliche, there was a lot of, you know, complacency, I'll call it, but then the force marks the digital change that uh and now we kind of understand if you're not a digital business, you're in trouble. Uh And so my question is how it relates to some of the trends that we've been talking about in terms of cloud containers, We've seen the SAs ification for the better part of a decade now, but specifically as it relates to migration, it's hard for customers to just migrate their application portfolio to the cloud. Uh It's hard to fund it. It takes a long time. It's complex. Um how do you see that cloud migration evolving? Maybe that's where hybrid comes in And again, I'm interested in how you guys think about it and how it affects your strategy. >>Yeah. Well it's a complex answer as you might imagine because 400,000 customers, we take the exact same code. The exact same ice so that I run on my laptop is the exact same being backup and replication image that a major bank protects almost 20,000 machines and a petabytes of data. And so what that means is that you have to look at things on a case by case basis for some of us continuing to operate proprietary systems on prem might be the best choice for a certain workload. But for many of us the Genie is kind of out of the bottle with 2020 we have to move faster. It's less about safety and a lot more about speed and favorable outcome. We'll fix it if it's broken but let's get going. So for organizations struggling with how to move to the cloud, believe it or not, backup and recovery is an excellent way to start to venture into that because you can start to move data backup ISm data movement engine. So we can start to see data there where it makes sense. But rick would be quick to point out we want to offer a safe return. We have instances of where people want to repatriate data back and having a portable data format is key to that Rick. >>Uh yeah, I had a conversation recently with an organization managing cloud sprawl. They decided to consolidate, we're going to use this cloud, so it was removing a presence from one cloud that starts with an A and migrating it to the other cloud that starts with an A. You know, So yeah, we've seen that need for portability repatriation on prem classic example going from on prem apps to software as a service models for critical apps. So data mobility is at the heart of VM and with all the different platforms, kubernetes comes into play as well. It's definitely aligning to the needs that we're seeing in the market for sure. >>So repatriation, I want to stay on that for a second because you're, you're an arms dealer, you don't care if they're in the cloud or on prem and I don't know, maybe you make more money in one or the other, but you're gonna ride whatever waves the market gives you so repatriation to me implies. Or maybe I'm just inferring that somebody's moved to the cloud and they feel like, wow, we've made a mistake, it was too fast, too expensive. It didn't work for us. So now we're gonna bring it back on prem. Is that what you're saying? Are you saying they actually want their data in both both places. As another layer of data protection Danny. I wonder if you could address that. What are you seeing? >>Well, one of the interesting things that we saw recently, Dave Russell actually did the survey on this is that customers will actually build their work laid loads in the cloud with the intent to bring it back on premises. And so that repatriation is real customers actually don't just accidentally fall into it, but they intend to do it. And the thing about being everyone says, hey, we're disrupting the market, we're helping you go through this transformation, we're helping you go forward. Actually take a slightly different view of this. The team gives them the confidence that they can move forward if they want to, but if they don't like it, then they can move back and so we give them the stability through this incredible pace, change of innovation. We're moving forward so so quickly, but we give them the ability to move forward if they want then to recover to repatriate if that's what they need to do in a very effective way. And Dave maybe you can touch on that study because I know that you talked to a lot of customers who do repatriate workloads after moving them to the cloud. >>Yeah, it's kind of funny Dave not in the analyst business right now, but thanks to Danny and our chief marketing Officer, we've got now half a dozen different research surveys that have either just completed or in flight, including the largest in the data protection industry's history. And so the survey that Danny alluded to, what we're finding is people are learning as they're going and in some cases what they thought would happen when they went to the cloud they did not experience. So the net kind of funny slide that we discovered when we asked people, what did you like most about going to the cloud and then what did you like least about going to the cloud? The two lists look very similar. So in some cases people said, oh, it was more stable. In other cases people said no, it was actually unstable. So rick I would suggest that that really depends on the practice that you bring to it. It's like moving from a smaller house to a larger house and hoping that it won't be messy again. Well if you don't change your habits, it's eventually going to end up in the same situation. >>Well, there's still door number three and that's data reuse and analytics. And I found a lot of organizations love the idea of at least manipulating data, running test f scenarios on yesterday's production, cloud workload completely removed from the cloud or even just analytics. I need this file. You know, those types of scenarios are very easy to do today with them. And you know, sometimes those repatriations, those portable recoveries, Sometimes people do that intentionally, but sometimes they have to do it. You know, whether it's fire, flood and blood and you know, oh, I was looks like today we're moving to the cloud because I've lost my data center. Right. Those are scenarios that, that portable data format really allows organizations to do that pretty easily with being >>it's a good discussion because to me it's not repatriation, it has this negative connotation, the zero sum game and it's not Danny what you describe and rick as well. It was kind of an experimentation, a purposeful. We're going to do it in the cloud because we can and it's cheap and low risk to spin it up and then we're gonna move it because we've always thought we're going to have it on prem. So, so you know, there is some zero sum game between the cloud and on prem. Clearly no question about it. But there's also this rising tide lifts all ship. I want to, I want to change the subject to something that's super important and and top of mind it's in the press and it ain't going away and that is cyber and specifically ransomware. I mean, since the solar winds hack and it seems to me that was a new milestone in the capabilities and aggressiveness of the adversary who is very well funded and quite capable. And what we're seeing is this idea of tucking into the supply chain of islands, so called island hopping. You're seeing malware that's self forming and takes different signatures very stealthy. And the big trend that we've seen in the last six months or so is that the bad guys will will lurk and they'll steal all kinds of sensitive data. And then when you have an incident response, they will punish you for responding. And they will say, okay, fine, you want to do that. We're going to hold you ransom. We're gonna encrypt your data. And oh, by the way, we stole this list of positive covid test results with names from your website and we're gonna release it if you don't pay their. I mean, it's like, so you have to be stealthy in your incident response. And this is a huge problem. We're talking about trillions of dollars lost each year in, in in cybercrime. And so, uh, you know, it's again, it's this uh the bad news is good news for companies like you. But how do you help customers deal with this problem? What are you seeing Danny? Maybe you can chime in and others who have thoughts? >>Well we're certainly seeing the rise of cyber like crazy right now and we've had a focus on this for a while because if you think about the last line of defense for customers, especially with ransomware, it is having secure backups. So whether it be, you know, hardened Linux repositories, but making sure that you can store the data, have it offline, have it, have it encrypted immutable. Those are things that we've been focused on for a long while. It's more than that. Um it's detection and monitoring of the environment, which is um certainly that we do with our monitoring tools and then also the secure recovery. The last thing that you want to do of course is bring your backups or bring your data back online only to be hit again. And so we've had a number of capabilities across our portfolio to help in all of these. But I think what's interesting is where it's going, if you think about unleashing a world where we're continuously delivering, I look at things like containers where you have continues delivery and I think every time you run that helm commander, every time you run that terra form command, wouldn't that be a great time to do a backup to capture your data so that you don't have an issue once it goes into production. So I think we're going towards a world where security and the protection against these cyber threats is built into the supply chain rather than doing it on just a time based uh, schedule. And I know rick you're pretty involved on the cyber side as well. Would you agree with that? I >>would. And you know, for organizations that are concerned about ransomware, you know, this is something that is taken very seriously and what Danny explained for those who are familiar with security, he kind of jumped around this, this universally acceptable framework in this cybersecurity framework there, our five functions that are a really good recipe on how you can go about this. And and my advice to IT professionals and decision makers across the board is to really align everything you do to that framework. Backup is a part of it. The security monitoring and user training. All those other things are are areas that that need to really follow that wheel of functions. And my little tip here and this is where I think we can introduce some differentiation is around detection and response. A lot of people think of backup product would shine in both protection and recovery, which it does being does, but especially on response and detection, you know, we have a lot of capabilities that become impact opportunities for organizations to be able to really provide successful outcomes through the other functions. So it's something we've worked on a lot. In fact we've covered here at the event. I'm pretty sure it will be on replay the updated white paper. All those other resources for different levels can definitely guide them through. >>So we follow up to the detection is what analytics that help you identify whatever lateral movement or people go in places they shouldn't go. I mean the hard part is is you know, the bad guys are living off the land, meaning they're using your own tooling to to hack you. So they're not it's not like they're introducing something new that shouldn't be there. They're they're just using making judo moves against you. So so specifically talk a little bit more about your your detection because that's critical. >>Sure. So I'll give you one example imagine we capture some data in the form of a backup. Now we have an existing advice that says, you know what Don't put your backup infrastructure with internet connectivity. Use explicit minimal permissions. And those three things right there and keep it up to date. Those four things right there will really hedge off a lot of the different threat vectors to the back of data, couple that with some of the mutability offline or air gapped capabilities that Danny mentioned and you have an additional level of resiliency that can really ensure that you can drive recovery from an analytic standpoint. We have an api that allows organizations to look into the backup data. Do more aggressive scanning without any exclusions with different tools on a flat file system. You know, the threats can't jump around in memory couple that with secure restore. When you reintroduce things into the environment From a recovery standpoint, you don't want to reintroduce threats. So there's protections, there's there's confidence building steps along the way with them and these are all generally available technologies. So again, I got this white paper, I think we're up to 50 pages now, but it's a very thorough that goes through a couple of those scenarios. But you know, it gets the uh, it gets quickly into things that you wouldn't expect from a backup product. >>Please send me a copy if you, if you don't mind. I this is a huge problem and you guys are global company. I admittedly have a bit of a US bias, but I was interviewing robert Gates one time the former defense secretary and we're talking about cyber war and I said, don't we have the best cyber, can't we let go on the offense? He goes, yeah, we can, but we got the most to lose. So this is really a huge problem for organizations. All right, guys, last question I gotta ask you. So what's life like under, under inside capital of the private equity? What's changed? What's, what's the same? Uh, do you hear from our good friend ratner at all? Give us the update there. >>Yes. Oh, absolutely fantastic. You know, it's interesting. So obviously acquired by insight partners in February of 2020, right, when the pandemic was hitting, but they essentially said light the fuse, keep the engine's going. And we've certainly been doing that. They haven't held us back. We've been hiring like crazy. We're up to, I don't know what the count is now, I think 4600 employees, but um, you know, people think of private equity and they think of cost optimizations and, and optimizing the business, That's not the case here. This is a growth opportunity and it's a growth opportunity simply because of the technology opportunity in front of us to keep, keep the engine's going. So we hear from right near, you know, on and off. But the new executive team at VM is very passionate about driving the success in the industry, keeping abreast of all the technology changes. It's been fantastic. Nothing but good things to say. >>Yes, insight inside partners, their players, we watched them watch their moves and so it's, you know, I heard Bill McDermott, the ceo of service now the other day talking about he called himself the rule of 60 where, you know, I always thought it was even plus growth, you know, add that up. And that's what he was talking about free cash flow. He's sort of changing the definition a little bit but but so what are you guys optimizing for you optimizing for growth? Are you optimising for Alberta? You optimizing for free cash flow? I mean you can't do All three. Right. What how do you think about that? >>Well, we're definitely optimizing for growth. No question. And one of the things that we've actually done in the past 12 months, 18 months is beginning to focus on annual recurring revenue. You see this in our statements, I know we're not public but we talk about the growth in A. R. R. So we're certainly focused on that growth in the annual recovering revenue and that that's really what we tracked too. And it aligns well with the cloud. If you look at the areas where we're investing in cloud native and the cloud and SAAS applications, it's very clear that that recurring revenue model is beneficial. Now We've been lucky, I think we're 13 straight quarters of double-digit growth. And and obviously they don't want to see that dip. They want to see that that growth continue. But we are optimizing on the growth trajectory. >>Okay. And you see you clearly have a 25% growth last quarter in A. R. R. Uh If I recall correctly, the number was evaluation was $5 billion last january. So obviously then, given that strategy, Dave Russell, that says that your tam is a lot bigger than just the traditional backup world. So how do you think about tam? I'll we'll close there >>and uh yeah, I think you look at a couple of different ways. So just in the backup recovery space or backup in replication to paying which one you want to use? You've got a large market there in excess of $8 billion $1 billion dollar ongoing enterprise. Now, if you look at recent i. D. C. Numbers, we grew and I got my handy HP calculator. I like to make sure I got this right. We grew 44.88 times faster than the market average year over year. So let's call that 45 times faster and backup. There's billions more to be made in traditional backup and recovery. However, go back to what we've been talking around digital transformation Danny talking about containers in the environment, deployment models, changing at the heart of backup and recovery where a data capture data management, data movement engine. We envision being able to do that not only for availability but to be able to drive the business board to be able to drive economies of scale faster for our organizations that we serve. I think the trick is continuing to do more of the same Danny mentioned, he knows the view's got lit. We haven't stopped doing anything. In fact, Danny, I think we're doing like 10 times more of everything that we used to be doing prior to the pandemic. >>All right, Danny will give you the last word, bring it home. >>So our goal has always been to be the most trusted provider of backup solutions that deliver modern data protection. And I think folks have seen at demon this year that we're very focused on that modern data protection. Yes, we want to be the best in the data center but we also want to be the best in the next generation, the next generation of I. T. So whether it be sas whether it be cloud VM is very committed to making sure that our customers have the confidence that they need to move forward through this digital transformation era. >>Guys, I miss flying. I mean, I don't miss flying, but I miss hanging with you all. We'll see you. Uh, for sure. Vim on 2022 will be belly to belly, but thanks so much for coming on the the virtual edition and thanks for having us. >>Thank you. >>All right. And thank you for watching everybody. This keeps continuous coverage of the mon 21. The virtual edition. Keep it right there for more great coverage. >>Mm

Published Date : May 26 2021

SUMMARY :

It's great to see you again. So Danny, you know, we heard you kind of your keynotes and we saw the general But I always focus in on the product because I, you know, we run product strategy here, I know, you know, it's kind of become cliche but you still got that D. N. A. that the administrator doesn't have to rethink, doesn't have to change their process so early on. Because based on the numbers that we see it doesn't you seem to be winning in both the traditional business It's a heck of a lot easier when you can say yes to so many things So let's talk about the future of it and I want all you guys to chime in here and Danny, You spin them up, you spin them down, you provision them, you d provisions and they're completely portable. I don't know what you think about that. So exactly what Danny said, you know, I think that the siloed approaches of the past So that's something uh you I really felt like it was a cliche, there was a lot of, you know, complacency, I'll call it, And so what that means is that you have to So data mobility is at the heart of VM and with all the different platforms, I wonder if you could address that. And Dave maybe you can touch on that study depends on the practice that you bring to it. And you know, sometimes those repatriations, those portable recoveries, And then when you have an incident response, they will punish you for responding. you know, hardened Linux repositories, but making sure that you can store the data, And you know, for organizations that are concerned about ransomware, I mean the hard part is is you know, Now we have an existing advice that says, you know what Don't put your backup infrastructure with internet connectivity. I this is a huge problem and you guys are global company. So we hear from right near, you know, on and off. called himself the rule of 60 where, you know, I always thought it was even plus growth, And one of the things that we've actually done in the past 12 So how do you think about tam? recovery space or backup in replication to paying which one you want to use? So our goal has always been to be the most trusted provider of backup solutions that deliver I mean, I don't miss flying, but I miss hanging with you all. And thank you for watching everybody.

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Zeus Kerravala, ZK Research | AWS re:Invent 2020


 

>>the >>globe. It's the Cube with digital coverage of AWS >>reinvent 2020 >>sponsored by Intel, AWS and our community partners. Everyone welcome back to the cubes. Virtual coverage of AWS reinvent 2020 Virtual I'm John for your host. Got a great segment here with two analyst day Volonte and Zia's Carvell who's head principles of zk research dot com. Guys. Great to see you A W s Kino. Thanks for >>coming on. Let's be back in the cube. >>Welcome back. Great to see you guys. Wanna get your thoughts? Um, it's mainly you because we talked with the enterprise a lot. You are leading analyst. You cover a broad range from networking all the way up to the C suite for enterprise buyers and and technology trends. Um, Andy Jassy laid down, in my opinion, what was directionally his next 20 mile stare. The next conquest for Amazon. And that is global. I t spend they locked in the infrastructures of service pass kicking ass. There. Check check. Hello, Enterprise. Different ballgame. What's your thoughts? >>Yeah, they have so much in different areas, obviously. You know, they have dominated cloud instances right there. Mawr compute storage memory. You know insists that anybody but you can see him, um, spreading their wings now, right? I think one of the more interesting announcements was actually what they're doing with Amazon connect. That's their contact center platform. And this is something that I think, Even last year, a lot of people weren't really even sure if they'd be in a long primary in the pocket. People about this market, they were asking, If you really think Amazon's in this, there's something they're experimenting. But we're here to stay. And I think one of the interesting things that they bring to market is, you know, almost unprecedented scale with their cloud platform as well as all the machine learning algorithms. And I think if if you believe that machine learning artificial intelligence is changing, I t. Forever and that's everything from the infrastructure to the network through the applications, then they have an inherent advantage because they have all those machine learning albums built into this stuff that they dio and so they can constantly look at these different markets and disruptive, disruptive, disrupt and take more and more sharing that and that's what they've done. E think that's you know, the context and announcements were great example that they're not doing the telephony things, and, you know, they're kind of bare table stakes. They do that pretty well, but they've just unloaded a whole bunch of ai based features that >>Dave, what's your take on this context center? Because it's not just call centers. I mean, there was a whole industry around call center, unified communications. That whole world. This is about the contact. It's about the person. This is not just a nuanced thing like telephony or, you know, PBX is in the old days. Remember those days? Things is not about the call. It's about the contact. This is what Jazzy saying. >>I think that way had Diana or on early. And I said, I like the fact that their AWS specifically is going after these solutions because several years ago it was just sort of. Here's a bunch of tools. Go figure it out. I think the contact center is I mean, everybody can relate Thio the pains of going through getting rerouted, having to restate all your credentials, not knowing who you are. And so between machine learning, Alexa, Natural language processing, better work flows. I mean there's this huge opportunity toe reinvent the whole call center contact center. So, uh, yeah, I think you called it John. It's a no brainer for a W s toe Really disrupt that >>business. Well, it also puts him in a position. You know, news is breaking on the day of and yet his keynote here at reinvent that, uh, you got Salesforce spying slack for 27 close toe, $28 billion. That's a 55% premium over when they announced it. And that's like a 30 x or 50 x on on revenue. Massive number to confess the message board software. I mean, so So. So. If Amazon can come in and get the context center model, which is not just voice, it's chat, it's machine learning. It's bots. And the innovation to create a step function kind of brings it back into the that integration of user network compute. You know, I just think that it feels very edgy in the sense of edge computing, because if I'm a person, I'm mobile. If I'm a person at work or at home, so there's a whole redefinition Zs, what's your take on this edge? Play from Amazon in context toe the enterprise software landscape. That seems to be, you know, focus on buying companies like Salesforce. >>Well, I think edges really the next big foray for computing. If one of the things and you ask we talked about this, you know, was that the compute, the unit of Compute, has gotten smaller and smaller, Right? We went from data centers to servers to virtual machines, the virtual machines and clouds. Now we're talking about containers and containers on edges, and this requires, um if you if you believe in the world of distributed computing where we're gonna have mawr containers running in MAWR, places on MAWR edges, right. The value proposition where companies is now they can move their data closer to the customer. They could move data closer to the user. And so, if I'm a retailer and I'm trying to understand what a customer is doing, I could do that in store. If I'm Tesla and I'm trying to understand what the drivers doing, I could do that in car, right? If I'm a cellular provider, I could do it by cellular edge. So the edge, I think, is where a lot of the innovation is going to be at Amazon has the luxury of this massive global network. You know, they just announced the number another a number of other local nodes, including Boston and a few other places. So they've got the footprint in place. And this this is what makes Amazon's are difficult to compete with, right? They built this massive network and this all these, no doubt for their e commerce business. And now they're leveraging that deliver I t services. You can't just go build this from the ground up the variety, right? You have to be able to monetize it another way. And they've been doing that with the commerce for a long time. And so it makes them. It makes it very, very difficult for them to capture Google could with Daniel forget about the item. Oh, yeah, so good. Microsoft. Possibly. But they I think that the more distributed compute becomes the more favors Amazon, >>I would add to that if I could, John, I mean, look good. Look at the prevailing way in which many of the infrastructure the old guard is Andy. Jesse calls them. Companies have pursued the edge they've essentially taking, taking x 86 boxes and, you know, maybe made him rugged and throwing them over the fence to the edge. And that really is not gonna play the edges. Now there's not one edge. I mean, there's a very highly specific use cases and factories and windmills. And maybe maybe it's small retail organizations, and whatever it is that those are gonna be really unique situations. And I think the idea of putting a programmable infrastructure at the edge is gonna win. I also think that the edge architecture is gonna be different. It's going to require much more efficient processing to do a I Influencing a lot of the data is gonna be, uh, stay at the edge. A lot of it's not gonna be persisted. Some of it's gonna come back to the cloud. But I think most of it is actually gonna gonna either not be persisted or stay at the edge and be affected in real time. When you think of autonomous vehicles so totally different programming model, >>well, I think that's the point of what I was saying earlier Zeus was talking about Is that it's It's the edges is just different. I mean, you got purpose built stuff. I mean, they were talking by the way they have snowball. So they have, ah, hard edge device. And they got out outpost now in multiple flavors and sizes. But they also were talking about computer vision and machine learning. We're going together for that. The panoramic appliance. I think it was where there's all these different cases to your point, Dave, where it's just different. At the edge, you have the zones for five G. I mean, if you go to a five g tower, that's essentially an edge. Just there's equipment up to this. Radios is transceivers and other back haul equipment. So when you look at the totality of what it is, the diversity, I think that's why this whole idea of Lambda and Containers is interesting. Toe Zia's. When you were saying about the compute sizes being small, because if you could put compute at the edge on small pieces to match the form factor that becomes interesting. I think that's what this Lambda container announcement I found interesting because I see that playing directly into that your reaction to >>that. It actually, um, makes it. If not done correctly, it could make I t much more complex because, um, containers air interesting because they're not like virtual machines. First live in perpetuity. Containers you They're very ephemeral, right? You spin them up to 30 seconds, you spin them up for a couple of minutes that you deprecate them. So at any given point in time, you could have thousands of containers, a handful of containers, millions of containers, Right? But it necessitates a common management. Uh huh. Underlay that could be used to visualize where these containers are, what's running on them. And that's what AWS provides. You know, all the stuff they're doing Lambda and Eks and things like that that lends itself to that. So a customer can then go and almost create a container architecture that spans all their cloud's edges, even on Prem. Now, uh, when Amazon has but still be able to manage it and simplify it, I think somebody's trying to do it themselves. They're gonna find that the complexity almost becomes untenable. Unless you have a Nike organization the size of Amazon companies don't. So we're >>gonna here, we're gonna hear from Deepak singing in a few sessions. He did the eks anywhere. That's essentially kubernetes service on the data center. But look at what they did with eks anywhere and then CCS, which has a common control plane to your point, that's compelling. And so, you know, if you're a developer or you're an enterprise, you might not have If you want to go with this. I t world. We talked about earlier zeros before you came on on our last segment. Most I t is not that built out in terms of capabilities. So learning new stuff is hard, so operating Amazon might be foreign to most I t shops. This is a challenge. Did you agree with that? Or or how do you see that? >>Um, well, a lot of Amazon used, obviously just the interviews and numbers of fucked that right. Um, but I think the concept of in a world where you have that common operating layer that spans it's no longer geographically limited to a data center or to a server. You know, it's it's now distributed across your entire multi cloud or distributed cloud environment. And so one of the important things right people remember is the world is becoming more dynamic and or distributed, and your I t strategy has to follow that. If you're doing things that are counted that you're not only standing still, you're actually going backwards. And so what Amazon is doing is they're allowing companies to be is dynamic distributors. They need to be to be able to maintain that that common operating layer that actually makes it management, because without it, you just you wind up in a situation. Like I said, that's incredible. A lot of people facing that today. And that's why that's why there's this big divergence, right? This five native cos they're going fast and legacy companies that can. >>Guys, I want to spend the next 10 minutes we have getting into more of the business side from this keynote because because I know your research on digital transmission first. I know you know the networking side up and down the stack and all that good stuff, but you've been doing a lot of research around the digital transformation with the cloud. Dave, you just put out a great great breaking and else think your 55th, um, episode on digital transformation with the cloud. It's very clear that Jackie is basically preaching, saying, Hey, Clay Christensen is former professor who passed away. He brought up this whole innovator's dilemma kind of theme and saying, Hey, if you don't get the reality that you're in, you better wake up and smell the coffee. It's a wake up call. That's what he's basically saying That's my take away. This is really this business management lesson. Leadership thinking is super important, and I know we've We've talked about people process, technology. Uh, let's Covad eyes this real quick. Bottom line. What is the playbook? Do you agree with jazz? His point of view here? Um, he's pretty being hardcore. He's like, literally saying adapter die in his own way. What, you guys thoughts on this? This is a true forcing function. This cove, In reality, >>I mean I mean, if you talk about the business transformation, digital transformation, business transformation, you know, what does that mean? I, like, said earlier that the last 10 years about I t transformation, I think the next 10 is gonna be about business transformation, organizational industry transformation, and I think what that means is the entire operational stack is gonna get digitized. So your sales you're marketing your your customer support your logistics. You know you're gonna have one interface to the customer as opposed toe, you know, fragmented stovepipe siloed. You know, data sets all over the place, and that is a major change. And I think that's ultimately what a W. S is trying to affect with its model and has obviously big challenges in doing so. But But that, to me, is what digital transformation is ultimately all about. And I think you're going to see it unfold very rapidly over the next several >>years. What's your reaction? What's your view on on the on Jackie? >>And he talked about his eight steps toe reinvention. Um and e think what digital transformation to me is the willingness to re invent disruptive own business even in the face that it might look horrible for your business, right? But understanding he is there something that I think is true. And a lot of, um, business leaders don't fully by this that if something is good for your customer, they're going to do it, and you can either make it happen, or you gonna watch it happen and then have the market taken away from me because there's a lot of cases you look at how slow you know, A lot of the banks, you know, operated until you know, the a lot of these, uh, cloud native, uh, money exchange systems came around the cape. Alan Ben more and things like that, right? Even retailers Amazon completely disrupted that model. You could say that Amazon killed, you know, Toys R us, but 20 rescue Toys R Us E. And I think there's got to be this hard willingness to look at your business model and be willing to disrupt yourself. And what Kobe did, John, I think, is a taught us a lesson that you have to be prepared for anything because nobody saw this coming. And sure you can. And a lot of companies thrived out of this, and a lot of one's gone away, but that the ability to be agile has never been more important. But you're only is Angela's. Ike lets you be, and that's what that's what. The W. Is going to sell us the ability to do anything you want with your business. But the staff, you have to have the business because they're willing to do that. >>You know, that's a great point. That's so smart. It's crime that's worth calling out. And we were talking before we came on live about our business with the Cube. There's no virtual, there's no floor anymore. So we had to go virtual if we weren't in the cloud. If we weren't doing R and D and tinkering with some software and having our studio, we'd be out of business. Dave. Everyone knows it. Now Get the Cube virtual. We have some software were position, and this kind of speaks directly to what Andy Jassy said. He said. Quote. If you're not in the process of figuring out as a company, how you're going to reinvent your customer experience in your product and reinvent who you are, you are starting to unwind. You may not realize it, but you are. What he's saying is you better wake up and smell the coffee and I want to get your guys reacted. You, particularly you around your experience and research. I've noticed that some customers that had cloud going on did well with co vid and said ones that didn't are still struggling not to catch up. So you're kind of intense. You got some companies that were that were on the wave, Maybe kind of figuring it out, that we're in good position and some that were flat footed and are desperate. Um, seems to be a trend. Do you agree with that? And what's your view on this idea of being ready? What does that even mean to be? Have readiness or >>take, you don't get the data points that Andy threw up there, right? That 50% of the companies that were the global fortune $500.2000 or are no longer here, Right? That Zatz Pretty shocking statistic. And that does come, uh, you know, from the willingness to disrupt your business. And if you got you're right. The companies that had a good, solid class raging in place, we're able to adapt their business very quickly. You could you look at retailers. Some had a very strong online presence. They had online customer service set up those companies didn't find other ones, were really forced to try and figure out how to let people in the store had a mimic. You know, the in store experience, you know, through from, uh, you know, support interface or whatever. Those are the ones that really struggling. So you're right. I think companies that were on the offensive plug to Dover companies that were fully in the cloud really accelerated their business and ones that didn't buy into it. I think they're struggling to survive in a lot of They're gone. >>Yeah, and all that. John, When Jesus was talking about his view of digital transformation, I was just writing down some of the examples to your point. The folks that were sort of had were cloud ready, covert ready, if you will. And those that weren't But think about think about automobiles. You know, there's testily even a manufacturer of automobiles or they software company. Personal health has completely changed over the last nine months with remote. You know, uh, telehealth automated manufacturing. You think about digital cash, e commerce and retail is completely, you know, accelerated. Obviously toe online. Think about kids in college and kids in high school and remote learning farming. You know, we've done a great job in terms of mono crops and actually creating a lot of food. But now I think the next 10 years is gonna be how do we get more nutritious food to people and so virtually every industry is ripe for disruption, and the cloud is the underpinning of that disruption. >>Alright, guys, got a few more minutes left. I want to get your thoughts quickly on the keynote. What it means for the customers that we're watching again. This is not a sales and marketing conference as they talk about. But if you're sitting in the audience, you guys, we're watching and we're virtual um Did it hit home with you? If you're a customer, what did he what? Give us Give the grades. Where do you Where do you hit a home run? Where he missed. Did he leave anything out? What's your take Zia's? We'll start with you. >>Um, I thought it was actually really good Keynote. I thought you did a good job of making the case for AWS. They talked about the open. They have more instances than anybody. So you could do almost any kind of compute in their cloud. I think one of the important lessons variety to is the importance. You can't just do everything. The software right? Hardware Still important silicon still important that, and to meet the needs of very special he needs from things like machine learning and AI. Amazon's actually spending their own silicon very much like Athens doing with their computers. And so if you are going to be a customer service focused company, you need to think of the I T. Stack and everything from the silicon, the hardware through the software, and build that integrated experience to Amazon's giving a tools to do that Now E. Do I would like to see Amazon be a little more, um, a supposed the cloud competitive friendly. The one thing I hear from customers all the time is they love the Amazon tools. They love the optimization capabilities, but you know, if they are adopting some kind of multi cloud strategy, the Amazon tools don't work in Azure and the capital don't work in Amazon. The same with Google, and it would be well within the best interests of those three companies. They find a way to get together and allow their common framework to work across clouds. Amazon's already got a lead that they could do that, and I don't think it's gonna be, but that that is something I think that's still missing from this world is they make it very difficult for customers to move the multi cloud. >>Well, some would say some people are saying, saying that the number one in the cloud I mean, got cloud wars Bob Evans over there saying Microsoft is dominating number one position over everybody else, multiple quarters in a row Now he's looking at revenue and granted. You got a lot of propping up there you got. You know, Windows server and sequel. You got a bunch of professional services, But clearly the I as in past side of the market, Microsoft is, like, way behind um So, yeah, they've got the numbers little legacy in their Microsoft should, and they got a little base. If I'm Amazon, I'm not. I'm worried about Microsoft more than anybody. I think you know, I looking at the Civil War between the Seattle forces. I mean, this is really Microsoft's gotta greatest all base, and they could flip that license deals and >>the cloud is good enough. I mean, it's myself doing very, very well with its classic Microsoft. You know >>they your point. Microsoft is the king of good enough, right? They put out features. They market heavily to the I t pro on. They put out licensing packages, so you're almost foolish to not at least fry their products. And then they do roll it out. So it's good enough and then you live with it for a while. But ultimately, whenever people use Microsoft, they do have an alternative under in there for a very special case. But e don't wanna >>the king of good enough. That's a great line. I love that. I'm gonna use that. But this Babel fish thing for Aurora that is a huge dagger. Potentially, it's an escape valve for customers. They wanna leave Microsoft. But clearly, if Microsoft you're gonna get penalized by running your license on Amazon. >>If our CEO our i t c t, I'd say, Okay, I definitely want to do business with with Amazon. That's what I heard today from Jassy, and I would want to hedge my bets either with Microsoft, especially if I'm a Microsoft shop or with Google's from analytics heavy unquestionably. I'd want to hedge my bets and have some kind of 70 30 80 20 mix. >>Look, if you're Andy Jassy and he's told me my interview, do it directly. I asked this question. He was very forthright. He doesn't hide from the fact that, uh, customers have multiple clouds, but they have a primary and secondary, but they're not gonna have, like, five or six major clouds. Yeah, it's hard to get these teams trained at to begin with. So there's a hedge. There's a supplier leverage. I get that. He's totally gets that. But if you're Amazon, you're gonna have your annual conference. You really don't wanna be in the business of talking about the other guys cloud, you say hybrid, right? It's on my show. You know, like you're competing. This is there's definitely competition between Microsoft and A W s. So you gotta respect that. But yeah, of course. There's multiple clouds called hybrid eks everywhere. Uh, container service. I mean, >>especially global, right? Different cloud providers of different strengths in different regions. You know, Microsoft, very strong in the Gulf. AWS isn't you know. So if you're a global company, um, you know, then you almost by default, have to go multi cloud multiple cloud vendors because of geographic differences. Obviously, China, with its own set of cloud providers. So, you know, smaller midsize businesses could get away with one, but As soon as you become global, you have to use more. >>Well, I'm a big fan of distributed computing. I loved the large scale concept of distribute computing. You got regions. Now you've got local zones. You got I O t edge. You got cloud going on Prem Edge. It's really an edge game at this point. Greater now distributed hyper Put hyper next to anything hyper cloud on your sounds better Piper >>Cube. And the opportunities the cloud providers and Amazon, you know, certainly is leading. This is the ability to take this complex, hyper distributed world and use their management tools toe create a normalized operating simplify What would be an overly complex world about it? >>Okay, we got a break. Just quick plug. There's a big salesforce event coming up on December 10th. Check it out on the Amazon site that that plug in you watching the cube stay tuned for more coverage after this break

Published Date : Dec 2 2020

SUMMARY :

It's the Cube with digital coverage of AWS Great to see you A W s Kino. Let's be back in the cube. Great to see you guys. And I think if if you believe that machine learning artificial intelligence is changing, you know, PBX is in the old days. And I said, I like the fact that their AWS specifically is going after these solutions because several And the innovation to create a step If one of the things and you ask we talked about this, you know, was that the compute, And I think the At the edge, you have the zones for five G. You spin them up to 30 seconds, you spin them up for a couple of minutes that you And so, you know, if you're a developer or you're an enterprise, And so one of the important things right people remember is the world is becoming more dynamic and or I know you know the networking side up and down the stack and all that good stuff, I mean I mean, if you talk about the business transformation, digital transformation, What's your view on on the on Jackie? The W. Is going to sell us the ability to do anything you want with your business. You may not realize it, but you are. You know, the in store experience, you know, through from, uh, you know, you know, accelerated. Where do you Where do you hit a home run? And so if you are going to be a customer service focused company, you need to think of the I T. I think you know, I looking at the Civil War between the Seattle forces. I mean, it's myself doing very, very well with its classic Microsoft. So it's good enough and then you live with it for a while. the king of good enough. If our CEO our i t c t, I'd say, Okay, I definitely want to do business with But if you're Amazon, you're gonna have your annual conference. So, you know, smaller midsize businesses could get away with one, but As soon as you become global, I loved the large scale concept of distribute This is the ability to take this complex, hyper distributed world and use their management Check it out on the Amazon site that that plug in you watching the cube stay tuned for more coverage

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Simon Walsh, NTT | Upgrade 2020 The NTT-Research Summit


 

>>from around the globe. It's the Cube covering upgrade twenty twenty, The NTT Research Summit presented by NTT Research. >>Welcome back. I'm stupid a man. And this is the Cubes coverage of Upgrade twenty twenty. Of course, it's the NTT Research Summit and happy to welcome to the program someone that watch the Cube for a long time. But first time on the program. Simon Walsh. He is the new CEO of NTT America's Simon. Great to see you and thanks so much for joining us. >>Thanks very much. Too good to be here. All right. See, >>A Zai mentioned your your previous companies that you've worked for are ones that the Cube and Cube audience are well aware of. Matter of fact, when I worked for some of those companies, NTT is one of the large global companies that I had the pleasure to interact with over the years. But if you could maybe let's start with just a little bit of your background. And as I said, it's only been a few months that you've been the CEO, so you know, what's it like coming into a role like this? You know, during the situation that we're all faced with in twenty twenty. >>Yeah, Thank you. I mean, my background is really in, You know, the platforms that enable the customers Thio run their technologies. Andi, Uh, you know, I spent some of my time in Europe and the media on then latterly the last five plus years in the Americas. I have to say I really enjoy It's a much better environment. If I think about it from a GDP and an economy perspective, it's, ah really dynamic place to work. I worked with companies headquartered from Europe running America's, and I've worked with companies that were headquartered in the Americas, running some of the European businesses. So I've crossed the continent's if you like. I recently joined NTT. I have to say, you know, it was a pretty lengthy process to explore, but that was partly, you know, interviews and due diligence because you want to make sure that, you know, you're you're buying into a company that, you know, number one, you can have ah, cultural compatibility with, but also somebody who you see really investing in technology that consult for, you know, the business agenda of the markets. So that's really a bit about my background and then, you know, joining. I mean, I literally joined last week of June, so my whole time has bean through, locked down in terms of employment. It's been very unique. Taking on a new post, exclusively remote. Andi I was a bit worried, you know, at a human level, just, you know, how do you connect with people? What I would comment is I've actually had the ability to really meet ah, lot more people in person because you can physically get to people's schedules a lot easier. So that's certainly helped, you know. And I've done my, uh, activities of meeting clients. Eso they've been very amenable to connecting talking to our business partners and spending, you know, considerable amount of time with my colleagues, uh, in the Americas and around the world. Andi, it's actually been very rewarding. I think, funnily enough, you probably physically closer because you're on a screen and you probably like twenty four inches away from each other. Whereas in a meeting room you'd be the other side of the table. So it's been unique, but so far so good. >>Well, yeah, absolutely. The the new abnormal is we. We have sometimes say what? We're all usedto looking in the screens all day talking to various people there. Uh, the impact on business, though, has been, uh, you know, obviously ah, lot of different things, depending on the company. But that discussion of digital transformation a few years ago it was like, Oh, I don't know if it's really is it a buzzword? But that the spotlight that's been shown here in twenty twenty is what Israel and what is not leveraging cloud services, giving people agility, being able to react fast because, boy in twenty twenty if we needed to react fast, so help bring us inside a little bit. And your time there, the discussion you're having with customers, that adoption moving along that journey for digital transformation, the impact that you're seeing and house NTT helping its customers as they need to accelerate and respond toe the realities that we see today. >>Yeah, so you're right into I mean, digital disruption has been ongoing for multiple years. Way used to call it technology and change, and now we call it digital disruption or digital transformation. So it's not necessarily new. I think the thing that's really accelerated in twenty twenty, You know, as a consequence of the pandemic is really the word distributed, uh, in that customers are undertaking their digital transformations understanding. You know what it is to modernize processes, you know, modernize the customer experience on Then they're finding that actually, they don't need in a board room and discuss, you know, the performance of the business so they now need to have distributed access to data on. I think the topics that we see very prevalent is the distributed nature off the workforce. Andi. Obviously there's always been a filled workforce, and we've had systems, crm systems and other systems that were built for a distributed workforce. But now we have toe think about our supply chain management systems and our HR systems, the P and L. And you know all of the activities that business undertakes with an entirely distributed workforce, and it's quite abnormal. And I think what we've learned is where is the data on how doe I amalgamate data from distributed systems. And so I see. And we're doing a lot of work with our clients relating to digital transformation, but really about how doe I join data from system a two system F in a distributed manner, most importantly, securely timely on in A in an interface that is usable on it sounds really easy is like Oh, great, yeah, it's just two different data points. Connect them together, make it secure, make it visible, create transparency. But we all know that the world is full of technical debt, legacy systems and platforms Very expensive and significant historical investments on those things Don't modernize themselves overnight. Quite often. The dollars to modernize them don't justify themselves. So we then end up layering on, you know, new technology. So you know what I'm seeing on in digital transformation is really about. How do we handle distributed data Distributed decision making on how we do that in a secure manner on through an interface that is, uh, user friendly? >>Yeah, way. Obviously know that there's had to be some prioritization. You know, the joke. I've had everybody came into twenty twenty with Okay, here. Here's what I'm gonna do for the first half of the year. Here's the objectives that I have, and we kind of throw those in the shredder rather early on Number one priority. I still hear it was probably that the number one priority coming into the year and it stays there, and you've mentioned it multiple times. Its security, you know, is absolutely front and center Still. How overall, though, How are your customers? You know, the c X So sweet. How are they adjusting their priorities? Are there certain projects that just go on hold? Are there certain ones that get front and center? Obviously, you know, that distributed work from anywhere. Telemedicine, uh, you know, teach and learn from anywhere have been top of mind. But any other key learnings you're finding or prioritization changes, some of which are gonna probably stay with us. Uh, you know, for the long term, >>Absolutely. We've definitely seems Thio customers re prioritizing. And I think there is obviously an inevitability to this, a za consequence of the pandemic. I mean, if you were undertaking a campus upgrade, you might just put that on pause for the moment. And we've absolutely seen that. But what we've really seen is a prioritization has been How do we get our information to our users? Whether the user is a customer or whether the user is an employee, you know, there's examples where there's lots of companies who are saying they've got, like, online detail, right. But now they've got to do curbside pickup because they've actually got inventory in the stores. But the stores couldn't open. So what you've seen is a re prioritization to say, Well, when we look out inventory management and the supply chain systems, are we factoring in that the inventory we have in a store could also be seen as inventory across the stores? And in fact, what we've really got now is a distributed warehouse. We've got inventory in the warehouse like wholesale, ready for distribution on. Then we've got inventory in a store retail ready for consumer consumption. What? We don't want that to be separate Infantry. We want that to be holistic on. Then how do we enable any any consumer anywhere to be able to arrange for curbside pickup, which we didn't used to do because we would come into the store or arrange for mail order? But the inventory may come from, you know, I may send something from San Francisco to somebody in Boston because it was in a storied inventory in San Francisco. Now, sure, it's got it's got some freight cost, but I've also got some other efficiency savings, and I'm reducing my working capital in my inventory expense. So we've seen prioritization for really how to take advantage of this. I come back to it. This word distributed is very simple in principle, but everything is now working on a new dynamic. So that's some of the prioritization we've seen. >>Um, you mentioned one of the things that might get put on hold is wait. If I was doing a corporate network update, that might not be the first thing. You know, we we Absolutely. We've gotten some great data on just the changing traffic patterns of the Internet, but the network is so critically important, everybody from home is, you know, dealing with Children doing their zoom classrooms while we're trying to dio video meetings. Um, NTT obviously has a strong, uh, you know, network component to what? Its businesses help us understand the services that are important there. What? What? You're working with customers. And how has this kind of transformed, uh, some of those activities? >>Yeah, Yeah, sure. Thank you. You're so right. I mean, I have to say I just like thio, pay my respects to colleagues and fellow workers around the world who are not just working from home but also home schooling in parallel. Uh, kids are fled the nest, you know, they're working for themselves now, so we don't have the extra activity of home schooling. But I can really have a lot of respect her colleagues who are trying to do both. It's a real fine art on. We've seen a lot of actually just talking of re prioritization. We've seen a lot of companies, including ourselves. You know, say to our colleagues, Look after your Children home, school them do everything you can to support your families on, then get to your work So that re prioritization. Justin behavior has been a key change that we've seen a lot of people do that flexibility to. You know, work is something you do not somewhere you go on. Therefore, as long as the work is done, we can flex around. You know your needs is a family, so that's one prioritization we've seen at, actually. But to your point on the network, it is quite amusing to me that we've been for years now talking about cloud on demand subscription services on Actually, the one asset that you need to really enable cloud is the network and its historically been the least cloudlike that you could possibly imagine Because you still need to specify a physical connection. You still need to specify a band with value you still need to specify. You know, the number of devices you get too attached to it. I think this is really a monstrous change that we're going to experience and really are experiencing the network as a service. I mean, we talk about I as has SAS. But what happened toe now, as I mean really, did we just think that everything was about computing software? The network is the underpin er on DSO. Really? We see a big change and this is where we've been very busy in the network as a service enabling customers tohave dynamic reallocation of resources on the network so that they can prioritize traffic, prioritize content, prioritize events, you know, a lot of customers are now doing activities such as hosting their own event, their own digital conference on. Do you want to prioritize what the user experience is when you host one of those events over perhaps a back office process that, quite frankly, wait a few days so we see a significant opportunity. This is where we've been very busy the last few months in really building out much more dynamic network of the service solutions. You know, the Cloud Network. And I think the whole software defined network agenda has materially accelerated. That's one major area on then. The other area has just been the phenomenal ship to I p voice on soft bone, actually almost the deletion of the phone in its entirety. Everybody using you know, teams or Skype or Google hangouts to really use as their collaboration mechanism on. Then you know, we're providing all the underlying transportation layer. But as I p voice, you know, that creates a much more integrated collaboration. Experience on git creates a cost saving because you're taking away classic voice services. >>Yeah, Simon Boy, I'm excited for that. I I remember when I got my first BlackBerry and they were trying to sell me some things. I'm like, Wait, this is an Internet endpoint. I can do all of these things there and of course you know it's taking taking it. The last dozen years. If If Ghana certain far, but and we always joke, it's like smartphones. We don't use them for phones anymore. We use them for all the messaging and all those services. So, uh, the the data and the network are so critically important, something I want to turn Thio, you know, upgrade twenty twenty. You know what? I'm excited about this. You know, we've talked about, you know, the major impacts of what's happened in twenty twenty, and we're looking at the here and now. But it's great in technology when we get to be able to look forward and look at some of the opportunities out there. So we'd love to hear from your standpoint, some of the areas. What's exciting? You what's exciting? That we can look forward to some of the areas and pockets of research that we see at the event. >>Yeah. Thank you. Strewn E. I think what I like about Aravind is the investment that we make to work with, You know, scientific community, academia, really invest in, you know, forward looking future proofing, how physics and different technologies might play a role in the future. And, you know, some of these investments and some of this research yields commercial products, and some of it doesn't. But it's still a very valuable opportunity for us to really look at you know where technology is going. I think the areas that particularly appealing to me on a personal level, just the whole thing of quantum computing. This is, uh, you know, I know we're already exploring the capabilities of quantum computing in, you know, some labs and Cem academia centers on really to understand, how can we take advantage of that? But I think if you then say and you take another area that we're exploring through the event Biosciences, if you then take the two together and you think Okay, how do we take quantum computing on? We take Biosciences on you think about health care, and then you think about the pandemic. You know? Are there things that we can do with simulations and technologies in the future that really would give us a greater comprehension and ability to accelerate understanding, understand, accelerate testing, and then really contribute to, you know, the health and welfare of society. Andi, I think that's really quite an exciting area for us. So that's a specific topic that I'm particularly interested in. I'm glad to see us doing a lot in that space quantum computing as well as you know, Biosciences. And I'd say, you know, one other area where I still think we're all trying to ascertain how it serves the business is really the area of Blockchain. I think this is, um, intriguing. I'm still mentally trying to master the subject. No amount of white papers has managed Thio overcome the topic of my brain yet, So I'm still working on it on. Then I think cryptography, I come back to the same subject security. I mean, we are dependent as citizens, businesses and nations on technology. Now, on our data is available how we secure it, How we make sure that it's encrypted is absolutely going to be critical. You see an increasing push nationally on globally to ensure that there is, you know, security of data on. I think the subject of cryptography and how we go forward with, you know, beyond one hundred and twenty eight bit is gonna be a very difficult and critical subjects. So these are the areas I'm very impressed with. >>Wonderful. Simon, I wanna give you the final word from update. Great. Twenty twenty. >>Yeah, thanks to you. Just thanks very much, Thio. Anybody that's attending what you'll find through various workshops. There's lots of insight from our strategic partners from research scientists from academia from ourselves. So thank you very much for participating. You know, we always value your feedback. So please tell us what we could do to improve the content to help you with your businesses. Onda, We look forward and hope that everybody stays safe. Thank you for connecting with us virtually >>well. Simon Walsh, Thank you so much. Great. Having a conversation and glad to have you in our cube alumni now, >>thank you very much to have a good day. >>Alright, Stay tuned. More coverage from upgrade twenty twenty. I'm still minimum. And thanks. As always, for watching the cube. Yeah,

Published Date : Sep 29 2020

SUMMARY :

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Simon Walsh, NTT | Upgrade 2020 The NTT-Research Summit


 

>> From around the globe, its theCUBE, covering the UPGRADE 2020, the NTT Research Summit presented by NTT research. >> Welcome back. I'm Stu Miniman and this is theCUBE's coverage of UPGRADE 2020. Of course, it's the NTT Research Summit and happy to welcome to the program, someone that's watched theCUBE for a long time, but first time on the program, Simon Walsh, he is the new CEO of NTT Americas. Simon, great to see you, and thanks so much for joining us. >> Thanks very much Stu, good to be here, nice to see you. >> As I mentioned, your previous companies that you've worked for are that theCUBE and theCUBE audience are well aware of. As a matter of fact, when I worked for some of those companies, NTT is one of the large global companies that I had the pleasure to interact with over the years. But if you could, maybe, let's start with just a bit of your background. And as I said, it's only been a few months that you've been the CEO. So, what's it like coming into a role like this, during the the situation that we're all faced with in 2020? >> Yeah. Thank you. My background is really in the platforms that enable the customers to run their technologies. And, I've spent some of my time in Europe and India and then lastly the last five plus years in the Americas, I have to say, I really enjoy it. It's a much better environment. And if I think about it from a GDP and an economy perspective, it's a really dynamic place to work. I've worked with companies, headquartered from Europe, running in Americas. And I've worked with companies that were headquartered in the Americas, running some of the European businesses. So, I've crossed the continents if you like. And I recently joined NTT and I have to say, it was a pretty lengthy process to explore, but that was partly, interviews and due diligence. Cause you want to make sure that, you're buying into a company that, number one, you can have a cultural compatibility with, but also somebody who you see really investing in technology that consult for the business agenda of the markets. So, that's really a bit about my background and then joining. I mean, I literally joined the last week of June, so, my whole time has been through lockdown in terms of employment. It's been very unique taking on a new post, exclusively remote, and I was a bit worried, at a human level, just, how do you connect with people? But what I would comment is I've actually had the ability to really meet a lot more people in person cause you can physically get to people's schedules a lot easier. So, that's certainly helped. And I've done my activities of meeting up clients. So, they've been very amenable to connecting, talking to our business partners and spending considerable amount of time with my colleagues in the Americas and around the world. And it's actually been very rewarding. I think, funnily enough, you probably physically closer because you're on a screen, and you're probably like 24 inches away from each other. Whereas in a meeting room you'd be the other side of a table. So, it's been unique, but so far so good. >> Oh yeah, absolutely. The new abnormal, as we've sometimes say we're all used to looking in the screens all day, talking to various people there. The impact on business though has been, obviously a lot of different things depending on the company, but that discussion of digital transformation a few years ago, it was like, "Oh, I don't know if it's real, is it a buzz word?" But that the spotlight that's been shown here in 2020 is what is real and what is not? Leveraging cloud services, giving people agility, being able to react fast because buoyant 2020th, we needed to react fast. So, help bring us inside a bit, and your time there, the discussions you're having with customers that adoption, moving along that journey for digital transformation, the impact that you're seeing and how's NTT helping its customers as they need to accelerate and respond to the realities that we see today. >> Yeah. So you're right Stu. I mean, digital disruption has been on varying for multiple years and we used to call it, technology and change and now we call it digital disruption or digital transformation. So, it's not necessarily new. I think the thing that's really accelerated in 2020, as a consequence of the pandemic is really the word distributed in that customers are undertaking their digital transformations, understanding what it is to modernize processes, modernize the customer experience. And then they're finding that actually they don't meet in a boardroom and discuss, the performance of the business. So, they now need to have distributed access to data. And I think that the topics that we see very prevalent is the distributed nature of the workforce. And obviously there's always been a field workforce and we've had systems. CRM systems and other systems that were built for a distributed workforce. But now we have to think about how supply chain management systems and our HR systems, the PNL, and, all of the activities that our business undertakes with an entirely distributed workforce. And it's quite abnormal. What I think what we've learned is where is the data and how do I amalgamate data from distributed systems? And so I see, we're doing a lot of work with our clients relating to digital transformation, but really about how do I join data from system A to System F in a distributed manner? And most importantly, securely, timely and in an interface that is usable. And it sounds really easy. It's like, Oh great. Yeah, it's just two different data points, connect them together, make it secure, make it visible, create transparency. But we all know that the world is full of technical debt, legacy systems and platforms, very expensive and significant historical investments. And those things don't modernize themselves overnight. And quite often the dollars to modernize them don't justify themselves. So, we then end up layering on new technology. So, what I'm seeing in digital transformation is really about how do we handle distributed data, distributed decision making, and how do we do that in a secure manner and through an interface that is user friendly. >> Yeah, we obviously know that there's had to be some prioritization. The joke I've had, everybody came into 2020 with, "Okay, here's what I'm going to do for the first half of the year. Here's the objectives that I have." And we kind of throw those in the shredder rather early on. Number one priority I still hear it was probably that the number one priority coming into the year and it stays there and you've mentioned it multiple times, it's security, it is absolutely front and center still. How overall though, how are your customers, the CXO suite, how are they adjusting their priorities? Are there certain projects that just go on hold? Are there certain ones that get front and center, obviously, you know, that distributed work from anywhere telemedicine, teach and learn from anywhere, have been top of mind. But any other key learnings you're finding or prioritization changes, some of which are going to probably stay with us, for the longterm. >> Absolutely. We've definitely seen customers reprioritizing. And I think there is obviously an inevitability to this as a consequence of the pandemic. I mean, if you were undertaking a campus upgrade, you might just put that on pause for the moment. And we've absolutely seen that. But what we've really seen as a prioritization has been, how do we get our information to our users, whether the user is a customer or whether the user is an employee? There's examples where there's lots of companies who say they've got like online e-tail, right? But now they've got to do curbside pickup because they've actually got inventory in the stores, but the stores couldn't open. So, what you've seen is a re-prioritization to say, well when we look at inventory management and the supply chain systems, are we factoring in the inventory we have in a store could also be seen as inventory across the stores? And in fact, what we've really got now is a distributed warehouse. We've got inventory in the warehouse like wholesale ready for distribution. And then we've got inventory in a store, retail ready for consumer consumption. What don't want that to be separate inventory. We want that to be holistic. And then how do we enable any consumer anywhere to be able to arrange for curbside pickup, which we didn't use to do because we would come into the store or arrange for mail order. But the inventory may come from you know, I may send something from San Francisco to somebody in Boston because it was in a store inventory in San Francisco. Now, sure, it's got some freight cost, but I've also got some other efficiency savings and I'm reducing my working capital or my inventory expense. So, we've seen prioritization for really how to take advantage of this. I come back to it, this word distributed is very simple in principal, but everything is now working on a new dynamic. So, that's some of the prioritization we've seen. >> You mentioned one of the things that might get put on hold is, wait if I was doing a corporate network update, that might not be the first thing, we absolutely, we've gotten some great data on just the changing traffic patterns of the internet, but the network is so critically important. Everybody from home is dealing with, you know, children doing their Zoom classrooms while we're trying to do video meetings. NTT obviously has a strong network component to what its business is. So, help us understand the services that are important there, what you're working with customers and how has this kind of transformed some of those activities? >> Yeah. Yeah, sure. Thank you. You're so right. I mean and I have to say, I just like to pay my respects to colleagues and fellow workers around the world who are not just working from home, but also homeschooling in parallel. Our kids fled the nest, either they're working for themselves now, so, we don't have the extra activity of homeschooling, but I can really have a lot of respect for colleagues who are trying to do both, it's a real fine art. And we've seen a lot of actually just talking of re-prioritization. We've seen a lot of companies including ourselves, say to our colleagues, look after your children, homeschool them, do everything you can to support your families and then get to your work. So, that re-prioritization just in behavior has been a key change that we've seen a lot of people do. That flexibility to, you know, work is something you do, not somewhere you go. And therefore, as long as the work is done, we can flex around, you know your needs as a family. So, that's one prioritization we've seen active actually. But to your point on the network, it's quite amusing to me that we've been for years now talking about cloud, on-demand subscription services. And actually the one asset that you need to really enable cloud is the network. And it's historically been the least cloud-like that you could possibly imagine because you still need to specify a physical connection. You still need to specify a bandwidth value. You still need to specify, the number of devices you've got to attach to it. I think this is really a monstrous change that we're going to experience and really are experiencing, the network as a service. I mean, we talk about IAS, PAS SAS, but what happened to NAS? I mean, really did we just think that everything was about computer and software? The networker is the underpinner. And so really we see a big change and this is where we've been very busy in the network as a service enabling customers to have, dynamic reallocation of resources on the network so that they can prioritize traffic, prioritize content, prioritize events. A lot of customers and are doing activities such as hosting their own event, their own digital conference. And you want to prioritize what the user experience is when you host one of those events over perhaps back office process that can quite frankly wait a few days. So, we see a significant opportunity. This is where we've been very busy the last few months in really building out much more dynamic network as a service solutions, the cloud network. And I think the whole software defined network agenda has materially accelerated. That's one major area. And then the other area has just been the phenomenal shift to IP voice and software and actually almost the deletion of the phone in its entirety. Everybody using, Teams or Skype or Google Hangouts to really use as their collaboration mechanism. And then, we're providing all the underlying transportation layer, but as IP voices, that creates a much more integrated collaboration experience, and it creates a cost saving cause you're taking away the classic voice services. >> Yeah. So Simon boy, I'm excited for that. I tell you, I remember when I got my first Blackberry and they were trying to sell me some things, I'm like, "Wait, this is an internet endpoint. I can do all of these things there." And of course, you know, it's taken me the last dozen years. If gone a certain far, but, and we always joke. It's like smartphones, we don't use them for phones anymore. We use them for all the messaging and all those services. So, the data and the network are so critically important. Simon, I want to turn to UPGRADE 2020, you know what I'm excited about this, we've talked about the major impacts of what's happened in 2020. And we're looking at the here and now, but it's great in technology when we get to be able to look forward and look at some of the opportunities out there. So, would love to hear from your standpoint, some of the areas, what's exciting you, what's exciting that we can look forward to some of the areas and pockets of research that we see at the event. >> Yeah, I think he's Stu. I think what I like about our event is the investment that we make to work with the scientific community, academia, and really invest in, forward-looking, future-proofing, how physics and different technologies might play a role in the future. And, some of these investments and some of this research yields, commercial products and some of it doesn't, but it's still a very valuable opportunity for us to really look at where technology is going. I think the areas that are particularly appealing to me on a personal level, just the whole thing of Quantum computing. This is, I know we're already exploring the capabilities of Quantum computing in some labs, and some academia centers and really to understanding how can we take advantage of that. But I think if you then say, and you take another area that we're exploring through the event, Biosciences. If you then take the two together and you think, okay, how do we take Quantum computing, and we take Biosciences and you think about healthcare, and then you think about the pandemic, are there things that we can do with simulations and technologies in the future that really would give us greater comprehension and ability to accelerate, understanding, accelerate testing, and then really contribute to the health and welfare of society. And I think that's really quite an exciting area for us. So, that's a specific topic that I'm particularly interested in. I'm glad to see us doing a lot in that space, Quantum computing, as well as the Biosciences. And I'd say one other area where I still think we're all trying to ascertain, how it serves the business is really the area of blockchain. I think this is intriguing. I'm still mentally trying to master the subject. No amount of white papers has managed to overcome the topic in my brain yet. So I'm still working on it. And then I think cryptography, I come back to the same subject security. I mean, we are dependent as citizens, businesses and nations on technology now, and our data is available how we secure it, how we make sure that it's encrypted is absolutely going to be critical. You see an increasing push nationally and globally to ensure that there is security of data. And I think the subject of cryptography, and how we go forward with, beyond 128 bit is going to be a very difficult and critical subject. So these are the areas I'm very impressed with. >> Wonderful. Simon, I want to give you the final word from UPGRADE 2020. >> Yeah. Thanks, Stu Just thanks very much to anybody that's attending. What you'll find through various workshops is lots of insight, from our strategic partners, from research scientists, from academia, from ourselves. So thank you very much for participating. We always value your feedback. So, please tell us what we could do to improve the content, to help you with your businesses. And we look forward and hope that everybody stays safe. Thank you for connecting with us virtually. >> Well, Simon Walsh. Thank you so much. Great having a conversation and glad to have you in our Cube alumni now. >> Thank you very much Stu. Have a good day. >> All right. And stay tuned more coverage from UPGRADE 2020 I'm Stu Miniman, and thanks as always for watching theCUBE. (upbeat music)

Published Date : Sep 25 2020

SUMMARY :

the NTT Research Summit and happy to welcome to the to be here, nice to see you. the pleasure to interact that enable the customers But that the spotlight that's And quite often the that there's had to be some But the inventory may come from you know, that might not be the first thing, the phenomenal shift to So, the data and the network and technologies in the future Simon, I want to give you the to help you with your businesses. and glad to have you Thank you very much I'm Stu Miniman, and thanks as

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Wei Li, Children’s National Research Institute | AWS Public Sector Online


 

>>from around the globe. It's the queue with digital coverage of AWS Public sector online brought to you by Amazon Web services. Welcome back. I'm stew minimum. And this is the Cube coverage of Amazon Web service Public sectors, online summit Always love. We have phenomenal practitioner discussion. Of course, public sector includes both government agencies, universities, education, broad swath, you know, inside that ecosystem and some really, you know, important and timely discussion we're having. Of course, with the global pandemic Kobe 19 happening. I'm really happy to welcome to the program Wei Li, who is a PhD and principal investigator as well as an assistant professor both Children National Research Institute associated with George Washington University way Thank you so much for joining us. >>Yeah. Thank you for the opportunity. We're here. >>Alright. Why don't we start with Ah, give us a little bit of you know, your research focus in general. And you know what projects it is that you're working on these days? Yeah, >>sure. So, yeah, so hello, everyone. So our laboratory is many interested in using computational biology and jim editing approaches to understand human genome and human disease. And we're particularly interesting in one gene editing technology will be called CRISPR screening. So this is a fascinating, high for proven technology because it tells you whether one doctor 20,000 human genes are connected with some certain pieces fit in type in one single experiment. So in the possibly developed some of the widely used every reasons to analyze the swimming data has been downloaded off by over 60,000 times. So it's really popular, and right now there are a couple of going projects. But basically we are trying to, for example, problem in machine learning and data mining approaches to find new clues of human disease from the original mix and screening big data on. We also collaborated with a lot of blacks around the world and to use this technology to use this technology to find new cures and drugs for cancer and other decisions. So this is the basic all the way off our current research programmes. Interns off the Conradi 19 research. I think one of the major projects we are having is that, um, we noticed that Christmas winning and other similar screening methods has been widely used in many years. Many research adapted to study waters infection. So in the past 10 years we have seen people you are using their Christmas screening and our AI suite, for example, to study HIV is a car wires, best bars, Western ire virus, Ebola influencers and also coronavirus. So that raises an interesting question from us if we collect all the screening data together. But these viruses, what a new information can we find that we cannot identify for the single study, for example, coe and identify new patterns or new human genes that are that are common in responsible for many different viruses? Type of all, we can find some genes that I work only for some certain people viruses so more well, we know that there are a lot of drugs that target different genes, and we are particularly interested in, for example, can repurpose some of these drugs to treat different hyper viruses, including Kobe, 18 19. So that's the one of the major profits off ongoing research, right and left ready to call the idea, writing So India. And we hope that we can find some new new Jim functions that after that that are broader, really essential for different hyper viruses. I also new drug targets that can potentially treat existing a new drug existing and new viruses, including compared to 19 >>Yeah, crisper. Shown a lot of promise is definitely a lot of excitement in the research community to be ableto work on this. You talked a little bit about, you know, big data, obviously a lot of computational power required to do some of the things you're talking about. Can you speak a little bit to the partnership between computer science and the medicine? How do you make sure on that? You know, there's that marrying of, you know, the people in the technology focus in the medical space. >>Yeah, so I think, Yeah, my my research background is actually from computer science. I call her on the grand graduates from their committed size. So I know a lot about some of the signs and have arisen. But right now it's quite interesting because our research for focus half on computer science and half on their medicine. So it's a complete heart experience, but it's really super was a super exciting to connect both women in science and medicine together. So I think most of the time we are focusing on the coding and the average analysis on. But at the same time, we also spent a lot of time like interpreting the results. In essence, we need a lot off. Yeah, knowledge from biology and medicine to make sense, to make our results since and interpret double in the end, we hope that our results can be They went into a son, for example, canonical, actionable solutions, including new drugs. >>Yeah, it's if you think about you know, the research space. You know, often you know its projects that you're taking months or years to investigate things for talking about the current code 19 pandemic. Of course, there's a critical need today for fast moving activities. So you know what? What are the outcomes from the cover? 19 aspects of of what you're working on. What are some of the outcomes that we might be able to help patients survivability and other things regarding, You know, this specific disease? >>Yeah, So I think there are two major are I would say there are two major benefits from their outcome of our research project. So the first the first thing is that we hope to find some genes that have that can be potentially drug targets. So if they are existing drug second heavily genes, then that would be perfect because we don't need to do anything. Apologies. We just need to try that. Extend existing drugs Toe cabinet is James and in the end, we hope that these drugs can have the broad on the wire. I would say the broad answer. Borrow activity. That means that and you leave, for example, if these drugs can be potentially used to treat Cooley 19 and sometimes in in several years later in the future if there's a new virus coming out. Hopefully they were doing like they're it's already the drugs that target known Gene. Hopefully, that's there were assume the noon numerous that never happened in something the future. But I hope that when the new risk is coming, we already have the new drugs to track it this way. Already have existing drugs to target these viruses, so that's one part and the alibis that way. We have, like, spend a lot of kind of, for example, collecting the genomics and screening data, and we are hoping that our research results can be freely accessible around the road by many different researchers in different laps. So that's why we are rely on AWS to build up there to process and to analyze the data as well as to, uh, to build up an integrated database and websites such that are the outcomes off our projects can be freely accessible around the world. Many other researchers. >>Yeah, great. I'm glad you connected the dots for us. For aws can you speak a little bit too? Obviously, Cloud has, you know, the ability for us to use, you know, nearly infinite computational capabilities. What's specific about AWS helps you along that project. Uh, let's start there. >>Yeah, So I think our AWS really helps us a lot because we developed on average and process their screening data actually takes, like, two or three days to Christmas one data. But if you were talking about, like, tens or hundreds or even thousands off the screen data existing, the high high performance cross team doesn't really help because it takes maybe years to finish. AWS provides, like flexible computing resources, especially the easy two instance that we can quickly deploy and process in military short amount of time. So our estimation is that we can reduce the amount of Time Media 2% to process the poverty Christmas. We need data from months to just a few days. So that's one part and the other guys that we are trying to build up the website and database, as I mentioned before, with which we host a large amount of data. And I think in that sense, AWS and the commuting instance as well as the AWS RDS service really helped us a lot because we don't need to worry too much about. There's a lot of the details of the after deployment off their database and the website. We just go ahead and use that as a service is really straightforward and save us a lot of kind of effort. >>Yeah, and you talk about the sharing of data. Information is so important, But of course it would, talking about medical data highly regulated. So you know what's important to the cloud to make sure that you can share with all the other researchers yet still make sure that there is the security and compliance that is required? >>Yeah, so yeah, that's a really good question. So right now, we don't really need to do if the patient information because all the data we get this from the public domain, it's It's both on the human sound lines, not on human patients. So we don't have their concerns about the privacy protections at this moment. But I think in the future, if you want to integrate genomics state our reach, this screen indeed A, which is already in my research plan. I think the highly secure AWS system actually really provided a really nice for us to do this job. >>Can you give us a little bit? Look forward as to where do you see this research going? What applicability is there before? What you're doing now? Both. You know, as this current pandemic plays out as well as applicability beyond Corp in 19. >>Yeah, sure, I think I think one of their major focus off our current, The company in 19 project is that we hope to find some drug targets tohave the broader under fire activity. So I think in the future, if they knew where it's coming out of the estimated locally in the 19 we hope that we are well prepared for that. I think in the future they're sharing as well as collateral cloud computing. You'll be becoming more and more important as you can see that most of us are working from home right now. So it's really critical to require us to have the platform toe accelerate accelerating sharing between research labs and around the world. And I think many different. I think aws provides this really nice preference for us to do this job well. >>Wei Li, thank you so much for sharing with our audience your updates, really important work. We wish your team the best of luck and hope that you also stay safe. >>Yeah, thank you so much. >>Alright, Stay with us for more coverage from AWS Public sector Summit online. I'm stew Minimum And thanks as always for watching the Cube >>Yeah, yeah, yeah, yeah, yeah

Published Date : Jun 30 2020

SUMMARY :

AWS Public sector online brought to you by Amazon Why don't we start with Ah, give us a little bit of you know, your research focus So in the past 10 years we have seen people you are using Shown a lot of promise is definitely a lot of excitement in the research community of the time we are focusing on the coding and the average analysis What are some of the outcomes that we might be able to So the first the first thing is that we hope to find some genes that Obviously, Cloud has, you know, the ability for us to use, So that's one part and the other guys that we are trying to build up the website and database, So you know what's important to the cloud to make sure that you can share with all the other researchers do if the patient information because all the data we get this from the public domain, Look forward as to where do you see this research going? The company in 19 project is that we hope to find some drug targets Wei Li, thank you so much for sharing with our audience your updates, Alright, Stay with us for more coverage from AWS Public sector Summit online.

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Nancy McGuire Choi, Polaris | PagerDuty Summit 2019


 

>>From San Francisco. It's the cube covering PagerDuty summit 2019 brought to you by PagerDuty. >>Hey, welcome back everybody. Jeff, Rick here with the cube. We're in downtown San Francisco at PagerDuty summit, the fourth year, the show third year. The cube being here. I think they finally outgrown the Western st Francis. We've got to have a better, a bigger venue but we're really excited to have our next guest doing super, super important work. We learned about this company a couple of weeks back at AWS. Imagine non profit, the Polaris company and we are happy to have Nancy Maguire. She's the CEO. >>Oh Nancy, great to see you Jeff. It's fantastic to be here. Thanks so much for having me and it's great to be back at the PagerDuty summit a second year in a row. Last year I was here last year. I'm on the big stage, is it? I've grown the venue. Are we ready to move to a larger, possibly a larger venue next year? They're doing incredible work. So really a really fortunate to interview Brad a couple of weeks ago. So for people that didn't see that, don't know players. Give us kind of the overview about what you guys are up to. What's your mission? Absolutely. So Polaris is an organization dedicated to ending human trafficking and restoring freedom to survivors. So for those that may not know what we're talking about when we talk about human trafficking is three main categories. Anybody who is forced to work against their will by means of force, fraud or coercion. >>Any adult in the commercial sex trade by means of force, fraud or coercion, and any minor, anyone 17 or younger in the commercial sex trade. And the way we think about this issue is in two halves that are complimentary. One is on the response side, we've got 25 million people around the world who fit that definition that I just described. And so it's about individual case management and helping to get them out of those situations. The way Polaris works on the response side of the issue is by operating to U S national human trafficking hotline. This is the nerve center for the anti-trafficking movement in the United States where we work 24 seven to connect to victims and survivors to the services they need to get help, stay safe, and began to rebuild their lives. So that's half of the story. The other half of the story is we recognize that the response side, while absolutely invaluable, doesn't get at solutions to the problems. >>So we work on longer term solutions to the issue of human trafficking. And the way we do that is through data and technology. So we haven't asked one of the largest data sets on human trafficking in the U S and we've mined that data for insight about how trafficking works. So we've learned there are 25 distinct types in the U S alone. We've then dug deeper to understand what are the legitimate businesses and industries that traffickers are using for their crimes. And those include social media, hotels, motels, transportation, financial services among others. And then we take those insights. We work with private sector companies, public sector, and law enforcement to get to upstream strategies to prevent and disrupt this issue at scale. So, unfortunately we don't have three days to dig through the that good list. But let's, let's unpack some of it cause it's super, super important on the, uh, on the data side, cause we're here at PG. >>So what are the types of data that you guys are looking at? The buildings mall and it was fascinating, Brad's conversation about the multiple kind of business models that you guys have have defined as was, was it lightning for sure. So what types of data are you looking at? Where are you getting the data? What are you doing with it? Yeah, absolutely. So I think the first thing to know is that this is a clandestine issue. And for so long the field has been data poor and it's been really hard to unpack what we mean by sex trafficking and labor trafficking to wrap our arms around the problem. And so we've had these really significant breakthroughs just in the last few years with a, by understanding that there are these 25 types. And that was through mining over 35,000 cases that we worked on on the national hotline over the years. >>And that our second major research initiative was to augment that with surveys and focus groups with survivors. So those with lived experience have now informed the data set and some examples of what we've learned, how our traffickers using hotels and motels for their operations, how do they use credit cards, how do they use buses and planes and trains and rideshares and how are victims recruited on social media. And conversely, how can they reach out for help, including through our hotline. Um, and so we're starting to really get granular about the nature of this problem. And then where are those key intersection points? Where do we have leverage? And a big part of the answer is, is the private sector, right? Right. So, uh, you know, the kind of the intersection from the clandestine in the dark and secret, you know, to, to the public, as you said, were things like credit cards or they need to get on planes. >>So they need hotels. It's a pretty interesting way to address the problem because there are these little, little, little points where they pop up into the light. Absolutely. So when you're doing that in your building, the longer term strategy one, it's to get the other, the people out of there. But are you trying to change the business models? I mean, how, what are some of these kind of longer term reservoirs? Absolutely. So right now the equation that traffickers perceive is this is the financial crime, right? It's not just a human rights abuse, right? Right. The equation they perceive is that this is high profit, low risk. We've flipped that equation. For instance, when financial institutions are tuned into, I have the built in red flag indicators for all the different types of trafficking that they might see. So it makes it simply too difficult for, or too risky for traffickers to bank and move their money. >>So that's one example. Another is in the realm of social media. So we've understood how traffickers are exploiting victims on social media. It can look like anything from grooming and recruitment on in sex trafficking to um, fake, uh, job ads on social media as well. So as we can help to inform social media companies, again working in tandem with victims and survivors to put those lived experiences into and leverage those insights into solutions, we can make change that equation for traffickers to it is simply too difficult and too risky to recruit online and push them to sort of more old school systems of recruitment that those are the sorts of upstream things that we believe are really going to change. Change the game, right? So it's recruiting, it's taking their money away, it's making it expensive for them to operate a lot of those types of, exactly. >>And the real focus is on these six systems and industries that we've identified. And tech is really a crucial, obviously social media companies, hotels, motels, transportation. Um, and for instance, one of the, one of our partners is Delta airlines and so they have been, I think one of the exemplars and really looking at this issue holistically and being all in from the CEO on down and leveraging again, why we think the private sector is so crucial is they've got the resources, the customer base, the engaged employees. Um, they've got the brand. And so for instance, what Delta does is they've trained all 60 plus thousand employees on how to, how to spot and detect human trafficking and what to do. They engage their customer base through PSA is and people can donate miles including that ended up, um, helping victims and survivors on our hotline to get flights to get out of their situations, um, and resources to, to support the hotline to scale. >>Um, and so it really takes that, we think the private sector is a huge piece of, of the puzzle and sort of bringing it back to the tech industry. The tech industry is uniquely position again with the tools, the resources that know how to actually supercharge this movement because it's going to be data in technology that's going to get us to scale. Right? Yeah. The, the Delta story is amazing. If for people that haven't seen it, um, you know, the CEO got completely behind this, basically train the entire company and other passengers to look for these anomalies. And, and what came up, some of the conversations in Seattle is it's really not that hard because you've got your business travelers and you got your families and you got these things that don't really fit. And that's, I don't know what percentage of the total flights, but it's a lot. >>So these things, if you're paying attention, it should be a lot easier to identify. So PagerDuty specifically, what are you guys doing with PagerDuty? Absolutely. Polaris and the broader anti-trafficking movement is engaged in a digital transformation. And so for us, that's on the response side, both on our hotline and on our data side so we can supercharge that learning and insight development. PagerDuty is central to our ability to, um, increase our efficiency on the hotline. It's, it's uh, uh, the hotline itself is composed of a number of different technologies. We cannot have any of those technologies go down because minutes and seconds matter on a crisis hotline. So PagerDuty helps us be as efficient as we can be in escalating urgent issues so they can immediately begin being worked on by our technical team. We don't lose those seconds and minutes and hours, um, as in sort of the, the old school model. >>So it's, it's part of our broader strategy and we've already been able to identify significant efficiency gains as a result when, when it's a response situation that someone's, someone got the number, they've got it, they got an opportunity to try to get out. What's the total time? Usually between they pick, picking up the phone and you giving them some action, which I don't know what the action is, runaway or somebody coming to get you or you know, it really depends on the situation. Um, of course if we're talking about a minor or a situation with imminent harm, um, but we can be talking about something, you know, an extraction or somebody getting to help within a matter of minutes. In other instances, safety planning at the victim and survivors wishes takes place over a period of calls over a period of contact. Sometimes it takes, it can take months or years to work up the courage to get to that point. >>So we do have ongoing communications with victims and survivors over time to support them, uh, to, to leave when they're, when they're ready. Right. Well, Nancy, it's such, it's such important, important work, not necessarily the most positive thing, but I'm sure there's a lot of great positive stories when you're helping these, these people get out of these crazy stories. Well, absolutely. And I think, you know, there was so much reason to be optimistic. This is a really unique moment in time and it's part of why I joined Polaris and joined this anti-trafficking movement is we're seeing, we're seeing unprecedented engagement from the private sector that I mentioned I think is absolutely critical to solving this issue when we've had real breakthroughs with the data so that we can get so much more granular and understanding how it works. So there's now really, as the time, I mean as, as as Jennifer said, she talking about digital transformation this morning, being a team sport, we think the anti-trafficking movement needs to be a team sport, right? >>We want to draw that circle a much bigger stick. Who's in that? Then we invite private sector technology companies and all of you out there to join us. Good. Well, hopefully we're helping get the word out and um, and again, you know, thank you for, for, for what you're doing. It's super important and it's much more pervasive and broad than, than I had ever imagined, perhaps some of these conversations. So thanks a lot. Thank you so much. All right. She's Nancy. I'm Jeff. You're watching the cube. We're a PagerDuty summit in downtown San Francisco. Thanks for watching. We'll see you next time.

Published Date : Sep 24 2019

SUMMARY :

summit 2019 brought to you by PagerDuty. the Polaris company and we are happy to have Nancy Maguire. So Polaris is an organization dedicated to ending human And the way we think about this And the way we do that is through And for so long the field has been data poor and it's been really hard clandestine in the dark and secret, you know, to, to the public, as you said, were things like credit cards So right now the equation that traffickers perceive is this is the So as we can help to inform social media companies, again working in tandem with victims And the real focus is on these six systems and industries that we've identified. of the puzzle and sort of bringing it back to the tech industry. So PagerDuty helps us be as efficient as we can be in escalating urgent issues someone got the number, they've got it, they got an opportunity to try to get out. engagement from the private sector that I mentioned I think is absolutely critical to solving this issue when we've had real hopefully we're helping get the word out and um, and again, you know, thank you for,

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Lenovo Transform 2.0 Keynote | Lenovo Transform 2018


 

(electronic dance music) (Intel Jingle) (ethereal electronic dance music) ♪ Okay ♪ (upbeat techno dance music) ♪ Oh oh oh oh ♪ ♪ Oh oh oh oh ♪ ♪ Oh oh oh oh oh ♪ ♪ Oh oh oh oh ♪ ♪ Oh oh oh oh oh ♪ ♪ Take it back take it back ♪ ♪ Take it back ♪ ♪ Take it back take it back ♪ ♪ Take it back ♪ ♪ Take it back take it back ♪ ♪ Yeah everybody get loose yeah ♪ ♪ Yeah ♪ ♪ Ye-yeah yeah ♪ ♪ Yeah yeah ♪ ♪ Everybody everybody yeah ♪ ♪ Whoo whoo ♪ ♪ Whoo whoo ♪ ♪ Whoo yeah ♪ ♪ Everybody get loose whoo ♪ ♪ Whoo ♪ ♪ Whoo ♪ ♪ Whoo ♪ >> As a courtesy to the presenters and those around you, please silence all mobile devices, thank you. (electronic dance music) ♪ Everybody get loose ♪ ♪ Whoo ♪ ♪ Whoo ♪ ♪ Whoo ♪ ♪ Whoo ♪ ♪ Whoo ♪ ♪ Whoo ♪ ♪ Whoo ♪ ♪ Whoo ♪ (upbeat salsa music) ♪ Ha ha ha ♪ ♪ Ah ♪ ♪ Ha ha ha ♪ ♪ So happy ♪ ♪ Whoo whoo ♪ (female singer scatting) >> Ladies and gentlemen, please take your seats. Our program will begin momentarily. ♪ Hey ♪ (female singer scatting) (male singer scatting) ♪ Hey ♪ ♪ Whoo ♪ (female singer scatting) (electronic dance music) ♪ All hands are in don't go ♪ ♪ Red all hands are in don't go ♪ ♪ Red red red red ♪ ♪ All hands are in don't go ♪ ♪ Red all hands are in don't go ♪ ♪ Red red red red ♪ ♪ All hands are in don't go ♪ ♪ Red all hands are in don't go ♪ ♪ All hands are in don't go ♪ ♪ Red all hands are in don't go ♪ ♪ Red red red red ♪ ♪ Red don't go ♪ ♪ All hands are in don't go ♪ ♪ In don't go ♪ ♪ Oh red go ♪ ♪ All hands are in don't go ♪ ♪ Red all hands are in don't go ♪ ♪ All hands are in don't go ♪ ♪ Red all hands are in don't go ♪ ♪ Red red red red ♪ ♪ All hands are red don't go ♪ ♪ All hands are in red red red red ♪ ♪ All hands are in don't go ♪ ♪ All hands are in red go ♪ >> Ladies and gentlemen, there are available seats. Towards house left, house left there are available seats. If you are please standing, we ask that you please take an available seat. We will begin momentarily, thank you. ♪ Let go ♪ ♪ All hands are in don't go ♪ ♪ Red all hands are in don't go ♪ ♪ All hands are in don't go ♪ ♪ Red all hands are in don't go ♪ (upbeat electronic dance music) ♪ Just make me ♪ ♪ Just make me ♪ ♪ Just make me ♪ ♪ Just make me ♪ ♪ Just make me ♪ ♪ I live ♪ ♪ Just make me ♪ ♪ Just make me ♪ ♪ Hey ♪ ♪ Yeah ♪ ♪ Oh ♪ ♪ Ah ♪ ♪ Ah ah ah ah ah ah ♪ ♪ Just make me ♪ ♪ Just make me ♪ (bouncy techno music) >> Ladies and gentlemen, once again we ask that you please take the available seats to your left, house left, there are many available seats. If you are standing, please make your way there. The program will begin momentarily, thank you. Good morning! This is Lenovo Transform 2.0! (keyboard clicks) >> Progress. Why do we always talk about it in the future? When will it finally get here? We don't progress when it's ready for us. We need it when we're ready, and we're ready now. Our hospitals and their patients need it now, our businesses and their customers need it now, our cities and their citizens need it now. To deliver intelligent transformation, we need to build it into the products and solutions we make every day. At Lenovo, we're designing the systems to fight disease, power businesses, and help you reach more customers, end-to-end security solutions to protect your data and your companies reputation. We're making IT departments more agile and cost efficient. We're revolutionizing how kids learn with VR. We're designing smart devices and software that transform the way you collaborate, because technology shouldn't just power industries, it should power people. While everybody else is talking about tomorrow, we'll keep building today, because the progress we need can't wait for the future. >> Please welcome to the stage Lenovo's Rod Lappen! (electronic dance music) (audience applauding) >> Alright. Good morning everyone! >> Good morning. >> Ooh, that was pretty good actually, I'll give it one more shot. Good morning everyone! >> Good morning! >> Oh, that's much better! Hope everyone's had a great morning. Welcome very much to the second Lenovo Transform event here in New York. I think when I got up just now on the steps I realized there's probably one thing in common all of us have in this room including myself which is, absolutely no one has a clue what I'm going to say today. So, I'm hoping very much that we get through this thing very quickly and crisply. I love this town, love New York, and you're going to hear us talk a little bit about New York as we get through here, but just before we get started I'm going to ask anyone who's standing up the back, there are plenty of seats down here, and down here on the right hand side, I think he called it house left is the professional way of calling it, but these steps to my right, your left, get up here, let's get you all seated down so that you can actually sit down during the keynote session for us. Last year we had our very first Lenovo Transform. We had about 400 people. It was here in New York, fantastic event, today, over 1,000 people. We have over 62 different technology demonstrations and about 15 breakout sessions, which I'll talk you through a little bit later on as well, so it's a much bigger event. Next year we're definitely going to be shooting for over 2,000 people as Lenovo really transforms and starts to address a lot of the technology that our commercial customers are really looking for. We were however hampered last year by a storm, I don't know if those of you who were with us last year will remember, we had a storm on the evening before Transform last year in New York, and obviously the day that it actually occurred, and we had lots of logistics. Our media people from AMIA were coming in. They took the, the plane was circling around New York for a long time, and Kamran Amini, our General Manager of our Data Center Infrastructure Group, probably one of our largest groups in the Lenovo DCG business, took 17 hours to get from Raleigh, North Carolina to New York, 17 hours, I think it takes seven or eight hours to drive. Took him 17 hours by plane to get here. And then of course this year, we have Florence. And so, obviously the hurricane Florence down there in the Carolinas right now, we tried to help, but still Kamran has made it today. Unfortunately, very tragically, we were hoping he wouldn't, but he's here today to do a big presentation a little bit later on as well. However, I do want to say, obviously, Florence is a very serious tragedy and we have to take it very serious. We got, our headquarters is in Raleigh, North Carolina. While it looks like the hurricane is just missing it's heading a little bit southeast, all of our thoughts and prayers and well wishes are obviously with everyone in the Carolinas on behalf of Lenovo, everyone at our headquarters, everyone throughout the Carolinas, we want to make sure everyone stays safe and out of harm's way. We have a great mixture today in the crowd of all customers, partners, industry analysts, media, as well as our financial analysts from all around the world. There's over 30 countries represented here and people who are here to listen to both YY, Kirk, and Christian Teismann speak today. And so, it's going to be a really really exciting day, and I really appreciate everyone coming in from all around the world. So, a big round of applause for everyone whose come in. (audience applauding) We have a great agenda for you today, and it starts obviously a very consistent format which worked very successful for us last year, and that's obviously our keynote. You'll hear from YY, our CEO, talk a little bit about the vision he has in the industry and how he sees Lenovo's turned the corner and really driving some great strategy to address our customer's needs. Kirk Skaugen, our Executive Vice President of DCG, will be up talking about how we've transformed the DCG business and once again are hitting record growth ratios for our DCG business. And then you'll hear from Christian Teismann, our SVP and General Manager for our commercial business, get up and talk about everything that's going on in our IDG business. There's really exciting stuff going on there and obviously ThinkPad being the cornerstone of that I'm sure he's going to talk to us about a couple surprises in that space as well. Then we've got some great breakout sessions, I mentioned before, 15 breakout sessions, so while this keynote section goes until about 11:30, once we get through that, please go over and explore, and have a look at all of the breakout sessions. We have all of our subject matter experts from both our PC, NBG, and our DCG businesses out to showcase what we're doing as an organization to better address your needs. And then obviously we have the technology pieces that I've also spoken about, 62 different technology displays there arranged from everything IoT, 5G, NFV, everything that's really cool and hot in the industry right now is going to be on display up there, and I really encourage all of you to get up there. So, I'm going to have a quick video to show you from some of the setup yesterday on a couple of the 62 technology displays we've got on up on stage. Okay let's go, so we've got a demonstrations to show you today, one of the greats one here is the one we've done with NC State, a high-performance computing artificial intelligence demonstration of fresh produce. It's about modeling the population growth of the planet, and how we're going to supply water and food as we go forward. Whoo. Oh, that is not an apple. Okay. (woman laughs) Second one over here is really, hey Jonas, how are you? Is really around virtual reality, and how we look at one of the most amazing sites we've got, as an install on our high-performance computing practice here globally. And you can see, obviously, that this is the Barcelona supercomputer, and, where else in New York can you get access to being able to see something like that so easily? Only here at Lenovo Transform. Whoo, okay. (audience applauding) So there's two examples of some of the technology. We're really encouraging everyone in the room after the keynote to flow into that space and really get engaged, and interact with a lot of the technology we've got up there. It seems I need to also do something about my fashion, I've just realized I've worn a vest two days in a row, so I've got to work on that as well. Alright so listen, the last thing on the agenda, we've gone through the breakout sessions and the demo, tonight at four o'clock, there's about 400 of you registered to be on the cruise boat with us, the doors will open behind me. the boat is literally at the pier right behind us. You need to make sure you're on the boat for 4:00 p.m. this evening. Outside of that, I want everyone to have a great time today, really enjoy the experience, make it as experiential as you possibly can, get out there and really get in and touch the technology. There's some really cool AI displays up there for us all to get involved in as well. So ladies and gentlemen, without further adieu, it gives me great pleasure to introduce to you a lover of tennis, as some of you would've heard last year at Lenovo Transform, as well as a lover of technology, Lenovo, and of course, New York City. I am obviously very pleasured to introduce to you Yang Yuanqing, our CEO, as we like to call him, YY. (audience applauding) (upbeat funky music) >> Good morning, everyone. >> Good morning. >> Thank you Rod for that introduction. Welcome to New York City. So, this is the second year in a row we host our Transform event here, because New York is indeed one of the most transformative cities in the world. Last year on this stage, I spoke about the Fourth Industrial Revolution, and our vision around the intelligent transformation, how it would fundamentally change the nature of business and the customer relationships. And why preparing for this transformation is the key for the future of our company. And in the last year I can assure you, we were being very busy doing just that, from searching and bringing global talents around the world to the way we think about every product and every investment we make. I was here in New York just a month ago to announce our fiscal year Q1 earnings, which was a good day for us. I think now the world believes it when we say Lenovo has truly turned the corner to a new phase of growth and a new phase of acceleration in executing the transformation strategy. That's clear to me is that the last few years of a purposeful disruption at Lenovo have led us to a point where we can now claim leadership of the coming intelligent transformation. People often asked me, what is the intelligent transformation? I was saying this way. This is the unlimited potential of the Fourth Industrial Revolution driven by artificial intelligence being realized, ordering a pizza through our speaker, and locking the door with a look, letting your car drive itself back to your home. This indeed reflect the power of AI, but it just the surface of it. The true impact of AI will not only make our homes smarter and offices more efficient, but we are also completely transformed every value chip in every industry. However, to realize these amazing possibilities, we will need a structure built around the key components, and one that touches every part of all our lives. First of all, explosions in new technology always lead to new structures. This has happened many times before. In the early 20th century, thousands of companies provided a telephone service. City streets across the US looked like this, and now bundles of a microscopic fiber running from city to city bring the world closer together. Here's what a driving was like in the US, up until 1950s. Good luck finding your way. (audience laughs) And today, millions of vehicles are organized and routed daily, making the world more efficient. Structure is vital, from fiber cables and the interstate highways, to our cells bounded together to create humans. Thankfully the structure for intelligent transformation has emerged, and it is just as revolutionary. What does this new structure look like? We believe there are three key building blocks, data, computing power, and algorithms. Ever wondered what is it behind intelligent transformation? What is fueling this miracle of human possibility? Data. As the Internet becomes ubiquitous, not only PCs, mobile phones, have come online and been generating data. Today it is the cameras in this room, the climate controls in our offices, or the smart displays in our kitchens at home. The number of smart devices worldwide will reach over 20 billion in 2020, more than double the number in 2017. These devices and the sensors are connected and generating massive amount of data. By 2020, the amount of data generated will be 57 times more than all the grains of sand on Earth. This data will not only make devices smarter, but will also fuel the intelligence of our homes, offices, and entire industries. Then we need engines to turn the fuel into power, and the engine is actually the computing power. Last but not least the advanced algorithms combined with Big Data technology and industry know how will form vertical industrial intelligence and produce valuable insights for every value chain in every industry. When these three building blocks all come together, it will change the world. At Lenovo, we have each of these elements of intelligent transformations in a single place. We have built our business around the new structure of intelligent transformation, especially with mobile and the data center now firmly part of our business. I'm often asked why did you acquire these businesses? Why has a Lenovo gone into so many fields? People ask the same questions of the companies that become the leaders of the information technology revolution, or the third industrial transformation. They were the companies that saw the future and what the future required, and I believe Lenovo is the company today. From largest portfolio of devices in the world, leadership in the data center field, to the algorithm-powered intelligent vertical solutions, and not to mention the strong partnership Lenovo has built over decades. We are the only company that can unify all these essential assets and deliver end to end solutions. Let's look at each part. We now understand the important importance data plays as fuel in intelligent transformation. Hundreds of billions of devices and smart IoTs in the world are generating better and powering the intelligence. Who makes these devices in large volume and variety? Who puts these devices into people's home, offices, manufacturing lines, and in their hands? Lenovo definitely has the front row seats here. We are number one in PCs and tablets. We also produces smart phones, smart speakers, smart displays. AR/VR headsets, as well as commercial IoTs. All of these smart devices, or smart IoTs are linked to each other and to the cloud. In fact, we have more than 20 manufacturing facilities in China, US, Brazil, Japan, India, Mexico, Germany, and more, producing various devices around the clock. We actually make four devices every second, and 37 motherboards every minute. So, this factory located in my hometown, Hu-fi, China, is actually the largest laptop factory in the world, with more than three million square feet. So, this is as big as 42 soccer fields. Our scale and the larger portfolio of devices gives us access to massive amount of data, which very few companies can say. So, why is the ability to scale so critical? Let's look again at our example from before. The early days of telephone, dozens of service providers but only a few companies could survive consolidation and become the leader. The same was true for the third Industrial Revolution. Only a few companies could scale, only a few could survive to lead. Now the building blocks of the next revolution are locking into place. The (mumbles) will go to those who can operate at the scale. So, who could foresee the total integration of cloud, network, and the device, need to deliver intelligent transformation. Lenovo is that company. We are ready to scale. Next, our computing power. Computing power is provided in two ways. On one hand, the modern supercomputers are providing the brute force to quickly analyze the massive data like never before. On the other hand the cloud computing data centers with the server storage networking capabilities, and any computing IoT's, gateways, and miniservers are making computing available everywhere. Did you know, Lenovo is number one provider of super computers worldwide? 170 of the top 500 supercomputers, run on Lenovo. We hold 89 World Records in key workloads. We are number one in x86 server reliability for five years running, according to ITIC. a respected provider of industry research. We are also the fastest growing provider of hyperscale public cloud, hyper-converged and aggressively growing in edge computing. cur-ges target, we are expand on this point soon. And finally to run these individual nodes into our symphony, we must transform the data and utilize the computing power with advanced algorithms. Manufactured, industry maintenance, healthcare, education, retail, and more, so many industries are on the edge of intelligent transformation to improve efficiency and provide the better products and services. We are creating advanced algorithms and the big data tools combined with industry know-how to provide intelligent vertical solutions for several industries. In fact, we studied at Lenovo first. Our IT and research teams partnered with our global supply chain to develop an AI that improved our demand forecasting accuracy. Beyond managing our own supply chain we have offered our deep learning supply focused solution to other manufacturing companies to improve their efficiency. In the best case, we have improved the demand, focused the accuracy by 30 points to nearly 90 percent, for Baosteel, the largest of steel manufacturer in China, covering the world as well. Led by Lenovo research, we launched the industry-leading commercial ready AR headset, DaystAR, partnering with companies like the ones in this room. This technology is being used to revolutionize the way companies service utility, and even our jet engines. Using our workstations, servers, and award-winning imaging processing algorithms, we have partnered with hospitals to process complex CT scan data in minutes. So, this enable the doctors to more successfully detect the tumors, and it increases the success rate of cancer diagnosis all around the world. We are also piloting our smart IoT driven warehouse solution with one of the world's largest retail companies to greatly improve the efficiency. So, the opportunities are endless. This is where Lenovo will truly shine. When we combine the industry know-how of our customers with our end-to-end technology offerings, our intelligent vertical solutions like this are growing, which Kirk and Christian will share more. Now, what will drive this transformation even faster? The speed at which our networks operate, specifically 5G. You may know that Lenovo just launched the first-ever 5G smartphone, our Moto Z3, with the new 5G Moto model. We are partnering with multiple major network providers like Verizon, China Mobile. With the 5G model scheduled to ship early next year, we will be the first company to provide a 5G mobile experience to any users, customers. This is amazing innovation. You don't have to buy a new phone, just the 5G clip on. What can I say, except wow. (audience laughs) 5G is 10 times the fast faster than 4G. Its download speed will transform how people engage with the world, driverless car, new types of smart wearables, gaming, home security, industrial intelligence, all will be transformed. Finally, accelerating with partners, as ready as we are at Lenovo, we need partners to unlock our full potential, partners here to create with us the edge of the intelligent transformation. The opportunities of intelligent transformation are too profound, the scale is too vast. No company can drive it alone fully. We are eager to collaborate with all partners that can help bring our vision to life. We are dedicated to open partnerships, dedicated to cross-border collaboration, unify the standards, share the advantage, and market the synergies. We partner with the biggest names in the industry, Intel, Microsoft, AMD, Qualcomm, Google, Amazon, and Disney. We also find and partner with the smaller innovators as well. We're building the ultimate partner experience, open, shared, collaborative, diverse. So, everything is in place for intelligent transformation on a global scale. Smart devices are everywhere, the infrastructure is in place, networks are accelerating, and the industries demand to be more intelligent, and Lenovo is at the center of it all. We are helping to drive change with the hundreds of companies, companies just like yours, every day. We are your partner for intelligent transformation. Transformation never stops. This is what you will hear from Kirk, including details about Lenovo NetApp global partnership we just announced this morning. We've made the investments in every single aspect of the technology. We have the end-to-end resources to meet your end-to-end needs. As you attend the breakout session this afternoon, I hope you see for yourself how much Lenovo has transformed as a company this past year, and how we truly are delivering a future of intelligent transformation. Now, let me invite to the stage Kirk Skaugen, our president of Data Center growth to tell you about the exciting transformation happening in the global Data C enter market. Thank you. (audience applauding) (upbeat music) >> Well, good morning. >> Good morning. >> Good morning! >> Good morning! >> Excellent, well, I'm pleased to be here this morning to talk about how we're transforming the Data Center and taking you as our customers through your own intelligent transformation journey. Last year I stood up here at Transform 1.0, and we were proud to announce the largest Data Center portfolio in Lenovo's history, so I thought I'd start today and talk about the portfolio and the progress that we've made over the last year, and the strategies that we have going forward in phase 2.0 of Lenovo's transformation to be one of the largest data center companies in the world. We had an audacious vision that we talked about last year, and that is to be the most trusted data center provider in the world, empowering customers through the new IT, intelligent transformation. And now as the world's largest supercomputer provider, giving something back to humanity, is very important this week with the hurricanes now hitting North Carolina's coast, but we take this most trusted aspect very seriously, whether it's delivering the highest quality products on time to you as customers with the highest levels of security, or whether it's how we partner with our channel partners and our suppliers each and every day. You know we're in a unique world where we're going from hundreds of millions of PCs, and then over the next 25 years to hundred billions of connected devices, so each and every one of you is going through this intelligent transformation journey, and in many aspects were very early in that cycle. And we're going to talk today about our role as the largest supercomputer provider, and how we're solving humanity's greatest challenges. Last year we talked about two special milestones, the 25th anniversary of ThinkPad, but also the 25th anniversary of Lenovo with our IBM heritage in x86 computing. I joined the workforce in 1992 out of college, and the IBM first personal server was launching at the same time with an OS2 operating system and a free mouse when you bought the server as a marketing campaign. (audience laughing) But what I want to be very clear today, is that the innovation engine is alive and well at Lenovo, and it's really built on the culture that we're building as a company. All of these awards at the bottom are things that we earned over the last year at Lenovo. As a Fortune now 240 company, larger than companies like Nike, or AMEX, or Coca-Cola. The one I'm probably most proud of is Forbes first list of the top 2,000 globally regarded companies. This was something where 15,000 respondents in 60 countries voted based on ethics, trustworthiness, social conduct, company as an employer, and the overall company performance, and Lenovo was ranked number 27 of 2000 companies by our peer group, but we also now one of-- (audience applauding) But we also got a perfect score in the LGBTQ Equality Index, exemplifying the diversity internally. We're number 82 in the top working companies for mothers, top working companies for fathers, top 100 companies for sustainability. If you saw that factory, it's filled with solar panels on the top of that. And now again, one of the top global brands in the world. So, innovation is built on a customer foundation of trust. We also said last year that we'd be crossing an amazing milestone. So we did, over the last 12 months ship our 20 millionth x86 server. So, thank you very much to our customers for this milestone. (audience applauding) So, let me recap some of the transformation elements that have happened over the last year. Last year I talked about a lot of brand confusion, because we had the ThinkServer brand from the legacy Lenovo, the System x, from IBM, we had acquired a number of networking companies, like BLADE Network Technologies, et cetera, et cetera. Over the last year we've been ramping based on two brand structures, ThinkAgile for next generation IT, and all of our software-defined infrastructure products and ThinkSystem as the world's highest performance, highest reliable x86 server brand, but for servers, for storage, and for networking. We have transformed every single aspect of the customer experience. A year and a half ago, we had four different global channel programs around the world. Typically we're about twice the mix to our channel partners of any of our competitors, so this was really important to fix. We now have a single global Channel program, and have technically certified over 11,000 partners to be technical experts on our product line to deliver better solutions to our customer base. Gardner recently recognized Lenovo as the 26th ranked supply chain in the world. And, that's a pretty big honor, when you're up there with Amazon and Walmart and others, but in tech, we now are in the top five supply chains. You saw the factory network from YY, and today we'll be talking about product shipping in more than 160 countries, and I know there's people here that I've met already this morning, from India, from South Africa, from Brazil and China. We announced new Premier Support services, enabling you to go directly to local language support in nine languages in 49 countries in the world, going directly to a native speaker level three support engineer. And today we have more than 10,000 support specialists supporting our products in over 160 countries. We've delivered three times the number of engineered solutions to deliver a solutions orientation, whether it's on HANA, or SQL Server, or Oracle, et cetera, and we've completely reengaged our system integrator channel. Last year we had the CIO of DXE on stage, and here we're talking about more than 175 percent growth through our system integrator channel in the last year alone as we've brought that back and really built strong relationships there. So, thank you very much for amazing work here on the customer experience. (audience applauding) We also transformed our leadership. We thought it was extremely important with a focus on diversity, to have diverse talent from the legacy IBM, the legacy Lenovo, but also outside the industry. We made about 19 executive changes in the DCG group. This is the most senior leadership team within DCG, all which are newly on board, either from our outside competitors mainly over the last year. About 50 percent of our executives were now hired internally, 50 percent externally, and 31 percent of those new executives are diverse, representing the diversity of our global customer base and gender. So welcome, and most of them you're going to be able to meet over here in the breakout sessions later today. (audience applauding) But some things haven't changed, they're just keeping getting better within Lenovo. So, last year I got up and said we were committed with the new ThinkSystem brand to be a world performance leader. You're going to see that we're sponsoring Ducati for MotoGP. You saw the Ferrari out there with Formula One. That's not a surprise. We want the Lenovo ThinkSystem and ThinkAgile brands to be synonymous with world record performance. So in the last year we've gone from 39 to 89 world records, and partners like Intel would tell you, we now have four times the number of world record workloads on Lenovo hardware than any other server company on the planet today, with more than 89 world records across HPC, Java, database, transaction processing, et cetera. And we're proud to have just brought on Doug Fisher from Intel Corporation who had about 10-17,000 people on any given year working for him in workload optimizations across all of our software. It's just another testament to the leadership team we're bringing in to keep focusing on world-class performance software and solutions. We also per ITIC, are the number one now in x86 server reliability five years running. So, this is a survey where CIOs are in a blind survey asked to submit their reliability of their uptime on their x86 server equipment over the last 365 days. And you can see from 2016 to 2017 the downtime, there was over four hours as noted by the 750 CXOs in more than 20 countries is about one percent for the Lenovo products, and is getting worse generation from generation as we went from Broadwell to Pearlie. So we're taking our reliability, which was really paramount in the IBM System X heritage, and ensuring that we don't just recognize high performance but we recognize the highest level of reliability for mission-critical workloads. And what that translates into is that we at once again have been ranked number one in customer satisfaction from you our customers in 19 of 22 attributes, in North America in 18 of 22. This is a survey by TVR across hundreds of customers of us and our top competitors. This is the ninth consecutive study that we've been ranked number one in customer satisfaction, so we're taking this extremely seriously, and in fact YY now has increased the compensation of every single Lenovo employee. Up to 40 percent of their compensation bonus this year is going to be based on customer metrics like quality, order to ship, and things of this nature. So, we're really putting every employee focused on customer centricity this year. So, the summary on Transform 1.0 is that every aspect of what you knew about Lenovo's data center group has transformed, from the culture to the branding to dedicated sales and marketing, supply chain and quality groups, to a worldwide channel program and certifications, to new system integrator relationships, and to the new leadership team. So, rather than me just talk about it, I thought I'd share a quick video about what we've done over the last year, if you could run the video please. Turn around for a second. (epic music) (audience applauds) Okay. So, thank you to all our customers that allowed us to publicly display their logos in that video. So, what that means for you as investors, and for the investor community out there is, that our customers have responded, that this year Gardner just published that we are the fastest growing server company in the top 10, with 39 percent growth quarter-on-quarter, and 49 percent growth year-on-year. If you look at the progress we've made since the transformation the last three quarters publicly, we've grown 17 percent, then 44 percent, then 68 percent year on year in revenue, and I can tell you this quarter I'm as confident as ever in the financials around the DCG group, and it hasn't been in one area. You're going to see breakout sessions from hyperscale, software-defined, and flash, which are all growing more than a 100 percent year-on-year, supercomputing which we'll talk about shortly, now number one, and then ultimately from profitability, delivering five consecutive quarters of pre-tax profit increase, so I think, thank you very much to the customer base who's been working with us through this transformation journey. So, you're here to really hear what's next on 2.0, and that's what I'm excited to talk about today. Last year I came up with an audacious goal that we would become the largest supercomputer company on the planet by 2020, and this graph represents since the acquisition of the IBM System x business how far we were behind being the number one supercomputer. When we started we were 182 positions behind, even with the acquisition for example of SGI from HP, we've now accomplished our goal actually two years ahead of time. We're now the largest supercomputer company in the world. About one in every four supercomputers, 117 on the list, are now Lenovo computers, and you saw in the video where the universities are said, but I think what I'm most proud of is when your customers rank you as the best. So the awards at the bottom here, are actually Readers Choice from the last International Supercomputing Show where the scientific researchers on these computers ranked their vendors, and we were actually rated the number one server technology in supercomputing with our ThinkSystem SD530, and the number one storage technology with our ThinkSystem DSS-G, but more importantly what we're doing with the technology. You're going to see we won best in life sciences, best in data analytics, and best in collaboration as well, so you're going to see all of that in our breakout sessions. As you saw in the video now, 17 of the top 25 research institutions in the world are now running Lenovo supercomputers. And again coming from Raleigh and watching that hurricane come across the Atlantic, there are eight supercomputers crunching all of those models you see from Germany to Malaysia to Canada, and we're happy to have a SciNet from University of Toronto here with us in our breakout session to talk about what they're doing on climate modeling as well. But we're not stopping there. We just announced our new Neptune warm water cooling technology, which won the International Supercomputing Vendor Showdown, the first time we've won that best of show in 25 years, and we've now installed this. We're building out LRZ in Germany, the first ever warm water cooling in Peking University, at the India Space Propulsion Laboratory, at the Malaysian Weather and Meteorological Society, at Uninett, at the largest supercomputer in Norway, T-Systems, University of Birmingham. This is truly amazing technology where we're actually using water to cool the machine to deliver a significantly more energy-efficient computer. Super important, when we're looking at global warming and some of the electric bills can be millions of dollars just for one computer, and could actually power a small city just with the technology from the computer. We've built AI centers now in Morrisville, Stuttgart, Taipei, and Beijing, where customers can bring their AI workloads in with experts from Intel, from Nvidia, from our FPGA partners, to work on their workloads, and how they can best implement artificial intelligence. And we also this year launched LICO which is Lenovo Intelligent Compute Orchestrator software, and it's a software solution that simplifies the management and use of distributed clusters in both HPC and AI model development. So, what it enables you to do is take a single cluster, and run both HPC and AI workloads on it simultaneously, delivering better TCO for your environment, so check out LICO as well. A lot of the customers here and Wall Street are very excited and using it already. And we talked about solving humanity's greatest challenges. In the breakout session, you're going to have a virtual reality experience where you're going to be able to walk through what as was just ranked the world's most beautiful data center, the Barcelona Supercomputer. So, you can actually walk through one of the largest supercomputers in the world from Barcelona. You can see the work we're doing with NC State where we're going to have to grow the food supply of the world by 50 percent, and there's not enough fresh water in the world in the right places to actually make all those crops grow between now and 2055, so you're going to see the progression of how they're mapping the entire globe and the water around the world, how to build out the crop population over time using AI. You're going to see our work with Vestas is this largest supercomputer provider in the wind turbine areas, how they're working on wind energy, and then with University College London, how they're working on some of the toughest particle physics calculations in the world. So again, lots of opportunity here. Take advantage of it in the breakout sessions. Okay, let me transition to hyperscale. So in hyperscale now, we have completely transformed our business model. We are now powering six of the top 10 hyperscalers in the world, which is a significant difference from where we were two years ago. And the reason we're doing that, is we've coined a term called ODM+. We believe that hyperscalers want more procurement power than an ODM, and Lenovo is doing about $18 billion of procurement a year. They want a broader global supply chain that they can get from a local system integrator. We're more than 160 countries around the world, but they want the same world-class quality and reliability like they get from an MNC. So, what we're doing now is instead of just taking off the shelf motherboards from somewhere, we're starting with a blank sheet of paper, we're working with the customer base on customized SKUs and you can see we already are developing 33 custom solutions for the largest hyperscalers in the world. And then we're not just running notebooks through this factory where YY said, we're running 37 notebook boards a minute, we're now putting in tens and tens and tens of thousands of server board capacity per month into this same factory, so absolutely we can compete with the most aggressive ODM's in the world, but it's not just putting these things in in the motherboard side, we're also building out these systems all around the world, India, Brazil, Hungary, Mexico, China. This is an example of a new hyperscale customer we've had this last year, 34,000 servers we delivered in the first six months. The next 34,000 servers we delivered in 68 days. The next 34,000 servers we delivered in 35 days, with more than 99 percent on-time delivery to 35 data centers in 14 countries as diverse as South Africa, India, China, Brazil, et cetera. And I'm really ashamed to say it was 99.3, because we did have a forklift driver who rammed their forklift right through the middle of the one of the server racks. (audience laughing) At JFK Airport that we had to respond to, but I think this gives you a perspective of what it is to be a top five global supply chain and technology. So last year, I said we would invest significantly in IP, in joint ventures, and M and A to compete in software defined, in networking, and in storage, so I wanted to give you an update on that as well. Our newest software-defined partnership is with Cloudistics, enabling a fully composable cloud infrastructure. It's an exclusive agreement, you can see them here. I think Nag, our founder, is going to be here today, with a significant Lenovo investment in the company. So, this new ThinkAgile CP series delivers the simplicity of the public cloud, on-premise with exceptional support and a marketplace of essential enterprise applications all with a single click deployment. So simply put, we're delivering a private cloud with a premium experience. It's simple in that you need no specialists to deploy it. An IT generalist can set it up and manage it. It's agile in that you can provision dozens of workloads in minutes, and it's transformative in that you get all of the goodness of public cloud on-prem in a private cloud to unlock opportunity for use. So, we're extremely excited about the ThinkAgile CP series that's now shipping into the marketplace. Beyond that we're aggressively ramping, and we're either doubling, tripling, or quadrupling our market share as customers move from traditional server technology to software-defined technology. With Nutanix we've been public, growing about more than 150 percent year-on-year, with Nutanix as their fastest growing Nutanix partner, but today I want to set another audacious goal. I believe we cannot just be Nutanix's fastest growing partner but we can become their largest partner within two years. On Microsoft, we are already four times our market share on Azure stack of our traditional business. We were the first to launch our ThinkAgile on Broadwell and on Skylake with the Azure Stack Infrastructure. And on VMware we're about twice our market segment share. We were the first to deliver an Intel-optimized Optane-certified VSAN node. And with Optane technology, we're delivering 50 percent more VM density than any competitive SSD system in the marketplace, about 10 times lower latency, four times the performance of any SSD system out there, and Lenovo's first to market on that. And at VMworld you saw CEO Pat Gelsinger of VMware talked about project dimension, which is Edge as a service, and we're the only OEM beyond the Dell family that is participating today in project dimension. Beyond that you're going to see a number of other partnerships we have. I'm excited that we have the city of Bogota Columbia here, an eight million person city, where we announced a 3,000 camera video surveillance solution last month. With pivot three you're going to see city of Bogota in our breakout sessions. You're going to see a new partnership with Veeam around backup that's launching today. You're going to see partnerships with scale computing in IoT and hyper-converged infrastructure working on some of the largest retailers in the world. So again, everything out in the breakout session. Transitioning to storage and data management, it's been a great year for Lenovo, more than a 100 percent growth year-on-year, 2X market growth in flash arrays. IDC just reported 30 percent growth in storage, number one in price performance in the world and the best HPC storage product in the top 500 with our ThinkSystem DSS G, so strong coverage, but I'm excited today to announce for Transform 2.0 that Lenovo is launching the largest data management and storage portfolio in our 25-year data center history. (audience applauding) So a year ago, the largest server portfolio, becoming the largest fastest growing server OEM, today the largest storage portfolio, but as you saw this morning we're not doing it alone. Today Lenovo and NetApp, two global powerhouses are joining forces to deliver a multi-billion dollar global alliance in data management and storage to help customers through their intelligent transformation. As the fastest growing worldwide server leader and one of the fastest growing flash array and data management companies in the world, we're going to deliver more choice to customers than ever before, global scale that's never been seen, supply chain efficiencies, and rapidly accelerating innovation and solutions. So, let me unwrap this a little bit for you and talk about what we're announcing today. First, it's the largest portfolio in our history. You're going to see not just storage solutions launching today but a set of solution recipes from NetApp that are going to make Lenovo server and NetApp or Lenovo storage work better together. The announcement enables Lenovo to go from covering 15 percent of the global storage market to more than 90 percent of the global storage market and distribute these products in more than 160 countries around the world. So we're launching today, 10 new storage platforms, the ThinkSystem DE and ThinkSystem DM platforms. They're going to be centrally managed, so the same XClarity management that you've been using for server, you can now use across all of your storage platforms as well, and it'll be supported by the same 10,000 plus service personnel that are giving outstanding customer support to you today on the server side. And we didn't come up with this in the last month or the last quarter. We're announcing availability in ordering today and shipments tomorrow of the first products in this portfolio, so we're excited today that it's not just a future announcement but something you as customers can take advantage of immediately. (audience applauding) The second part of the announcement is we are announcing a joint venture in China. Not only will this be a multi-billion dollar global partnership, but Lenovo will be a 51 percent owner, NetApp a 49 percent owner of a new joint venture in China with the goal of becoming in the top three storage companies in the largest data and storage market in the world. We will deliver our R and D in China for China, pooling our IP and resources together, and delivering a single route to market through a complementary channel, not just in China but worldwide. And in the future I just want to tell everyone this is phase one. There is so much exciting stuff. We're going to be on the stage over the next year talking to you about around integrated solutions, next-generation technologies, and further synergies and collaborations. So, rather than just have me talk about it, I'd like to welcome to the stage our new partner NetApp and Brad Anderson who's the senior vice president and general manager of NetApp Cloud Infrastructure. (upbeat music) (audience applauding) >> Thank You Kirk. >> So Brad, we've known each other a long time. It's an exciting day. I'm going to give you the stage and allow you to say NetApp's perspective on this announcement. >> Very good, thank you very much, Kirk. Kirk and I go back to I think 1994, so hey good morning and welcome. My name is Brad Anderson. I manage the Cloud Infrastructure Group at NetApp, and I am honored and privileged to be here at Lenovo Transform, particularly today on today's announcement. Now, you've heard a lot about digital transformation about how companies have to transform their IT to compete in today's global environment. And today's announcement with the partnership between NetApp and Lenovo is what that's all about. This is the joining of two global leaders bringing innovative technology in a simplified solution to help customers modernize their IT and accelerate their global digital transformations. Drawing on the strengths of both companies, Lenovo's high performance compute world-class supply chain, and NetApp's hybrid cloud data management, hybrid flash and all flash storage solutions and products. And both companies providing our customers with the global scale for them to be able to meet their transformation goals. At NetApp, we're very excited. This is a quote from George Kurian our CEO. George spent all day yesterday with YY and Kirk, and would have been here today if it hadn't been also our shareholders meeting in California, but I want to just convey how excited we are for all across NetApp with this partnership. This is a partnership between two companies with tremendous market momentum. Kirk took you through all the amazing results that Lenovo has accomplished, number one in supercomputing, number one in performance, number one in x86 reliability, number one in x86 customers sat, number five in supply chain, really impressive and congratulations. Like Lenovo, NetApp is also on a transformation journey, from a storage company to the data authority in hybrid cloud, and we've seen some pretty impressive momentum as well. Just last week we became number one in all flash arrays worldwide, catching EMC and Dell, and we plan to keep on going by them, as we help customers modernize their their data centers with cloud connected flash. We have strategic partnerships with the largest hyperscalers to provide cloud native data services around the globe and we are having success helping our customers build their own private clouds with just, with a new disruptive hyper-converged technology that allows them to operate just like hyperscalers. These three initiatives has fueled NetApp's transformation, and has enabled our customers to change the world with data. And oh by the way, it has also fueled us to have meet or have beaten Wall Street's expectations for nine quarters in a row. These are two companies with tremendous market momentum. We are also building this partnership for long term success. We think about this as phase one and there are two important components to phase one. Kirk took you through them but let me just review them. Part one, the establishment of a multi-year commitment and a collaboration agreement to offer Lenovo branded flash products globally, and as Kurt said in 160 countries. Part two, the formation of a joint venture in PRC, People's Republic of China, that will provide long term commitment, joint product development, and increase go-to-market investment to meet the unique needs to China. Both companies will put in storage technologies and storage expertise to form an independent JV that establishes a data management company in China for China. And while we can dream about what phase two looks like, our entire focus is on making phase one incredibly successful and I'm pleased to repeat what Kirk, is that the first products are orderable and shippable this week in 160 different countries, and you will see our two companies focusing on the here and now. On our joint go to market strategy, you'll see us working together to drive strategic alignment, focused execution, strong governance, and realistic expectations and milestones. And it starts with the success of our customers and our channel partners is job one. Enabling customers to modernize their legacy IT with complete data center solutions, ensuring that our customers get the best from both companies, new offerings the fuel business success, efficiencies to reinvest in game-changing initiatives, and new solutions for new mission-critical applications like data analytics, IoT, artificial intelligence, and machine learning. Channel partners are also top of mind for both our two companies. We are committed to the success of our existing and our future channel partners. For NetApp channel partners, it is new pathways to new segments and to new customers. For Lenovo's channel partners, it is the competitive weapons that now allows you to compete and more importantly win against Dell, EMC, and HP. And the good news for both companies is that our channel partner ecosystem is highly complementary with minimal overlap. Today is the first day of a very exciting partnership, of a partnership that will better serve our customers today and will provide new opportunities to both our companies and to our partners, new products to our customers globally and in China. I am personally very excited. I will be on the board of the JV. And so, I look forward to working with you, partnering with you and serving you as we go forward, and with that, I'd like to invite Kirk back up. (audience applauding) >> Thank you. >> Thank you. >> Well, thank you, Brad. I think it's an exciting overview, and these products will be manufactured in China, in Mexico, in Hungary, and around the world, enabling this amazing supply chain we talked about to deliver in over 160 countries. So thank you Brad, thank you George, for the amazing partnership. So again, that's not all. In Transform 2.0, last year, we talked about the joint ventures that were coming. I want to give you a sneak peek at what you should expect at future Lenovo events around the world. We have this Transform in Beijing in a couple weeks. We'll then be repeating this in 20 different locations roughly around the world over the next year, and I'm excited probably more than ever about what else is coming. Let's talk about Telco 5G and network function virtualization. Today, Motorola phones are certified on 46 global networks. We launched the world's first 5G upgradable phone here in the United States with Verizon. Lenovo DCG sells to 58 telecommunication providers around the world. At Mobile World Congress in Barcelona and Shanghai, you saw China Telecom and China Mobile in the Lenovo booth, China Telecom showing a video broadband remote access server, a VBRAS, with video streaming demonstrations with 2x less jitter than they had seen before. You saw China Mobile with a virtual remote access network, a VRAN, with greater than 10 times the throughput and 10x lower latency running on Lenovo. And this year, we'll be launching a new NFV company, a software company in China for China to drive the entire NFV stack, delivering not just hardware solutions, but software solutions, and we've recently hired a new CEO. You're going to hear more about that over the next several quarters. Very exciting as we try to drive new economics into the networks to deliver these 20 billion devices. We're going to need new economics that I think Lenovo can uniquely deliver. The second on IoT and edge, we've integrated on the device side into our intelligent devices group. With everything that's going to consume electricity computes and communicates, Lenovo is in a unique position on the device side to take advantage of the communications from Motorola and being one of the largest device companies in the world. But this year, we're also going to roll out a comprehensive set of edge gateways and ruggedized industrial servers and edge servers and ISP appliances for the edge and for IoT. So look for that as well. And then lastly, as a service, you're going to see Lenovo delivering hardware as a service, device as a service, infrastructure as a service, software as a service, and hardware as a service, not just as a glorified leasing contract, but with IP, we've developed true flexible metering capability that enables you to scale up and scale down freely and paying strictly based on usage, and we'll be having those announcements within this fiscal year. So Transform 2.0, lots to talk about, NetApp the big news of the day, but a lot more to come over the next year from the Data Center group. So in summary, I'm excited that we have a lot of customers that are going to be on stage with us that you saw in the video. Lots of testimonials so that you can talk to colleagues of yourself. Alamos Gold from Canada, a Canadian gold producer, Caligo for data optimization and privacy, SciNet, the largest supercomputer we've ever put into North America, and the largest in Canada at the University of Toronto will be here talking about climate change. City of Bogota again with our hyper-converged solutions around smart city putting in 3,000 cameras for criminal detection, license plate detection, et cetera, and then more from a channel mid market perspective, Jerry's Foods, which is from my home state of Wisconsin, and Minnesota which has about 57 stores in the specialty foods market, and how they're leveraging our IoT solutions as well. So again, about five times the number of demos that we had last year. So in summary, first and foremost to the customers, thank you for your business. It's been a great journey and I think we're on a tremendous role. You saw from last year, we're trying to build credibility with you. After the largest server portfolio, we're now the fastest-growing server OEM per Gardner, number one in performance, number one in reliability, number one in customer satisfaction, number one in supercomputing. Today, the largest storage portfolio in our history, with the goal of becoming the fastest growing storage company in the world, top three in China, multibillion-dollar collaboration with NetApp. And the transformation is going to continue with new edge gateways, edge servers, NFV solutions, telecommunications infrastructure, and hardware as a service with dynamic metering. So thank you for your time. I've looked forward to meeting many of you over the next day. We appreciate your business, and with that, I'd like to bring up Rod Lappen to introduce our next speaker. Rod? (audience applauding) >> Thanks, boss, well done. Alright ladies and gentlemen. No real secret there. I think we've heard why I might talk about the fourth Industrial Revolution in data and exactly what's going on with that. You've heard Kirk with some amazing announcements, obviously now with our NetApp partnership, talk about 5G, NFV, cloud, artificial intelligence, I think we've hit just about all the key hot topics. It's with great pleasure that I now bring up on stage Mr. Christian Teismann, our senior vice president and general manager of commercial business for both our PCs and our IoT business, so Christian Teismann. (techno music) Here, take that. >> Thank you. I think I'll need that. >> Okay, Christian, so obviously just before we get down, you and I last year, we had a bit of a chat about being in New York. >> Exports. >> You were an expat in New York for a long time. >> That's true. >> And now, you've moved from New York. You're in Munich? >> Yep. >> How does that feel? >> Well Munich is a wonderful city, and it's a great place to live and raise kids, but you know there's no place in the world like New York. >> Right. >> And I miss it a lot, quite frankly. >> So what exactly do you miss in New York? >> Well there's a lot of things in New York that are unique, but I know you spent some time in Japan, but I still believe the best sushi in the world is still in New York City. (all laughing) >> I will beg to differ. I will beg to differ. I think Mr. Guchi-san from Softbank is here somewhere. He will get up an argue very quickly that Japan definitely has better sushi than New York. But obviously you know, it's a very very special place, and I have had sushi here, it's been fantastic. What about Munich? Anything else that you like in Munich? >> Well I mean in Munich, we have pork knuckles. >> Pork knuckles. (Christian laughing) Very similar sushi. >> What is also very fantastic, but we have the real, the real Oktoberfest in Munich, and it starts next week, mid-September, and I think it's unique in the world. So it's very special as well. >> Oktoberfest. >> Yes. >> Unfortunately, I'm not going this year, 'cause you didn't invite me, but-- (audience chuckling) How about, I think you've got a bit of a secret in relation to Oktoberfest, probably not in Munich, however. >> It's a secret, yes, but-- >> Are you going to share? >> Well I mean-- >> See how I'm putting you on the spot? >> In the 10 years, while living here in New York, I was a regular visitor of the Oktoberfest at the Lower East Side in Avenue C at Zum Schneider, where I actually met my wife, and she's German. >> Very good. So, how about a big round of applause? (audience applauding) Not so much for Christian, but more I think, obviously for his wife, who obviously had been drinking and consequently ended up with you. (all laughing) See you later, mate. >> That's the beauty about Oktoberfest, but yes. So first of all, good morning to everybody, and great to be back here in New York for a second Transform event. New York clearly is the melting pot of the world in terms of culture, nations, but also business professionals from all kind of different industries, and having this event here in New York City I believe is manifesting what we are trying to do here at Lenovo, is transform every aspect of our business and helping our customers on the journey of intelligent transformation. Last year, in our transformation on the device business, I talked about how the PC is transforming to personalized computing, and we've made a lot of progress in that journey over the last 12 months. One major change that we have made is we combined all our device business under one roof. So basically PCs, smart devices, and smart phones are now under the roof and under the intelligent device group. But from my perspective makes a lot of sense, because at the end of the day, all devices connect in the modern world into the cloud and are operating in a seamless way. But we are also moving from a device business what is mainly a hardware focus historically, more and more also into a solutions business, and I will give you during my speech a little bit of a sense of what we are trying to do, as we are trying to bring all these components closer together, and specifically also with our strengths on the data center side really build end-to-end customer solution. Ultimately, what we want to do is make our business, our customer's businesses faster, safer, and ultimately smarter as well. So I want to look a little bit back, because I really believe it's important to understand what's going on today on the device side. Many of us have still grown up with phones with terminals, ultimately getting their first desktop, their first laptop, their first mobile phone, and ultimately smartphone. Emails and internet improved our speed, how we could operate together, but still we were defined by linear technology advances. Today, the world has changed completely. Technology itself is not a limiting factor anymore. It is how we use technology going forward. The Internet is pervasive, and we are not yet there that we are always connected, but we are nearly always connected, and we are moving to the stage, that everything is getting connected all the time. Sharing experiences is the most driving force in our behavior. In our private life, sharing pictures, videos constantly, real-time around the world, with our friends and with our family, and you see the same behavior actually happening in the business life as well. Collaboration is the number-one topic if it comes down to workplace, and video and instant messaging, things that are coming from the consumer side are dominating the way we are operating in the commercial business as well. Most important beside technology, that a new generation of workforce has completely changed the way we are working. As the famous workforce the first generation of Millennials that have now fully entered in the global workforce, and the next generation, it's called Generation Z, is already starting to enter the global workforce. By 2025, 75 percent of the world's workforce will be composed out of two of these generations. Why is this so important? These two generations have been growing up using state-of-the-art IT technology during their private life, during their education, school and study, and are taking these learnings and taking these behaviors in the commercial workspace. And this is the number one force of change that we are seeing in the moment. Diverse workforces are driving this change in the IT spectrum, and for years in many of our customers' focus was their customer focus. Customer experience also in Lenovo is the most important thing, but we've realized that our own human capital is equally valuable in our customer relationships, and employee experience is becoming a very important thing for many of our customers, and equally for Lenovo as well. As you have heard YY, as we heard from YY, Lenovo is focused on intelligent transformation. What that means for us in the intelligent device business is ultimately starting with putting intelligence in all of our devices, smartify every single one of our devices, adding value to our customers, traditionally IT departments, but also focusing on their end users and building products that make their end users more productive. And as a world leader in commercial devices with more than 33 percent market share, we can solve problems been even better than any other company in the world. So, let's talk about transformation of productivity first. We are in a device-led world. Everything we do is connected. There's more interaction with devices than ever, but also with spaces who are increasingly becoming smart and intelligent. YY said it, by 2020 we have more than 20 billion connected devices in the world, and it will grow exponentially from there on. And users have unique personal choices for technology, and that's very important to recognize, and we call this concept a digital wardrobe. And it means that every single end-user in the commercial business is composing his personal wardrobe on an ongoing basis and is reconfiguring it based on the work he's doing and based where he's going and based what task he is doing. I would ask all of you to put out all the devices you're carrying in your pockets and in your bags. You will see a lot of you are using phones, tablets, laptops, but also cameras and even smartwatches. They're all different, but they have one underlying technology that is bringing it all together. Recognizing digital wardrobe dynamics is a core factor for us to put all the devices under one roof in IDG, one business group that is dedicated to end-user solutions across mobile, PC, but also software services and imaging, to emerging technologies like AR, VR, IoT, and ultimately a AI as well. A couple of years back there was a big debate around bring-your-own-device, what was called consumerization. Today consumerization does not exist anymore, because consumerization has happened into every single device we build in our commercial business. End users and commercial customers today do expect superior display performance, superior audio, microphone, voice, and touch quality, and have it all connected and working seamlessly together in an ease of use space. We are already deep in the journey of personalized computing today. But the center point of it has been for the last 25 years, the mobile PC, that we have perfected over the last 25 years, and has been the undisputed leader in mobility computing. We believe in the commercial business, the ThinkPad is still the core device of a digital wardrobe, and we continue to drive the success of the ThinkPad in the marketplace. We've sold more than 140 million over the last 26 years, and even last year we exceeded nearly 11 million units. That is about 21 ThinkPads per minute, or one Thinkpad every three seconds that we are shipping out in the market. It's the number one commercial PC in the world. It has gotten countless awards but we felt last year after Transform we need to build a step further, in really tailoring the ThinkPad towards the need of the future. So, we announced a new line of X1 Carbon and Yoga at CES the Consumer Electronics Show. And the reason is not we want to sell to consumer, but that we do recognize that a lot of CIOs and IT decision makers need to understand what consumers are really doing in terms of technology to make them successful. So, let's take a look at the video. (suspenseful music) >> When you're the number one business laptop of all time, your only competition is yourself. (wall shattering) And, that's different. Different, like resisting heat, ice, dust, and spills. Different, like sharper, brighter OLA display. The trackpoint that reinvented controls, and a carbon fiber roll cage to protect what's inside, built by an engineering and design team, doing the impossible for the last 25 years. This is the number one business laptop of all time, but it's not a laptop. It's a ThinkPad. (audience applauding) >> Thank you very much. And we are very proud that Lenovo ThinkPad has been selected as the best laptop in the world in the second year in a row. I think it's a wonderful tribute to what our engineers have been done on this one. And users do want awesome displays. They want the best possible audio, voice, and touch control, but some users they want more. What they want is super power, and I'm really proud to announce our newest member of the X1 family, and that's the X1 extreme. It's exceptionally featured. It has six core I9 intel chipset, the highest performance you get in the commercial space. It has Nvidia XTX graphic, it is a 4K UHD display with HDR with Dolby vision and Dolby Atmos Audio, two terabyte in SSD, so it is really the absolute Ferrari in terms of building high performance commercial computer. Of course it has touch and voice, but it is one thing. It has so much performance that it serves also a purpose that is not typical for commercial, and I know there's a lot of secret gamers also here in this room. So you see, by really bringing technology together in the commercial space, you're creating productivity solutions of one of a kind. But there's another category of products from a productivity perspective that is incredibly important in our commercial business, and that is the workstation business . Clearly workstations are very specifically designed computers for very advanced high-performance workloads, serving designers, architects, researchers, developers, or data analysts. And power and performance is not just about the performance itself. It has to be tailored towards the specific use case, and traditionally these products have a similar size, like a server. They are running on Intel Xeon technology, and they are equally complex to manufacture. We have now created a new category as the ultra mobile workstation, and I'm very proud that we can announce here the lightest mobile workstation in the industry. It is so powerful that it really can run AI and big data analysis. And with this performance you can go really close where you need this power, to the sensors, into the cars, or into the manufacturing places where you not only wannna read the sensors but get real-time analytics out of these sensors. To build a machine like this one you need customers who are really challenging you to the limit. and we're very happy that we had a customer who went on this journey with us, and ultimately jointly with us created this product. So, let's take a look at the video. (suspenseful music) >> My world involves pathfinding both the hardware needs to the various work sites throughout the company, and then finding an appropriate model of desktop, laptop, or workstation to match those needs. My first impressions when I first seen the ThinkPad P1 was I didn't actually believe that we could get everything that I was asked for inside something as small and light in comparison to other mobile workstations. That was one of the I can't believe this is real sort of moments for me. (engine roars) >> Well, it's better than general when you're going around in the wind tunnel, which isn't alway easy, and going on a track is not necessarily the best bet, so having a lightweight very powerful laptop is extremely useful. It can take a Xeon processor, which can support ECC from when we try to load a full car, and when we're analyzing live simulation results. through and RCFT post processor or example. It needs a pretty powerful machine. >> It's come a long way to be able to deliver this. I hate to use the word game changer, but it is that for us. >> Aston Martin has got a lot of different projects going. There's some pretty exciting projects and a pretty versatile range coming out. Having Lenovo as a partner is certainly going to ensure that future. (engine roars) (audience applauds) >> So, don't you think the Aston Martin design and the ThinkPad design fit very well together? (audience laughs) So if Q, would get a new laptop, I think you would get a ThinkPad X P1. So, I want to switch gears a little bit, and go into something in terms of productivity that is not necessarily on top of the mind or every end user but I believe it's on top of the mind of every C-level executive and of every CEO. Security is the number one threat in terms of potential risk in your business and the cost of cybersecurity is estimated by 2020 around six trillion dollars. That's more than the GDP of Japan and we've seen a significant amount of data breach incidents already this years. Now, they're threatening to take companies out of business and that are threatening companies to lose a huge amount of sensitive customer data or internal data. At Lenovo, we are taking security very, very seriously, and we run a very deep analysis, around our own security capabilities in the products that we are building. And we are announcing today a new brand under the Think umbrella that is called ThinkShield. Our goal is to build the world's most secure PC, and ultimately the most secure devices in the industry. And when we looked at this end-to-end, there is no silver bullet around security. You have to go through every aspect where security breaches can potentially happen. That is why we have changed the whole organization, how we look at security in our device business, and really have it grouped under one complete ecosystem of solutions, Security is always something where you constantly are getting challenged with the next potential breach the next potential technology flaw. As we keep innovating and as we keep integrating, a lot of our partners' software and hardware components into our products. So for us, it's really very important that we partner with companies like Intel, Microsoft, Coronet, Absolute, and many others to really as an example to drive full encryption on all the data seamlessly, to have multi-factor authentication to protect your users' identity, to protect you in unsecured Wi-Fi locations, or even simple things like innovation on the device itself, to and an example protect the camera, against usage with a little thing like a thinkShutter that you can shut off the camera. SO what I want to show you here, is this is the full portfolio of ThinkShield that we are announcing today. This is clearly not something I can even read to you today, but I believe it shows you the breadth of security management that we are announcing today. There are four key pillars in managing security end-to-end. The first one is your data, and this has a lot of aspects around the hardware and the software itself. The second is identity. The third is the security around online, and ultimately the device itself. So, there is a breakout on security and ThinkShield today, available in the afternoon, and encourage you to really take a deeper look at this one. The first pillar around productivity was the device, and around the device. The second major pillar that we are seeing in terms of intelligent transformation is the workspace itself. Employees of a new generation have a very different habit how they work. They split their time between travel, working remotely but if they do come in the office, they expect a very different office environment than what they've seen in the past in cubicles or small offices. They come into the office to collaborate, and they want to create ideas, and they really work in cross-functional teams, and they want to do it instantly. And what we've seen is there is a huge amount of investment that companies are doing today in reconfiguring real estate reconfiguring offices. And most of these kind of things are moving to a digital platform. And what we are doing, is we want to build an entire set of solutions that are just focused on making the workspace more productive for remote workforce, and to create technology that allow people to work anywhere and connect instantly. And the core of this is that we need to be, the productivity of the employee as high as possible, and make it for him as easy as possible to use these kind of technologies. Last year in Transform, I announced that we will enter the smart office space. By the end of last year, we brought the first product into the market. It's called the Hub 500. It's already deployed in thousands of our customers, and it's uniquely focused on Microsoft Skype for Business, and making meeting instantly happen. And the product is very successful in the market. What we are announcing today is the next generation of this product, what is the Hub 700, what has a fantastic audio quality. It has far few microphones, and it is usable in small office environment, as well as in major conference rooms, but the most important part of this new announcement is that we are also announcing a software platform, and this software platform allows you to run multiple video conferencing software solutions on the same platform. Many of you may have standardized for one software solution or for another one, but as you are moving in a world of collaborating instantly with partners, customers, suppliers, you always will face multiple software standards in your company, and Lenovo is uniquely positioned but providing a middleware platform for the device to really enable multiple of these UX interfaces. And there's more to come and we will add additional UX interfaces on an ongoing base, based on our customer requirements. But this software does not only help to create a better experience and a higher productivity in the conference room or the huddle room itself. It really will allow you ultimately to manage all your conference rooms in the company in one instance. And you can run AI technologies around how to increase productivity utilization of your entire conference room ecosystem in your company. You will see a lot more devices coming from the node in this space, around intelligent screens, cameras, and so on, and so on. The idea is really that Lenovo will become a core provider in the whole movement into the smart office space. But it's great if you have hardware and software that is really supporting the approach of modern IT, but one component that Kirk also mentioned is absolutely critical, that we are providing this to you in an as a service approach. Get it what you want, when you need it, and pay it in the amount that you're really using it. And within UIT there is also I think a new philosophy around IT management, where you're much more focused on the value that you are consuming instead of investing into technology. We are launched as a service two years back and we already have a significant number of customers running PC as a service, but we believe as a service will stretch far more than just the PC device. It will go into categories like smart office. It might go even into categories like phone, and it will definitely go also in categories like storage and server in terms of capacity management. I want to highlight three offerings that we are also displaying today that are sort of building blocks in terms of how we really run as a service. The first one is that we collaborated intensively over the last year with Microsoft to be the launch pilot for their Autopilot offering, basically deploying images easily in the same approach like you would deploy a new phone on the network. The purpose really is to make new imaging and enabling new PC as seamless as it's used to be in the phone industry, and we have a complete set of offerings, and already a significant number customers have deployed Autopilot with Lenovo. The second major offering is Premier Support, like in the in the server business, where Premier Support is absolutely critical to run critical infrastructure, we see a lot of our customers do want to have Premier Support for their end users, so they can be back into work basically instantly, and that you have the highest possible instant repair on every single device. And then finally we have a significant amount of time invested into understanding how the software as a service really can get into one philosophy. And many of you already are consuming software as a service in many different contracts from many different vendors, but what we've created is one platform that really can manage this all together. All these things are the foundation for a device as a service offering that really can manage this end-to-end. So, implementing an intelligent workplace can be really a daunting prospect depending on where you're starting from, and how big your company ultimately is. But how do you manage the transformation of technology workspace if you're present in 50 or more countries and you run an infrastructure for more than 100,000 people? Michelin, famous for their tires, infamous for their Michelin star restaurant rating, especially in New York, and instantly recognizable by the Michelin Man, has just doing that. Please welcome with me Damon McIntyre from Michelin to talk to us about the challenges and transforming collaboration and productivity. (audience applauding) (electronic dance music) Thank you, David. >> Thank you, thank you very much. >> We on? >> So, how do you feel here? >> Well good, I want to thank you first of all for your partnership and the devices you create that helped us design, manufacture, and distribute the best tire in the world, okay? I just had to say it and put out there, alright. And I was wondering, were those Michelin tires on that Aston Martin? >> I'm pretty sure there is no other tire that would fit to that. >> Yeah, no, thank you, thank you again, and thank you for the introduction. >> So, when we talk about the transformation happening really in the workplace, the most tangible transformation that you actually see is the drastic change that companies are doing physically. They're breaking down walls. They're removing cubes, and they're moving to flexible layouts, new desks, new huddle rooms, open spaces, but the underlying technology for that is clearly not so visible very often. So, tell us about Michelin's strategy, and the technology you are deploying to really enable this corporation. >> So we, so let me give a little bit a history about the company to understand the daunting tasks that we had before us. So we have over 114,000 people in the company under 170 nationalities, okay? If you go to the corporate office in France, it's Clermont. It's about 3,000 executives and directors, and what have you in the marketing, sales, all the way up to the chain of the global CIO, right? Inside of the Americas, we merged in Americas about three years ago. Now we have the Americas zone. There's about 28,000 employees across the Americas, so it's really, it's really hard in a lot of cases. You start looking at the different areas that you lose time, and you lose you know, your productivity and what have you, so there, it's when we looked at different aspects of how we were going to manage the meeting rooms, right? because we have opened up our areas of workspace, our CIO, CEOs in our zones will no longer have an office. They'll sit out in front of everybody else and mingle with the crowd. So, how do you take those spaces that were originally used by an individual but now turn them into like meeting rooms? So, we went through a large process, and looked at the Hub 500, and that really met our needs, because at the end of the day what we noticed was, it was it was just it just worked, okay? We've just added it to the catalog, so we're going to be deploying it very soon, and I just want to again point that I know everybody struggles with this, and if you look at all the minutes that you lose in starting up a meeting, and we know you know what I'm talking about when I say this, it equates to many many many dollars, okay? And so at the end the day, this product helps us to be more efficient in starting up the meeting, and more productive during the meeting. >> Okay, it's very good to hear. Another major trend we are seeing in IT departments is taking a more hands-off approach to hardware. We're seeing new technologies enable IT to create a more efficient model, how IT gets hardware in the hands of end-users, and how they are ultimately supporting themselves. So what's your strategy around the lifecycle management of the devices? >> So yeah you mentioned, again, we'll go back to the 114,000 employees in the company, right? You imagine looking at all the devices we use. I'm not going to get into the number of devices we have, but we have a set number that we use, and we have to go through a process of deploying these devices, which we right now service our own image. We build our images, we service them through our help desk and all that process, and we go through it. If you imagine deploying 25,000 PCs in a year, okay? The time and the daunting task that's behind all that, you can probably add up to 20 or 30 people just full-time doing that, okay? So, with partnering with Lenovo and their excellent technology, their technical teams, and putting together the whole process of how we do imaging, it now lifts that burden off of our folks, and it shifts it into a more automated process through the cloud, okay? And, it's with the Autopilot on the end of the project, we'll have Autopilot fully engaged, but what I really appreciate is how Lenovo really, really kind of got with us, and partnered with us for the whole process. I mean it wasn't just a partner between Michelin and Lenovo. Microsoft was also partnered during that whole process, and it really was a good project that we put together, and we hope to have something in a full production mode next year for sure. >> So, David thank you very, very much to be here with us on stage. What I really want to say, customers like you, who are always challenging us on every single aspect of our capabilities really do make the big difference for us to get better every single day and we really appreciate the partnership. >> Yeah, and I would like to say this is that I am, I'm doing what he's exactly said he just said. I am challenging Lenovo to show us how we can innovate in our work space with your devices, right? That's a challenge, and it's going to be starting up next year for sure. We've done some in the past, but I'm really going to challenge you, and my whole aspect about how to do that is bring you into our workspace. Show you how we make how we go through the process of making tires and all that process, and how we distribute those tires, so you can brainstorm, come back to the table and say, here's a device that can do exactly what you're doing right now, better, more efficient, and save money, so thank you. >> Thank you very much, David. (audience applauding) Well it's sometimes really refreshing to get a very challenging customers feedback. And you know, we will continue to grow this business together, and I'm very confident that your challenge will ultimately help to make our products even more seamless together. So, as we now covered productivity and how we are really improving our devices itself, and the transformation around the workplace, there is one pillar left I want to talk about, and that's really, how do we make businesses smarter than ever? What that really means is, that we are on a journey on trying to understand our customer's business, deeper than ever, understanding our customer's processes even better than ever, and trying to understand how we can help our customers to become more competitive by injecting state-of-the-art technology in this intelligent transformation process, into core processes. But this cannot be done without talking about a fundamental and that is the journey towards 5G. I really believe that 5G is changing everything the way we are operating devices today, because they will be connected in a way like it has never done before. YY talked about you know, 20 times 10 times the amount of performance. There are other studies that talk about even 200 times the performance, how you can use these devices. What it will lead to ultimately is that we will build devices that will be always connected to the cloud. And, we are preparing for this, and Kirk already talked about, and how many operators in the world we already present with our Moto phones, with how many Telcos we are working already on the backend, and we are working on the device side on integrating 5G basically into every single one of our product in the future. One of the areas that will benefit hugely from always connected is the world of virtual reality and augmented reality. And I'm going to pick here one example, and that is that we have created a commercial VR solution for classrooms and education, and basically using consumer type of product like our Mirage Solo with Daydream and put a solution around this one that enables teachers and schools to use these products in the classroom experience. So, students now can have immersive learning. They can studying sciences. They can look at environmental issues. They can exploring their careers, or they can even taking a tour in the next college they're going to go after this one. And no matter what grade level, this is how people will continue to learn in the future. It's quite a departure from the old world of textbooks. In our area that we are looking is IoT, And as YY already elaborated, we are clearly learning from our own processes around how we improve our supply chain and manufacturing and how we improve also retail experience and warehousing, and we are working with some of the largest companies in the world on pilots, on deploying IoT solutions to make their businesses, their processes, and their businesses, you know, more competitive, and some of them you can see in the demo environment. Lenovo itself already is managing 55 million devices in an IoT fashion connecting to our own cloud, and constantly improving the experience by learning from the behavior of these devices in an IoT way, and we are collecting significant amount of data to really improve the performance of these systems and our future generations of products on a ongoing base. We have a very strong partnership with a company called ADLINK from Taiwan that is one of the leading manufacturers of manufacturing PC and hardened devices to create solutions on the IoT platform. The next area that we are very actively investing in is commercial augmented reality. I believe augmented reality has by far more opportunity in commercial than virtual reality, because it has the potential to ultimately improve every single business process of commercial customers. Imagine in the future how complex surgeries can be simplified by basically having real-time augmented reality information about the surgery, by having people connecting into a virtual surgery, and supporting the surgery around the world. Visit a furniture store in the future and see how this furniture looks in your home instantly. Doing some maintenance on some devices yourself by just calling the company and getting an online manual into an augmented reality device. Lenovo is exploring all kinds of possibilities, and you will see a solution very soon from Lenovo. Early when we talked about smart office, I talked about the importance of creating a software platform that really run all these use cases for a smart office. We are creating a similar platform for augmented reality where companies can develop and run all their argumented reality use cases. So you will see that early in 2019 we will announce an augmented reality device, as well as an augmented reality platform. So, I know you're very interested on what exactly we are rolling out, so we will have a first prototype view available there. It's still a codename project on the horizon, and we will announce it ultimately in 2019, but I think it's good for you to take a look what we are doing here. So, I just wanted to give you a peek on what we are working beyond smart office and the device productivity in terms of really how we make businesses smarter. It's really about increasing productivity, providing you the most secure solutions, increase workplace collaboration, increase IT efficiency, using new computing devices and software and services to make business smarter in the future. There's no other company that will enable to offer what we do in commercial. No company has the breadth of commercial devices, software solutions, and the same data center capabilities, and no other company can do more for your intelligent transformation than Lenovo. Thank you very much. (audience applauding) >> Thanks mate, give me that. I need that. Alright, ladies and gentlemen, we are done. So firstly, I've got a couple of little housekeeping pieces at the end of this and then we can go straight into going and experiencing some of the technology we've got on the left-hand side of the room here. So, I want to thank Christian obviously. Christian, awesome as always, some great announcements there. I love the P1. I actually like the Aston Martin a little bit better, but I'll take either if you want to give me one for free. I'll take it. We heard from YY obviously about the industry and how the the fourth Industrial Revolution is impacting us all from a digital transformation perspective, and obviously Kirk on DCG, the great NetApp announcement, which is going to be really exciting, actually that Twitter and some of the social media panels are absolutely going crazy, so it's good to see that the industry is really taking some impact. Some of the publications are really great, so thank you for the media who are obviously in the room publishing right no. But now, I really want to say it's all of your turn. So, all of you up the back there who are having coffee, it's your turn now. I want everyone who's sitting down here after this event move into there, and really take advantage of the 15 breakouts that we've got set there. There are four breakout sessions from a time perspective. I want to try and get you all out there at least to use up three of them and use your fourth one to get out and actually experience some of the technology. So, you've got four breakout sessions. A lot of the breakout sessions are actually done twice. If you have not downloaded the app, please download the app so you can actually see what time things are going on and make sure you're registering correctly. There's a lot of great experience of stuff out there for you to go do. I've got one quick video to show you on some of the technology we've got and then we're about to close. Alright, here we are acting crazy. Now, you can see obviously, artificial intelligence machine learning in the browser. God, I hate that dance, I'm not a Millenial at all. It's effectively going to be implemented by healthcare. I want you to come around and test that out. Look at these two guys. This looks like a Lenovo management meeting to be honest with you. These two guys are actually concentrating, using their brain power to race each others in cars. You got to come past and give that a try. Give that a try obviously. Fantastic event here, lots of technology for you to experience, and great partners that have been involved as well. And so, from a Lenovo perspective, we've had some great alliance partners contribute, including obviously our number one partner, Intel, who's been a really big loyal contributor to us, and been a real part of our success here at Transform. Excellent, so please, you've just seen a little bit of tech out there that you can go and play with. I really want you, I mean go put on those black things, like Scott Hawkins our chief marketing officer from Lenovo's DCG business was doing and racing around this little car with his concentration not using his hands. He said it's really good actually, but as soon as someone comes up to speak to him, his car stops, so you got to try and do better. You got to try and prove if you can multitask or not. Get up there and concentrate and talk at the same time. 62 different breakouts up there. I'm not going to go into too much detai, but you can see we've got a very, very unusual numbering system, 18 to 18.8. I think over here we've got a 4849. There's a 4114. And then up here we've got a 46.1 and a 46.2. So, you need the decoder ring to be able to understand it. Get over there have a lot of fun. Remember the boat leaves today at 4:00 o'clock, right behind us at the pier right behind us here. There's 400 of us registered. Go onto the app and let us know if there's more people coming. It's going to be a great event out there on the Hudson River. Ladies and gentlemen that is the end of your keynote. I want to thank you all for being patient and thank all of our speakers today. Have a great have a great day, thank you very much. (audience applauding) (upbeat music) ♪ Ba da bop bop bop ♪ ♪ Ba da bop bop bop ♪ ♪ Ba da bop bop bop ♪ ♪ Ba da bop bop bop ♪ ♪ Ba da bop bop bop ♪ ♪ Ba da bop bop bop ♪ ♪ Ba da bop bop bop ba do ♪

Published Date : Sep 13 2018

SUMMARY :

and those around you, Ladies and gentlemen, we ask that you please take an available seat. Ladies and gentlemen, once again we ask and software that transform the way you collaborate, Good morning everyone! Ooh, that was pretty good actually, and have a look at all of the breakout sessions. and the industries demand to be more intelligent, and the strategies that we have going forward I'm going to give you the stage and allow you to say is that the first products are orderable and being one of the largest device companies in the world. and exactly what's going on with that. I think I'll need that. Okay, Christian, so obviously just before we get down, You're in Munich? and it's a great place to live and raise kids, And I miss it a lot, but I still believe the best sushi in the world and I have had sushi here, it's been fantastic. (Christian laughing) the real Oktoberfest in Munich, in relation to Oktoberfest, at the Lower East Side in Avenue C at Zum Schneider, and consequently ended up with you. and is reconfiguring it based on the work he's doing and a carbon fiber roll cage to protect what's inside, and that is the workstation business . and then finding an appropriate model of desktop, in the wind tunnel, which isn't alway easy, I hate to use the word game changer, is certainly going to ensure that future. And the core of this is that we need to be, and distribute the best tire in the world, okay? that would fit to that. and thank you for the introduction. and the technology you are deploying and more productive during the meeting. how IT gets hardware in the hands of end-users, You imagine looking at all the devices we use. and we really appreciate the partnership. and it's going to be starting up next year for sure. and how many operators in the world Ladies and gentlemen that is the end of your keynote.

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Tim Smith, AppNexus | BigData NYC 2017


 

>> Announcer: Live, from Midtown Manhattan, it's theCUBE. Covering Big Data, New York City, 2017. Brought to you by SiliconANGLE Media and its ecosystem sponsors. >> Okay welcome back, everyone. Live in Manhattan, New York City, in Hell's Kitchen, this is theCUBE's special event, our annual CUBE-Wikibon Research Big Data event in Manhattan. Alongside Strata, Hadoop; formerly Hadoop World, now called Strata Data, as the world continues. This is our annual event; it's our fifth year here, sixth overall, wanted to kind of move from uptown. I'm John Furrier, the co-host of theCUBE, with Peter Burris, Head of Research at SiliconANGLE and GM of Wikibon Research. Our next guest is Tim Smith, who's the SVP of technical operations at AppNexus; technical operations for large scale is an understatement. But before we get going; Tim, just talk about what AppNexus as a company, what you guys do, what's the core business? >> Sure, AppNexus is the second largest digital advertising marketplace after google. We're an internet technology company that harnessed, we harness data and machine learning to power the companies that comprise the open internet. We began by building a powerful technology platform, in which we embedded core capabilities, tools and features. With me so far? >> Yeah, we got it. >> Okay, on top of that platform, we built a core suite of cloud-based enterprise products that enable the buying and selling of digital advertising, and a scale-transparent and low-cost marketplace where other companies can transact; either using our enterprise products, or those offered by other companies. If you want to hear a little about the daily peaks, peak feeds and speeds, it is Strata, we should probably talk about that. We do about 11.8 billion impressions transacted on a daily basis. Each of those is a real-time auction conducted in a fraction of a second, well under half a second. We see about 225 billion impressions per day, and we handle about 5 million queries per second at peak load. We produce about 150 terabytes of data each day, and we move about 400 gigabits into and out of the internet at peak, all those numbers are daily peaks. Makes sense? >> Yep. >> Okay, so by way of comparison, which might be useful for people, I believe the NYSE currently does roughly 2 million trades per day. So if we round that up to 3 million trades a day and assume the NYSE were to conduct that volume every single day of the year; 7 days a week, 365 days a year, that'd be about a billion trades a year. Similarly, I believe Visa did about 28-and-a-half billion transactions in their fiscal third quarter. I'll round that up to 30 billion, and average it out to about 333 million transactions per day and annualize it to about 4 billion transactions per year. Little bit of math, but as I mentioned, AppNexus does an excess of 10 billion transactions per day. And so it seems reasonable to say that AppNexus does roughly 10 times the transaction volume in one day, than the NYSE does in a year. And similarly, it seems reasonable to say that AppNexus daily does more than two times the transaction volume that Visa does in a year. Obviously, these are all just very rough numbers based on publicly available information about the NYSE and Visa, and both the NYSE and Visa do far, far more volume than AppNexus when measured in terms of dollars. So given our volumes, it's imperative that AppNexus does each transaction with the maximum efficiency and lowest reasonable possible cost, and that is one of the most challenging aspects of my job. >> So thanks for spending the time to give the overview. There's a lot of data; I mean 10 billion a day is massive volume. I mean the internet, and you see the scale, is insane. We're in a new era right now of web-scale. We've seen it in Facebook, and it's enormous. It's only going to get bigger, right? So on the online ad tech, you guys are essentially doing like a Google model, that's not everything but Google, which is still huge numbers. Then you include Microsoft and everybody else. Really heavy lifting, IT-like situation. What's the environment like? And just talk about, you know, what's it like for you guys. Because you got a lot of opp's, I mean terms of dev opp's. You can't break anything, because that 10 billion transaction or near, it's a significant impact. So you have to have everything buttoned-up super tight, yet you got to innovate and grow with the future growth. What's the IT environment like? >> It's interesting. We have about 8,000 servers spread across about seven data centers on three continents, and we run, as you mentioned, around the clock. There's no closing bell; downtime is not acceptable. So when you look at our environment, you're talking about four major categories of server complexes. We have real-time processing, which is the actual ad serving. We have a data pipeline, which is what we call our big data environment. We also have client-facing environment and an infrastructure environment. So we use a lot of different tools and applications, but I think the most relevant ones to this discussion are Hadoop and its friends HDFS, and Hive and Spark. And then we use the Vertica Analytics Platform. And together Hadoop and its friends, and Vertica comprise our entire data pipeline. They're both very disk-intensive. They're cluster based applications, and it's a lot of challenge to keep them up and running. >> So what are some of those challenges? Just explain a little bit, because you also have a lot of opportunity. I mean, it's money flowing through the air, basically; digital air, if you will. I mean, they got a lot of stuff happening. Take us through the challenges. >> You know, our biggest apps are all clustered. And all of our clusters are built with commodity servers, just like a lot of other environments. The big data app clusters traditionally have had internal disks, while almost all of our other servers are very light on disk. One of the biggest challenges is, since the server is the fundamental building block of a cluster, then regardless of whether you need more compute or more storage, you always have to add more servers to get it. That really limits flexibility and creates a lot of inefficiencies, and I really, really am obsessive about reducing and eliminating inefficiencies. So, with me so far? >> Yep. >> Great. The inefficiencies result from two major factors. First, not all workloads require the same ratio of compute to storage. Some workloads are more compute-intensive, and others are really less dependent on storage, while other workloads require a lot more storage. So we have to use standard server configurations and as a result, we wind up with underutilized compute and storage. This is undesirable, it's inefficient, yet given our scale, we have to use standardized configurations. So that's the first big challenge. The second is the compute to disk ratio. It's generally fixed when you buy the servers. Yes, we can certainly add more disks in the field, but that's a labor intensive, and it's complicated from a logistics and an asset management standpoint, and you're fundamentally limited by the number of disk slots in the server. So now you're right back into the trap of more storage requires more servers, regardless of whether you need more compute or not. And then you compound the inefficiencies. >> Couldn't you just move the resources from, unused resources, from one cluster to the other? >> I've been asked that a lot; and no, it's just not that simple. Each application cluster becomes a silo due to its configuration of storage and compute. This means you just can't move servers from clusters because the clusters are optimized for the workloads, and the fact that you can't move resources from one cluster to another, it's more inefficiencies. And then they're compounded over time since workloads change, and the ideal ratio of compute-to-storage changes. And the end result is unused resources trapped in silos and configurations that are no longer optimized for your workload. And there's only really one solution that we've been able to find. And to paraphrase an orator far, far more talented than I am, namely Ronald Reagan, we need to open this gate, tear down these silos. The silos just have to go away. They fundamentally limit flexibility and efficiency. >> What were some of the other issues caused by using servers with internal drives? >> You have more maintenance, you've got to deal with the logistics. But the biggest problem is service and storage have significantly different life cycles. Servers typically have a three year life cycle before they're obsolete. Storage typically is four to six years. You can sometimes stretch that a little further with the storage. Inside the servers that are replaced every 3 years, we end up replacing storage before the end of its effective lifetime; that's inefficient. Further, since the storage is inside the servers, we have to do massive data migrations when we replace servers. Migrations, they're time consuming, they're logistically difficult, and they're high risk. >> So how did DriveScale help you guys? Because you guys certainly have a challenging environment, you laid out the the story, and we appreciate that. How did DriveScale help you with the challenges? >> Well, what we really wanted to do was disaggregate storage from servers, and DriveScale enables us to do that. Disaggregating resources is a new term in the industry, but I think lot of people are focusing on it. I can explain it if you think that would make sense. >> What do you mean by disaggregating resources? Can you explain that, and how it works? >> Sure, so instead of buying servers with internal drives, we now buy diskless servers with JBODs. And DriveScale lets us easily compose servers with whatever amount of disk storage we need, from the server resource pool and the disk resource pool; and they're separate pools. This means we have the right balance of compute and storage for each workload, and we can easily adjust it over time. And all of this is done via software, so it's easy to do with a GUI or in our case, at our scale, scripting. And it's done on demand, and it's much more efficient. >> How does it help you with the underutilized resource challenge you mentioned earlier? >> Well, since we can add and remove resources from each cluster, we can manage exactly how much compute power and storage is deployed for each workload. Since this is all done via software, it can be done quickly and easily. We don't have to send a technician into a data center to physically swap drives, add drives, move drives. It's all done via software and it's very, very efficient. >> Can you move resources between silos? >> Well, yes and no. First off, our goal is no more silos. That said, we still have clusters, and once we completely migrate to DriveScale, all of our compute and storage resources will be consolidated into just a few common pools. And disk storage will no longer differentiate pools; thus, we have fewer pools. For more, we have fewer pools and can use the resources in each pool for more workloads. And when our needs change and they always do, we can reallocate resources as needed. >> What of the life cycle management challenge? How you guys address that? >> Well that's addressed with DriveScale. The compute and the storage are now disaggregated or separated into diskless servers and JBODs, so we can upgrade one without touching the other. We want to upgrade servers to take advantage of new processors or new memory architectures, we just replace the servers, re-combine the disks with the new servers, and we're back up and operating. It saves the cost of buying new disks when we don't need to, and it also simplifies logistics and reduces risk, as we no longer have to run the old plant and the new plant concurrently, and do a complicated data migration. >> What about this qualifying server and storage vendors? Do you still do that? Or how's that impact -- >> We actually don't have to do it. We're still using the same server vendor. We've used Dell for many, many years, we continue to use them. We are using them for storage and there was no real work, we just had to add DriveScale into the mix. >> What's it like working with DriveScale? >> They're really wonderful to work with. They have a really seasoned team. They were at Sun Microsystems and Cisco, they built some of the really foundational products that changed the internet, that the internet was built on. They're really talented, they really bright, and they're really focused on customer success. >> Great story, thanks for sharing that. My final question for you is, you guys have a very big, awesome environment, you've got a lot of scale there. It's great for a startup to get into an environment like this, because one, they could get access to the data, work with a good team like you have. What's it like working with a startup? >> You know it's always challenging at first; too many things to do. >> They got talented guys. Most of the startups, those early day startups, they got all their A players out there. >> They have their A players, and we've been very pleased working with them. We're dealing with the top talent, some of the top talent in the industry, that created the industry. They have a proven track record. We really don't have any concerns, we know they're committed to our success and they have a great team, and great investors. >> A final, final question. For your friends out there are watching, and other practitioners who are trying to run things at scale with a cloud. What's your advice to them? You've been operating at scale, and a lot of, billions of transactions, I mean huge; it's only going to get bigger. Put your IT friendly advice hat on. What's the mindset of operators out there, technical op's, as dev op's comes in seeing a lot of that. What do people need to be thinking about to run at scale? >> There's no magic silver bullet. There's no magic answers. The public cloud is very helpful in a lot of ways, but you really have to think hard about your economics, you have to think about your scale. You just have to be sure that you're going into each decision knowing that you've looked at the costs and the benefits, the performance, the risks, and you don't expect there to be simple answers. >> Yeah, there's no magic beans as they say. You've got to make it work for the business. >> No magic beans, I wish there were. >> Tim, thanks so much for the story. Appreciate the commentaries. Live coverage at Big Data NYC, it's theCUBE. Be back with more after this short break. (upbeat techno music)

Published Date : Sep 27 2017

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AI for Good Panel - Precision Medicine - SXSW 2017 - #IntelAI - #theCUBE


 

>> Welcome to the Intel AI Lounge. Today, we're very excited to share with you the Precision Medicine panel discussion. I'll be moderating the session. My name is Kay Erin. I'm the general manager of Health and Life Sciences at Intel. And I'm excited to share with you these three panelists that we have here. First is John Madison. He is a chief information medical officer and he is part of Kaiser Permanente. We're very excited to have you here. Thank you, John. >> Thank you. >> We also have Naveen Rao. He is the VP and general manager for the Artificial Intelligence Solutions at Intel. He's also the former CEO of Nervana, which was acquired by Intel. And we also have Bob Rogers, who's the chief data scientist at our AI solutions group. So, why don't we get started with our questions. I'm going to ask each of the panelists to talk, introduce themselves, as well as talk about how they got started with AI. So why don't we start with John? >> Sure, so can you hear me okay in the back? Can you hear? Okay, cool. So, I am a recovering evolutionary biologist and a recovering physician and a recovering geek. And I implemented the health record system for the first and largest region of Kaiser Permanente. And it's pretty obvious that most of the useful data in a health record, in lies in free text. So I started up a natural language processing team to be able to mine free text about a dozen years ago. So we can do things with that that you can't otherwise get out of health information. I'll give you an example. I read an article online from the New England Journal of Medicine about four years ago that said over half of all people who have had their spleen taken out were not properly vaccinated for a common form of pneumonia, and when your spleen's missing, you must have that vaccine or you die a very sudden death with sepsis. In fact, our medical director in Northern California's father died of that exact same scenario. So, when I read the article, I went to my structured data analytics team and to my natural language processing team and said please show me everybody who has had their spleen taken out and hasn't been appropriately vaccinated and we ran through about 20 million records in about three hours with the NLP team, and it took about three weeks with a structured data analytics team. That sounds counterintuitive but it actually happened that way. And it's not a competition for time only. It's a competition for quality and sensitivity and specificity. So we were able to indentify all of our members who had their spleen taken out, who should've had a pneumococcal vaccine. We vaccinated them and there are a number of people alive today who otherwise would've died absent that capability. So people don't really commonly associate natural language processing with machine learning, but in fact, natural language processing relies heavily and is the first really, highly successful example of machine learning. So we've done dozens of similar projects, mining free text data in millions of records very efficiently, very effectively. But it really helped advance the quality of care and reduce the cost of care. It's a natural step forward to go into the world of personalized medicine with the arrival of a 100-dollar genome, which is actually what it costs today to do a full genome sequence. Microbiomics, that is the ecosystem of bacteria that are in every organ of the body actually. And we know now that there is a profound influence of what's in our gut and how we metabolize drugs, what diseases we get. You can tell in a five year old, whether or not they were born by a vaginal delivery or a C-section delivery by virtue of the bacteria in the gut five years later. So if you look at the complexity of the data that exists in the genome, in the microbiome, in the health record with free text and you look at all the other sources of data like this streaming data from my wearable monitor that I'm part of a research study on Precision Medicine out of Stanford, there is a vast amount of disparate data, not to mention all the imaging, that really can collectively produce much more useful information to advance our understanding of science, and to advance our understanding of every individual. And then we can do the mash up of a much broader range of science in health care with a much deeper sense of data from an individual and to do that with structured questions and structured data is very yesterday. The only way we're going to be able to disambiguate those data and be able to operate on those data in concert and generate real useful answers from the broad array of data types and the massive quantity of data, is to let loose machine learning on all of those data substrates. So my team is moving down that pathway and we're very excited about the future prospects for doing that. >> Yeah, great. I think that's actually some of the things I'm very excited about in the future with some of the technologies we're developing. My background, I started actually being fascinated with computation in biological forms when I was nine. Reading and watching sci-fi, I was kind of a big dork which I pretty much still am. I haven't really changed a whole lot. Just basically seeing that machines really aren't all that different from biological entities, right? We are biological machines and kind of understanding how a computer works and how we engineer those things and trying to pull together concepts that learn from biology into that has always been a fascination of mine. As an undergrad, I was in the EE, CS world. Even then, I did some research projects around that. I worked in the industry for about 10 years designing chips, microprocessors, various kinds of ASICs, and then actually went back to school, quit my job, got a Ph.D. in neuroscience, computational neuroscience, to specifically understand what's the state of the art. What do we really understand about the brain? And are there concepts that we can take and bring back? Inspiration's always been we want to... We watch birds fly around. We want to figure out how to make something that flies. We extract those principles, and then build a plane. Don't necessarily want to build a bird. And so Nervana's really was the combination of all those experiences, bringing it together. Trying to push computation in a new a direction. Now, as part of Intel, we can really add a lot of fuel to that fire. I'm super excited to be part of Intel in that the technologies that we were developing can really proliferate and be applied to health care, can be applied to Internet, can be applied to every facet of our lives. And some of the examples that John mentioned are extremely exciting right now and these are things we can do today. And the generality of these solutions are just really going to hit every part of health care. I mean from a personal viewpoint, my whole family are MDs. I'm sort of the black sheep of the family. I don't have an MD. And it's always been kind of funny to me that knowledge is concentrated in a few individuals. Like you have a rare tumor or something like that, you need the guy who knows how to read this MRI. Why? Why is it like that? Can't we encapsulate that knowledge into a computer or into an algorithm, and democratize it. And the reason we couldn't do it is we just didn't know how. And now we're really getting to a point where we know how to do that. And so I want that capability to go to everybody. It'll bring the cost of healthcare down. It'll make all of us healthier. That affects everything about our society. So that's really what's exciting about it to me. >> That's great. So, as you heard, I'm Bob Rogers. I'm chief data scientist for analytics and artificial intelligence solutions at Intel. My mission is to put powerful analytics in the hands of every decision maker and when I think about Precision Medicine, decision makers are not just doctors and surgeons and nurses, but they're also case managers and care coordinators and probably most of all, patients. So the mission is really to put powerful analytics and AI capabilities in the hands of everyone in health care. It's a very complex world and we need tools to help us navigate it. So my background, I started with a Ph.D. in physics and I was computer modeling stuff, falling into super massive black holes. And there's a lot of applications for that in the real world. No, I'm kidding. (laughter) >> John: There will be, I'm sure. Yeah, one of these days. Soon as we have time travel. Okay so, I actually, about 1991, I was working on my post doctoral research, and I heard about neural networks, these things that could compute the way the brain computes. And so, I started doing some research on that. I wrote some papers and actually, it was an interesting story. The problem that we solved that got me really excited about neural networks, which have become deep learning, my office mate would come in. He was this young guy who was about to go off to grad school. He'd come in every morning. "I hate my project." Finally, after two weeks, what's your project? What's the problem? It turns out he had to circle these little fuzzy spots on these images from a telescope. So they were looking for the interesting things in a sky survey, and he had to circle them and write down their coordinates all summer. Anyone want to volunteer to do that? No? Yeah, he was very unhappy. So we took the first two weeks of data that he created doing his work by hand, and we trained an artificial neural network to do his summer project and finished it in about eight hours of computing. (crowd laughs) And so he was like yeah, this is amazing. I'm so happy. And we wrote a paper. I was the first author of course, because I was the senior guy at age 24. And he was second author. His first paper ever. He was very, very excited. So we have to fast forward about 20 years. His name popped up on the Internet. And so it caught my attention. He had just won the Nobel Prize in physics. (laughter) So that's where artificial intelligence will get you. (laughter) So thanks Naveen. Fast forwarding, I also developed some time series forecasting capabilities that allowed me to create a hedge fund that I ran for 12 years. After that, I got into health care, which really is the center of my passion. Applying health care to figuring out how to get all the data from all those siloed sources, put it into the cloud in a secure way, and analyze it so you can actually understand those cases that John was just talking about. How do you know that that person had had a splenectomy and that they needed to get that pneumovax? You need to be able to search all the data, so we used AI, natural language processing, machine learning, to do that and then two years ago, I was lucky enough to join Intel and, in the intervening time, people like Naveen actually thawed the AI winter and we're really in a spring of amazing opportunities with AI, not just in health care but everywhere, but of course, the health care applications are incredibly life saving and empowering so, excited to be here on this stage with you guys. >> I just want to cue off of your comment about the role of physics in AI and health care. So the field of microbiomics that I referred to earlier, bacteria in our gut. There's more bacteria in our gut than there are cells in our body. There's 100 times more DNA in that bacteria than there is in the human genome. And we're now discovering a couple hundred species of bacteria a year that have never been identified under a microscope just by their DNA. So it turns out the person who really catapulted the study and the science of microbiomics forward was an astrophysicist who did his Ph.D. in Steven Hawking's lab on the collision of black holes and then subsequently, put the other team in a virtual reality, and he developed the first super computing center and so how did he get an interest in microbiomics? He has the capacity to do high performance computing and the kind of advanced analytics that are required to look at a 100 times the volume of 3.2 billion base pairs of the human genome that are represented in the bacteria in our gut, and that has unleashed the whole science of microbiomics, which is going to really turn a lot of our assumptions of health and health care upside down. >> That's great, I mean, that's really transformational. So a lot of data. So I just wanted to let the audience know that we want to make this an interactive session, so I'll be asking for questions in a little bit, but I will start off with one question so that you can think about it. So I wanted to ask you, it looks like you've been thinking a lot about AI over the years. And I wanted to understand, even though AI's just really starting in health care, what are some of the new trends or the changes that you've seen in the last few years that'll impact how AI's being used going forward? >> So I'll start off. There was a paper published by a guy by the name of Tegmark at Harvard last summer that, for the first time, explained why neural networks are efficient beyond any mathematical model we predict. And the title of the paper's fun. It's called Deep Learning Versus Cheap Learning. So there were two sort of punchlines of the paper. One is is that the reason that mathematics doesn't explain the efficiency of neural networks is because there's a higher order of mathematics called physics. And the physics of the underlying data structures determined how efficient you could mine those data using machine learning tools. Much more so than any mathematical modeling. And so the second thing that was a reel from that paper is that the substrate of the data that you're operating on and the natural physics of those data have inherent levels of complexity that determine whether or not a 12th layer of neural net will get you where you want to go really fast, because when you do the modeling, for those math geeks in the audience, a factorial. So if there's 12 layers, there's 12 factorial permutations of different ways you could sequence the learning through those data. When you have 140 layers of a neural net, it's a much, much, much bigger number of permutations and so you end up being hardware-bound. And so, what Max Tegmark basically said is you can determine whether to do deep learning or cheap learning based upon the underlying physics of the data substrates you're operating on and have a good insight into how to optimize your hardware and software approach to that problem. >> So another way to put that is that neural networks represent the world in the way the world is sort of built. >> Exactly. >> It's kind of hierarchical. It's funny because, sort of in retrospect, like oh yeah, that kind of makes sense. But when you're thinking about it mathematically, we're like well, anything... The way a neural can represent any mathematical function, therfore, it's fully general. And that's the way we used to look at it, right? So now we're saying, well actually decomposing the world into different types of features that are layered upon each other is actually a much more efficient, compact representation of the world, right? I think this is actually, precisely the point of kind of what you're getting at. What's really exciting now is that what we were doing before was sort of building these bespoke solutions for different kinds of data. NLP, natural language processing. There's a whole field, 25 plus years of people devoted to figuring out features, figuring out what structures make sense in this particular context. Those didn't carry over at all to computer vision. Didn't carry over at all to time series analysis. Now, with neural networks, we've seen it at Nervana, and now part of Intel, solving customers' problems. We apply a very similar set of techniques across all these different types of data domains and solve them. All data in the real world seems to be hierarchical. You can decompose it into this hierarchy. And it works really well. Our brains are actually general structures. As a neuroscientist, you can look at different parts of your brain and there are differences. Something that takes in visual information, versus auditory information is slightly different but they're much more similar than they are different. So there is something invariant, something very common between all of these different modalities and we're starting to learn that. And this is extremely exciting to me trying to understand the biological machine that is a computer, right? We're figurig it out, right? >> One of the really fun things that Ray Chrisfall likes to talk about is, and it falls in the genre of biomimmicry, and how we actually replicate biologic evolution in our technical solutions so if you look at, and we're beginning to understand more and more how real neural nets work in our cerebral cortex. And it's sort of a pyramid structure so that the first pass of a broad base of analytics, it gets constrained to the next pass, gets constrained to the next pass, which is how information is processed in the brain. So we're discovering increasingly that what we've been evolving towards, in term of architectures of neural nets, is approximating the architecture of the human cortex and the more we understand the human cortex, the more insight we get to how to optimize neural nets, so when you think about it, with millions of years of evolution of how the cortex is structured, it shouldn't be a surprise that the optimization protocols, if you will, in our genetic code are profoundly efficient in how they operate. So there's a real role for looking at biologic evolutionary solutions, vis a vis technical solutions, and there's a friend of mine who worked with who worked with George Church at Harvard and actually published a book on biomimmicry and they wrote the book completely in DNA so if all of you have your home DNA decoder, you can actually read the book on your DNA reader, just kidding. >> There's actually a start up I just saw in the-- >> Read-Write DNA, yeah. >> Actually it's a... He writes something. What was it? (response from crowd member) Yeah, they're basically encoding information in DNA as a storage medium. (laughter) The company, right? >> Yeah, that same friend of mine who coauthored that biomimmicry book in DNA also did the estimate of the density of information storage. So a cubic centimeter of DNA can store an hexabyte of data. I mean that's mind blowing. >> Naveen: Highly done soon. >> Yeah that's amazing. Also you hit upon a really important point there, that one of the things that's changed is... Well, there are two major things that have changed in my perception from let's say five to 10 years ago, when we were using machine learning. You could use data to train models and make predictions to understand complex phenomena. But they had limited utility and the challenge was that if I'm trying to build on these things, I had to do a lot of work up front. It was called feature engineering. I had to do a lot of work to figure out what are the key attributes of that data? What are the 10 or 20 or 100 pieces of information that I should pull out of the data to feed to the model, and then the model can turn it into a predictive machine. And so, what's really exciting about the new generation of machine learning technology, and particularly deep learning, is that it can actually learn from example data those features without you having to do any preprogramming. That's why Naveen is saying you can take the same sort of overall approach and apply it to a bunch of different problems. Because you're not having to fine tune those features. So at the end of the day, the two things that have changed to really enable this evolution is access to more data, and I'd be curious to hear from you where you're seeing data come from, what are the strategies around that. So access to data, and I'm talking millions of examples. So 10,000 examples most times isn't going to cut it. But millions of examples will do it. And then, the other piece is the computing capability to actually take millions of examples and optimize this algorithm in a single lifetime. I mean, back in '91, when I started, we literally would have thousands of examples and it would take overnight to run the thing. So now in the world of millions, and you're putting together all of these combinations, the computing has changed a lot. I know you've made some revolutionary advances in that. But I'm curious about the data. Where are you seeing interesting sources of data for analytics? >> So I do some work in the genomics space and there are more viable permutations of the human genome than there are people who have ever walked the face of the earth. And the polygenic determination of a phenotypic expression translation, what are genome does to us in our physical experience in health and disease is determined by many, many genes and the interaction of many, many genes and how they are up and down regulated. And the complexity of disambiguating which 27 genes are affecting your diabetes and how are they up and down regulated by different interventions is going to be different than his. It's going to be different than his. And we already know that there's four or five distinct genetic subtypes of type II diabetes. So physicians still think there's one disease called type II diabetes. There's actually at least four or five genetic variants that have been identified. And so, when you start thinking about disambiguating, particularly when we don't know what 95 percent of DNA does still, what actually is the underlining cause, it will require this massive capability of developing these feature vectors, sometimes intuiting it, if you will, from the data itself. And other times, taking what's known knowledge to develop some of those feature vectors, and be able to really understand the interaction of the genome and the microbiome and the phenotypic data. So the complexity is high and because the variation complexity is high, you do need these massive members. Now I'm going to make a very personal pitch here. So forgive me, but if any of you have any role in policy at all, let me tell you what's happening right now. The Genomic Information Nondiscrimination Act, so called GINA, written by a friend of mine, passed a number of years ago, says that no one can be discriminated against for health insurance based upon their genomic information. That's cool. That should allow all of you to feel comfortable donating your DNA to science right? Wrong. You are 100% unprotected from discrimination for life insurance, long term care and disability. And it's being practiced legally today and there's legislation in the House, in mark up right now to completely undermine the existing GINA legislation and say that whenever there's another applicable statute like HIPAA, that the GINA is irrelevant, that none of the fines and penalties are applicable at all. So we need a ton of data to be able to operate on. We will not be getting a ton of data to operate on until we have the kind of protection we need to tell people, you can trust us. You can give us your data, you will not be subject to discrimination. And that is not the case today. And it's being further undermined. So I want to make a plea to any of you that have any policy influence to go after that because we need this data to help the understanding of human health and disease and we're not going to get it when people look behind the curtain and see that discrimination is occurring today based upon genetic information. >> Well, I don't like the idea of being discriminated against based on my DNA. Especially given how little we actually know. There's so much complexity in how these things unfold in our own bodies, that I think anything that's being done is probably childishly immature and oversimplifying. So it's pretty rough. >> I guess the translation here is that we're all unique. It's not just a Disney movie. (laughter) We really are. And I think one of the strengths that I'm seeing, kind of going back to the original point, of these new techniques is it's going across different data types. It will actually allow us to learn more about the uniqueness of the individual. It's not going to be just from one data source. They were collecting data from many different modalities. We're collecting behavioral data from wearables. We're collecting things from scans, from blood tests, from genome, from many different sources. The ability to integrate those into a unified picture, that's the important thing that we're getting toward now. That's what I think is going to be super exciting here. Think about it, right. I can tell you to visual a coin, right? You can visualize a coin. Not only do you visualize it. You also know what it feels like. You know how heavy it is. You have a mental model of that from many different perspectives. And if I take away one of those senses, you can still identify the coin, right? If I tell you to put your hand in your pocket, and pick out a coin, you probably can do that with 100% reliability. And that's because we have this generalized capability to build a model of something in the world. And that's what we need to do for individuals is actually take all these different data sources and come up with a model for an individual and you can actually then say what drug works best on this. What treatment works best on this? It's going to get better with time. It's not going to be perfect, because this is what a doctor does, right? A doctor who's very experienced, you're a practicing physician right? Back me up here. That's what you're doing. You basically have some categories. You're taking information from the patient when you talk with them, and you're building a mental model. And you apply what you know can work on that patient, right? >> I don't have clinic hours anymore, but I do take care of many friends and family. (laughter) >> You used to, you used to. >> I practiced for many years before I became a full-time geek. >> I thought you were a recovering geek. >> I am. (laughter) I do more policy now. >> He's off the wagon. >> I just want to take a moment and see if there's anyone from the audience who would like to ask, oh. Go ahead. >> We've got a mic here, hang on one second. >> I have tons and tons of questions. (crosstalk) Yes, so first of all, the microbiome and the genome are really complex. You already hit about that. Yet most of the studies we do are small scale and we have difficulty repeating them from study to study. How are we going to reconcile all that and what are some of the technical hurdles to get to the vision that you want? >> So primarily, it's been the cost of sequencing. Up until a year ago, it's $1000, true cost. Now it's $100, true cost. And so that barrier is going to enable fairly pervasive testing. It's not a real competitive market becaue there's one sequencer that is way ahead of everybody else. So the price is not $100 yet. The cost is below $100. So as soon as there's competition to drive the cost down, and hopefully, as soon as we all have the protection we need against discrimination, as I mentioned earlier, then we will have large enough sample sizes. And so, it is our expectation that we will be able to pool data from local sources. I chair the e-health work group at the Global Alliance for Genomics and Health which is working on this very issue. And rather than pooling all the data into a single, common repository, the strategy, and we're developing our five-year plan in a month in London, but the goal is to have a federation of essentially credentialed data enclaves. That's a formal method. HHS already does that so you can get credentialed to search all the data that Medicare has on people that's been deidentified according to HIPPA. So we want to provide the same kind of service with appropriate consent, at an international scale. And there's a lot of nations that are talking very much about data nationality so that you can't export data. So this approach of a federated model to get at data from all the countries is important. The other thing is a block-chain technology is going to be very profoundly useful in this context. So David Haussler of UC Santa Cruz is right now working on a protocol using an open block-chain, public ledger, where you can put out. So for any typical cancer, you may have a half dozen, what are called sematic variance. Cancer is a genetic disease so what has mutated to cause it to behave like a cancer? And if we look at those biologically active sematic variants, publish them on a block chain that's public, so there's not enough data there to reidentify the patient. But if I'm a physician treating a woman with breast cancer, rather than say what's the protocol for treating a 50-year-old woman with this cell type of cancer, I can say show me all the people in the world who have had this cancer at the age of 50, wit these exact six sematic variants. Find the 200 people worldwide with that. Ask them for consent through a secondary mechanism to donate everything about their medical record, pool that information of the core of 200 that exactly resembles the one sitting in front of me, and find out, of the 200 ways they were treated, what got the best results. And so, that's the kind of future where a distributed, federated architecture will allow us to query and obtain a very, very relevant cohort, so we can basically be treating patients like mine, sitting right in front of me. Same thing applies for establishing research cohorts. There's some very exciting stuff at the convergence of big data analytics, machine learning, and block chaining. >> And this is an area that I'm really excited about and I think we're excited about generally at Intel. They actually have something called the Collaborative Cancer Cloud, which is this kind of federated model. We have three different academic research centers. Each of them has a very sizable and valuable collection of genomic data with phenotypic annotations. So you know, pancreatic cancer, colon cancer, et cetera, and we've actually built a secure computing architecture that can allow a person who's given the right permissions by those organizations to ask a specific question of specific data without ever sharing the data. So the idea is my data's really important to me. It's valuable. I want us to be able to do a study that gets the number from the 20 pancreatic cancer patients in my cohort, up to the 80 that we have in the whole group. But I can't do that if I'm going to just spill my data all over the world. And there are HIPAA and compliance reasons for that. There are business reasons for that. So what we've built at Intel is this platform that allows you to do different kinds of queries on this genetic data. And reach out to these different sources without sharing it. And then, the work that I'm really involved in right now and that I'm extremely excited about... This also touches on something that both of you said is it's not sufficient to just get the genome sequences. You also have to have the phenotypic data. You have to know what cancer they've had. You have to know that they've been treated with this drug and they've survived for three months or that they had this side effect. That clinical data also needs to be put together. It's owned by other organizations, right? Other hospitals. So the broader generalization of the Collaborative Cancer Cloud is something we call the data exchange. And it's a misnomer in a sense that we're not actually exchanging data. We're doing analytics on aggregated data sets without sharing it. But it really opens up a world where we can have huge populations and big enough amounts of data to actually train these models and draw the thread in. Of course, that really then hits home for the techniques that Nervana is bringing to the table, and of course-- >> Stanford's one of your academic medical centers? >> Not for that Collaborative Cancer Cloud. >> The reason I mentioned Standford is because the reason I'm wearing this FitBit is because I'm a research subject at Mike Snyder's, the chair of genetics at Stanford, IPOP, intrapersonal omics profile. So I was fully sequenced five years ago and I get four full microbiomes. My gut, my mouth, my nose, my ears. Every three months and I've done that for four years now. And about a pint of blood. And so, to your question of the density of data, so a lot of the problem with applying these techniques to health care data is that it's basically a sparse matrix and there's a lot of discontinuities in what you can find and operate on. So what Mike is doing with the IPOP study is much the same as you described. Creating a highly dense longitudinal set of data that will help us mitigate the sparse matrix problem. (low volume response from audience member) Pardon me. >> What's that? (low volume response) (laughter) >> Right, okay. >> John: Lost the school sample. That's got to be a new one I've heard now. >> Okay, well, thank you so much. That was a great question. So I'm going to repeat this and ask if there's another question. You want to go ahead? >> Hi, thanks. So I'm a journalist and I report a lot on these neural networks, a system that's beter at reading mammograms than your human radiologists. Or a system that's better at predicting which patients in the ICU will get sepsis. These sort of fascinating academic studies that I don't really see being translated very quickly into actual hospitals or clinical practice. Seems like a lot of the problems are regulatory, or liability, or human factors, but how do you get past that and really make this stuff practical? >> I think there's a few things that we can do there and I think the proof points of the technology are really important to start with in this specific space. In other places, sometimes, you can start with other things. But here, there's a real confidence problem when it comes to health care, and for good reason. We have doctors trained for many, many years. School and then residencies and other kinds of training. Because we are really, really conservative with health care. So we need to make sure that technology's well beyond just the paper, right? These papers are proof points. They get people interested. They even fuel entire grant cycles sometimes. And that's what we need to happen. It's just an inherent problem, its' going to take a while. To get those things to a point where it's like well, I really do trust what this is saying. And I really think it's okay to now start integrating that into our standard of care. I think that's where you're seeing it. It's frustrating for all of us, believe me. I mean, like I said, I think personally one of the biggest things, I want to have an impact. Like when I go to my grave, is that we used machine learning to improve health care. We really do feel that way. But it's just not something we can do very quickly and as a business person, I don't actually look at those use cases right away because I know the cycle is just going to be longer. >> So to your point, the FDA, for about four years now, has understood that the process that has been given to them by their board of directors, otherwise known as Congress, is broken. And so they've been very actively seeking new models of regulation and what's really forcing their hand is regulation of devices and software because, in many cases, there are black box aspects of that and there's a black box aspect to machine learning. Historically, Intel and others are making inroads into providing some sort of traceability and transparency into what happens in that black box rather than say, overall we get better results but once in a while we kill somebody. Right? So there is progress being made on that front. And there's a concept that I like to use. Everyone knows Ray Kurzweil's book The Singularity Is Near? Well, I like to think that diadarity is near. And the diadarity is where you have human transparency into what goes on in the black box and so maybe Bob, you want to speak a little bit about... You mentioned that, in a prior discussion, that there's some work going on at Intel there. >> Yeah, absolutely. So we're working with a number of groups to really build tools that allow us... In fact Naveen probably can talk in even more detail than I can, but there are tools that allow us to actually interrogate machine learning and deep learning systems to understand, not only how they respond to a wide variety of situations but also where are there biases? I mean, one of the things that's shocking is that if you look at the clinical studies that our drug safety rules are based on, 50 year old white guys are the peak of that distribution, which I don't see any problem with that, but some of you out there might not like that if you're taking a drug. So yeah, we want to understand what are the biases in the data, right? And so, there's some new technologies. There's actually some very interesting data-generative technologies. And this is something I'm also curious what Naveen has to say about, that you can generate from small sets of observed data, much broader sets of varied data that help probe and fill in your training for some of these systems that are very data dependent. So that takes us to a place where we're going to start to see deep learning systems generating data to train other deep learning systems. And they start to sort of go back and forth and you start to have some very nice ways to, at least, expose the weakness of these underlying technologies. >> And that feeds back to your question about regulatory oversight of this. And there's the fascinating, but little known origin of why very few women are in clinical studies. Thalidomide causes birth defects. So rather than say pregnant women can't be enrolled in drug trials, they said any woman who is at risk of getting pregnant cannot be enrolled. So there was actually a scientific meritorious argument back in the day when they really didn't know what was going to happen post-thalidomide. So it turns out that the adverse, unintended consequence of that decision was we don't have data on women and we know in certain drugs, like Xanax, that the metabolism is so much slower, that the typical dosing of Xanax is women should be less than half of that for men. And a lot of women have had very serious adverse effects by virtue of the fact that they weren't studied. So the point I want to illustrate with that is that regulatory cycles... So people have known for a long time that was like a bad way of doing regulations. It should be changed. It's only recently getting changed in any meaningful way. So regulatory cycles and legislative cycles are incredibly slow. The rate of exponential growth in technology is exponential. And so there's impedance mismatch between the cycle time for regulation cycle time for innovation. And what we need to do... I'm working with the FDA. I've done four workshops with them on this very issue. Is that they recognize that they need to completely revitalize their process. They're very interested in doing it. They're not resisting it. People think, oh, they're bad, the FDA, they're resisting. Trust me, there's nobody on the planet who wants to revise these review processes more than the FDA itself. And so they're looking at models and what I recommended is global cloud sourcing and the FDA could shift from a regulatory role to one of doing two things, assuring the people who do their reviews are competent, and assuring that their conflicts of interest are managed, because if you don't have a conflict of interest in this very interconnected space, you probably don't know enough to be a reviewer. So there has to be a way to manage the conflict of interest and I think those are some of the keypoints that the FDA is wrestling with because there's type one and type two errors. If you underregulate, you end up with another thalidomide and people born without fingers. If you overregulate, you prevent life saving drugs from coming to market. So striking that balance across all these different technologies is extraordinarily difficult. If it were easy, the FDA would've done it four years ago. It's very complicated. >> Jumping on that question, so all three of you are in some ways entrepreneurs, right? Within your organization or started companies. And I think it would be good to talk a little bit about the business opportunity here, where there's a huge ecosystem in health care, different segments, biotech, pharma, insurance payers, etc. Where do you see is the ripe opportunity or industry, ready to really take this on and to make AI the competitive advantage. >> Well, the last question also included why aren't you using the result of the sepsis detection? We do. There were six or seven published ways of doing it. We did our own data, looked at it, we found a way that was superior to all the published methods and we apply that today, so we are actually using that technology to change clinical outcomes. As far as where the opportunities are... So it's interesting. Because if you look at what's going to be here in three years, we're not going to be using those big data analytics models for sepsis that we are deploying today, because we're just going to be getting a tiny aliquot of blood, looking for the DNA or RNA of any potential infection and we won't have to infer that there's a bacterial infection from all these other ancillary, secondary phenomenon. We'll see if the DNA's in the blood. So things are changing so fast that the opportunities that people need to look for are what are generalizable and sustainable kind of wins that are going to lead to a revenue cycle that are justified, a venture capital world investing. So there's a lot of interesting opportunities in the space. But I think some of the biggest opportunities relate to what Bob has talked about in bringing many different disparate data sources together and really looking for things that are not comprehensible in the human brain or in traditional analytic models. >> I think we also got to look a little bit beyond direct care. We're talking about policy and how we set up standards, these kinds of things. That's one area. That's going to drive innovation forward. I completely agree with that. Direct care is one piece. How do we scale out many of the knowledge kinds of things that are embedded into one person's head and get them out to the world, democratize that. Then there's also development. The underlying technology's of medicine, right? Pharmaceuticals. The traditional way that pharmaceuticals is developed is actually kind of funny, right? A lot of it was started just by chance. Penicillin, a very famous story right? It's not that different today unfortunately, right? It's conceptually very similar. Now we've got more science behind it. We talk about domains and interactions, these kinds of things but fundamentally, the problem is what we in computer science called NP hard, it's too difficult to model. You can't solve it analytically. And this is true for all these kinds of natural sorts of problems by the way. And so there's a whole field around this, molecular dynamics and modeling these sorts of things, that are actually being driven forward by these AI techniques. Because it turns out, our brain doesn't do magic. It actually doesn't solve these problems. It approximates them very well. And experience allows you to approximate them better and better. Actually, it goes a little bit to what you were saying before. It's like simulations and forming your own networks and training off each other. There are these emerging dynamics. You can simulate steps of physics. And you come up with a system that's much too complicated to ever solve. Three pool balls on a table is one such system. It seems pretty simple. You know how to model that, but it actual turns out you can't predict where a balls going to be once you inject some energy into that table. So something that simple is already too complex. So neural network techniques actually allow us to start making those tractable. These NP hard problems. And things like molecular dynamics and actually understanding how different medications and genetics will interact with each other is something we're seeing today. And so I think there's a huge opportunity there. We've actually worked with customers in this space. And I'm seeing it. Like Rosch is acquiring a few different companies in space. They really want to drive it forward, using big data to drive drug development. It's kind of counterintuitive. I never would've thought it had I not seen it myself. >> And there's a big related challenge. Because in personalized medicine, there's smaller and smaller cohorts of people who will benefit from a drug that still takes two billion dollars on average to develop. That is unsustainable. So there's an economic imperative of overcoming the cost and the cycle time for drug development. >> I want to take a go at this question a little bit differently, thinking about not so much where are the industry segments that can benefit from AI, but what are the kinds of applications that I think are most impactful. So if this is what a skilled surgeon needs to know at a particular time to care properly for a patient, this is where most, this area here, is where most surgeons are. They are close to the maximum knowledge and ability to assimilate as they can be. So it's possible to build complex AI that can pick up on that one little thing and move them up to here. But it's not a gigantic accelerator, amplifier of their capability. But think about other actors in health care. I mentioned a couple of them earlier. Who do you think the least trained actor in health care is? >> John: Patients. >> Yes, the patients. The patients are really very poorly trained, including me. I'm abysmal at figuring out who to call and where to go. >> Naveen: You know as much the doctor right? (laughing) >> Yeah, that's right. >> My doctor friends always hate that. Know your diagnosis, right? >> Yeah, Dr. Google knows. So the opportunities that I see that are really, really exciting are when you take an AI agent, like sometimes I like to call it contextually intelligent agent, or a CIA, and apply it to a problem where a patient has a complex future ahead of them that they need help navigating. And you use the AI to help them work through. Post operative. You've got PT. You've got drugs. You've got to be looking for side effects. An agent can actually help you navigate. It's like your own personal GPS for health care. So it's giving you the inforamation that you need about you for your care. That's my definition of Precision Medicine. And it can include genomics, of course. But it's much bigger. It's that broader picture and I think that a sort of agent way of thinking about things and filling in the gaps where there's less training and more opportunity, is very exciting. >> Great start up idea right there by the way. >> Oh yes, right. We'll meet you all out back for the next start up. >> I had a conversation with the head of the American Association of Medical Specialties just a couple of days ago. And what she was saying, and I'm aware of this phenomenon, but all of the medical specialists are saying, you're killing us with these stupid board recertification trivia tests that you're giving us. So if you're a cardiologist, you have to remember something that happens in one in 10 million people, right? And they're saying that irrelevant anymore, because we've got advanced decision support coming. We have these kinds of analytics coming. Precisely what you're saying. So it's human augmentation of decision support that is coming at blazing speed towards health care. So in that context, it's much more important that you have a basic foundation, you know how to think, you know how to learn, and you know where to look. So we're going to be human-augmented learning systems much more so than in the past. And so the whole recertification process is being revised right now. (inaudible audience member speaking) Speak up, yeah. (person speaking) >> What makes it fathomable is that you can-- (audience member interjects inaudibly) >> Sure. She was saying that our brain is really complex and large and even our brains don't know how our brains work, so... are there ways to-- >> What hope do we have kind of thing? (laughter) >> It's a metaphysical question. >> It circles all the way down, exactly. It's a great quote. I mean basically, you can decompose every system. Every complicated system can be decomposed into simpler, emergent properties. You lose something perhaps with each of those, but you get enough to actually understand most of the behavior. And that's really how we understand the world. And that's what we've learned in the last few years what neural network techniques can allow us to do. And that's why our brain can understand our brain. (laughing) >> Yeah, I'd recommend reading Chris Farley's last book because he addresses that issue in there very elegantly. >> Yeah we're seeing some really interesting technologies emerging right now where neural network systems are actually connecting other neural network systems in networks. You can see some very compelling behavior because one of the things I like to distinguish AI versus traditional analytics is we used to have question-answering systems. I used to query a database and create a report to find out how many widgets I sold. Then I started using regression or machine learning to classify complex situations from this is one of these and that's one of those. And then as we've moved more recently, we've got these AI-like capabilities like being able to recognize that there's a kitty in the photograph. But if you think about it, if I were to show you a photograph that happened to have a cat in it, and I said, what's the answer, you'd look at me like, what are you talking about? I have to know the question. So where we're cresting with these connected sets of neural systems, and with AI in general, is that the systems are starting to be able to, from the context, understand what the question is. Why would I be asking about this picture? I'm a marketing guy, and I'm curious about what Legos are in the thing or what kind of cat it is. So it's being able to ask a question, and then take these question-answering systems, and actually apply them so that's this ability to understand context and ask questions that we're starting to see emerge from these more complex hierarchical neural systems. >> There's a person dying to ask a question. >> Sorry. You have hit on several different topics that all coalesce together. You mentioned personalized models. You mentioned AI agents that could help you as you're going through a transitionary period. You mentioned data sources, especially across long time periods. Who today has access to enough data to make meaningful progress on that, not just when you're dealing with an issue, but day-to-day improvement of your life and your health? >> Go ahead, great question. >> That was a great question. And I don't think we have a good answer to it. (laughter) I'm sure John does. Well, I think every large healthcare organization and various healthcare consortiums are working very hard to achieve that goal. The problem remains in creating semantic interoperatability. So I spent a lot of my career working on semantic interoperatability. And the problem is that if you don't have well-defined, or self-defined data, and if you don't have well-defined and documented metadata, and you start operating on it, it's real easy to reach false conclusions and I can give you a classic example. It's well known, with hundreds of studies looking at when you give an antibiotic before surgery and how effective it is in preventing a post-op infection. Simple question, right? So most of the literature done prosectively was done in institutions where they had small sample sizes. So if you pool that, you get a little bit more noise, but you get a more confirming answer. What was done at a very large, not my own, but a very large institution... I won't name them for obvious reasons, but they pooled lots of data from lots of different hospitals, where the data definitions and the metadata were different. Two examples. When did they indicate the antibiotic was given? Was it when it was ordered, dispensed from the pharmacy, delivered to the floor, brought to the bedside, put in the IV, or the IV starts flowing? Different hospitals used a different metric of when it started. When did surgery occur? When they were wheeled into the OR, when they were prepped and drapped, when the first incision occurred? All different. And they concluded quite dramatically that it didn't matter when you gave the pre-op antibiotic and whether or not you get a post-op infection. And everybody who was intimate with the prior studies just completely ignored and discounted that study. It was wrong. And it was wrong because of the lack of commonality and the normalization of data definitions and metadata definitions. So because of that, this problem is much more challenging than you would think. If it were so easy as to put all these data together and operate on it, normalize and operate on it, we would've done that a long time ago. It's... Semantic interoperatability remains a big problem and we have a lot of heavy lifting ahead of us. I'm working with the Global Alliance, for example, of Genomics and Health. There's like 30 different major ontologies for how you represent genetic information. And different institutions are using different ones in different ways in different versions over different periods of time. That's a mess. >> Our all those issues applicable when you're talking about a personalized data set versus a population? >> Well, so N of 1 studies and single-subject research is an emerging field of statistics. So there's some really interesting new models like step wedge analytics for doing that on small sample sizes, recruiting people asynchronously. There's single-subject research statistics. You compare yourself with yourself at a different point in time, in a different context. So there are emerging statistics to do that and as long as you use the same sensor, you won't have a problem. But people are changing their remote sensors and you're getting different data. It's measured in different ways with different sensors at different normalization and different calibration. So yes. It even persists in the N of 1 environment. >> Yeah, you have to get started with a large N that you can apply to the N of 1. I'm actually going to attack your question from a different perspective. So who has the data? The millions of examples to train a deep learning system from scratch. It's a very limited set right now. Technology such as the Collaborative Cancer Cloud and The Data Exchange are definitely impacting that and creating larger and larger sets of critical mass. And again, not withstanding the very challenging semantic interoperability questions. But there's another opportunity Kay asked about what's changed recently. One of the things that's changed in deep learning is that we now have modules that have been trained on massive data sets that are actually very smart as certain kinds of problems. So, for instance, you can go online and find deep learning systems that actually can recognize, better than humans, whether there's a cat, dog, motorcycle, house, in a photograph. >> From Intel, open source. >> Yes, from Intel, open source. So here's what happens next. Because most of that deep learning system is very expressive. That combinatorial mixture of features that Naveen was talking about, when you have all these layers, there's a lot of features there. They're actually very general to images, not just finding cats, dogs, trees. So what happens is you can do something called transfer learning, where you take a small or modest data set and actually reoptimize it for your specific problem very, very quickly. And so we're starting to see a place where you can... On one end of the spectrum, we're getting access to the computing capabilities and the data to build these incredibly expressive deep learning systems. And over here on the right, we're able to start using those deep learning systems to solve custom versions of problems. Just last weekend or two weekends ago, in 20 minutes, I was able to take one of those general systems and create one that could recognize all different kinds of flowers. Very subtle distinctions, that I would never be able to know on my own. But I happen to be able to get the data set and literally, it took 20 minutes and I have this vision system that I could now use for a specific problem. I think that's incredibly profound and I think we're going to see this spectrum of wherever you are in your ability to get data and to define problems and to put hardware in place to see really neat customizations and a proliferation of applications of this kind of technology. >> So one other trend I think, I'm very hopeful about it... So this is a hard problem clearly, right? I mean, getting data together, formatting it from many different sources, it's one of these things that's probably never going to happen perfectly. But one trend I think that is extremely hopeful to me is the fact that the cost of gathering data has precipitously dropped. Building that thing is almost free these days. I can write software and put it on 100 million cell phones in an instance. You couldn't do that five years ago even right? And so, the amount of information we can gain from a cell phone today has gone up. We have more sensors. We're bringing online more sensors. People have Apple Watches and they're sending blood data back to the phone, so once we can actually start gathering more data and do it cheaper and cheaper, it actually doesn't matter where the data is. I can write my own app. I can gather that data and I can start driving the correct inferences or useful inferences back to you. So that is a positive trend I think here and personally, I think that's how we're going to solve it, is by gathering from that many different sources cheaply. >> Hi, my name is Pete. I've very much enjoyed the conversation so far but I was hoping perhaps to bring a little bit more focus into Precision Medicine and ask two questions. Number one, how have you applied the AI technologies as you're emerging so rapidly to your natural language processing? I'm particularly interested in, if you look at things like Amazon Echo or Siri, or the other voice recognition systems that are based on AI, they've just become incredibly accurate and I'm interested in specifics about how I might use technology like that in medicine. So where would I find a medical nomenclature and perhaps some reference to a back end that works that way? And the second thing is, what specifically is Intel doing, or making available? You mentioned some open source stuff on cats and dogs and stuff but I'm the doc, so I'm looking at the medical side of that. What are you guys providing that would allow us who are kind of geeks on the software side, as well as being docs, to experiment a little bit more thoroughly with AI technology? Google has a free AI toolkit. Several other people have come out with free AI toolkits in order to accelerate that. There's special hardware now with graphics, and different processors, hitting amazing speeds. And so I was wondering, where do I go in Intel to find some of those tools and perhaps learn a bit about the fantastic work that you guys are already doing at Kaiser? >> Let me take that first part and then we'll be able to talk about the MD part. So in terms of technology, this is what's extremely exciting now about what Intel is focusing on. We're providing those pieces. So you can actually assemble and build the application. How you build that application specific for MDs and the use cases is up to you or the one who's filling out the application. But we're going to power that technology for multiple perspectives. So Intel is already the main force behind The Data Center, right? Cloud computing, all this is already Intel. We're making that extremely amenable to AI and setting the standard for AI in the future, so we can do that from a number of different mechanisms. For somebody who wants to develop an application quickly, we have hosted solutions. Intel Nervana is kind of the brand for these kinds of things. Hosted solutions will get you going very quickly. Once you get to a certain level of scale, where costs start making more sense, things can be bought on premise. We're supplying that. We're also supplying software that makes that transition essentially free. Then taking those solutions that you develop in the cloud, or develop in The Data Center, and actually deploying them on device. You want to write something on your smartphone or PC or whatever. We're actually providing those hooks as well, so we want to make it very easy for developers to take these pieces and actually build solutions out of them quickly so you probably don't even care what hardware it's running on. You're like here's my data set, this is what I want to do. Train it, make it work. Go fast. Make my developers efficient. That's all you care about, right? And that's what we're doing. We're taking it from that point at how do we best do that? We're going to provide those technologies. In the next couple of years, there's going to be a lot of new stuff coming from Intel. >> Do you want to talk about AI Academy as well? >> Yeah, that's a great segway there. In addition to this, we have an entire set of tutorials and other online resources and things we're going to be bringing into the academic world for people to get going quickly. So that's not just enabling them on our tools, but also just general concepts. What is a neural network? How does it work? How does it train? All of these things are available now and we've made a nice, digestible class format that you can actually go and play with. >> Let me give a couple of quick answers in addition to the great answers already. So you're asking why can't we use medical terminology and do what Alexa does? Well, no, you may not be aware of this, but Andrew Ian, who was the AI guy at Google, who was recruited by Google, they have a medical chat bot in China today. I don't speak Chinese. I haven't been able to use it yet. There are two similar initiatives in this country that I know of. There's probably a dozen more in stealth mode. But Lumiata and Health Cap are doing chat bots for health care today, using medical terminology. You have the compound problem of semantic normalization within language, compounded by a cross language. I've done a lot of work with an international organization called Snowmed, which translates medical terminology. So you're aware of that. We can talk offline if you want, because I'm pretty deep into the semantic space. >> Go google Intel Nervana and you'll see all the websites there. It's intel.com/ai or nervanasys.com. >> Okay, great. Well this has been fantastic. I want to, first of all, thank all the people here for coming and asking great questions. I also want to thank our fantastic panelists today. (applause) >> Thanks, everyone. >> Thank you. >> And lastly, I just want to share one bit of information. We will have more discussions on AI next Tuesday at 9:30 AM. Diane Bryant, who is our general manager of Data Centers Group will be here to do a keynote. So I hope you all get to join that. Thanks for coming. (applause) (light electronic music)

Published Date : Mar 12 2017

SUMMARY :

And I'm excited to share with you He is the VP and general manager for the And it's pretty obvious that most of the useful data in that the technologies that we were developing So the mission is really to put and analyze it so you can actually understand So the field of microbiomics that I referred to earlier, so that you can think about it. is that the substrate of the data that you're operating on neural networks represent the world in the way And that's the way we used to look at it, right? and the more we understand the human cortex, What was it? also did the estimate of the density of information storage. and I'd be curious to hear from you And that is not the case today. Well, I don't like the idea of being discriminated against and you can actually then say what drug works best on this. I don't have clinic hours anymore, but I do take care of I practiced for many years I do more policy now. I just want to take a moment and see Yet most of the studies we do are small scale And so that barrier is going to enable So the idea is my data's really important to me. is much the same as you described. That's got to be a new one I've heard now. So I'm going to repeat this and ask Seems like a lot of the problems are regulatory, because I know the cycle is just going to be longer. And the diadarity is where you have and deep learning systems to understand, And that feeds back to your question about regulatory and to make AI the competitive advantage. that the opportunities that people need to look for to what you were saying before. of overcoming the cost and the cycle time and ability to assimilate Yes, the patients. Know your diagnosis, right? and filling in the gaps where there's less training We'll meet you all out back for the next start up. And so the whole recertification process is being are there ways to-- most of the behavior. because he addresses that issue in there is that the systems are starting to be able to, You mentioned AI agents that could help you So most of the literature done prosectively So there are emerging statistics to do that that you can apply to the N of 1. and the data to build these And so, the amount of information we can gain And the second thing is, what specifically is Intel doing, and the use cases is up to you that you can actually go and play with. You have the compound problem of semantic normalization all the websites there. I also want to thank our fantastic panelists today. So I hope you all get to join that.

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