hi everybody welcome back to re invent 2022. this is thecube's exclusive coverage we're here at the satellite set it's up on the fifth floor of the Venetian Conference Center and this is part of the global startup program the AWS startup showcase series that we've been running all through last year and and into this year with AWS and featuring some of its its Global Partners Ed wallson series the CEO of chaos search many times Cube Alum and Kevin Miller there's also a cube Alum vice president GM of S3 at AWS guys good to see you again yeah great to see you Dave hi Kevin this is we call this our Super Bowl so this must be like your I don't know uh World Cup it's a pretty big event yeah it's the World Cup for sure yeah so a lot of S3 talk you know I mean that's what got us all started in 2006 so absolutely what's new in S3 yeah it's been a great show we've had a number of really interesting launches over the last few weeks and a few at the show as well so you know we've been really focused on helping customers that are running Mass scale data Lakes including you know whether it's structured or unstructured data we actually announced just a few just an hour ago I think it was a new capability to give customers cross-account access points for sharing data securely with other parts of the organization and that's something that we'd heard from customers is as they are growing and have more data sets and they're looking to to get more out of their data they are increasingly looking to enable multiple teams across their businesses to access those data sets securely and that's what we provide with cross-count access points we also launched yesterday our multi-region access point failover capabilities and so again this is where customers have data sets and they're using multiple regions for certain critical workloads they're now able to to use that to fail to control the failover between different regions in AWS and then one other launch I would just highlight is some improvements we made to storage lens which is our really a very novel and you need capability to help customers really understand what storage they have where who's accessing it when it's being accessed and we added a bunch of new metrics storage lens has been pretty exciting for a lot of customers in fact we looked at the data and saw that customers who have adopted storage lens typically within six months they saved more than six times what they had invested in turning storage lens on and certainly in this environment right now we have a lot of customers who are it's pretty top of mind they're looking for ways to optimize their their costs in the cloud and take some of those savings and be able to reinvest them in new innovation so pretty exciting with the storage lens launch I think what's interesting about S3 is that you know pre-cloud Object Store was this kind of a niche right and then of course you guys announced you know S3 in 2006 as I said and okay great you know cheap and deep storage simple get put now the conversations about how to enable value from from data absolutely analytics and it's just a whole new world and Ed you've talked many times I love the term yeah we built chaos search on the on the shoulders of giants right and so the under underlying that is S3 but the value that you can build on top of that has been key and I don't think we've talked about his shoulders and Giants but we've talked about how we literally you know we have a big Vision right so hard to kind of solve the challenge to analytics at scale we really focus on the you know the you know Big Data coming environment get analytics so we talk about the on the shoulders Giants obviously Isaac Newton's you know metaphor of I learned from everything before and we layer on top so really when you talk about all the things come from S3 like I just smile because like we picked it up naturally we went all in an S3 and this is where I think you're going Dave but everyone is so let's just cut the chase like so any of the data platforms you're using S3 is what you're building but we did it a little bit differently so at first people using a cold storage like you said and then they ETL it up into a different platforms for analytics of different sorts now people are using it closer they're doing caching layers and cashing out and they're that's where but that's where the attributes of a scale or reliability are what we did is we actually make S3 a database so literally we have no persistence outside that three and that kind of comes in so it's working really well with clients because most of the thing is we pick up all these attributes of scale reliability and it shows up in the clients environments and so when you launch all these new scalable things we just see it like our clients constantly comment like one of our biggest customers fintech in uh Europe they go to Black Friday again black Friday's not one days and they lose scale from what is it 58 terabytes a day and they're going up to 187 terabytes a day and we don't Flinch they say how do you do that well we built our platform on S3 as long as you can stream it to S3 so they're saying I can't overrun S3 and it's a natural play so it's it's really nice that but we take out those attributes but same thing that's why we're able to you know help clients get you know really you know Equifax is a good example maybe they're able to consolidate 12 their divisions on one platform we couldn't have done that without the scale and the performance of what you can get S3 but also they saved 90 I'm able to do that but that's really because the only persistence is S3 and what you guys are delivering but and then we really for focus on shoulders Giants we're doing on top of that innovating on top of your platforms and bringing that out so things like you know we have a unique data representation that makes it easy to ingest this data because it's kind of coming at you four v's of big data we allow you to do that make it performant on s3h so now you're doing hot analytics on S3 as if it's just a native database in memory but there's no memory SSC caching and then multi-model once you get it there don't move it leverage it in place so you know elasticsearch access you know Cabana grafana access or SQL access with your tools so we're seeing that constantly but we always talk about on the shoulders of giants but even this week I get comments from our customers like how did you do that and most of it is because we built on top of what you guys provided so it's really working out pretty well and you know we talk a lot about digital transformation of course we had the pleasure sitting down with Adam solipski prior John Furrier flew to Seattle sits down his annual one-on-one with the AWS CEO which is kind of cool yeah it was it's good it's like study for the test you know and uh and so but but one of the interesting things he said was you know we're one of our challenges going forward is is how do we go Beyond digital transformation into business transformation like okay well that's that's interesting I was talking to a customer today AWS customer and obviously others because they're 100 year old company and they're basically their business was they call them like the Uber for for servicing appliances when your Appliance breaks you got to get a person to serve it a service if it's out of warranty you know these guys do that so they got to basically have a you know a network of technicians yeah and they gotta deal with the customers no phone right so they had a completely you know that was a business transformation right they're becoming you know everybody says they're coming a software company but they're building it of course yeah right on the cloud so wonder if you guys could each talk about what's what you're seeing in terms of changing not only in the sort of I.T and the digital transformation but also the business transformation yeah I know I I 100 agree that I think business transformation is probably that one of the top themes I'm hearing from customers of all sizes right now even in this environment I think customers are looking for what can I do to drive top line or you know improve bottom line or just improve my customer experience and really you know sort of have that effect where I'm helping customers get more done and you know it is it is very tricky because to do that successfully the customers that are doing that successfully I think are really getting into the lines of businesses and figuring out you know it's probably a different skill set possibly a different culture different norms and practices and process and so it's it's a lot more than just a like you said a lot more than just the technology involved but when it you know we sort of liquidate it down into the data that's where absolutely we see that as a critical function for lines of businesses to become more comfortable first off knowing what data sets they have what data they they could access but possibly aren't today and then starting to tap into those data sources and then as as that progresses figuring out how to share and collaborate with data sets across a company to you know to correlate across those data sets and and drive more insights and then as all that's being done of course it's important to measure the results and be able to really see is this what what effect is this having and proving that effect and certainly I've seen plenty of customers be able to show you know this is a percentage increase in top or bottom line and uh so that pattern is playing out a lot and actually a lot of how we think about where we're going with S3 is related to how do we make it easier for customers to to do everything that I just described to have to understand what data they have to make it accessible and you know it's great to have such a great ecosystem of partners that are then building on top of that and innovating to help customers connect really directly with the businesses that they're running and driving those insights well and customers are hours today one of the things I loved that Adam said he said where Amazon is strategically very very patient but tactically we're really impatient and the customers out there like how are you going to help me increase Revenue how are you going to help me cut costs you know we were talking about how off off camera how you know software can actually help do that yeah it's deflationary I love the quote right so software's deflationary as costs come up how do you go drive it also free up the team and you nail it it's like okay everyone wants to save money but they're not putting off these projects in fact the digital transformation or the business it's actually moving forward but they're getting a little bit bigger but everyone's looking for creative ways to look at their architecture and it becomes larger larger we talked about a couple of those examples but like even like uh things like observability they want to give this tool set this data to all the developers all their sres same data to all the security team and then to do that they need to find a way an architect should do that scale and save money simultaneously so we see constantly people who are pairing us up with some of these larger firms like uh or like keep your data dog keep your Splunk use us to reduce the cost that one and one is actually cheaper than what you have but then they use it either to save money we're saving 50 to 80 hard dollars but more importantly to free up your team from the toil and then they they turn around and make that budget neutral and then allowed to get the same tools to more people across the org because they're sometimes constrained of getting the access to everyone explain that a little bit more let's say I got a Splunk or data dog I'm sifting through you know logs how exactly do you help so it's pretty simple I'll use dad dog example so let's say using data dog preservability so it's just your developers your sres managing environments all these platforms are really good at being a monitoring alerting type of tool what they're not necessarily great at is keeping the data for longer periods like the log data the bigger data that's where we're strong what you see is like a data dog let's say you're using it for a minister for to keep 30 days of logs which is not enough like let's say you're running environment you're finding that performance issue you kind of want to look to last quarter in last month in or maybe last Black Friday so 30 days is not enough but will charge you two eighty two dollars and eighty cents a gigabyte don't focus on just 280 and then if you just turn the knob and keep seven days but keep two years of data on us which is on S3 it goes down to 22 cents plus our list price of 80 cents goes to a dollar two compared to 280. so here's the thing what they're able to do is just turn a knob get more data we do an integration so you can go right from data dog or grafana directly into our platform so the user doesn't see it but they save money A lot of times they don't just save the money now they use that to go fund and get data dog to a lot more people make sense so it's a creativity they're looking at it and they're looking at tools we see the same thing with a grafana if you look at the whole grafana play which is hey you can't put it in one place but put Prometheus for metrics or traces we fit well with logs but they're using that to bring down their costs because a lot of this data just really bogs down these applications the alerting monitoring are good at small data they're not good at the big data which is what we're really good at and then the one and one is actually less than you paid for the one so it and it works pretty well so things are really unpredictable right now in the economy you know during the pandemic we've sort of lockdown and then the stock market went crazy we're like okay it's going to end it's going to end and then it looked like it was going to end and then it you know but last year it reinvented just just in that sweet spot before Omicron so we we tucked it in which which was awesome right it was a great great event we really really missed one physical reinvent you know which was very rare so that's cool but I've called it the slingshot economy it feels like you know you're driving down the highway and you got to hit the brakes and then all of a sudden you're going okay we're through it Oh no you're gonna hit the brakes again yeah so it's very very hard to predict and I was listening to jassy this morning he was talking about yeah consumers they're still spending but what they're doing is they're they're shopping for more features they might be you know buying a TV that's less expensive you know more value for the money so okay so hopefully the consumer spending will get us out of this but you don't really know you know and I don't yeah you know we don't seem to have the algorithms we've never been through something like this before so what are you guys seeing in terms of customer Behavior given that uncertainty well one thing I would highlight that I think particularly going back to what we were just talking about as far as business and digital transformation I think some customers are still appreciating the fact that where you know yesterday you may have had to to buy some Capital put out some capital and commit to something for a large upfront expenditure is that you know today the value of being able to experiment and scale up and then most importantly scale down and dynamically based on is the experiment working out am I seeing real value from it and doing that on a time scale of a day or a week or a few months that is so important right now because again it gets to I am looking for a ways to innovate and to drive Top Line growth but I I can't commit to a multi-year sort of uh set of costs to to do that so and I think plenty of customers are finding that even a few months of experimentation gives them some really valuable insight as far as is this going to be successful or not and so I think that again just of course with S3 and storage from day one we've been elastic pay for what you use if you're not using the storage you don't get charged for it and I think that particularly right now having the applications and the rest of the ecosystem around the storage and the data be able to scale up and scale down is is just ever more important and when people see that like typically they're looking to do more with it so if they find you usually find these little Department projects but they see a way to actually move faster and save money I think it is a mix of those two they're looking to expand it which can be a nightmare for sales Cycles because they take longer but people are looking well why don't you leverage this and go across division so we do see people trying to leverage it because they're still I don't think digital transformation is slowing down but a lot more to be honest a lot more approvals at this point for everything it is you know Adam and another great quote in his in his keynote he said if you want to save money the Cloud's a place to do it absolutely and I read an article recently and I was looking through and I said this is the first time you know AWS has ever seen a downturn because the cloud was too early back then I'm like you weren't paying attention in 2008 because that was the first major inflection point for cloud adoption where CFO said okay stop the capex we're going to Opex and you saw the cloud take off and then 2010 started this you know amazing cycle that we really haven't seen anything like it where they were doubling down in Investments and they were real hardcore investment it wasn't like 1998 99 was all just going out the door for no clear reason yeah so that Foundation is now in place and I think it makes a lot of sense and it could be here for for a while where people are saying Hey I want to optimize and I'm going to do that on the cloud yeah no I mean I've obviously I certainly agree with Adam's quote I think really that's been in aws's DNA from from day one right is that ability to scale costs with with the actual consumption and paying for what you use and I think that you know certainly moments like now are ones that can really motivate change in an organization in a way that might not have been as palatable when it just it didn't feel like it was as necessary yeah all right we got to go give you a last word uh I think it's been a great event I love all your announcements I think this is wonderful uh it's been a great show I love uh in fact how many people are here at reinvent north of 50 000. yeah I mean I feel like it was it's as big if not bigger than 2019. people have said ah 2019 was a record when you count out all the professors I don't know it feels it feels as big if not bigger so there's great energy yeah it's quite amazing and uh and we're thrilled to be part of it guys thanks for coming on thecube again really appreciate it face to face all right thank you for watching this is Dave vellante for the cube your leader in Enterprise and emerging Tech coverage we'll be right back foreign

>>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.

(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)

>>We're back at the red hat summit, 2022, the Cube's continuous coverage. This is day one. We're here all day tomorrow as well. My name is Dave LAN. I'm here with Paul Gillon. Matt Hicks is here. He's executive vice president of products and technologies at red hat. Matt. Good to see you. Thanks for coming on. Nice to see you face to >>Face. Thanks. Thanks Dave. Thanks fall. It's uh, good to be here. >>So you took a different tack with your, uh, keynote today, had a homage to ate a love lace and Serena VA Ramian, which was kind of cool. And your, your point was they weren't noted at their time and nobody was there to build on their early ideas. I mean, ate a lovely, I think it was a century before, right. Ram illusion was a, you know, decade plus, but, and you tied that to open source. You can give us your kind of bumper sticker of your premise there. >>Yeah. You know, I think I have a unique seat in this from red hat where we see, we see new engineers that come in that sort of compete on a world stage and open source and the, the best, which is easy to track just in contributions are not necessarily from the background you would expect them from. And, and it, for me, it's always really inspiring. Like you have this potential in, in people and open source is a great model for getting that out. We told the history story, cuz it, I think when you look over history, just some of that potential that's been ignored before. Um, sure. It's happening right now. But getting that tied into open source models, we think can hopefully let us tap into a little more than, than we have in the past. So >>Greatly. So when you're thinking about innovation and specific to open source, is it a case where I wonder, I really know the history here of open source. Maybe you can educate me. Is it the case where open source observes, uh, a de factacto standard let's say, or some other proprietary approach and says, Hey, we can build that in open and that's so the, the inspiration, or is it an innovation flywheel that just invents? >>I think it's both at this stage. So in the, in the early days, if you take something like Linux, it was a little more of, you know, there was the famous memo of like, this is gonna be a hobbyist project. We're just gonna light up X 86 hardware and have an operating system we can work with. That was a little more of like this standards were there, but it was, can we just build a better operating system with it, be >>Better than Unix cuz would live up to the promise of units. >>That's right. Where in Unix you had some standardization to models, but it wasn't open in that same sense. Uh, Linux has gone well beyond a hobbyist project at this point. Uh, but that was maybe that clone model, um, to units these days though, if you take something like Kubernetes or take something like Ansible, that's just more pure innovation, you didn't necessarily have a Kubernetes model that you're building a better version of it was distributed computing and how can we really make that tick and, um, bring a lot of great minds into that to build it. Um, so I think you see both of 'em, which is it's one of the things that makes open source fun. Like it, it has a broad reach at this point. >>There's one major area of software that opensource has not penetrated yet. And that is applications. I mean, we, there have been, you know, sugar CRM there have been open E R P applications and, and such, none of them really taken off and in fact tend to be drawn back to being proprietary. Why do you suppose opensource has been limited to infrastructure and has hasn't branched out further? >>Yeah, I think part of it is, uh, where can you find a, a model where lots of different companies are, are comfortable contributing into, if you have one solution and one domain from one company you're gonna struggle more getting a real vibrant community built around that. When you pick an area like infrastructure or core platforms, you have a lot of hardware providers, the use cases span from traditional apps to AI. You have a lot of places to run that it's a massive companies. So >>Volume really, it, >>It really is. You just have an interest that spans beyond companies and that's where we've seen open source projects really pick up and build critical mass. How about crypto >>Dows? I mean, that's right. Isn't that the, a form of open source? I mean, is it, isn't that the application really what exactly what you're talking about? It is true or >>It, well, if you look at cryptography encryption algorithms even go to, um, quantum going forward, I think a lot of quantum access will be driven in an open source model. The machines themselves, uh, will be machines, but things like kids kit, uh, that is how most people will access that. So it is a powerful model for getting into areas that are, um, pretty bleeding edge on it as well. >>We were talking, go ahead. We were talking before Andy mentioned that hardware and software increasingly intersecting. That was the theme we heard at the, at the keynote this morning. Yeah. Why do you believe that's happening and how do you see that? How does that affect what you do? >>Uh, I, I think the reason that's happening is there is a push to make decisions closer and closer to users on it because on one side, like law of physics and then on the other of it's just a better experience for it. And so whether that is in transportation or it's in telecommunications, so you see this push outside of data centers to be able to get at that data locally for it. Uh, but if that's the draw, I think also we're seeing hardware architectures are changing. There are, um, standards like arm that are lower power that lets you run pretty powerful compute at the edge as well. And I think it's that combination saying we can do a lot at the edge now and that actually benefits us building user experiences in a lot of different domains is, is making this pull to the edge, uh, really quickly. But it's, it's a, it's an exciting time to be seeing that happening >>And, and, and pretty powerful is almost an understatement. When you think about what the innovations that are going on. Right. I mean, in, in, in, in particular, at the edge mm-hmm, <affirmative>, I mean, you're seeing Moore's law be blown. Everybody says Moore's law is dead, but you're seeing the performance of when you combine the GPU and the CPU and the NPU and the Excel. I mean, it blows away anything we've historically known. Yeah. So you think about the innovations in software that occurred as a result of Moore's law. What are the new beachheads that we could potentially see in open source? >>I think when you start taking the, um, AI patterns on this and AI is a broad space, but if you go even to like machine learning of optimization type use cases, you start, uh, leveraging how you're gonna train those models, which gets you into, you know, CPUs and GPU and TPUs in that world. And then you also have the, how am I gonna take that train model, put it on a really lightweight device and efficiently ask that model questions. And that gets you into a different architecture design. Uh, but that combination, I think we're gonna see these domains build differently where you have mass compute training type capabilities, and then push that as close to the user, as you can, to make decisions that are more dynamic than traditional codes. >>So a lot of the AI that's done today is modeling that's done in the cloud. Yep. And what you're talking about at the edge, and you think about, you know, vehicles is real time influencing. Yep. And that's, that's massive amounts of data. It's a different architecture. Right. And requires different hardware presumably and different software. So, and you guys, well, Linux is obviously there. Yeah. >>That's, that is the, where we get excited about things like the GM announcement you are in the square, in that, um, aspect of running compute right at the end user and actually dealing with sensor and data, that's changing there to help, you know, in this case, like driver's assistance capabilities with it. But I think that the innovation we'll see in that space will be limitless on it. So it's, it's a nice combination of it too. And you'll still have traditional applications that are gonna use those models. I think of it almost as it's like the new middleware, we have our traditional middleware techniques that we know and patterns. Um, they will actually be augmented with things like, um, machine learning models and those capabilities to just be more dynamic. So it's a fun time right now seeing >>That conversion a lot of data too. And again, I wonder how much of that is even gonna be persisted prob probably enough, cuz there's gonna be so much of it, how much it'll come back to the cloud a lot, but maybe not most of it, but it's still massive amounts relative to what we've seen before >>It is. And this is, you know, you've heard our announcement around OpenShift streams in those capabilities. So in red hat, what we do, we will always focus on hybrid with it because a lot of that data it'll be dropped at the edge cuz you won't need it, but the data you act on and the data you need, you will probably need at your indice and in your cloud. And maybe even on premise and capabilities like Kafka and the ability to pick and stream and stay consistent. We think there's a set of really exciting services to be able to enable that class of development where, um, hopefully we'll be at the center of, of that. >>You, you announced, uh, today an agreement with GM, uh, to, to build on their all to five platform, uh, auto industry, very proprietary historically, uh, with their technology. Do you think that this is an opportunity to crank that open? >>A absolutely. I think in, I've been involved with opensource for, for a while, but I think all of them started in a very proprietary model. And then you get to a tipping point where open source models can just unlock more innovation than proprietary models and you see 'em tip and flip. And I think in the automotive industry and actually in a lot of other industries, the capabilities of being able to combine hardware and software fast with the latest capabilities, it'll drive more innovation than just sticking to proprietary models. So yeah, I believe it will be one of many things to come there. >>You've been involved in open surf for a while. Like how long of a while people must joke about when they look at you, Matt, they must say, oh, did you start when you were five? Yeah. >>It's >>Uh, you get that a lot. >>I, I do, uh, it's my, my children, I think aged me a bit, but uh, but yeah, for me it was the mid nineties. That's when I started with, uh, with open source. >>It was uh, wow. So >>It's been a long, long >>Run. You made the statement in your keynote, that software development is, is, is messy. I presumably part of your job is to make it less messy. But now we talk about all this, these new beachheads, this new new innovations, a lot of it's unknown. Yeah. And it could be really messy. So who are the, who is there a new breed of developer that's emerging? Are they gonna come over from the cloud developers or is it the, is it the OT crowd and the, and the OT crowd? That's gonna be the new developers. >>I, I wish I knew, but I would say, I think you, I do think you'll get to almost like a laws of physics type challenge where you won't learn everything. You're not gonna know, uh, the depths of 5g implementation and Kubernetes and Linux on that. And so for us, this is where ecosystem providers are really, really critical where you have to know your intersection points, but you also have to partner really well to actually drive innovation in some of these spaces cuz uh, the domains themselves are massive on it. So our areas we're gonna know hybrid, we're gonna know, you know, open source based platforms to enable hybrid. And then we're gonna partner with companies that know their domains and industries really well to bring solutions to customers. So >>I'm curious about partnering, uh, cuz Paul cor may mentioned that as well as, as being critical, do you have sort of a template for partnering or is each partnership unique? >>Um, >>I think at this point, uh, the market's changing so fast that, uh, we do have templates of, uh, who are you going to embed solutions with? Who are you going to co-sell with? And co-create uh, the challenge in technology though, is it shifts so quickly. If you go back five years, maybe even 10 years, public cloud probably wasn't as dominant. Um, as it is now, now we're starting to see the uptick of edge solutions, probably being, having as much draw as public cloud. And so I think for us, the partnership follows the innovation on those curves and finding the right model where that works for customers is the key thing for us. But I wish there was more of a pattern. We could say it stays stable for decades, but I think it changes with the market on, we do that. >>But you know, it's funny cuz you you've, you see every 15 years or so the industry gets disrupted. I mean we certainly saw it with mainframes and PC and then the internet and then the cloud, uh, you guys have kind of been there. Well Linux throughout, I mean, okay. It built the, built the internet, built the cloud, it's building the edge. So it's almost, I don't wanna say your disruption proof cause that's just, that's gonna jinx you, but, but in, but you've architected the products in a way that they're compatible with these new errors. Mm-hmm <affirmative> of industry, >>Everything needs an operating >>System. Everything needs an operating system, but you've seen operating systems come and go, you know, and, and Linux has survived so many different waves. Why, how >>You know, I, I think for us, when you see open source projects, they definitely get to a critical mass where you have so much contribution, so much innovation there that they're gonna be able to follow the trends pretty well. If you look at a Linux, whatever the next hardware innovation that comes out is Linux has enough gravity that, um, it's open, it's successful, you're gonna design to it. The capability will be there. I think you're seeing similar things in Kubernetes now where if you're going to try to drive application innovation, it is a model that gives you a ton of reach. You have thousands of contributors. That's been our model though is find those projects be influential in, 'em be able to drive value in life cycles. But I think it's that open source model that gives us the durability where it can keep changing and tracking to new patterns. So, so >>Yeah, there's been a lot of open source that wasn't able to sustain. So I think you guys obviously have a magic formula. That's true. >>We, there is a, there is some art to picking, I think millions of projects. Uh, but you've gotta watch for that. >>Yeah. Open source is also a place place where failed products go to die. Yeah. <laugh> so you have to be sure you're not, you're not in that corner. >>Yeah. Well >>Look at Kubernetes. I mean the fact that that actually happened is it's astounding to me when you think about it, I mean even red hat was ready to go on a different path. What if that had happened? Who knows? Maybe it never would've maybe to your point about Ava Lovelace, maybe it would've taken a decade to, or run revolution. >>You know, I think in some of these you have to, you have to watch really closely. We obviously have a lot of signals of what will make good long term health. And I, I don't think everyone looks at those the same. We look at 'em from trademark controls and how foundations are structured and um, who the contributors are and the spread of that. And it's not perfect. But I think for us, you have to have those that longevity built in there where you will have a spike of popularity that has the tendency to just, um, fall apart on it. So we've been yeah. Doing that pretty >>Well conditions for a long life is something that's a that's maybe it's an art form. I don't know if it's a data form. It's a culture. Maybe, maybe it's >>Cultural. Yeah. Probably a combination some days I think I'm like this could part art, part science. Yeah. But, uh, but it's certainly a fun space to be in and see that happen. It, um, yeah, it's inspiring to me. Yeah. >>Matt Hicks. Great to have you back on the cube and uh, good job on the keynote really, um, interesting angle that you took. So >>Congratulations. Thanks for having me. >>Yeah. You're very welcome. All right. Keep it right there. Dave ante for Paul Gillon red hat summit, 2022 from Boston. You're watching the cube.

(upbeat music) >> I'm Dave Nicholson and welcome to Dell Technologies World 2022. I'm delighted to be joined by Tony Bishop. Tony is senior vice president, enterprise strategy at Digital Realty. Tony, welcome to theCUBE. >> Thank you, Dave. Happy to be here. >> So Tony, tell me about your role at Digital Realty and give us a little background on Digital Realty and what you do. >> Absolutely, so my job is to figure out how to make our product and experience relevant for enterprises and partners alike. Digital Realty is probably one of the best kept secrets in the industry. It's the largest provider of multi-tenant data center capacity in the world, over 300 data centers, 50 submetros, 26 countries, six continents. So it's a substantial provider of data center infrastructure capacity to hyperscale clouds to the largest enterprise in the world and everywhere in between. >> So what's the connection with Dell? What are you guys doing with Dell? >> I think it's going to be a marriage made in heaven in terms of the partnership. You think of Dell as the largest leading provider of critical IT infrastructure for companies around the world. They bring expertise in building the most relevant performant efficient infrastructure, combine that with the largest most relevant full spectrum capability provider of data center capacity. And together you create this integrated pre-engineered kind of experience where infrastructure can be delivered on demand, secure and compliant, performant and efficient and really unlock the opportunity that's trapped in the world around data. >> So speaking of data, you have a unique view at Digital Realty because you're seeing things in aggregate, in a way that maybe a single client wouldn't be seeing them. What are some of the trends and important things we need to be aware of as we move forward from a data center, from an IT perspective, frankly. >> Yeah, it's an excellent question. The good part of the vantage point is we see emerging trends as they start to unfold 'cause you have the most unique diverse set of customers coming together and coming together, almost organized like in a community effect because you have them connecting and attaching to each other's infrastructure sharing data. And what we've seen is in explosion in data being created, data being processed, aggregated, stored, and then being enriched. And it's really around that, what we call the data creation life cycle, where what we're seeing is that data then needs to be shared across many different devices, applications, systems, companies, users, and that ends up creating this new type of workflow driven world that's very intelligent and is going to cause a radical explosion in all our eyes of needing more infrastructure and more infrastructure faster and more infrastructure as a service. >> Yeah, when you talk about data and you talk about all of these connectivity points and communication points, talk about how some of those are explained to us. Some of these are outside of your facilities and some of them are within your facilities. In this virtualized abstracted world we live in it's easy to think that everything lives in our endpoint mobile device but talk about how that gravity associated with data affects things moving forward. >> Absolutely, glad you brought up about the mobile device because I think it's probably the easiest thing to attach to, to think about how the mobile device has radically liberated and transformed end users and in versions of mobile devices, even being sensors, not just people on a mobile phone proliferating everywhere. So that proliferation of these endpoints that are accessing and coming over different networks mobile networks, wifi networks, corporate networks, all end up generating data that then needs to be brought together and processed. And what we found is that we've found a study that we've been spending multiple years and multiple millions of dollars building into an index in a tool called the Data Gravity Index where we've been able to quantify not only this data creation life cycle, but how big and how fast and how it creates a gravitational effect because as more data gets shared with more applications, it becomes very localized. And so we've now measured and predicted for 700 mentors around the world where that data gravity effect is occurring and it's affecting every industry, every enterprise, and it's going to fundamentally change how infrastructure needs to be architected because it needs to become data centric. It used to be connectivity centric but with these mobile phones and endpoints going everywhere you have to create a meeting place. And it has to be a meeting place where the data comes together and then systems and services are brought and user traffic comes in and out of. >> So in other words, despite your prowess in this space you guys have yet to solve the speed of light issue and the cost of bandwidth moving between sites. So is it fair to say that in an ideal world you could have dozens of actually different customers, separate entities that are physically living in data center locations that are built and posted and run by Digital Realty, communicating with one another. So when these services are communicating instead of communicating over a hundred miles or a thousand miles, it's like one side of the chicken wire fence to the other, not that you use chicken wire in your data center but you get the point, is that fair. >> It is, it's like the mall analogy, right? You're building these data malls and everybody's bringing their relevant infrastructure and then using private secure connections between each other and then enabling the ability for data to be exchanged, enriched and new business be conducted. So no, physics hasn't been solved, Dave, just to add to that. And what we're finding is it's not just physics. One of the other things that we're continuing to see and hear from customers and that we continue to study as a trend is regulations, compliance and security are becoming as big a factors as physics is. So it's not just physics and cost which I agree with what you're saying but there's also these other dimensions that's in effect in placement, connectivity in the management of data and infrastructure, basically, in all major metros around the world where companies do business and providers support them, or customers come to meet them both physically and digitally. It's an interesting trend, right? I think a number of the industrians call it a digital twin where there's a virtual version and of a digital version and a physical version and that's probably the best way to think of us, is that secure meeting place where each can have their own secure infrastructure of what's being digitized but actually being placed physically. >> Yeah, that's interesting. When you look at this from the Dell, Digital Realty partnership perspective we know here at theCUBE that Dell is trying to make consumption of what they build, very, very simple for end user customers. Removing the complexity of the underlying hardware. There's a saying that the hardware doesn't matter anymore. You hear things referred to as serverless or no code, low code, those sort of abstract away from the reality of what's going on under the covers. But APEX, as an example from Dell allows things to be consumed as operational expense, dramatically simplifying the process of consuming that hardware. Now, if you go down to almost the concrete layer where Digital Realty starts up, you're looking at things like density and square footage and power consumption, right? >> Yep. >> So tell me, you mentioned infrastructure. Tell me about the kind of optimization from a hardware standpoint that you expect to see from Dell. >> Yeah, in the data center, the subset of an industry, they call it digital or mission critical infrastructure, the space, the power, the secure housing, how do you create physical isolation? How do you deal with cooling and containment? How do you deal with different physical loads? 'Cause some of the more dense computers likely working with Dell and some of the various semiconductors that Dell takes and wraps into intelligent compute and storage blocks, the specialized processing for our use cases like artificial intelligence and machine learning, they run very fast, they generate a lot of heat and they consume a lot of power. So that means you have to be very smart about the critical infrastructure and the type of server infrastructure storage coming together where the heat can be quickly removed. The power is obviously distributed to it, so it can run as constant and as fast as possible to unlock insights and processing. And then you also need to be able to deal with things like, hey, the cabling between the server and the storage has to be that when you're running parallel calculations that there's an equal distance between the cabling. Well, if I don't think about how I'm physically bringing the server storage and all of that together and then having space that can accommodate and ensure the equal cabling in the layout, oh and then handle these very heavy physical computers. So that physical load into the floor, it becomes very problematic. So it's hidden, most people don't understand that engineering but that's the partnership that why we're excited about with Dell is you're bringing all that critical expertise of supporting all those various types of use cases of infrastructure combinations and then combining the engineering understanding of how do I build for the right performance, the right density, the right TCO and also do it where physical layout of having things in proximity and in a contiguous space can then be the way to unlock processing of data and connecting to others. >> Yeah, so from an end user perspective, I don't need to care about any of what you just said. All I heard was wawawawawa (chuckles). I will consume my APEX delivered Dell by the drink, as a service, as OPEX, however I want to consume it. But I can rest assured that Digital Realty and Dell are actually taking care of those meaningful things that are happening under the hood. Maybe I'm revealing my long term knuckle dragging hardware guy credentials when I just get that little mentioning. >> (indistinct) you got it, performance secure compliant and I don't need to worry about it. The two of you're taking care of it and you're taking care of it for me. And every major mentor around the world delivered in the experience it needs to be delivered in. >> So from the Digital Realty point of view, what are the things that not necessarily keep you up at night worrying, but sort of wake you up in the morning early with a sense of renewed opportunity when it comes to the data center space, a lot of people would think, well we're in the era of cloud, no one's building any data centers except for monster cloud players. But that's definitely not the case, is it? There's a demand for what you folks are building and delivering. So first, what's the opportunity look like and then what are the constraints that are out there? Is it dirt, is it power? What are the constraints you face? >> We have probably all the above, is the shortest answer, right? So we're not wawawa, right Dave? But what we are is the opportunity is huge because it's not one platform, there's many platforms there isn't one business that exists today that doesn't use many applications, doesn't consume many different services both internally and externally, and doesn't generate a ton of data that they may not even know where it is. So that's the exciting part. And that continues to force a requirement that says I need to be able to connect to all those clouds which you can do at our platform but I also need to be able to put infrastructure or the storage of data next to it and in between it. So it's like an integration approach that says if I think physical first think physical that's within logical proximity to where I have employees, customers, partners, I have business presence. That's what drives us, and in our industry continues to grow both. And we see it in our own business. It's a double digit growth rate for both commercial oriented enterprises and service providers in the telco cloud, or content kind of space. So it's kind of like a best of both worlds. I think that's what gets us excited. If I should take a second part of the question, what ends up boring is like all of us, it is a physical world, physical world start with, do we have enough power? Is it durable, sustainable and secure? Is it available? Do we have the right connectivity options. Keeping things available is a full-time job, making it so that you can accommodate local nuances when you start going in different regions and countries and metros there's a lot of regional policy compliance or market specific needs that have to be factored in. But you're still trying to deliver that consistent physical availability and experience. So it's a good problem to have but it's a critical infrastructure problem that I would put in the same kind of bucket as power companies, energy companies, telecommunication companies, because it's a meeting place for all of that. >> So you've been in this business, not just at Digital Realty but you you've been in this part of the IT world for a while. >> Yeah. >> How has the persona of a customer for a Digital Realty changed over time? Have we seen the kind of consolidation that people would expect in this space in terms of fewer but larger customers coming in and seeking floor space? >> Well, I think it's been the opposite of what probably people predict. And I pause there intentionally being very candid and open. And it's probably why that using data as the proxy to understand, is that it's a many to many world that's only getting bigger, not smaller. As much as companies consolidate, there's more that appear. Innovation is driving new businesses and new industries or the digitization of old industries which is then creating a whole multiplier effect. So what we're seeing is we're actually seeing a rapid uptake in the enterprise side of our business which is why I'm here in driving that. That really was much more nominal five years ago for being the provider of the space and capabilities for telcos and large hyperscalers continues to go because it's not like a once and done, it's I need to do this in many places. I need to continue to bring as there's a push towards the edge, I need to be able to create meeting places for all of it. And so to us, we're seeing a constant growth in more companies becoming customers on the enterprise side more enterprises deploying in more places solving more use cases. And more service providers figuring out new ways to monetize by bringing their infrastructure and making an accessibility to be connected to on our platform. >> So if I'm here hearing you right, you're saying that people who believe that we are maybe a few years away from everything being in a single cloud are completely off base. >> Mmh hmm. >> That is not the direction that we're heading, from your view, right? >> We love our cloud customers, they're going to continue to grow. But it's not all going to one cloud. I think what you would see is, that you would see where a great way to assess that and break it down is enterprise IT, Gartner's Forecast 4.2, four and a half trillion a year in spend, less than a third of that's hitting public cloud. So there's a long tail first of all, it's not going to one cloud of people. There's like seven or eight major players and then you go, okay, well, what do I do if it's not in seven or eight major players? Well, then I need to put it next to it. Oh, that's why we'll go to a Digital Realty. >> Makes a lot of sense. Tony Bishop, Digital Realty. Thanks for joining us on theCUBE. Have a great Dell Technologies World. For me, Dave Nicholson, stay tuned more live coverage from Dell Technologies World 2022 as we resume in just a moment. (soft music)

>>Welcome to the cubes coverage of VMworld 2021. I'm Lisa Martin, two guests joining me next. Matt Morgan is here. Vice-president cloud infrastructure business group at VMware and Steven Jones joins us as well. Director of services at AWS gentlemen. That's great to have you on the program. >>Thank you, Lisa. >>Glad to see everyone's doing well. Here we are virtual. So we are just around the four year anniversary of VMware cloud on AWS. Can't believe it's been 20 17, 4 years. Matt talked to us about VMware AWS partnership and how it's progressed over that time. >>The partnership has been fantastic and it's evolved. We announced VM-ware cloud on AWS general availability all the way back at VMworld, 2017, we've been releasing new features and capabilities every other week with 16 major platform releases and 300 features as customers have requested. So it's been an incredible co-engineering relationship with AWS. We've also expanded our go to market by announcing a resale program in which AWS can resell VMware cloud on AWS. We did that back in 2019 and in 2020, we've announced that AWS is VMware's preferred public cloud partner for vSphere based workloads. And VMware is AWS's preferred service for vSphere based workloads. >>So as you said, Matt, a tremendous amount of evolution and just a short four year timeframe. Stephen talked to me about the partnership through AWS, this lens. >>Yeah. You bet. Look, I agree with Matt that the partnership has been fantastic and it's just amazing to see how fast four years has gone. I really think that AWS and VMware really are a really good example of how two technology companies can work together for them. The benefit of our mutual customers, um, as Matt indicated, VM-ware is our preferred service for vSphere based workloads. And we're broadly working together as a single team across both engineering and go-to-market functions to help customers drive business value from the, the, the investments they made over the years. And then also as they work to transform their businesses into the future with cloud technology, >>Let's talk about digital transformation. That is a term we've been, we've been talking about that for many years on this program. And at every event we've all been at, right. What we've seen in the last year and a half is a massive acceleration. Now talk to me about how VMware and AWS are helping customers facilitate that digital transformation. >>So our customers see modern it infrastructure as the core pillar of a digital transformation strategy and public cloud has been a digital transformation enabler for organizations. And that's because they have so many benefits when they embraced the public cloud, including the ability to elastically consume infrastructure. That's required the ability to employ a pay as you go financial model and the ability to reduce operational overhead, which helps save both monetary costs, but also provides more flexibility. But the big driver now is the ability to embrace innovative cloud services and those services help accelerate application development, deployment and management VMware cloud on AWS is a prime example of such an offering, which not only provides these benefits, but enhances them with operational consistency working the same way their it architecture works today, giving them familiarity and enterprise robustness that VMware technologies are known for, but being able to maximize the power of the global AWS cloud >>And every year from a customer adoption perspective, that's doubling Steven walked through a couple of customer examples that really highlight the value of VMC on AWS. >>Yeah, I've got a couple here. I think, uh, Kiko Milano is a good one. There a then our Italian company, they sell cosmetics and beauty products through about 900 retail stores in 27 different markets. So quite large, but they found that their on premises data center and outsourcing partner was just too inflexible for the changing needs of their company. And within four months, uh, Kiko actually migrated all of their core workloads to Amazon. Is he too, and particularly surprised how easy it was to migrate over 300 servers to the VMware cloud on AWS offering. And this is, this is key because the actually leveraging the same platform that they were used to, which was BMR. Uh, the Kiko team actually didn't have to perform any testing or modify any other existing applications. They also, they didn't have to actually train their teams again, because again, they were already up-skilled with being able to leverage the BMR technology. >>So again, we think it's the best of both worlds customers like Kiko can come and use VMware cloud on AWS, consolidate their server footprint and also take advantage of, of a hyperscale platform. That's pretty cool. Another customer, uh, SAP global ratings that our company provides a high quality market intelligence in the form of credit ratings, research, and thought leadership to help educate market participants to make better financial decisions who doesn't want to make a better financial decision. Right? So in order to accelerate their business growth and globalization really meet new business capabilities, they knew they needed to move a hundred percent to the cloud and wanted to know how they're actually going to do that. Now they also have an aging data center system outages, which are becoming more frequent, which to them actually concerned that they actually might, um, uh, face in the future, some penalties from the sec. >>So they didn't want to do that. So over the period of about eight months, think about this eight months, they moved to 150 financial apps to AWS leveraging VMware on AWS. Uh, pretty impressive. They reduce technical debt, uh, from legacy systems that were hosted on sun Solaris, Oracle excavator, and a X. And then now actually able to meet the goal demands of their business. The fun part here is they're actually meeting their uptime, uh, needs a hundred percent of the time since it actually moves these workloads to the VMware cloud on AWS. So pretty exciting. See customers link this kind of journey, >>Absolutely impressive journeys. Also short time periods to do a massive change there. It sounds like the familiarity with VMware in the console is a huge facilitator of the speed of migration and folks being able to get up and running. Stephen talked to me about some of the trends that you were seeing in organizations like the customers that you just mentioned. >>Yeah. So there are some emergency transfer store and a lot of customers want to leverage the same cloud operating models, but also in their own data centers. So they can take advantage of agility and innovation of cloud will also meeting requirements that they sometimes have that keep them from adopting cloud. Uh, you can think of workloads that sometimes have low latency requirements, right? Or they need to process large volumes of data locally. Uh, other times customers tell us they really need the flexibility to run data workloads, um, in a particular area that has data sovereignty or residency requirements. So when, as we talk about customers, um, they tell us that not only do they want to minimize their, their need to actually manage and operate infrastructure, um, and focus on business innovation is sometimes need to do this, um, in a, in a data center this close to them, if that makes sense. So they're looking for the best again of both worlds. >>Got it. The best of both worlds and Matt, you have some breaking news to share. What is it? >>So today we're announcing the general availability of VMware cloud on AWS outposts. >>Awesome. Congratulations. Tell me about that. Let's dig into it. >>So for customers looking to extend their AWS centric model to an on-premise location, that data center edge location via more cloud on AWS, outposts delivers the agility and innovation of AWS cloud, but on premises and VMware cloud on AWS outpost is based on VMware cloud, a jointly engineered service. So together we're delivering this service on premises as a service. This gives us the capability to integrate VMware's enterprise class architecture and platform with next generation dedicated Amazon nitro based ECE to bare metal instances. It provides a deeply integrated hybrid cloud operating environment that extends from a customer's data center to these particular services running on premises in the data center, the edge, or to the public cloud and having a unified control plane between all of it. >>A unified control plan is absolutely critical. Uh, Stephen eight, >>We have a detailed plan to offer integrated AWS services, and that capability really enhances the innovation angle for customers as they embraced the modernization of their applications. >>Another great example of how deep the partnership is Steven AWS outpost was announced at reinvent, I think 2019, which was the last time I was at an event in person. So coming up on a couple of years here, when GA talked to me about some of the key use cases that you're seeing, where it really excels. >>Yeah. So Matt, Matt highlighted a number of these, right. And you're right. It was 2019. Uh, we were all together back then and hopefully we can do that, uh, very soon here, um, quickly on apple. So overall, since, since we're talking about outposts, uh, VMware cloud on a post as well. So the thing here and Matt highlighted this is that without posts, we actually live we've leveraged, leveraged literally the same hardware and control plane technology that we leverage in our own data centers so that the customers will come to know and love and expect about the AWS platform and VMC on AWS, uh, uh, is, is, is the exact same thing that we'll be able to get with the Apple's technology. I'll give you a couple of customer examples. I think that that actually speaks to the use cases best. So, um, you remember, I talked a little bit about data locality and residency requirements. >>So first ABI Dhabi bank, uh, is the largest bank in the United Arab Emirates, right? And they were offering corporate investment and personal banking service, and they wanted to deliver a digital banking service, including email and mobile payments, but they had to follow a specific residency and data retention requirements and they had to do it in the UAE. And so what they've done is they've actually leveraged multiple AWS outposts in the UAE to allow them to provide business continuity while also leveraging the same API APIs that they had to come to know about, uh, and love about the AWS services in region, right? Phillips healthcare is another really good example. Um, you can imagine that, uh, what they do every day is, is, uh, very important things like predictive analytics for preventative treatments. And so outposts Phillips has actually taken those and that developed cloud applications, again, deployed on the same infrastructure they were used to within region. Now they can actually do this in clinics at hospitals, and they're in managing that the same tools providing, uh, same end-to-end, um, view and to their own providers, 19 administrators. And so they actually estimate they have over 70,000 servers now distributed across 12,000 locations or 1200 locations. Excuse me. So that's an example of, again, just two use cases that really broadened the reach and the flexibility of customers to run workloads in the cloud, but in a on-premise fashion. Does that make sense? >>Yes, it does. And you mentioned two great stories there. One in financial services, the other one healthcare, two industries that have had to massively pivot in the last 18 months amongst many others, but let's talk a little bit more Steven, about some of the things that you're hearing from some of the early customers of BMC on outpost. What are some of the near term opportunities that you're uncovering? >>Yeah, I've got to say here too, that, uh, customers are VMware customers have been asking us for this for quite some time. I'm sure Matt would agree. Um, so look from, uh, go back to some of the use cases we've discussed low latency compute requirements. So one of our higher education customers today who has migrated workloads to be more cloud on AWS, um, is looking at, uh, extending the same capability to an on-premise experience specifically for, um, uh, school applications that require a low latency, um, uh, integration, um, from a local data processing perspective. Again, one of our VMware on AWS top biopharmaceutical companies, uh, here again in the U S um, is planning to use VMware cloud on AWS outposts for health management applications with patient records that need to be retained locally at the hospital hospital sites. And then finally you can kind of going back to the story around data residency. We have a large telco provider in Europe that is planning to use this particular offering for their applications that need to remain on premises to meet regulatory requirements. So again, you know, we're just super pleased with the amount of interest, not only in VMware cloud on AWS, but also in this new run that we're announcing today. And we're really excited to be able to support the VMware cloud experience really on the AWS Apple's platform for a of these use cases. >>One of the things we've talked about for many years with both VMware and AWS is the dedication to listening to the voice of the customer. Not obviously this is a great example, Steven, as you said, VMware customers have been asking for this for awhile. So while customers have a ton of choice, I want you guys to unpack what the differentiators are of this service. And Matt, if we can start with you to bring you back into the conversation, we'd love to get your, your input on those differentiators. >>Yeah, absolutely. So people have to look at this for the service that's delivered and on the VMware side of the equation, we're delivering the full VMware cloud infrastructure capability. This is delivered as a service as a cloud service on premises. So why is this valuable? Well, it relieves the it burden of infrastructure management and fully maximizes the value of a fully managed cloud service, giving an organization, the capability to unlock the renovation, budgets, and start to invest truly an innovation. This is all about continuous life cycle management, ongoing service monitoring, automated processes to ensure the health and security the infrastructure. And of course, this is backed by expert VMware site recovery and reliability engineers, to ensure that everything works perfectly. We also enable organizations to leverage best in class enterprise grade capabilities that we've talked about in our compute storage and networking for best-in-class resiliency auto-scaling and intrinsic availability. >>So there's no long procurement cycles to set up these environments. And that means it's developer ready right out of the box. We're also deeply integrated with what customers do today. So end to end hybrid cloud usually requires end-to-end hybrid processes. And with this integration into those processes is instant, no reconfiguration, no conversion, no refactoring, no rearchitecture of existing applications using VMware HDX or B motion organizations can move applications to leverage this cloud service instantly. It allows you to use established on premises governance, security, and operational policies, and ensures that that workload portability I mentioned goes both ways. It's bi-directional as customers need to have portability to meet their business requirements. As we mentioned earlier, there's a unified hybrid control plane with a single pane of glass to manage resources across the end-to-end hybrid cloud environment. And we're giving direct access to 200 plus native AWS services. And that enables an organization to truly modernize their applications, starting where they are today. And so that gives you the real capability to deliver a unique service. One that gives you an organization, the ability to migrate without any downtime have fast, fast cost effective capabilities and a low risk to their hybrid cloud strategy. >>Excellent. That's a pretty jam packed list of differentiators there, but one of the things that it really sounds like not from what you said is how much work has gone on to make the transition smooth for customers, give them that flexibility and that portability that they need. Those are marketing terms you and I know are used very frequently, but it really seems like the work that you've done here will be done straight to that. I want to ask you Stephen, that same question from AWS's perspective, what really differentiates the solution. >>It is a good question. I'll just, uh, I'll agree that there has been a ton of work first that is, has gone, gone into actually making this happen. Right. Um, and to, to all the points that Matt made. And I would just add that again. 80 was outpost is built on the same AWS nitro system and infrastructure. The customers have already come to love in the cloud. And so gone really are the days where customers have to worry about procuring and racking and stacking their own gear layer on all the benefits, the map outline from a VMware perspective. And again, we, we really believe the customers are getting the best of both worlds here. Um, with, with specifically with the compute that comes in the outpost rack, um, customers actually get getting kind of built in redundancy and resiliency, hard security, all those things that customers don't know, they need certain things. >>The customers know they need to pay attention to, but also want some help with. And so we've, we, we put a lot of thought and effort into this. Um, but could I just, uh, explain a little bit about the customer experience, um, when a customer orders and AWS outposts rack, right? AWS actually signs up, uh, to do a fully managed experience here. Like we'll bring people in to actually do site assessments. Um, we'll manage the hardware, setup, the installation and the maintenance of that gear over time. Well, VM-ware also manages the, the software defined data center construct as well as, um, the, the single point for, uh, for support questions. And so together, we really thought through how customers is met, but it get an end to end experience from hardware all the way up through application modernization. It's pretty exciting, >>Very deep partnership there. And we're out of time, but I do want to ask you guys, where can customers go, who are interested in learning more about this new service? >>So at VM world, there are a collection of DMR cloud, AWS sessions, including sessions, dedicated to VMware cloud on AWS outpost. We encourage everyone who's attending VMworld to look up those sessions and you'll learn all about the hardware, the service, the capabilities, the procurement, and how to get started. In addition, on vmware.com, we have a web portal for you to gain additional knowledge through a digital consumption. That's vmware.com/vmc-outposts. >>Awesome. Matt, thank you. I'm sure folks will be just drinking up all of this information at the sessions at VMworld 2021. And I hope to see you in person at next year's VM. I'm crossing my fingers. Great to see you guys Format Morgan and Steve Jones. I'm Lisa Martin, and you're watching the cubes coverage of the em world to 2021.

(upbeat techno music) >> LISA MARTIN: Welcome to today's session of theCubes presentation of the AWS startup showcase, new breakthroughs in DevOps, data analytics, and cloud management tools. This segment features Privacera, and we're going to be talking about data and analytics. I'm Lisa Martin, and today we're joined by Balaji Ganesan the Co-Founder and CEO Privacera. Balaji is going to be talking about accelerating cloud migration and secure self-service analytics with Privacera. Balaji, great to see you again. >> BALAJI GANESAN: Great see you Lisa, and thank you for having me again. >> LISA MARTIN: Our pleasure. Talk to me a little bit about Privacera and specifically what you guys are focused on. >> Yeah, absolutely. Let me start off talking about the problem we are trying to solve. Privacera today is at the intersection of data, data analytics and data governance. And we have seen in the news every time is the use of data in the organizations is increasing and more organizations are becoming data driven. And to solve customer, understand customer more, or to solve supply chain, the use of data is prevalent. And with that, what we are seeing is true data democratization that is happening now in the cloud, where more and more enterprise users are looking for access to the data. And if you look at the world of data teams and IT teams. On one hand, business users are looking for more access to the data, more use cases, more tools, and faster access to the data to drive business decisions, and that's the world they are living in. And every business, every industry is going towards that part. But on the other hand, governance and especially security privacy within has become table stakes, right. Where it's become a board level topic and on especially topics around, how do you get visibility on what data you have? Do you know where your sensitive data is? And making sure you're taking care of all the protections and stipulations around that. But you also have mandates around making sure that people have access to the data only for that purpose, and right people having access to the right data, only the right data and nothing more, is a mandate that is becoming more and more prevalent. Again, driven through privacy regulations and legal mandate. But operationalizing that in the context of data and data democratization is incredibly hard, because these teams are dealing with variety of databases and tools and each have its own way of doing controls. And so if they have a mandate of making sure right people have access to the right data, it's incredibly hard to operationalize that, it's incredibly complex doing manually. And that's the dual mandate we live in today is, on one hand, more users are looking for access to the data, On the other hand, you know, you need to have governance, you need to have guard rails, and how do you balance that out? And for us, it's not a zero sum game and we believe we can balance both, and that's essentially where Privacera comes in, where we are providing a horizontals single pane of glass which helps enterprises to do two major things, right. One is them get visibility, accurately, on what data they have, what is sensitive data and what is not at a pretty fine grain level. And we can leverage that information to build policies and rules in a more unified manner, or on who can access what data, and enforce them across any kind of database or application. And what it helps enterprises to do that is they can deal with this unified layer to get visibility, this deal with this unified layer to manage policies in one place, and they can make sure that these policies are enforced across anywhere that users are accessing data. So in effect, the net result is users can use any tool, any applications to access data. On the other hand, you are governing that, you're governing the access and making sure that people have only access to the data they are supposed to and nothing more. And that is where we are helping those dual mandate coming. >> LISA MARTIN: Talk to me about the timing. Are we at an inflection point? You talked about the data sharing, governance security being a board level conversation, you and I have talked about that before, but also the balancing the need to be able to give the right people access to only the data that they need. Are we at an inflection point in time for Privacera to be able to solve this problem for companies in lots of industries? >> Absolutely. So, if you're taking step back at a macro level, there are a couple of things happening at the macro level, right. Which digitization has become made sure that there's more data than ever than enterprises are sitting in. And the fact that they are now also migrating to the cloud and to the public cloud, which is giving rise to newer architecture, newer way of doing things. And traditionally it used to be the case that you have to make copies of data, and to make it available for different business groups. But now you are at that point where cloud, you definitely don't have to do that, you can make data available in the cloud and run a service on top of it to make data available. And in fact, I'm going to use a use case of Sun Life that are on that that part of it, where Sun Life is a valued customer of us, it's an insurance company and they are in that midst of their journey as well, where they're migrating from on-premise and to cloud, and in this case being AWS. And cloud gives them a lot of flexibility, agility for them to go and accelerate those data initiatives. So at a macro level like Sun Life, digitization has become prominent, and like Sun Life, many other companies are accelerating their cloud migration. But what Sun Life has is, they have to have a lot of mandates built in, in terms of governance and security, being an insurance industry, being dealing with a lot of sensitive data, both which are mandate to have a lot of regulations around it. And Sun Life is global, they are in Canada, they are in US, you have to make sure those are mandates are met then. For the teams which are doing that it's hard to meet that mandate. And how do you balance governance and accelerate cloud migration and use of data? And that's essentially where we are at that inflection point today, where these mandates are coming at cross hairs to each other, right. But companies cannot ignore governance and accelerate cloud migration. On the other hand, they can't just make the data siloed so much that they ignore the use of data part of it. So we are at this interesting inflection point where these drivers are coming in and it crosses each other and it's intersecting at these data teams. We're trying to deal with this dual mandates at the end of the day. And this is exactly what Sun Life was facing, and where they started looking at a solution like Privacera and where we are able to quickly, on the AWS environment, build that unifier layer of access governance, where they can go and manage policies in one place and migrate policies which have been built in the on-premise world to the cloud. And what did help them do that is they were able to build in governance from day one and they were able to quickly get to a faster time to value. It would have taken them in months or maybe a year to get to that stage. They were able to do that in weeks with our tool. And so what we are seeing at this inflection point now is, there are these trends coming at potentially a friction with each other, but it's not a zero sum game, right. It should not be treated as a zero sum game. You can have governance and use of data, and that's essentially where Privacera's mission is. >> LISA MARTIN: Let's talk about digital transformation. You should that great example of Sun Life and the really accelerated time to value that they're getting with Privacera. But if we think about some of the business drivers for data management, modernization, how have they changed and accelerated particularly in the last 18 months? What are some of the business drivers for data management modernization that you see emerging? >> BALAJI GANESAN: Absolutely, Yeah. So, I think what we are seeing is businesses are more hungry for data as, than ever before, and they are not willing to wait for IT teams to complete an infrastructure and a project for many, many years to get access to the data. And cloud makes it possible for them to go and even build tools like Snowflake, for example, where they can quickly go and use that in a SaaS environment and solution without having a dependency, a huge dependency on IT teams. So the world of IT is changing, where business teams can go and gain access to their more modern tools faster than ever before. Infrastructure doesn't have to be built for many, many years before you can realize some of the business initiatives. So cloud is really transforming the agility, the time to value part of it, so what we are seeing that part. From a data management point of view, governance in general, which includes quality, metadata, includes security, privacy, all of this are becoming very, very serious topics, and it's not like they haven't existed before, but given the growth of data you no longer can grow unimpeded, without having those foundational layer of governance. You cannot grow without having your metadata strategy aligned, right. You cannot grow without good quality measures in (indistinct). And security privacy is in that bucket. It used to be the case before that people will do projects and then worry about security. In 2021 that's no longer the case, right. Companies are looking at building these governance mandates upfront, they are thinking about building access governance upfront, building security upfront. Because if you don't do that, if you go and scale in an environment with all those layers, you end up exposing that for risk. But you also have a friction, a friction of not being onboarding more data, because that needs to be compliant as well. So more organizations, more proactive organizations are realizing that they need to be more holistic. They need to put in more governance roadmap very early on in their journey. And that's what Sun Life did, they were very proactive as part of the cloud migration journey, to think about these things upfront and not think of them as an after fact. After fact are something that comes later, most proactive organizations are doing both. >> LISA MARTIN: The need for being able to build things in that print, I'm thinking automation. Talk to me about some of the risks that an enterprise is going to run into if security isn't automated, governance and strategies aren't automated or embedded, as you said upfront. >> BALAJI GANESAN: Yep. I think the risk comes up when is in twofold. One is, many companies have started doing manually and manual work and it becomes fairly a complex initiative. And we were talking to one customer where they have started with snowflake, but quickly they ended up having about 2 million policies in snowflake alone, right, it's not they had some more of the other parts. And 2 million policies across various business groups, but if you need to prove right people have access to the right data, it's incredibly hard when you've grown so much inorganically in many, many ways as part of it. And most organizations have realized that that is going to be untenable, right. And because again, going back, they have this dual mandate that they need to meet. So the risks are for companies which don't do it upfront is it becomes a blocker. At some point, governance becomes a blocker of putting even more data in, or more users in because you have to now go and clean up and make sure that again, right people have access to the right data, set those infrastructure in. And that sets back the company away a bit again as part of it. So, we have seen governance becoming a blocker in data initiatives, and we believe that by enabling this upfront, it can be a true enabler, it can be an accelerant in case. And more proactive organizations like Sun Life have realized that part of doing it early enough, setting those foundations early enough helps them being more agile and helps them meet those business objectives faster. >> LISA MARTIN: I can also imagine too, from a liability perspective, the lack of visibility into where sensitive data is stored, how it's used, who can use it, it is a huge risk for any type of organization, right? >> BALAJI GANESAN: Any type of organization. And with what we have seen with privacy regulations now is, privacy impacts any type of organizations which have customer data. And there's more onus now than ever before to go and make sure that you have clear visibility on what is sensitive data, what is personal information and clear protections around that, and make sure it's used for those right purposes. And it has become real, it's become real in every industry. So while it used to be that healthcare industries has certain regulations, or financial industry, would you count those as part of a regulated industries? What privacy regulations have done is now impacting consumer tech companies, .com companies now who have data that they need to be cognizant now of legal and privacy implications upfront. So, there is an incredible amount of risk, as you pointed out, of not taking care of things upfront. And if you outgrow your data initiatives without putting those fundamental layers in you're exposing the risk, and those risks are coming out in recent examples we are seeing in breaches. There are numerous examples of companies which have failed to put in a more comprehensive strategy and that has resulted in, you know, data getting exposed in the cloud, employees who are not supposed to have access to the data or have access to the data and it gets leaked. So it's broader implications. There are implications around security, there's implications around breaches, there are implications are on privacy that we are seeing across the board. >> LISA MARTIN: So let's talk about roles and responsibilities now. If we're talking about data access governance, if it's no longer just exclusively the domain of IT or data governance teams, and it's distributed across these teams, do you think that data governance responsibilities need to be shared responsibilities or de-centralized? >> BALAJI GANESAN: Yeah, that's a great question, Lisa, and let's take even Sun Life for example, they are a massive organization, data security organizations, there's compliance teams, and there is data teams. And what most organizations are realizing now at heads, it's untenable, it's not scalable to have one central team being the policeman. It's just not feasible, and it's just not feasible while you can provide mandates. The onus of actually making it happen has to be decentralized and has to be shared across the board with data teams, and data teams have to be trained, have to be enabled to go and share those responsibilities, because you are as good as your weakest link. It doesn't matter if you have a really good mandate at the top, but if there are teams which are doing it more open and don't have those controls built in, the organizations is exposed. And so what organizations, or the most modern organizations are realizing that security governance cannot be always top-down. You can provide a mandate, you can have a central team do that, but it's not feasible for that team to police the entire organization, and you don't want to do that. You don't want to police everybody. You want to encourage people to do the right thing. So the onus and responsibility needs to be distributed apart. And that includes people, that includes processes, that includes technology that needs to come in. And most modern organizations are going towards that world, where they're thinking about your data is distributed everywhere, your business teams are accessing data in their own world, how do you in-build governance into that part? And we are seeing this notion of data mesh coming up more and more in organizations, which is driving the need for my data is distributed, business teams have their own ownership of data, how do you make sure you have a (indistinct) of strategy around leveraging data and analytics around it without the need for data to be copied all into one place and one team doing that. And the connotation of data mesh is coming up more and more, and to realize, the organizations are realizing it's just not feasible for one team to drive all their data initiatives, but they also realizing that governance and security falls in the same boat, right. So you cannot have governance being driven by a governance team and police the entire organization. Your data is going to be used where it is store, business teams are going to be doing on their own. But how do you enable those governance in those shared paradigm is the next evolution of that, and some more organizations are doing that already. >> LISA MARTIN: Let's talk about data sharing, internal data sharing within organizations, having the ownership, the governance, not just sharing it internally within organizations, but across organizations. What are some of the business needs that you guys are seeing in the market? >> BALAJI GANESAN: Yes. So going back to the old business strategy is making sure that organizations can leverage data for driving business agility. So data is not a domain for a specific business groups, but organization how they can break down silos, which are existing in the past and leverage data to the maximum value for the organization. So, if you have a marketing team owning marketing data, can this marketing data be accessed by supply chain teams? Or to get some inputs on customers and how they are behaving? So, it doesn't have a lot of value if marketing team holds that data on its own and leverages that. So organizations are trying, chief data officers, one of the biggest things they are trying to do is, how do you break those silos in and make it a more, a common paradigm? Which means that you need to start sharing data. You may, again, in the data governance paradigm or data mesh paradigm, business owners can still own the data and the marketing team can still own the data, but how can you share the data and make sure, again, governance is maintained? You don't want to go and have a very open sharing mechanism that everybody has access to it. You want to do it in a way that only right people have access to the right data for right purpose. So how do you share that data internally? And then it's the extension of that is organizations want to share data across organizations, whether you're in a healthcare industry, whether you are in consumer tech, and that can drive more business value as part of it. But it's the same paradigm. You don't want to share everything. You want to maintain your IP, you want to maintain the compliance, but how do you leverage the data and unblock those silos? And so, again, going back, the paradigm we live in is how organizations can balance both? How you can share data, break down those silos, but how do you bring governance in and security in? That's the interesting paradigm we live in today. >> LISA MARTIN: That external data sharing, something that you brought up is interesting. If that's not governed secured, I imagine huge challenges and risks for organizations. How does Privacera help with that and some of the other AWS partners in that external data sharing, making sure it's done safely and secure? >> BALAJI GANESAN: Yes, absolutely. And so one of the paradigms, again, our mission for us is, how can help organizations in this dual mandate of sharing data, but preserving compliance, security and privacy within that part of it? What we are doing is we are taking our notch into these controls into the next level of governance, right. So we are providing tools to make it very easy for enterprises to share data internally, as well as externally, without the need for writing a lot of policies as part of it. The traditional paradigm has to be that if you need to share data, you have to go and write a rule and a policy, in every layer of the data exist as part of it. What we are doing is we are abstracting that, and we are providing a very easy mechanism. You'll see more announcements coming up in the next few months around our data sharing paradigm is, can you just make it easy for people to share data on few clicks without the need for writing rules and policies and knowing a lot about underlying databases? And we take all that complexity and we translate that complexity internally. So what we are doing is making it for an organization to share in few clicks a data, a marketing team to share data based on a business purpose, and have time limits around it, have governance around it, but not needing for the marketing team to go and hire somebody to understand and write a policies around that. So removing that friction, part of it, removing those complexity and going back to the role of providing that governance layer of sharing, and it applies to both internal and external sharing, again. Behind the scenes we are leveraging the power of the underlying data platforms. We are leveraging the power of what AWS provides. We have deep integrations with things like Lake Formation and other things which are providing more deeper controls, but those complexities are abstracted for the user, they don't have to understand all of those nuances. They have to simply go and say, I want to share this data with X user. Do I want to do it or not, and if I do it for what purposes? And that's it. And just making that easy enough while taking all the complexity away is what we're doing. Again, going back to the goal. We want users to share data, we want users to leverage data, not be a zero sum game. But how they can do that without the need for hiring, understanding a lot of complexity. With taking over the complexity, what we are seeing that it makes it easier, it's an accelerant, it's a faster time to value. >> LISA MARTIN: Faster time to value also by abstracting the complexities, removing the friction, you probably make workforce productivity and collaboration and partnerships even more valuable. One of the things last question that I wanted to bring up is a marketing term that is one that I, kind of like fingernails on a chalkboard, for me as a marketer it's feature proofing. You know, as we've seen in the last year and a half, there was a a lot of us, a lot of industries that weren't future ready when the pandemic struck. When Privacera thinks of making enterprises ready for the future, as data volumes continue to expand and grow as does sources of data, what is future-proofing for your enterprise customers? What does that mean to you? >> BALAJI GANESAN: Yeah, that's a great question, because we have these conversations with CIOs and Chief Data Officers, and you always look in the prism of not just what organizations are doing today, but what are they going to do three years, five years down the line? And the trends I've talked about in before, the digitization, the public cloud, these are long-term trends, these are happening across the organization. So most organizations, like Sun Life, have data in the cloud. They continue to have data on-premise and they potentially tomorrow can be multicloud as well. And if you look at what is going to happen in the next three, five years is data use is going to accelerate, cloud migration is going to accelerate, users, companies are going to be in hybrid cloud and multicloud, but governance privacy is becoming even more stringent. So the trends are secular trends that are going accelerating. And so what we are doing is not a short term, it's built for the medium and the long-term part of it. And our solution, what we are doing is by abstracting out the complexity, we are also making it easier for organizations to scale. They are not dependent on one platform or a solution. They are dealing at a higher governance level, and we have abstracted out the complexity and dependency with a specific platform. So tomorrow they can switch that and put something else in. They don't have to reinvent those policies. They don't have to reinvent the data sharing paradigm, right. And by abstracting that we are future proofing and in terms of how their data strategy is going to be, and that's the value that we simply add, we can provide. And that's the value that we are providing is you don't have to change your governance when you're changing your data platforms. You don't have to change your governance based on what cloud you are choosing, your governance needs to be stuck, all right. Your governance needs to be strategic, your platforms can change. Privacera is in that, is that glue which is enabling you to have a cohesive long-term strategy, but that is scalable, not just today, but tomorrow in the multicloud and hybrid cloud world. >> LISA MARTIN: Got it, Privacera that glue. Point the audience audience, Balaji, as we wrap things up here, to where they can go to learn more about Privacera, what you guys are able to do, and maybe even find that Sun Life case study. >> BALAJI GANESAN: Absolutely. Bulk of the information is available in privacera.com and so you can go and find us and we'll make those case studies and videos available as well. If you have any questions you can drop a note privacera.com or reach out to any of our account representative. >> LISA MARTIN: And hopefully we'll see you at re:Invent in person, crossing fingers. >> BALAJI GANESAN: Absolutely, looking forward to that. And really looking forward to a world where we can see each other in person and in the conference and in the community together again. So we are really looking forward to that. And we are planning big time to be an active participant in that. >> LISA MARTIN: Excellent, I look forward to that. For Balaji Ganesan, I am Lisa Martin. This has been part of our coverage of the AWS startup showcase new breakthroughs in DevOps, data analytics and cloud management tools. Thanks for watching. (upbeat techno music)

(Upbeat music) >> Okay, welcome back everyone, to theCUBE's Coverage of Red Hat Summit 2021 virtual I'm John Furrier, your host of theCUBE got two great guests from Deloitte Consulting Dave Knight who manages the Red Hat Relationship, Lee he's the lead there, and Mike Bourgeois who's the Public Sector Managing Director both from Deloitte Consulting LLP official name. Guys, great to come on, and we were just talking before camera about all the stories. Great to have you on theCUBE, thanks for coming on. >> Yeah, thanks for having me. >> Like I said we were just talking about all the stories from the transition from pre-COVID, COVID. Now we've got a view into post-COVID. I want to dig into that 'cause there's a lot of things happening. You guys have been in the trenches, front lines bringing solutions, but before we get into that, can you guys just introduce yourself share your roles at Deloitte and give us a quick overview of what you work on. >> Yeah, so again, thanks for having us John Dave Knight I'm a solution architect and Global Red Hat Alliance Manager for Deloitte. I've got responsibility for making sure that play nicely in the sandbox together or we've got a joint customer and solutions to deliver to those customers. >> Hi everyone, thanks for having us John, I'm a Managing Director Mike Bushwa out of Boston Texas. I am coming up on year 20 and Public Sector Consulting. My area of expertise is large state government systems that serve the needs of millions of citizens and thousands of state workers, good to be here. >> Yeah. Great to have you. And I wanted to chime in with you right away because Mike you are living in probably one of the hottest markets Public Sector. I've been following that for many, many years, generations actually from the early computer industry GSA contracts, all these contracts you've got all the Public Sector, they move very slowly but now the pandemic, there was no place to hide. Everything got pulled back, disruption, you can't just shut down critical infrastructure and critical services. People had to move fast. What was your experience and how is it now give us a taste of some of the challenges and the landscape. >> You bet John, so we talked a little bit before we started this, but my 20 year consulting career, I can't think of anything really in close to this, other than maybe Y2K and as Dave mentioned the Affordable Care Act Legislation in 2009, though that was a much smaller scale as it turned out to be. So I would be remiss not to share examples of extraordinary challenges our clients have had related to the pandemic. Department of Labor and Health and Human Service Agencies for example, responded to the pandemic in rapid timeframe that were rarely seen in government. Citizens that were used to coming in appealed offices, We're now required to do most things virtually. Deloitte has been privileged to assist clients with digital solutions across the country in response to this unprecedented event. And so I'd like to share just a couple of examples. The first is for Department of Labor, the pandemic contributed to millions of layoffs throughout the country Department of Labor workers found called volumes increasing by a 1000% in some cases, the amount of increased volume required agencies across the country hire temporary workers to help out. Millions of new unemployment claims needed to be filed in benefits rapidly provided to citizens of name. So the big challenge was the agency had to figure out how to rapidly file claims into the unemployment system, rather than requiring new citizens to use an external web application they were really unfamiliar, the agency needed more efficient approach. The approach we used was to create an internal web application that enabled workers to file unemployment insurance claims on behalf of citizens. Workers collected the necessary data from citizens and claims were filed into the system. The application enabled workers to focus on filing claims rather than sort of a technical support role showing how to people use an external web application. More citizen were served in much less time, claims are filed efficiently by train workers which resulted in benefits being received in a much more timely fashion. And so a second example is, with Department of Human Services. So one stay as mentioned Citizens were used to going into field offices but suddenly they were told you can't come into the field office. So once they provided a 100% virtual application and the important part here is certification solution for the Disaster Supplemental Nutrition Assistance Program or DSNAP for short. this application was stood up in two weeks, families who needed food assistance can now apply and be certified for benefits remotely. Today over 50,000 cases have certified and citizens receiving food nutrition assistance. Back to you John. >> So, I mean obviously there's some great use cases you got, basically I got to work at home, new architecture there you got to have a new workflows. I mean, this poses some real challenges. How did you guys put it together? I mean, Dave take us through where this all fits in with the Red Hat, because obviously now it's new deployment new capabilities have to be deployed for the pandemic. How does this bring together the partnership with Red Hat? >> Yeah, so great question and it really plays to the strength of both Deloitte and Red Hat, right? The success stories that Mike has illustrated show how we can quickly pivot as a firm to delivering these types of solutions and help our customers think through innovative ways to solve the problems. So, I mean the prime example that Mike just gave, everything used to be done in offices. Now it's all done remotely cause you can't go to the office even if you want to. And that is very much aligned with the innovation we get with our partnership with Red Hat, right? They've led the way in open source and some of the technologies that we've leveraged that our solutions include, answerable for automation, some of the middleware products, and I would say one of the cornerstones is the OpenShift Platform. Now that allows us to greatly accelerate the development and delivery of those solutions to our customers. Sort of again, aligning our innovative thinking with Red Hats Innovative Technologies. >> What would you say if someone said, "what's the partnership strengths and what needs specifically are you addressing with customers and customer needs?" >> So I, again, I think our lean towards innovation is a common thread across both firms and where we have our greatest strength. We like to take our customers on a journey but it's not our journey, it's their journey, right? So we help them figure out where they want to go and how they want to get there in a way that aligns with their business goals, their budgets all the sort of factors that drive those things and Red Hat is very open to that approach. They sort of invented the crowdsourcing of open source they made it into a business model. They've developed that from literally nothing. And that aligns very nicely with us. That's one of the key strengths. We also are firm believers in open source again to the degree that our customers like the leverage that to drive their journeys. And we're seeing that, especially in the Public Sector Space as being a key driver of the technologies they employ. >> Mike, I want to come back to you on this open ma component open question, open source, open to technology open innovation out in the open as Red Hat calls it. How does Red Hat open source software, address the needs for your customers for security and on-premise considerations. >> I'll talk a little bit about open source principles in general still the open source principles of transparency meritocracy community problem solving and collaboration. These are on its of both software innovation as well as organizational transformation. One of the highest demand transformation needs that I'm seeing in the market is the desire to adopt innovative technology, and most importantly, moving workloads to the cloud. It's no longer a thought, it is an imperative moving workloads to the cloud, on new deals hosted in the cloud, on an existing, is it large systems let Deloitte help us get to the cloud. So I believe the key to success embracing the cloud is recognizing first the need for change in people, processes and technology. The vehicle for this transformation is DevSecOps and innovative open source platforms, such as the OpenShift platform that Dave mentioned. OpenShift focuses on people, processes and technology and the security conversation becomes even easier. I mean, I see Linux was around for years, and we've always used Linux on our Java based workloads now we can have the conversation about saying, Hey, well that se Linux operating system we've been using for years now, there's this really cool Container Management Platform that we can solve real problems like auto scaling, in my Health and Human Services career, I can remember every year when open enrollment comes around systems engineers are teed up, and ready to manually add those to a BMR cluster or something like that. Well, now we don't have to do these things. We can rely on Kubernetes so auto scale, and then and get rid of those instances when workload demands seven resolved. So it's a really cool technology kind of behind the scenes. It's not the dog and pony show sometimes but in the end it helps the clients and Deloitte remain consistent with those service level agreements. >> That's a great example about the open enrollment illustrates the fact that, you got to provision more stuff to take that load on it. It's always hard in Public Sector you might not have the speed. So I got to follow up and ask you, you guys have had wins in the Public Sector lately with Red Hat, you guys Deloitte and Red Hat working together and get some wins under your belt, on around cloud and cloud and technology obviously with the pandemic has needs there. Are you guys seeing any particular sector challenges specifically around Public Sector as it goes this next level a lot of modernization happening we're seeing that, but any challenges that you're seeing, can you give some examples of how these challenges are being addressed? First talk about the challenges and then give some examples of how they're overcoming them. >> So I can jump in here with this one then, and Mike I think you probably have some maybe Public Sector specific examples, but one of the things that I think is common across all industries is resource constraints, right? And particularly as we look for human resources and not in the HR sense, but developers, CIS admins those types of resources as Mike said, the cloud is here to stay, right? And it's not something that people are thinking about it's de facto part of the conversation. And that's great, but it leads to silos of skills which puts further sort of strain on a limited pool of resources within most sites IT organization. So something like an OpenShift, something like an Ansible solves problems related to resource constraints, because they're skills that are portable across cloud environments, right? If you can manage OpenShift you can manage OpenShift on-prem, you can manage it recently released AWS version of that ROSA on the Azure version of that. So it's no matter where you're running it you've got a common set of skills and access sort of a force multiplier, same thing with Ansible automation, right? If you can write scripts, with an Ansible you can do those repeatable tasks in a much more efficient fashion. And again sort of multiplying the capacity of your existing workforce. >> So you've got an operating leverage there. I mean, this is what you're getting at is that, Public Sector and other commercial areas they kind of got to get used to this fact that, you get some leverage here, you get some operating leverage. >> More or less has always been a thing in IT. And it's not relenting that's for sure. >> It's been more at the more, with less has always been kind of a tagline for budget cuts, right? You can squeeze more out of the investment. Here it's kind of like do more with less than the sense of there's more net new things happening with leverage. So, I mean, do you agree with that? What's your take on that? >> Yeah, I think that's exactly right. It's more with less from a resource perspective, right? Typically it was budget, but no money is just another resource. Now we're getting into the personnel side of it. The other thing I would say is, something like an OpenShift Platform allows the Mike's point around DevOps, it allows the developers to develop, right? I have an article in wired.com about this, where developers are saddled with meetings and they have to become concerned with infrastructure and they have traditionally and security. And I am I doing all these things that aren't related to development. If you have a good DevOps Platform in place the security folks can build guard rails into the platform and the developers can just go develop which is what they want to do in the first place. Yeah exactly, that's another riff on the more, with less, again in a resource, the human resource way versus the budget way. >> Yeah, and that really is where OpenShift ties in. Mike what's your take on this? Because with this kind of program ability infrastructure as code DevSecOps kind of modern developers, Public Sector loves that, because they just want to build the new apps. They got to modernize. So change the infrastructure once. And then a lot of ma many benefits on top of it. It's almost like, it sounds like an operating system to me. >> Yeah, lots of thoughts going around my head right now but I'll say the more with less to me when I'm having client conversations is imagine a world of higher innovation, more technology at lower costs, right? I mean, so CIO is light up when I explained to them the orders of magnitude cost savings on top of the innovation introduced to their environment. So when moving workloads to the cloud is not as easy as just packaging up a binary and dropping in on a name, your cloud provider, right? There's an entire, a blueprinting strategy. There's a Cloud Native Architecture, modernization discussion, so we do those sorts of things, at Deloitte and we work with clients very closely to do that. I want to say teaming with Red Hat allows us to be proactive with our design and reference architecture validation. The Collaborative Partnership in Relationship allows us to connect senior engineers from Deloitte and Red Hat. So we have low level strategic discussions, we validate our assumptions and optimize to use a Red Hat technology. What we're doing in Public Sector is separating the monolithic application into layers. And whenever it comes to technologies like Ansible, like OpenShift, like Jenkins, all of these things that any application needs and Public Sector, we're saying out to the account teams across the country, look this is a slower layer DevOps Platform. And by the way, you can run any .Net or Java based workload on it. So we're trying to make opinionated reference architecture so that regardless of the solution, we can just go to market with that platform that tried and true production application. So I'll give a quick example John, if now's a convenient time regarding, well, one of the things that we've done for particular state client. >> Definitely yeah, give the use cases we love those. >> Yes so one of the impactful modernization that struck my mind was the State of Washington. They've mentioned the affordable care act earlier, there are two major things that came out of that. One was the eligibility and enrollment systems had to be modified across all 50 states. But the second thing and the primary driver behind the affordable care act was health insurance exchange. A way for millions of citizens to have access to healthcare using Subsidized Health Insurance Plans. So in Washington and health benefits exchange is that health insurance exchange, State of Washington has been a client of Deloitte since 2012. The solution was originally designed using closed source proprietary products. There are three drivers for change. The first is the API gateway was end of life and needed to be replaced. Number two was the client wanted it to move health benefit exchange to the cloud from an on-premise hosting arrangement. And third is reducing cost of those solution with innovative products. So the agency was looking for a platform that provided flexibility, auto-scaling and performance and lower cost of ownership. So we worked with the agency and we evaluated a variety of API Management and Integration Platforms after reviewing the outcomes for each proof of concept the agency decided to move forward with Red Hats, three skill API Management Platform, Red Hat Fuse for Integration and OpenShift Container Platform that offered the auto-scaling continuous integration tools and out of the box monitoring and reporting capabilities proactively monitor the health of the solution. I often describe a little bit of OpenShift as a data center or DevSecOps in the box. It just is all there. You don't need to add layers on top of OpenShift install and configure it, tune it and just you're off and running in a short amount of time. So three outcomes I'll mention, go ahead, John. >> NO continue, I thought you were finished. So on the outcomes side, the first outcome the agency substantially lower the cost of ownership using commercially supported open source while increasing access to innovative emerging technology. So the agency wanted a solution not only to meet their current needs, but extend the solution going forward. The beautiful thing about OpenShift is you can drop a container images into the platform without installing an operating system. It's all just there and it's spreading to be extended. The number two outcome cloud migration. Deloitte work collaboratively with the agencies and infrastructure and managed services team to successfully migrate the health benefit exchange to the cloud. And the last thing a bit obvious, but that's successful release, working collaboratively with our client. We were able to migrate the solution within 100 days from making the products decision. The cut over to the new solution was seamless with minimal downtime and zero production issues or exceptionally proud of that. >> Great stuff, great use case. And again, those are great business examples. Dave, I want to get this last question to you and Mike can chime in too. As Red Hat Summit evolves, and we're hearing the theme here at the event about transformation is the innovation, Innovation is about scale. When you hear the words like in a box or Hybrid Cloud you hear about an operating environment. So it's an opportunity to set the table for the next generation, this is what I see. What do you guys see as people talk about Hybrid Cloud and soon to be Multiple Cloud? Because you guys you said have tough relationships. You deal with IBM and Red Hat and you probably deal with other people. Clients want, from what we hear they want back to the Multi Vendor Open Connection Distributed Environment. That's what they want. So how does your relationship evolve, given all this is happening? How do you see the future, please chime in. >> Thanks, that's a fantastic question. I actually think the market is coming catching up to where I've been thinking for quite a while. And that is the Hybrid is kind of where it's at. A lot of customers have been in some sort of Hybrid mode as part of the step or a journey to the cloud, getting all the way to the cloud. But I think we're seeing some transition. I know customers are starting to ask me more and more about Hybrid solutions for a variety of reasons, right? The easy workloads for the most part have either been moved or be are being moved, or at least there's a strategy and a plan to get them moved. And now we're starting to be asked about some of the more difficult architecture type questions, right? The workloads that are a little bit more sticky to the on-premise model. And so Hybrid becoming more of the endpoint as opposed to a step along the journey. The other big thing is some repatriation, right? Workloads coming off of cloud. Maybe they seem like good candidates but for whatever reason, the cost drivers or other things weren't realized, let's get them back on premise. Maybe it's a regulatory thing and new regulations are making folks uncomfortable. So I see Hybrid as a pretty interesting next wave of cloud, Deloitte as a far or we're skilling up or tooling up in order to address the needs of our customers, again are starting to ask us these really challenging questions about Hybrid Cloud and Hybrid Cloud Architectures. >> Yeah and just the key point there is that you think about it like with the way you're discussing it, it's a platform, not a tool, right? So if you think about it like a platform then you can move things around and look at architectures and changes of how resources and workloads are deployed and then what data you're getting from it. Whether you bring it to a factory, for instance you say, Hey, okay, we're going to put it on prem because it's a factory or whatever, and you need more data. What was the changeover? This is like a day to operations kind of mindset. What's your comment on that? >> Well I mean I have actually going back three years now, one of the marketing lines that we developed internally, was moved to a platform, not a provider. But because you get that flexibility, now, the reality is what works stay where they're put for a variety of reasons. But I think one of those reasons could be, because they're put in places where they tend to not want to move, right? So if we could put them into a platform where, there is some portability built into the platform, I think we might have a different sort of outcomes for customers. And I think architecture is absolutely the key, right? That to me is the secret sauce here. >> Mike set up for you to close us out here, platform, Public Sector, Hybrid, that's what they want. It's an ideal scenario for anyone in Public Sector and in general, and why wouldn't you want to have a great platform that's it can be programmed, and rearchitected at will for the benefit of the business powered by software. What's your thoughts? >> Yeah, all good points and I will agree with Dave that Hybrid is certainly evolving. Eight years ago, Hybrid was consuming and address validation API in the cloud and not custom coding that, but today I do agree that Hybrid Cloud is all about a vehicle a way of moving workloads across data centers. It's an architecture that is encapsulated by something like an OpenShift so that you can federate your workloads across data centers. You can put them in one or easily moved them to the other. Maybe that's for a variety of reasons. It could be compute and storage is being reduced by one provider versus the other. So the solutions were we're designing today, they are data center agnostic, we're not being tied to data centers anymore. The best design solutions, you can just let them move in their easy manner. So that that's my take on Hybrid Cloud. And I would say the and Red Hat are making investments to help us advance that thinking help us advance those solutions. We had Deloitte have created a Red Hat OpenShift lab environment, and we've done this purposely to validate reference architectures to show account teams the way we have delivered the very very large accounts to show them what DevSecOps to means from a product perspective and to give them opinionated processes to be successful in delivering these large type solutions. >> Dave, Mike, thanks for coming on, and I appreciate you guys coming on theCUBE and sharing the perspective on the Red Hat Relationship with Deloitte Consulting. Thanks for coming on. >> Thank you. >> Thank you, John. >> This is CUBE Coverage of Red Hat Summit 2021, am John for your host, thanks for watching.

(upbeat music) >> Hi everyone, thank you for joining us at the Data Cloud Summit. The last couple of months have been an exciting time at Snowflake. And yet, what's even more compelling to all of us at Snowflake is what's ahead. Today I have the opportunity to share new product developments that will extend the reach and impact of our Data Cloud and improve the experience of Snowflake users. Our product strategy is focused on four major areas. First, Data Cloud content. In the Data Cloud silos are eliminated and our vision is to bring the world's data within reach of every organization. You'll hear about new data sets and data services available in our data marketplace and see how previous barriers to sourcing and unifying data are eliminated. Second, extensible data pipelines. As you gain frictionless access to a broader set of data through the Data Cloud, Snowflakes platform brings additional capabilities and extensibility to your data pipelines, simplifying data ingestion, and transformation. Third, data governance. The Data Cloud eliminates silos and breaks down barriers and in a world where data collaboration is the norm, the importance of data governance is ratified and elevated. We'll share new advancements to support how the world's most demanding organizations mobilize your data while maintaining high standards of compliance and governance. Finally, our fourth area focuses on platform performance and capabilities. We remain laser focused on continuing to lead with the most performant and capable data platform. We have some exciting news to share about the core engine of Snowflake. As always, we love showing you Snowflake in action, and we prepared some demos for you. Also, we'll keep coming back to the fact that one of the characteristics of Snowflake that we're proud as staff is that we offer a single platform from which you can operate all of your data workloads, across clouds and across regions, which workloads you may ask, specifically, data warehousing, data lake, data science, data engineering, data applications, and data sharing. Snowflake makes it possible to mobilize all your data in service of your business without the cost, complexity and overhead of managing multiple systems, tools and vendors. Let's dive in. As you heard from Frank, the Data Cloud offers a unique capability to connect organizations and create collaboration and innovation across industries fueled by data. The Snowflake data marketplace is the gateway to the Data Cloud, providing visibility for organizations to browse and discover data that can help them make better decisions. For data providers on the marketplace, there is a new opportunity to reach new customers, create new revenue streams, and radically decrease the effort and time to data delivery. Our marketplace dramatically reduces the friction of sharing and collaborating with data opening up new possibilities to all participants in the Data Cloud. We introduced the Snowflake data marketplace in 2019. And it is now home to over 100 data providers, with half of them having joined the marketplace in the last four months. Since our most recent product announcements in June, we have continued broadening the availability of the data marketplace, across regions and across clouds. Our data marketplace provides the opportunity for data providers to reach consumers across cloud and regional boundaries. A critical aspect of the Data Cloud is that we envisioned organizations collaborating not just in terms of data, but also data powered applications and services. Think of instances where a provider doesn't want to open access to the entirety of a data set, but wants to provide access to business logic that has access and leverages such data set. That is what we call data services. And we want Snowflake to be the platform of choice for developing discovering and consuming such rich building blocks. To see How the data marketplace comes to live, and in particular one of these data services, let's jump into a demo. For all of our demos today, we're going to put ourselves in the shoes of a fictional global insurance company. We've called it Insureco. Insurance is a data intensive and highly regulated industry. Having the right access control and insight from data is core to every insurance company's success. I'm going to turn it over to Prasanna to show how the Snowflake data marketplace can solve a data discoverability and access problem. >> Let's look at how Insureco can leverage data and data services from the Snowflake data marketplace and use it in conjunction with its own data in the Data Cloud to do three things, better detect fraudulent claims, arm its agents with the right information, and benchmark business health against competition. Let's start with detecting fraudulent claims. I'm an analyst in the Claims Department. I have auto claims data in my account. I can see there are 2000 auto claims, many of these submitted by auto body shops. I need to determine if they are valid and legitimate. In particular, could some of these be insurance fraud? By going to the Snowflake data marketplace where numerous data providers and data service providers can list their offerings, I find the quantifying data service. It uses a combination of external data sources and predictive risk typology models to inform the risk level of an organization. Quantifying external sources include sanctions and blacklists, negative news, social media, and real time search engine results. That's a wealth of data and models built on that data which we don't have internally. So I'd like to use Quantifind to determine a fraud risk score for each auto body shop that has submitted a claim. First, the Snowflake data marketplace made it really easy for me to discover a data service like this. Without the data marketplace, finding such a service would be a lengthy ad hoc process of doing web searches and asking around. Second, once I find Quantifind, I can use Quantifind service against my own data in three simple steps using data sharing. I create a table with the names and addresses of auto body shops that have submitted claims. I then share the table with Quantifind to start the risk assessment. Quantifind does the risk scoring and shares the data back with me. Quantifind uses external functions which we introduced in June to get results from their risk prediction models. Without Snowflake data sharing, we would have had to contact Quantifind to understand what format they wanted the data in, then extract this data into a file, FTP the file to Quantifind, wait for the results, then ingest the results back into our systems for them to be usable. Or I would have had to write code to call Quantifinds API. All of that would have taken days. In contrast, with data sharing, I can set this up in minutes. What's more, now that I have set this up, as new claims are added in the future, they will automatically leverage Quantifind's data service. I view the scores returned by Quantifind and see the two entities in my claims data have a high score for insurance fraud risk. I open up the link returned by Quantifind to read more, and find that this organization has been involved in an insurance crime ring. Looks like that is a claim that we won't be approving. Using the Quantifind data service through the Snowflake data marketplace gives me access to a risk scoring capability that we don't have in house without having to call custom APIs. For a provider like Quantifind this drives new leads and monetization opportunities. Now that I have identified potentially fraudulent claims, let's move on to the second part. I would like to share this fraud risk information with the agents who sold the corresponding policies. To do this, I need two things. First, I need to find the agents who sold these policies. Then I need to share with these agents the fraud risk information that we got from Quantifind. But I want to share it such that each agent only sees the fraud risk information corresponding to claims for policies that they wrote. To find agents who sold these policies, I need to look up our Salesforce data. I can find this easily within Insureco's internal data exchange. I see there's a listing with Salesforce data. Our sales Ops team has published this listing so I know it's our officially blessed data set, and I can immediately access it from my Snowflake account without copying any data or having to set up ETL. I can now join Salesforce data with my claims to identify the agents for the policies that were flagged to have fraudulent claims. I also have the Snowflake account information for each agent. Next, I create a secure view that joins on an entitlements table, such that each agent can only see the rows corresponding to policies that they have sold. I then share this directly with the agents. This share contains the secure view that I created with the names of the auto body shops, and the fraud risk identified by Quantifind. Finally, let's move on to the third and last part. Now that I have detected potentially fraudulent claims, I'm going to move on to building a dashboard that our executives have been asking for. They want to see how Insureco compares against other auto insurance companies on key metrics, like total claims paid out for the auto insurance line of business nationwide. I go to the Snowflake data marketplace and find SNL U.S. Insurance Statutory Data from SNP. This data is included with Insureco's existing subscription with SMP so when I request access to it, SMP can immediately share this data with me through Snowflake data sharing. I create a virtual database from the share, and I'm ready to query this data, no ETL needed. And since this is a virtual database, pointing to the original data in SNP Snowflake account, I have access to the latest data as it arrives in SNPs account. I see that the SNL U.S. Insurance Statutory Data from SNP has data on assets, premiums earned and claims paid out by each us insurance company in 2019. This data is broken up by line of business and geography and in many cases goes beyond the data that would be available from public financial filings. This is exactly the data I need. I identify a subset of comparable insurance companies whose net total assets are within 20% of Insureco's, and whose lines of business are similar to ours. I can now create a Snow site dashboard that compares Insureco against similar insurance companies on key metrics, like net earned premiums, and net claims paid out in 2019 for auto insurance. I can see that while we are below median our net earned premiums, we are doing better than our competition on total claims paid out in 2019, which could be a reflection of our improved claims handling and fraud detection. That's a good insight that I can share with our executives. In summary, the Data Cloud enabled me to do three key things. First, seamlessly fine data and data services that I need to do my job, be it an external data service like Quantifind and external data set from SNP or internal data from Insureco's data exchange. Second, get immediate live access to this data. And third, control and manage collaboration around this data. With Snowflake, I can mobilize data and data services across my business ecosystem in just minutes. >> Thank you Prasanna. Now I want to turn our focus to extensible data pipelines. We believe there are two different and important ways of making Snowflakes platform highly extensible. First, by enabling teams to leverage services or business logic that live outside of Snowflake interacting with data within Snowflake. We do this through a feature called external functions, a mechanism to conveniently bring data to where the computation is. We announced this feature for calling regional endpoints via AWS gateway in June, and it's currently available in public preview. We are also now in public preview supporting Azure API management and will soon support Google API gateway and AWS private endpoints. The second extensibility mechanism does the converse. It brings the computation to Snowflake to run closer to the data. We will do this by enabling the creation of functions and procedures in SQL, Java, Scala or Python ultimately providing choice based on the programming language preference for you or your organization. You will see Java, Scala and Python available through private and public previews in the future. The possibilities enabled by these extensibility features are broad and powerful. However, our commitment to being a great platform for data engineers, data scientists and developers goes far beyond programming language. Today, I am delighted to announce Snowpark a family of libraries that will bring a new experience to programming data in Snowflake. Snowpark enables you to write code directly against Snowflake in a way that is deeply integrated into the languages I mentioned earlier, using familiar concepts like DataFrames. But the most important aspect of Snowpark is that it has been designed and optimized to leverage the Snowflake engine with its main characteristics and benefits, performance, reliability, and scalability with near zero maintenance. Think of the power of a declarative SQL statements available through a well known API in Scala, Java or Python, all these against data governed in your core data platform. We believe Snowpark will be transformative for data programmability. I'd like to introduce Sri to showcase how our fictitious insurance company Insureco will be able to take advantage of the Snowpark API for data science workloads. >> Thanks Christian, hi, everyone? I'm Sri Chintala, a product manager at Snowflake focused on extensible data pipelines. And today, I'm very excited to show you a preview of Snowpark. In our first demo, we saw how Insureco could identify potentially fraudulent claims. Now, for all the valid claims InsureCo wants to ensure they're providing excellent customer service. To do that, they put in place a system to transcribe all of their customer calls, so they can look for patterns. A simple thing they'd like to do is detect the sentiment of each call so they can tell which calls were good and which were problematic. They can then better train their claim agents for challenging calls. Let's take a quick look at the work they've done so far. InsureCo's data science team use Snowflakes external functions to quickly and easily train a machine learning model in H2O AI. Snowflake has direct integrations with H2O and many other data science providers giving Insureco the flexibility to use a wide variety of data science libraries frameworks or tools to train their model. Now that the team has a custom trained sentiment model tailored to their specific claims data, let's see how a data engineer at Insureco can use Snowpark to build a data pipeline that scores customer call logs using the model hosted right inside of Snowflake. As you can see, we have the transcribed call logs stored in the customer call logs table inside Snowflake. Now, as a data engineer trained in Scala, and used to working with systems like Spark and Pandas, I want to use familiar programming concepts to build my pipeline. Snowpark solves for this by letting me use popular programming languages like Java or Scala. It also provides familiar concepts in APIs, such as the DataFrame abstraction, optimized to leverage and run natively on the Snowflake engine. So here I am in my ID, where I've written a simple scalar program using the Snowpark libraries. The first step in using the Snowpark API is establishing a session with Snowflake. I use the session builder object and specify the required details to connect. Now, I can create a DataFrame for the data in the transcripts column of the customer call logs table. As you can see, the Snowpark API provides native language constructs for data manipulation. Here, I use the Select method provided by the API to specify the column names to return rather than writing select transcripts as a string. By using the native language constructs provided by the API, I benefit from features like IntelliSense and type checking. Here you can see some of the other common methods that the DataFrame class offers like filters like join and others. Next, I define a get sentiment user defined function that will return a sentiment score for an input string by using our pre trained H2O model. From the UDF, we call the score method that initializes and runs the sentiment model. I've built this helper into a Java file, which along with the model object and license are added as dependencies that Snowpark will send to Snowflake for execution. As a developer, this is all programming that I'm familiar with. We can now call our get sentiment function on the transcripts column of the DataFrame and right back the results of the score transcripts to a new target table. Let's run this code and switch over to Snowflake to see the score data and also all the work that Snowpark has done for us on the back end. If I do a select star from scored logs, we can see the sentiment score of each call right alongside the transcript. With Snowpark all the logic in my program is pushed down into Snowflake. I can see in the query history that Snowpark has created a temporary Java function to host the pre trained H20 model, and that the model is running right in my Snowflake warehouse. Snowpark has allowed us to do something completely new in Snowflake. Let's recap what we saw. With Snowpark, Insureco was able to use their preferred programming language, Scala and use the familiar DataFrame constructs to score data using a machine learning model. With support for Java UDFs, they were able to run a train model natively within Snowflake. And finally, we saw how Snowpark executed computationally intensive data science workloads right within Snowflake. This simplifies Insureco's data pipeline architecture, as it reduces the number of additional systems they have to manage. We hope that extensibility with Scala, Java and Snowpark will enable our users to work with Snowflake in their preferred way while keeping the architecture simple. We are very excited to see how you use Snowpark to extend your data pipelines. Thank you for watching and with that back to you, Christian. >> Thank you Sri. You saw how Sri could utilize Snowpark to efficiently perform advanced sentiment analysis. But of course, if this use case was important to your business, you don't want to fully automate this pipeline and analysis. Imagine being able to do all of the following in Snowflake, your pipeline could start far upstream of what you saw in the demo. By storing your actual customer care call recordings in Snowflake, you may notice that this is new for Snowflake. We'll come back to the idea of storing unstructured data in Snowflake at the end of my talk today. Once you have the data in Snowflake, you can use our streams and past capabilities to call an external function to transcribe these files. To simplify this flow even further, we plan to introduce a serverless execution model for tasks where Snowflake can automatically size and manage resources for you. After this step, you can use the same serverless task to execute sentiment scoring of your transcript as shown in the demo with incremental processing as each transcript is created. Finally, you can surface the sentiment score either via snow side, or through any tool you use to share insights throughout your organization. In this example, you see data being transformed from a raw asset into a higher level of information that can drive business action, all fully automated all in Snowflake. Turning back to Insureco, you know how important data governance is for any major enterprise but particularly for one in this industry. Insurance companies manage highly sensitive data about their customers, and have some of the strictest requirements for storing and tracking such data, as well as managing and governing it. At Snowflake, we think about governance as the ability to know your data, manage your data and collaborate with confidence. As you saw in our first demo, the Data Cloud enables seamless collaboration, control and access to data via the Snowflake data marketplace. And companies may set up their own data exchanges to create similar collaboration and control across their ecosystems. In future releases, we expect to deliver enhancements that create more visibility into who has access to what data and provide usage information of that data. Today, we are announcing a new capability to help Snowflake users better know and organize your data. This is our new tagging framework. Tagging in Snowflake will allow user defined metadata to be attached to a variety of objects. We built a broad and robust framework with powerful implications. Think of the ability to annotate warehouses with cost center information for tracking or think of annotating tables and columns with sensitivity classifications. Our tagging capability will enable the creation of companies specific business annotations for objects in Snowflakes platform. Another key aspect of data governance in Snowflake is our policy based framework where you specify what you want to be true about your data, and Snowflake enforces those policies. We announced one such policy earlier this year, our dynamic data masking capability, which is now available in public preview. Today, we are announcing a great complimentary a policy to achieve row level security to see how role level security can enhance InsureCo's ability to govern and secure data. I'll hand it over to Artin for a demo. >> Hello, I'm Martin Avanes, Director of Product Management for Snowflake. As Christian has already mentioned, the rise of the Data Cloud greatly accelerates the ability to access and share diverse data leading to greater data collaboration across teams and organizations. Controlling data access with ease and ensuring compliance at the same time is top of mind for users. Today, I'm thrilled to announce our new row access policies that will allow users to define various rules for accessing data in the Data Cloud. Let's check back in with Insureco to see some of these in action and highlight how those work with other existing policies one can define in Snowflake. Because Insureco is a multinational company, it has to take extra measures to ensure data across geographic boundaries is protected to meet a wide range of compliance requirements. The Insureco team has been asked to segment what data sales team members have access to based on where they are regionally. In order to make this possible, they will use Snowflakes row access policies to implement row level security. We are going to apply policies for three Insureco's sales team members with different roles. Alice, an executive must be able to view sales data from both North America and Europe. Alex in North America sales manager will be limited to access sales data from North America only. And Jordan, a Europe sales manager will be limited to access sales data from Europe only. As a first step, the security administrator needs to create a lookup table that will be used to determine which data is accessible based on each role. As you can see, the lookup table has the row and their associated region, both of which will be used to apply policies that we will now create. Row access policies are implemented using standard SQL syntax to make it easy for administrators to create policies like the one our administrators looking to implement. And similar to masking policies, row access policies are leveraging our flexible and expressive policy language. In this demo, our admin users to create a row access policy that uses the row and region of a user to determine what row level data they have access to when queries are executed. When users queries are executed against the table protected by such a row access policy, Snowflakes query engine will dynamically generate and apply the corresponding predicate to filter out rows the user is not supposed to see. With the policy now created, let's log in as our Sales Users and see if it worked. Recall that as a sales executive, Alice should have the ability to see all rows from North America and Europe. Sure enough, when she runs her query, she can see all rows so we know the policy is working for her. You may also have noticed that some columns are showing masked data. That's because our administrator's also using our previously announced data masking capabilities to protect these data attributes for everyone in sales. When we look at our other users, we should notice that the same columns are also masked for them. As you see, you can easily combine masking and row access policies on the same data sets. Now let's look at Alex, our North American sales manager. Alex runs to st Korea's Alice, row access policies leverage the lookup table to dynamically generate the corresponding predicates for this query. The result is we see that only the data for North America is visible. Notice too that the same columns are still masked. Finally, let's try Jordan, our European sales manager. Jordan runs the query and the result is only the data for Europe with the same columns also masked. And you reintroduced masking policies, today you saw row access policies in action. And similar to our masking policies, row access policies in Snowflake will be accepted Hands of capability integrated seamlessly across all of Snowflake everywhere you expect it to work it does. If you're accessing data stored in external tables, semi structured JSON data, or building data pipelines via streams or plan to leverage Snowflakes data sharing functionality, you will be able to implement complex row access policies for all these diverse use cases and workloads within Snowflake. And with Snowflakes unique replication feature, you can instantly apply these new policies consistently to all of your Snowflake accounts, ensuring governance across regions and even across different clouds. In the future, we plan to demonstrate how to combine our new tagging capabilities with Snowflakes policies, allowing advanced audit and enforcing those policies with ease. And with that, let's pass it back over to Christian. >> Thank you Artin. We look forward to making this new tagging and row level security capabilities available in private preview in the coming months. One last note on the broad area of data governance. A big aspect of the Data Cloud is the mobilization of data to be used across organizations. At the same time, privacy is an important consideration to ensure the protection of sensitive, personal or potentially identifying information. We're working on a set of product capabilities to simplify compliance with privacy related regulatory requirements, and simplify the process of collaborating with data while preserving privacy. Earlier this year, Snowflake acquired a company called Crypto Numerix to accelerate our efforts on this front, including the identification and anonymization of sensitive data. We look forward to sharing more details in the future. We've just shown you three demos of new and exciting ways to use Snowflake. However, I want to also remind you that our commitment to the core platform has never been greater. As you move workloads on to Snowflake, we know you expect exceptional price performance and continued delivery of new capabilities that benefit every workload. On price performance, we continue to drive performance improvements throughout the platform. Let me give you an example comparing an identical set of customers submitted queries that ran both in August of 2019, and August of 2020. If I look at the set of queries that took more than one second to compile 72% of those improved by at least 50%. When we make these improvements, execution time goes down. And by implication, the required compute time is also reduced. Based on our pricing model to charge for what you use, performance improvements not only deliver faster insights, but also translate into cost savings for you. In addition, we have two new major announcements on performance to share today. First, we announced our search optimization service during our June event. This service currently in public preview can be enabled on a table by table basis, and is able to dramatically accelerate lookup queries on any column, particularly those not used as clustering columns. We initially support equality comparisons only, and today we're announcing expanded support for searches in values, such as pattern matching within strings. This will unlock a number of additional use cases such as analytics on logs data for performance or security purposes. This expanded support is currently being validated by a few customers in private preview, and will be broadly available in the future. Second, I'd like to introduce a new service that will be in private preview in a future release. The query acceleration service. This new feature will automatically identify and scale out parts of a query that could benefit from additional resources and parallelization. This means that you will be able to realize dramatic improvements in performance. This is especially impactful for data science and other scan intensive workloads. Using this feature is pretty simple. You define a maximum amount of additional resources that can be recruited by a warehouse for acceleration, and the service decides when it would be beneficial to use them. Given enough resources, a query over a massive data set can see orders of magnitude performance improvement compared to the same query without acceleration enabled. In our own usage of Snowflake, we saw a common query go 15 times faster without changing the warehouse size. All of these performance enhancements are extremely exciting, and you will see continued improvements in the future. We love to innovate and continuously raise the bar on what's possible. More important, we love seeing our customers adopt and benefit from our new capabilities. In June, we announced a number of previews, and we continue to roll those features out and see tremendous adoption, even before reaching general availability. Two have those announcements were the introduction of our geospatial support and policies for dynamic data masking. Both of these features are currently in use by hundreds of customers. The number of tables using our new geography data type recently crossed the hundred thousand mark, and the number of columns with masking policies also recently crossed the same hundred thousand mark. This momentum and level of adoption since our announcements in June is phenomenal. I have one last announcement to highlight today. In 2014, Snowflake transformed the world of data management and analytics by providing a single platform with first class support for both structured and semi structured data. Today, we are announcing that Snowflake will be adding support for unstructured data on that same platform. Think of the abilities of Snowflake used to store access and share files. As an example, would you like to leverage the power of SQL to reason through a set of image files. We have a few customers as early adopters and we'll provide additional details in the future. With this, you will be able to leverage Snowflake to mobilize all your data in the Data Cloud. Our customers rely on Snowflake as the data platform for every part of their business. However, the vision and potential of Snowflake is actually much bigger than the four walls of any organization. Snowflake has created a Data Cloud a data connected network with a vision where any Snowflake customer can leverage and mobilize the world's data. Whether it's data sets, or data services from traditional data providers for SaaS vendors, our marketplace creates opportunities for you and raises the bar in terms of what is possible. As examples, you can unify data across your supply chain to accelerate your time and quality to market. You can build entirely new revenue streams, or collaborate with a consortium on data for good. The possibilities are endless. Every company has the opportunity to gain richer insights, build greater products and deliver better services by reaching beyond the data that he owns. Our vision is to enable every company to leverage the world's data through seamless and governing access. Snowflake is your window into this data network into this broader opportunity. Welcome to the Data Cloud. (upbeat music)

>>from around the globe. It's the Cube with digital coverage of Dell Technologies. World digital experience brought to you by Dell Technologies. Hey, Welcome back, everybody. Jeffrey here with the Cube. Welcome back to our ongoing coverage of Dell Technology. World 2020. The digital experience, Uh, not in person like nothing this year, 2020. But the digital experience allows to do a lot of things that you couldn't do in person. And we're excited to have our next guest. He is Deepak Prasad, the director of product management for Dell Technologies. Cloud deep. Uh, great to see you. >>Hello, Jeff. Nice to meet you as well. >>You too. So let's let's back up, like, 10,000 square feet, cause you know, Cloud came in with a big giant rage. I guess it's been a while now with AWS and Public Cloud. And people are putting their depth tests on there. And, you know, we've seen this explosion of public cloud, and then we have hybrid cloud and multi cloud. And then, you know, basically people figured out that not everything can go to a public cloud. A lot of stuff. Shouldn't some stuffs gonna stay in data centers? for all different reasons, >>but >>basically it's horses for courses. So we're a little ways into this. How are you guys, Adele, really thinking about Cloud and helping your customers think about what cloud is beyond, you know, kind of the hype. >>Well, that's a great question, Jeff. At Dell, we think of Cloud really as an operating model and as an operating experience rather than a destination. So it's interesting that you bring up Public Cloud and Private Cloud, but we take a step back and think of what does that experience really represent? So if you think off, uh, you know what defines that cloud operating model? It's, ah, democratization of technology. Access off resource is through a p. I s through self service portals ability to pay as you go in a very simplified commerce experience and the agility of cloud. You know, the promise off instant availability of infinite scalability. Now, if if you look at you know the landscape around this until now, that has only been delivered in a consistent way by public cloud vendors, which leads people to believe that really cloud is the destination, not an operating model. But we think that we are capable of bringing those experiences those tenets off the cloud operating model to the on premises experience and really taking location out of the conversation. So this really allows our customers to focus mawr on their workloads than visions. They want to drive, and then they can fit there, uh, requirements their application requirements to the location where those resource is our regardless of having toe worry about it. This is public or private. They will get the same operating experience. They will get the same scalability, the same simplified commerce, the same access Thio resource is >>right. Well, let's talk about some of some of those things because, as you said, there's a lot of behaviors that are involved in cloud and cloud operating. You know, one of the behaviors that I think gave the public cloud an early leg up was just simply provisioning, right? Simply, if somebody needs some capacity, they need some horsepower to get interesting. It would be tested in the early days. No, they didn't have to provision. They didn't have to put in an order with I t and wait for so long to get a box assigned to them or purchased or whatever, right? They just swipe the credit card and went, How have you kind of help People have that kind of ease of use ease of, uh, he's of spin up piece of creation on what the right verb is because I think that's a really core piece of what enabled early cloud adoption. >>No, absolutely, you're spot on. And that was a big part of it that if somebody needed resource is instead of waiting for weeks and months, they could go on and and sign up for those resource and get almost instantaneous access. And we believe that what we're doing in this area is really transforming the business. Today. We can deliver resource is to customers in their data center in 14 days and really are aggressively looking to cut that down further. So what this really means is not just shipping Resource is in 14 days, but actually delivering a cloud experience in the customer's data center or of cola location, whatever, you know, location of their choice in 14 days and making that available to the customers, not just through the traditional procurement process. But we're actually very proud to announce the cloud Council, the Dell Technologies Cloud Council, through which customers can, in a self service way, order those ordered those resource is and have it show up and be operational in their environment in 14 days. So we're really bringing that speed of cloud to the on premise experience, >>right? So how how does it actually work? Do you pre? Do you pre ship some amount of capacity beyond what you believe is currently needed just to kind of forward que you will, if you will capacity. How does it work from from both the implementation strategy in terms of the actual compute and storage capacity, as well as on kind of the purchasing peace? Because those air to kind of very >>different work flows? No, that's a That's a great question. So for us, our strength are really in supply chain management that allows us to build capabilities across the world in areas from where we can ship the customers almost on the on demand basis. So as soon as we get in order that the customer needs a probably probably cloud deployment in a certain location, were able to mobilize those resource is from those locations and have it instance she hated in customers environ. So it's really built a strength off over the years off optimizing supply chain, if you will, and just bring taking that to the next level off. >>Okay, so we don't, >>uh environment we said. Yeah, >>no problem. I was gonna say the another great characteristics of cloud right is is spinning up, which we hear about all the time versus spinning down and write. The easiest example is always use. If you're running, you know, some promotion. If your pizza hut you're running a promotion for the Super Bowl, obviously, right? Your demand for that thing is gonna be huge. You want to spin up to be able to take advantage of all the people cash in their coupon, and then when the Super Bowls over, >>you >>want to spend those resource is down because you're not going to necessarily need that capacity. How do you guys accomplish that type of flexibility in your solution? >>So in our subscription model, we have different ways to address customer environment. So we allow customers to start very small and then and then grow the subscription as the requirements growth and the key thing of our subscription, which is really unique, is the ability to quote Terminate. So, for example, if if a customer started off on the three year subscription with the, uh resource is for, say, 100 virtual machines and somewhere along the way they needed to add resource is for 50 more virtual machines, so they will pay for the 150 virtual machines. But that extra 50 virtual machines does not create an orphan or a child subscription. At the end of three years, everything terminates together, so it really gives them flexibility with, you know, ability to start small and not have to worry about vendor lock in. And now we started off with sort of a reserved instance type off subscription model. But we're definitely bringing usage based models as well, which allows more, even more flexibility with respect to speeding up and speeding down. Right. >>And then what are some of the real specific reasons that people go for this type of solution versus a public cloud where some of the rial inherent advantages of doing this within my own infrastructure, my own data center, my own, you know, kind of virtual four walls, if you will. >>Yeah, you know, we strongly believe that the decision should really be guided by workload requirements. There's certain workloads that work really well in on premises environment. For example, you could take virtual desktop environments V. D. I. That works really well from a performance standpoint in In on premise, environment versus a public cloud environment. Similarly, there are other workloads were not public cloud deniers that that are best suited for public cloud. But it's really it should be something that's that comes from understanding your application. Understanding the leighton see requirements, understanding the data requirements for those applications. You know, what are your egress? Uh, issues. Or, you know, uh, the profile off the workload that you're trying to implement That should really be the driving force in where the workload this place >>and then, uh, tell us a little bit about the partnership with VM Ware because that's a huge asset that you have, you know, now you know, basically side by side and you can leverage the technology as well as a lot of the assets that are envy. And where how does that change? The way you guys have taken the Dell Cloud platform to market >>it really is a a differentiating factor for us. From a technology standpoint, it allows us to bring the best of both worlds best off off the hardware infrastructure as well as the best off the cloud. Stack the cloud software infrastructure together in one cohesive and and well developed package. So, uh, the Dell Technologies Cloud Platform from a technology standpoint is implemented with our VX rail appliances, which is a hyper converge infrastructure as well as VM ware clad foundation from a software standpoint. Now the code developed and jointly engineered capabilities allow for unique, unique feature off. Remember Cloud Foundation, where it can do lifecycle management off the entire stack, both the hardware and the software from a single interface. So it understands Vieques rails and understands the different form where levels and the X, where manager software versions etcetera. And then it would automatically select what is the best and well tested and supported software bundle that could be deployed without causing, you know, typical issues with version mismatches and trying to chase down different hardware compatibility, matrices, etcetera. All of those are eliminated, so it's a integrated lifecycle management experience. That's great. E. I'm sorry I have >>a little bit, a little bit of a lot of here, so I I apologize. >>I >>was just gonna say you've been at this for a while. Your product, you know, product management. So you're really thinking about speeds and feeds and you're thinking about roadmap and futures? I wonder if you can share your perspective on this evolution from kind of this race of to pure public cloud to this. This big discussion I think we had packed Elson. You're talking about a hybrid cloud back at being where 2013. So then, you know kind of this hybrid cloud and multi cloud and really kind of this maturation of this space as we as we've progressed for Ah, while now probably 10 years. >>Yeah. Yeah. And, uh, majority of our customers live in a multi cloud world. They have resource is that they consumed from one or more multi hyper sorry, uh, public cloud vendors and they have one or more on premise vendors as well, For their resource is and managing that complex environment across multiple providers with different skill set different tools, different sls. While it sounds really interesting to, you know, have workload drive your your deployment and place the workloads where they're best suited. It does prevent. It does present a challenge off managing a complex and and getting even more complex by the day, multi cloud environment. And that's where we think we have an advantage. Uh, based on some of the work that we're doing with the Dell Technologies Cloud console to bring a true multi cloud experience to our customers. Not one of the benefits of not being a, you know, a public cloud provider is that we are agnostic toe. All public cloud providers were fully accepting that certain workloads need to live in those environments. And through our cloud council, we will make it easy for customers to manage not only their on premises, assets and on premises. Cloud resource is, but also cloud resource is that reside in multiple public cloud vendors? >>That's good. Yeah, because it helps, right, because they've got stuff everywhere. It's like that, you know, there is no del technology, right? There's a lot of there's a lot of people that work there. There's a lot of project. There's a lot of, you know, kind of pieces to that puzzle. I wonder too. If you could share your perspective on kind of application modernization, right, That's always another big, you know, kind of topic. You should You should you take those old legacy APS. And could you should you try to rebuild them in, um, or cloud native way using containers and and all this flexibility and deploy them or, you know, which one. Should you just leave alone right there, running fine. They've been running fine for a while. They've got some basic core functionality that may be do or don't need toe to kind of modernize if you will. And maybe those resources should be spent on building in a new applications and new kind of areas of competitive differentiation. When you're working with their clients, how do you tell them to think about at modernization? >>Yeah, we looked at it from a business requirement standpoint. Off how what end goals. A customer trying to achieve through that application. And in some cases, you know, on you cover the spectrum, right there. Some cases modernization just means swapping out the hardware and putting it, putting that application on a more modern, more powerful hardware. At the other end, it z you know, going toe assassin model off, you know, everything available through through a cloud application. And in between those two extremities, there's, you know, virtualization that is re factoring this continual ization and micro services based implementation. But it comes down to understanding why that application is meant to deliver for who and what business requirements and business objectives that fulfills. That's how we use as a guiding principle on how to position application modernization to customers. >>All right, that's super helpful, because I'm sure that's a big topic. And, you know, there's probably certain APS that you just should not. You just shouldn't touch. You should probably just even Malone. They're running just fine. Let them do their thing. All >>right, fine. I'm sorry. No. Is this interesting? I was a conversation with the customer just earlier today where they have a portion off their infrastructure of some applications that they absolutely wanted to leave alone and and just change out the underlying hardware. But there are other applications where they really want to adopt, continue ization and re factor those out, rewrite those applications so that they can have more scalability and more flexibility around that. So it really is is determined by the needs. Yeah. >>Um so last question, del Tech world this year was a digital experience, like all the other shows that we've seen here in 2020 just But it's a huge event, right? A big, big show, and we're excited to be back to cover it again. But I'm curious if there's some special announcements within such a big show. Sometimes things get lost a little bit here in there, but any special announcements You want to make sure that get highlighted that people may have missed within this kind of see if content over the last several days >>22 major things that that I'm very excited to share with you One is Dell Technologies Cloud platform. We actually discussing and talking about Dell Technologies cloud platform in the concept off instant capacity blocks. So in the past, we talked about it with respect to notes. Uh, you know, adult technology cloud platform. You can have, you know, so many notes in it to power your your on premises. Cloud resource is but really have changed the conversation and look into how cloud customers air consuming those resource is and we really want to drive focus to that and introduced the concept of instance Capacity blocks instances are think of it as a workload profile, you know, CPU and memory put together and then, uh, in different combinations in a pre defined way to address different workload needs. So this really changes the conversation for our customers that they don't have to worry about designing or or speaking out the hardware platforms, but really understand how many resource is they need, how many, how much you know, processing power, how much memory, how much stories they need and they define their requirements was in those terms, and we will deliver those instance capacity blocks to them in their data centers. So behind the scenes is built by best in class. Uh, you know, hardware from Vieques rails and best in class software from being where, but it's really delivered in terms off instant capacity blocks. The second interesting thing that I wanna share with you and I profession a few times is Dell Technologies Cloud console. We're building this single pane of glass to manage our customers entire journey from on premises to multi cloud hybrid cloud with consistency off. How you can discover services how you can order services and how you can grow your the manager footprint. So those are a couple things from adult technology standpoint that we're really excited to share with people. >>Well, congratulations. I know you've been busting your tail for for quite a while on these types of projects, and it's nice to be able to finally release him out to the world. >>Well, it's just my pleasure. Alright. Thank you very much. >>Well, thank you for stopping by again. Congratulations. And will continue the ongoing coverage of Dell Technology World 2020. The digital experience. I'm Jeff Frick. He's to Park Prasad. You're watching the Cube. See you next time. Thanks for watching.

>> Narrator: From around the globe, it's theCube. With digital coverage of VMworld 2020. Brought to you by VMware and its ecosystem partners. >> Hello, and welcome back to theCube virtual coverage of VMworld 2020. I'm John Furrier, host of theCube. VMworld's not in person this year, it's on the virtual internet. A lot of content, check it out, vmworld.com, a lot of great stuff, online demos, and a lot of great keynotes. Here we got a great conversation to unpack, the NVIDIA, the AI and all things Cloud Native. With Krish Prasad, who's the SVP and GM of Cloud Platform, Business Unit, and Manuvir Das head of enterprise computing at NVIDIA. Gentlemen, great to see you virtually. Thanks for joining me on the virtual Cube, for the virtual VMworld 2020. >> Thank you John. >> Pleasure to be here. >> Quite a world. And I think one of the things that obviously we've been talking about all year since COVID is the acceleration of this virtualized environment with media and everyone working at home remote. Really puts the pressure on digital transformation Has been well discussed and documented. You guys have some big news, obviously on the main stage NVIDIA CEO, Jensen there legend. And of course, you know, big momentum with with AI and GPUs and all things, you know, computing. Krish, what are your announcements today? You got some big news. Could you take a minute to explain the big announcements today? >> Yeah, John. So today we want to make two major announcements regarding our partnership with NVIDIA. So let's take the first one, and talk through it and then we can get to the second announcement later. In the first one, as you well know, NVIDIA is the leader in AI and VMware as the leader in virtualization and cloud. This announcement is about us teaming up, deliver a jointly engineered solution to the market to bring AI to every enterprise. So as you well know, VMware has more than 300,000 customers worldwide. And we believe that this solution would enable our customers to transform their data centers or AI applications running on top of their virtualized VMware infrastructure that they already have. And we think that this is going to vastly accelerate the adoption of AI and essentially democratize AI in the enterprise. >> Why AI? Why now Manuvir? Obviously we know the GPUs have set the table for many cool things, from mining Bitcoin to really providing a great user experience. But AI has been a big driver. Why now? Why VMware now? >> Yes. Yeah. And I think it's important to understand this is about AI more than even about GPUs, you know. This is a great moment in time where AI has finally come to life, because the hardware and software has come together to make it possible. And if you just look at industries and different parts of life, how is AI impacting? So for example, if you're a company on the internet doing business, everything you do revolves around making recommendations to your customers about what they should do next. This is based on AI. Think about the world we live in today, with the importance of healthcare, drug discovery, finding vaccines for something like COVID. That work is dramatically accelerated if you use AI. And what we've been doing in NVIDIA over the years is, we started with the hardware technology with the GPU, the Parallel Processor, if you will, that could really make these algorithms real. And then we worked very hard on building up the ecosystem. You know, we have 2 million developers today who work with NVIDIA AI. That's thousands of companies that are using AI today. But then if you think about what Krish said, you know about the number of customers that VMware has, which is in the hundreds of thousands, the opportunity before us really now is, how do we democratize this? How do we take this power of AI, that makes every customer and every person better and put it in the hands of every enterprise customer? And we need a great vehicle for that, and that vehicle is VMware. >> Guys, before we get to the next question, I would just want to get your personal take on this, because again, we've talked many times, both of you've been on theCube on this topic. But now I want to highlight, you mentioned the GPU that's hardware. This is software. VMware had hardware partners and then still software's driving it. Software's driving everything. Whether it's something in space, it's an IOT device or anything at the edge of the network. Software, is the value. This has become so obvious. Just share your personal take on this for folks who are now seeing this for the first time. >> Yeah. I mean, I'll give you my take first. I'm a software guy by background, I learned a few years ago for the first time that an array is a storage device and not a data structure in programming. And that was a shock to my system. Definitely the world is based on algorithms. Algorithms are implemented in software. Great hardware enables those algorithms. >> Krish, your thoughts. we live we're living in the future right now. >> Yeah, yeah. I would say that, I mean, the developers are becoming the center. They are actually driving the transformation in this industry, right? It's all about the application development, it's all about software, the infrastructure itself is becoming software defined. And the reason for that is you want the developers to be able to craft the infrastructure the way they need for the applications to run on top of. So it's all about software like I said. >> Software defined. Yeah, just want to get that quick self-congratulatory high five amongst ourselves virtually. (laughs) Congratulations. >> Exactly. >> Krish, last time we spoke at VMworld, we were obviously in person, but we talked about Tanzu and vSphere. Okay, you had Project Pacific. Does this expand? Does this announcement expand on that offering? >> Absolutely. As you know John, for the past several years, VMware has been on this journey to define the Hybrid Cloud Infrastructure, right? Essentially is the software stack that we have, which will enable our customers to provide a cloud operating model to their developers, irrespective of where they want to land their workloads. Whether they want to land their workloads On-Premise, or if they want it to be on top of AWS, Google, Azure, VMware stack is already running across all of them as you well know. And in addition to that, we have around, you know, 4,000, 5,000 service providers who are also running our Platform to deliver cloud services to their customers. So as part of that journey, last year, we took the Platform and we added one further element to it. Traditionally, our platform has been used by customers for running via VMs. Last year, we natively integrated Kubernetes into our platform. This was the big re architecture of vSphere, as we talked about. That was delivered to the market. And essentially now customers can use the same platform to run Kubernetes, Containers and VM workloads. The exact same platform, it is operationally the same. So the same skillsets, tools and processes can be used to run Kubernetes as well as VM applications. And the same platform runs, whether you want to run it On-Premise or in any of the clouds, as we talked about before. So that vastly simplifies the operational complexity that our customers have to deal with. And this is the next chapter in that journey, by doing the same thing for AI workload. >> You guys had great success with these Co-Engineering joined efforts. VMware and now with NVIDIA is interesting. It's very relevant and is very cool. So it's cool and relevant, so check, check. Manuvir, talk about this, because how do you bring that vision to the enterprises? >> Yeah, John, I think, you know, it's important to understand there is some real deep Computer Science here between the Engineers at VMware and NVIDIA. Just to lay that out, you can think of this as a three layer stack, right? The first thing that you need is, clearly you need the hardware that is capable of running these algorithms, that's what the GPU enable. Then you need a great software stack for AI, all the right Algorithmics that take advantage of that hardware. This is actually where NVIDIA spends most of its effort today. People may sometimes think of NVIDIA as a GPU company, but we have much more a software company now, where we have over the years created a body of work of all of the software that it actually takes to do good AI. But then how do you marry the software stack with the hardware? You need a platform in the middle that supports the applications and consumes the hardware and exposes it properly. And that's where vSphere, you know, as Krish described with either VMs or Containers comes into the picture. So the Computer Science here is, to wire all these things up together with the right algorithmics so that you get real acceleration. So as examples of early work that the two teams have done together, we have workloads in healthcare, for example. In cancer detection, where the acceleration we get with this new stack is 30X, right? The workload is running 30 times faster than it was running before this integration just on CPUs. >> Great performance increase again. You guys are hiring a lot of software developers. I can attest to knowing folks in Silicon Valley and around the world. So I know you guys are bringing the software jobs to the table on a great product by the way, so congratulations. Krish, Democratization of AI for the enterprise. This is a liberating opportunity, because one of the things we've heard from your customers and also from VMware, but mostly from the customer's successes, is that there's two types of extremes. There's the, I'm going to modernize my business, certainly COVID forcing companies, whether they're airlines or whatever, not a lot going on, they have an opportunity to modernize, to essentially modern apps that are getting a tailwind from these new digital transformation accelerated. How does AI democratize this? Cause you got people and you've got technology. (laughs) Right? So share your thoughts on how you see this democratizing. >> That's a very good question. I think if you look at how people are running AI applications today, like you go to an enterprise, you would see that there is a silo of bare metal sun works on the side, where the AI stack is run. And you have people with specialized skills and different tools and utilities that manage that environment. And that is what is standing in the way of AI taking off in the enterprise, right? It is not the use case. There are all these use cases which are mission critical that all companies want to do, right? Worldwide, that has been the case. It is about the complexity of life that is standing in the way. So what we are doing with this is we are saying, "hey, that whole solution stack that Manuvir talked about, is integrated into the VMware Virtualized Infrastructure." Whether it's On-Prem or in the cloud. And you can manage that environment with the exact same tools and processes and skills that you traditionally had for running any other application on VMware infrastructure. So, you don't need to have anything special to run this. And that's what is going to give us the acceleration that we talked about and essentially hive the Democratization of AI. >> That's a great point. I just want to highlight that and call that out, because AI's every use case. You could almost say theCube could have AI and we do actually have a little bit of AI and some of our transcriptions and work. But it's not so much just use cases, it's actually not just saying you got to do it. So taking down that blocker, the complexity, certainly is the key. And that's a great point. We're going to call that out after. Alright, let's move on to the second part of the announcement. Krish Project Monterey. This is a big deal. And it looks like a, you know, kind of this elusive, it's architectural thing, but it's directionally really strategic for VMware. Could you take a minute to explain this announcement? Frame this for us. >> Absolutely. I think John, you remember Pat got on stage last year at Vmworld and said, you know, "we are undertaking the biggest re architecture of the vSphere platform in the last 10 years." And he was talking about natively embedding Kubernetes, in vSphere, right? Remember Tanzu and Project Pacific. This year we are announcing Project Monterrey. It's a project that is significant with several partners in the industry, along with NVIDIA was one of the key partners. And what we are doing is we are reimagination of the data center for the next generation applications. And at the center of it, what we are going to do is rearchitect vSphere and ESX. So that the ESX can normally run on the CPU, but it'll also run on the Smart Mix. And what this gives us is the whole, let's say data center, infrastructure type services to be offloaded from running on the CPU onto the Smart Mix. So what does this provide the applications? The applications then will perform better. And secondly, it provides an extra layer of security for the next generation applications. Now we are not going to stop there. We are going to use this architecture and extended it so that we can finally eliminate one of the big silos that exist in the enterprise, which is the bare metal silo. Right? Today we have virtualized environments and bare metal, and what this architecture will do is bring those bare metal environments also under ESX management. So you ESX will manage environments which are virtualized and environments which are running bare metal OS. And so that's one big breakthrough and simplification for the elimination of silo or the elimination of, you know, specialized skills to keep it running. And lastly, but most importantly, where we are going with this. That just on the question you asked us earlier about software defined and developers being in control. Where we want to go with this is give developers, the application developers, the ability to really define and create their run time on the Fly, dynamically. So think about it. If dynamically they're able to describe how the application should run. And the infrastructure essentially kind of attaches computer resources on the Fly, whether they are sitting in the same server or somewhere in the network as pools of resources. Bring it all together and compose the runtime environment for them. That's going to be huge. And they won't be constrained anymore by the resources that are tied to the physical server that they are running on. And that's the vision of where we are taking it. It is going to be the next big change in the industry in terms of enterprise computing. >> Sounds like an Operating System to me. Yeah. Run time, assembly orchestration, all these things coming together, exciting stuff. Looking forward to digging in more after Vmworld. Manuvir, how does this connect to NVIDIA and AI? Tie that together for us. >> Yeah, It's an interesting question, because you would think, you know, okay, so NVIDIA this GPU company or this AI company. But you have to remember that INVIDIA is also a networking company. Because friends at Mellanox joined us not that long ago. And the interesting thing is that there's a Yin and Yang here, because, Krish described the software vision, which is brilliant. And what this does is it imposes a lot on the host CPU of the server to do. And so what we've be doing in parallel is developing hardware. A new kind of "Nick", if you will, we call it a DPU or a Data Processing Unit or a Smart Nick that is capable of hosting all this stuff. So, amusingly when Krish and I started talking, we exchanged slides and we basically had the same diagram for our vision of where things go with that software, the infrastructure software being offloaded, data center infrastructure on a chip, if you will. Right? And so it's a very natural confluence. We are very excited to be part of this, >> Yeah. >> Monterey program with Krish and his team. And we think our DPU, which is called the NVIDIA BlueField-2, is a pretty good device to empower the work that Krish's team is doing. >> Guys it's awesome stuff. And I got to say, you know, I've been covering Vmworld now 11 years with theCube, and I've known VMware since its founding, just the evolution. And just recently before VMworld, you know, you saw the biggest IPO in the history of Wall Street, Snowflake an Enterprise Data Cloud Company. The number one IPO ever. Enterprise tech is so exciting. This is really awesome. And NVIDIA obviously well known, great brand. You own some chip company as well, and get processors and data and software. Guys, customers are going to be very interested in this, so what should customers do to find out more? Obviously you've got Project Monterey, strategic direction, right? Framed perfectly. You got this announcement. If I'm a customer, how do I get involved? How do I learn more? And what's in it for me. >> Yeah, John, I would say, sorry, go ahead, Krish. >> No, I was just going to say sorry Manuvir. I was just going to say like a lot of these discussions are going to be happening, there are going to be panel discussions there are going to be presentations at Vmworld. So I would encourage customers to really look at these topics around Project Monterey and also about the AI work we are doing with NVIDIA and attend those sessions and be active and we will have a ways for them to connect with us in terms of our early access programs and whatnot. And then as Manuvir was about to say, I think Manuvir, I will give it to you about GTC. >> Yeah, I think right after that, we have the NVIDIA conference, which is GTC, where we'll also go over this. And I think some of this work is a lot closer to hand than people might imagine. So I would encourage watching all the sessions and learning more about how to get started. >> Yeah, great stuff. And just for the folks @vmworld.com watching, Cloud City's got 60 solution demos, go look for the sessions. You got the EX, the expert sessions, Raghu, Joe Beda amongst other people from VMware are going to be there. And of course, a lot of action on the content. Guys, thanks so much for coming on. Congratulations on the news, big news. NVIDIA on the Bay in Virtual stage here at VMworld. And of course you're in theCube. Thanks for coming. Appreciate it. >> Thank you for having us. Okay. >> Thank you very much. >> This is Cube's coverage of VMworld 2020 virtual. I'm John Furrier, host of theCube virtual, here in Palo Alto, California for VMworld 2020. Thanks for watching. (upbeat music)

>>from the Cube Studios in Palo Alto in Boston, connecting with thought leaders all around the world. This is a cube conversation. >>Hey, welcome back. You're ready, Jeffrey here with the Cuban Apollo Alto studios today, and we're excited. You know, we're slowly coming out of the, uh, out of the summer season. We're getting ready to jump back into the fall. Season, of course, is still covet. Everything is still digital. But you know, what we're seeing is a digital events allow a lot of things that you couldn't do in the physical space. Mainly get a lot more people to attend that don't have to get in airplanes and file over the country. So to preview this brand new inaugural event that's coming up in about a month, we have We have a new guest. He's Dave and Everen. He is the senior vice president of marketing. Former ran tous. Dave. Great to see you. >>Happy to be here today. Thank you. >>Yeah. So tell us about this inaugural event. You know, we did an event with Miranda's years ago. I had to look it up like 2014. 15. Open stack was hot and you guys sponsored a community event in the Bay Area because the open stack events used to move all over the country each and every year. But you guys said, and the top one here in the Bay Area. But now you're launching something brand new based on some new activity that you guys have been up to over the last several months. So let us give us give us the word. >>Yeah, absolutely. So we definitely have been organizing community events in a variety of open source communities over the years. And, you know, we saw really, really good success with with the Cube And are those events in opens tax Silicon Valley days? And, you know, with the way things have gone this year, we've really seen that virtual events could be very successful and provide a new, maybe slightly different form of engagement but still very high level of engagement for our guests and eso. We're excited to put this together and invite the entire cloud native industry to join us and learn about some of the things that Mantis has been working on in recent months. A zwelling as some of the interesting things that are going on in the Cloud native and kubernetes community >>Great. So it's the inaugural event is called Moran Sous launchpad 2020. The Wares and the Winds in September 16th. So we're about a month away and it's all online is their registration. Costars is free for the community. >>It's absolutely free. Eso everyone is welcome to attend You. Just visit Miranda's dot com and you'll see the info for registering for the event and we'd love it. We love to see you there. It's gonna be a fantastic event. We have multiple tracks catering to developers, operators, general industry. Um, you know, participants in the community and eso we'd be happy to see you on join us on and learn about some of the some of the things we're working on. >>That's awesome. So let's back up a step for people that have been paying as close attention as they might have. Right? So you guys purchase, um, assets from Docker at the end of last year, really taken over there, they're they're kind of enterprise solutions, and you've been doing some work with that. Now, what's interesting is we we cover docker con, um, A couple of months ago, a couple three months ago. Time time moves fast. They had a tremendously successful digital event. 70,000 registrants, people coming from all over the world. I think they're physical. Event used to be like four or 5000 people at the peak, maybe 6000 Really tremendous success. But a lot of that success was driven, really by the by the strength of the community. The docker community is so passionate. And what struck me about that event is this is not the first time these people get together. You know, this is not ah, once a year, kind of sharing of information and sharing ideas, but kind of the passion and and the friendships and the sharing of information is so, so good. You know, it's a super or, um, rich development community. You guys have really now taken advantage of that. But you're doing your Miranda's thing. You're bringing your own technology to it and really taking it to more of an enterprise solution. So I wonder if you can kind of walk people through the process of, you know, you have the acquisition late last year. You guys been hard at work. What are we gonna see on September 16. >>Sure, absolutely. And, you know, just thio Give credit Thio Docker for putting on an amazing event with Dr Khan this year. Uh, you know, you mentioned 70,000 registrants. That's an astounding number. And you know, it really is a testament thio. You know, the community that they've built over the years and continue to serve eso We're really, really happy for Docker as they kind of move into, you know, the next the next path in their journey and, you know, focus more on the developer oriented, um, solution and go to market. So, uh, they did a fantastic job with the event. And, you know, I think that they continue toe connect with their community throughout the year on That's part of what drives What drove so many attendees to the event assed faras our our history and progress with with Dr Enterprise eso. As you mentioned mid November last year, we did acquire Doctor Enterprise assets from Docker Inc and, um, right away we noticed tremendous synergy in our product road maps and even in the in the team's eso that came together really, really quickly and we started executing on a Siris of releases. Um that are starting Thio, you know, be introduced into the market. Um, you know, one was introduced in late May and that was the first major release of Dr Enterprise produced exclusively by more antis. And we're going to announce at the launch pad 2020 event. Our next major release of the Doctor Enterprise Technology, which will for the first time include kubernetes related in life cycle management related technology from Mirant is eso. It's a huge milestone for our company. Huge benefit Thio our customers on and the broader user community around Dr Enterprise. We're super excited. Thio provide a lot of a lot of compelling and detailed content around the new technology that will be announcing at the event. >>So I'm looking at the at the website with with the agenda and there's a little teaser here right in the middle of the spaceship Docker Enterprise Container Cloud. So, um, and I glanced into you got a great little layout, five tracks, keynote track D container track operations and I t developer track and keep track. But I did. I went ahead and clicked on the keynote track and I see the big reveal so I love the opening keynote at at 8 a.m. On the 76 on the September 16th is right. Um, I, Enel CEO who have had on many, many times, has the big reveal Docker Enterprise Container Cloud. So without stealing any thunder, uh, can you give us any any little inside inside baseball on on what people should expect or what they can get excited about for that big announcement? >>Sure, absolutely so I definitely don't want to steal any thunder from Adrian, our CEO. But you know, we did include a few Easter eggs, so to speak, in the website on Dr Enterprise. Container Cloud is absolutely the biggest story out of the bunch eso that's visible on the on the rocket ship as you noticed, and in the agenda it will be revealed during Adrian's keynote, and every every word in the product name is important, right? So Dr Enterprise, based on Dr Enterprise Platform Container Cloud and there's the new word in there really is Cloud eso. I think, um, people are going to be surprised at the groundbreaking territory that were forging with with this release along the lines of a cloud experience and what we are going to provide to not only I t operations and the Op Graders and Dev ops for cloud environment, but also for the developers and the experience that we could bring to developers As they become more dependent on kubernetes and get more hands on with kubernetes. We think that we're going thio provide ah lot of ways for them to be more empowered with kubernetes while at the same time lowering the bar, the bar or the barrier of entry for kubernetes. As many enterprises have have told us that you know kubernetes can be difficult for the broader developer community inside the organization Thio interact with right? So this is, uh, you know, a strategic underpinning of our our product strategy. And this is really the first step in a non going launch of technologies that we're going to make bigger netease easier for developing. >>I was gonna say the other Easter egg that's all over the agenda, as I'm just kind of looking through the agenda. It's kubernetes on 80 infrastructure multi cloud kubernetes Miranda's open stack on kubernetes. So Goober Netease plays a huge part and you know, we talk a lot about kubernetes at all the events that we cover. But as you said, kind of the new theme that we're hearing a little bit more Morris is the difficulty and actually managing it so looking, kind of beyond the actual technology to the operations and the execution in production. And it sounds like you guys might have a few things up your sleeve to help people be more successful in in and actually kubernetes in production. >>Yeah, absolutely. So, uh, kubernetes is the focus of most of the companies in our space. Obviously, we think that we have some ideas for how we can, you know, really begin thio enable enable it to fulfill its promise as the operating system for the cloud eso. If we think about the ecosystem that's formed around kubernetes, uh, you know, it's it's now really being held back on Lee by adoption user adoption. And so that's where our focus in our product strategy really lives is around. How can we accelerate the move to kubernetes and accelerate the move to cloud native applications on? But in order to provide that acceleration catalyst, you need to be able to address the needs of not only the operators and make their lives easier while still giving them the tools they need for things like policy enforcement and operational insights. At the same time, Foster, you know, a grassroots, um, upswell of developer adoption within their company on bond Really help the I t. Operations team serve their customers the developers more effectively. >>Well, Dave, it sounds like a great event. We we had a great time covering those open stack events with you guys. We've covered the doctor events for years and years and years. Eso super engaged community and and thanks for, you know, inviting us back Thio to cover this inaugural event as well. So it should be terrific. Everyone just go to Miranda's dot com. The big pop up Will will jump up. You just click on the button and you can see the full agenda on get ready for about a month from now. When when the big reveal, September 16th will happen. Well, Dave, thanks for sharing this quick update with us. And I'm sure we're talking a lot more between now in, uh, in the 16 because I know there's a cube track in there, so we look forward to interview in our are our guests is part of the part of the program. >>Absolutely. Eso welcome everyone. Join us at the event and, uh, you know, stay tuned for the big reveal. >>Everybody loves a big reveal. All right, well, thanks a lot, Dave. So he's Dave. I'm Jeff. You're watching the Cube. Thanks for watching. We'll see you next time.

>> Announcer: From the Cube studios in Palo Alto in Boston, connecting with thought leaders all around the world, this is theCube Conversation. >> Hi, I'm Stu Miniman. And welcome to this special presentation. We have a launch from Dell Technologies updates from the VxRail family. We're going to do things a little bit different here. We actually have a launch video Shannon Champion, of Dell Technologies. And the way we do things a lot of times, is, analysts get a little preview or when you're watching things. You might have questions on it. So, rather than me just wanting it, or you wanting yourself I actually brought in a couple of Dell Technologies expertS two of our Cube alumni, happy to welcome you back to the program. Jon Siegal, he is the Vice President of Product Marketing, and Chad Dunn, who's the Vice President of Product Management, both of them with Dell Technologies. Gentlemen, thanks so much for joining us. >> Good to see you Stu. >> Great to be here. >> All right, and so what we're going to do is we're going to be rolling the video here. I've got a button I'm going to press, Andrew will stop it here and then we'll kind of dig in a little bit, go into some questions when we're all done. We're actually holding a crowd chat, where you will be able to ask your questions, talk to the experts and everything. And so a little bit different way to do a product announcement. Hope you enjoy it. And with that, it's VxRail. Taking HCI to the extremes is the theme. We'll see what that means and everything. But without any further ado, let's let Shannon take the video away. >> Hello, and welcome. My name is Shannon Champion, and I'm looking forward to taking you through what's new with VxRail. Let's get started. We have a lot to talk about. Our launch covers new announcements addressing use cases across the Core, Edge and Cloud and spans both new hardware platforms and options, as well as the latest in software innovations. So let's jump right in. Before we talk about our announcements, let's talk about where customers are adopting VxRail today. First of all, on behalf of the entire Dell Technologies and VxRail teams, I want to thank each of our over 8000 customers, big and small in virtually every industry, who've chosen VxRail to address a broad range of workloads, deploying nearly 100,000 nodes today. Thank you. Our promise to you is that we will add new functionality, improve serviceability, and support new use cases, so that we deliver the most value to you, whether in the Core, at the Edge or for the Cloud. In the Core, VxRail from day one has been a catalyst to accelerate IT transformation. Many of our customers started here and many will continue to leverage VxRail to simply extend and enhance your VMware environment. Now we can support even more demanding applications such as In-Memory databases, like SAP HANA, and more AI and ML applications, with support for more and more powerful GPUs. At the Edge, video surveillance, which also uses GPUs, by the way, is an example of a popular use case leveraging VxRail alongside external storage. And right now we all know the enhanced role that IT is playing. And as it relates to VDI, VxRail has always been a great option for that. In the Cloud, it's all about Kubernetes, and how Dell Technologies Cloud platform, which is VCF on VxRail can deliver consistent infrastructure for both traditional and Cloud native applications. And we're doing that together with VMware. VxRail is the only jointly engineered HCI system built with VMware for VMware environments, designed to enhance the native VMware experience. This joint engineering with VMware and investments in software innovation together deliver an optimized operational experience at reduced risk for our customers. >> Alright, so Shannon talked a bit about, the important role of IT Of course right now, with the global pandemic going on. It's really, calling in, essential things, putting, platforms to the test. So, I really love to hear what both of you are hearing from customers. Also, VDI, of course, in the early days, it was, HCI-only-does-VDI. Now, we know there are many solutions, but remote work is putting that back front and center. So, Jon, why don't we start with you as the what is (muffled speaking) >> Absolutely. So first of all, Stu, thank you, I want to do a shout out to our VxRail customers around the world. It's really been humbling, inspiring, and just amazing to see The impact of our VxRail customers around the world and what they're having on on human progress here. Just for a few examples, there are genomics companies that we have running VxRail that have rolled out testing at scale. We also have research universities out in the Netherlands, doing the antibody detection. The US Navy has stood up a floating hospital to of course care for those in need. So we are here to help that's been our message to our customers, but it's amazing to see how much they're helping society during this. So just just a pleasure there. But as you mentioned, just to hit on the VDI comments, so to your points too, HCI, VxRail, VDI, that was an initial use case years ago. And it's been great to see how many of our existing VxRail customers have been able to pivot very quickly leveraging VxRail to add and to help bring their remote workforce online and support them with their existing VxRail. Because VxRail is flexible, it is agile, to be able to support those multiple workloads. And in addition to that, we've also rolled out some new VDI bundles to make it simpler for customers more cost effective cater to everything from knowlEdge workers to multimedia workers. You name it, you know from 250, desktops up to 1000. But again, back to your point VxRail, HCI, is well beyond VDI, it crossed the chasm a couple years ago actually. And VDI now is less than a third of the typical workloads, any of our customers out there, it supports now a range of workloads that you heard from Shannon, whether it's video surveillance, whether it's general purpose, all the way to mission critical applications now with SAP HAN. So, this has changed the game for sure. But the range of work loads and the flexibility of the actual rules which really helping our existing customers during this pandemic. >> Yeah, I agree with you, Jon, we've seen customers really embrace HCI for a number of workloads in their environments, from the ones that we sure all knew and loved back in the initial days of HCI. Now, the mission critical things now to Cloud native workloads as well, and the sort of the efficiencies that customers are able to get from HCI. And specifically, VxRail gives them that ability to pivot. When these, shall we say unexpected circumstances arise? And I think that that's informing their their decisions and their opinions on what their IP strategies look like as they move forward. They want that same level of agility, and ability to react quickly with their overall infrastructure. >> Excellent. Now I want to get into the announcements. What I want my team actually, your team gave me access to the CIO from the city of Amarillo, so maybe they can dig up that footage, talk about how fast they pivoted, using VxRail to really spin up things fast. So let's hear from the announcement first and then definitely want to share that that customer story a little bit later. So let's get to the actual news that Shannon's going to share. >> Okay, now what's new? I am pleased to announce a number of exciting updates and new platforms, to further enable IT modernization across Core, Edge and Cloud. I will cover each of these announcements in more detail, demonstrating how only VxRail can offer the breadth of platform configurations, automation, orchestration and Lifecycle Management, across a fully integrated hardware and software full stack with consistent, simplified operations to address the broadest range of traditional and modern applications. I'll start with hybrid Cloud and recap what you may have seen in the Dell Technologies Cloud announcements just a few weeks ago, related to VMware Cloud foundation on VxRail. Then I'll cover two brand new VxRail hardware platforms and additional options. And finally circle back to talk about the latest enhancements to our VxRail HCI system software capabilities for Lifecycle Management. Let's get started with our new Cloud offerings based on VxRail. VxRail is the HCI foundation for Dell Technologies, Cloud Platform, bringing automation and financial models, similar to public Cloud to On-premises environments. VMware recently introduced Cloud foundation for Delta, which is based on vSphere 7.0. As you likely know by now, vSphere 7.0 was definitely an exciting and highly anticipated release. In keeping with our synchronous release commitment, we introduced VxRail 7.0 based on vSphere 7.0 in late April, which was within 30 days of VMware's release. Two key areas that VMware focused on we're embedding containers and Kubernetes into vSphere, unifying them with virtual machines. And the second is improving the work experience for vSphere administrators with vSphere Lifecycle Manager or VLCM. I'll address the second point a bit in terms of how VxRail fits in in a moment for VCF 4 with Tom Xu, based on vSphere 7.0 customers now have access to a hybrid Cloud platform that supports native Kubernetes workloads and management, as well as your traditional VM-based workloads. So containers are now first class citizens of your private Cloud alongside traditional VMs and this is now available with VCF 4.0, on VxRail 7.0. VxRail's tight integration with VMware Cloud foundation delivers a simple and direct path not only to the hybrid Cloud, but also to deliver Kubernetes at Cloud scale with one complete automated platform. The second Cloud announcement is also exciting. Recent VCF for networking advancements have made it easier than ever to get started with hybrid Cloud, because we're now able to offer a more accessible consolidated architecture. And with that Dell Technologies Cloud platform can now be deployed with a four-node configuration, lowering the cost of an entry level hybrid Cloud. This enables customers to start smaller and grow their Cloud deployment over time. VCF and VxRail can now be deployed in two different ways. For small environments, customers can utilize a consolidated architecture which starts with just four nodes. Since the management and workload domains share resources in this architecture, it's ideal for getting started with an entry level Cloud to run general purpose virtualized workloads with a smaller entry point. Both in terms of required infrastructure footprint as well as cost, but still with a Consistent Cloud operating model. For larger environments where dedicated resources and role-based access control to separate different sets of workloads is usually preferred. You can choose to deploy a standard architecture which starts at eight nodes for independent management and workload domains. A standard implementation is ideal for customers running applications that require dedicated workload domains that includes Horizon, VDI, and vSphere with Kubernetes. >> Alright, Jon, there's definitely been a lot of interest in our community around everything that VMware is doing with vSphere 7.0. understand if you wanted to use the Kubernetes piece, it's VCF as that so we've seen the announcements, Dell, partnering in there it helps us connect that story between, really the VMware strategy and how they talk about Cloud and where does VxRail fit in that overall, Delta Cloud story? >> Absolutely. So first of all Stu, the VxRail course is integral to the Delta Cloud strategy. it's been VCF on VxRail equals the Delta Cloud platform. And this is our flagship on prem Cloud offering, that we've been able to enable operational consistency across any Cloud, whether it's On-prem, in the Edge or in the public Cloud. And we've seen the Dell tech Cloud Platform embraced by customers for a couple key reasons. One is it offers the fastest hybrid Cloud deployment in the market. And this is really, thanks to a new subscription offer that we're now offering out there where in less than 14 days, it can be still up and running. And really, the Dell tech Cloud does bring a lot of flexibility in terms of consumption models, overall when it comes to VxRail. Secondly, I would say is fast and easy upgrades. This is what VxRail brings to the table for all workloads, if you will, into especially critical in the Cloud. So the full automation of Lifecycle Management across the hardware and software stack across the VMware software stack, and in the Dell software and hardware supporting that, together, this enables essentially the third thing, which is customers can just relax. They can be rest assured that their infrastructure will be continuously validated, and always be in a continuously validated state. And this is the kind of thing that those three value propositions together really fit well, with any on-prem Cloud. Now you take what Shannon just mentioned, and the fact that now you can build and run modern applications on the same VxRail infrastructure alongside traditional applications. This is a game changer. >> Yeah, I love it. I remember in the early days talking with Dunn about CI, how does that fit in with Cloud discussion and the line I've used the last couple years is, modernize the platform, then you can modernize the application. So as companies are doing their full modernization, then this plays into what you're talking about. All right, we can let Shannon continue, we can get some more before we dig into some more analysis. >> That's good. >> Let's talk about new hardware platforms and updates. that result in literally thousands of potential new configuration options. covering a wide breadth of modern and traditional application needs across a range of the actual use cases. First up, I am incredibly excited to announce a brand new Dell EMC VxRail series, the D series. This is a ruggedized durable platform that delivers the full power of VxRail for workloads at the Edge in challenging environments or for space constrained areas. VxRail D series offers the same compelling benefits as the rest of the VxRail portfolio with simplicity, agility and lifecycle management. But in a lightweight short depth at only 20 inches, it's adorable form factor that's extremely temperature-resilient, shock resistant, and easily portable. It even meets milspec standards. That means you have the full power of lifecycle automation with VxRail HCI system software and 24 by seven single point of support, enabling you to rapidly react to business needs, no matter the location or how harsh the conditions. So whether you're deploying a data center at a mobile command base, running real-time GPS mapping on the go, or implementing video surveillance in remote areas, you can ensure availability, integrity and confidence for every workload with the new VxRail ruggedized D series. >> All right, Chad we would love for you to bring us in a little bit that what customer requirement for bringing this to market. I remember seeing, Dell servers ruggedized, of course, Edge, really important growth to build on what Jon was talking about, Cloud. So, Chad, bring us inside, what was driving this piece of the offering? >> Sure Stu. Yeah, yeah, having been at the hardware platforms that can go out into some of these remote locations is really important. And that's being driven by the fact that customers are looking for compute performance and storage out at some of these Edges or some of the more exotic locations. whether that's manufacturing plants, oil rigs, submarine ships, military applications, places that we've never heard of. But it's also about extending that operational simplicity of the the sort of way that you're managing your data center that has VxRails you're managing your Edges the same way using the same set of tools. You don't need to learn anything else. So operational simplicity is absolutely key here. But in those locations, you can take a product that's designed for a data center where definitely controlling power cooling space and take it some of these places where you get sand blowing or seven to zero temperatures, could be Baghdad or it could be Ketchikan, Alaska. So we built this D series that was able to go to those extreme locations with extreme heat, extreme cold, extreme altitude, but still offer that operational simplicity. Now military is one of those applications for the rugged platform. If you look at the resistance that it has to heat, it operates at a 45 degrees Celsius or 113 degrees Fahrenheit range, but it can do an excursion up to 55 C or 131 degrees Fahrenheit for up to eight hours. It's also resistant to heat sand, dust, vibration, it's very lightweight, short depth, in fact, it's only 20 inches deep. This is a smallest form factor, obviously that we have in the VxRail family. And it's also built to be able to withstand sudden shocks certified to withstand 40 G's of shock and operation of the 15,000 feet of elevation. Pretty high. And this is sort of like wherever skydivers go to when they want the real thrill of skydiving where you actually need oxygen to, to be for that that altitude. They're milspec-certified. So, MIL-STD-810G, which I keep right beside my bed and read every night. And it comes with a VxRail stick hardening package is packaging scripts so that you can auto lock down the rail environment. And we've got a few other certifications that are on the roadmap now for naval shock requirements. EMI and radiation immunity often. >> Yeah, it's funny, I remember when we first launched it was like, "Oh, well everything's going to white boxes. "And it's going to be massive, "no differentiation between everything out there." If you look at what you're offering, if you look at how public Clouds build their things, but I called it a few years or is there's a pure optimization. So you need to scale, you need similarities but you know you need to fit some, very specific requirements, lots of places, so, interesting stuff. Yeah, certifications, always keep your teams busy. Alright, let's get back to Shannon to view on the report. >> We are also introducing three other hardware-based additions. First, a new VxRail E Series model based on where the first time AMD EPYC processors. These single socket 1U nodes, offer dual socket performance with CPU options that scale from eight to 64 Cores, up to a terabyte of memory and multiple storage options making it an ideal platform for desktop VDI analytics and computer aided design. Next, the addition of the latest Nvidia Quadro RTX GPUs brings the most significant advancement in computer graphics in over a decade to professional work flows. Designers and artists across industries can now expand the boundary of what's possible, working with the largest and most complex graphics rendering, deep learning and visual computing workloads. And Intel Optane DC persistent memory is here, and it offers high performance and significantly increased memory capacity with data persistence at an affordable price. Data persistence is a critical feature that maintains data integrity, even when power is lost, enabling quicker recovery and less downtime. With support for Intel obtain DC persistent memory customers can expand in memory intensive workloads and use cases like SAP HANA. Alright, let's finally dig into our HCI system software, which is the Core differentiation for VxRail regardless of your workload or platform choice. Our joining engineering with VMware and investments in VxRail HCI system software innovation together deliver an optimized operational experience at reduced risk for our customers. Under the covers, VxRail offers best in class hardware, married with VMware HCI software, either vSAN or VCF. But what makes us different stems from our investments to integrate the two. Dell Technologies has a dedicated VxRail team of about 400 people to build market sell and support a fully integrated hyper converged system. That team has also developed our unique VxRail HCI system software, which is a suite of integrated software elements that extend VMware native capabilities to deliver seamless, automated operational experience that customers cannot find elsewhere. The key components of VxRail HCI system software shown around the arc here that include the extra manager, full stack lifecycle management, ecosystem connectors, and support. I don't have time to get into all the details of these elements today, but if you're interested in learning more, I encourage you to meet our experts. And I will tell you how to do that in a moment. I touched on the LCM being a key feature to the vSphere 7.0 earlier and I'd like to take the opportunity to expand on that a bit in the context of VxRail Lifecycle Management. The LCM adds valuable automation to the execution of updates for customers, but it doesn't eliminate the manual work still needed to define and package the updates and validate all of the components prior to applying them. With VxRail customers have all of these areas addressed automatically on their behalf, freeing them to put their time into other important functions for their business. Customers tell us that Lifecycle management continues to be a major source of the maintenance effort they put into their infrastructure, and then it tends to lead to overburden IT staff, that it can cause disruptions to the business if not managed effectively, and that it isn't the most efficient economically. Automation of Lifecycle Management and VxRail results in the utmost simplicity from a customer experience perspective, and offers operational freedom from maintaining infrastructure. But as shown here, our customers not only realize greater IT team efficiencies, they have also reduced downtime with fewer unplanned outages, and reduced overall cost of operations. With VxRail HCI system software, intelligent Lifecycle Management upgrades of the fully integrated hardware and software stack are automated, keeping clusters and continuously validated states while minimizing risks and operational costs. How do we ensure Continuously validated states for VxRail. VxRail labs execute an extensive, automated, repeatable process on every firmware and software upgrade and patch to ensure clusters are in continuously validated states of the customers choosing across their VxRail environment. The VxRail labs are constantly testing, analyzing, optimizing, and sequencing all of the components in the upgrade to execute in a single package for the full stack. All the while VxRail is backed by Dell EMC's world class services and support with a single point of contact for both hardware and software. IT productivity skyrockets with single click non disruptive upgrades of the fully integrated hardware and software stack without the need to do extensive research and testing. taking you to the next VxRail version of your choice, while always in a continuously validated state. You can also confidently execute automated VxRail upgrades. No matter what hardware generation or node types are in the cluster. They don't have to all be the same. And upgrades with VxRail are faster and more efficient with leapfrogging simply choose any VxRail version you desire. And be assured you will get there in a validated state while seamlessly bypassing any other release in between. Only VxRail can do that. >> All right, so Chad, the lifecycle management piece that Shannon was just talking about is, not the sexiest, it's often underappreciated. There's not only the years of experience, but the continuous work you're doing, reminds me back the early vSAN deployments versus VxRail jointly developed, jointly tested between Dell and VMware. So bring us inside why, 2020 Lifecycle Management still, a very important piece, especially in the VM family line. >> Yes, Stu, I think it's sexy, but, I'm pretty big nerd. (all laughing) Yeah, this is really always been our bread and butter. And in fact, it gets even more important, the larger the deployments come, when you start to look at data centers full of VxRails and all the different hardware software, firmware combinations that could exist out there. It's really the value that you get out of that VxRail HCI system software that Shannon was talking about and how it's optimized around the VMware use case. Very tightly integrated with each VMware component, of course, and the intelligence of being able to do all the firmware, all of the drivers, all the software all together in tremendous value to our customers. But to deliver that we really need to make a fairly large investment. So as Shannon mentioned, we run about 25,000 hours of testing across Each major release for patches, express patches, that's about 7000 hours for each of those. So, obviously, there's a lot of parallelism. And we're always developing new test scenarios for each release that we need to build in as we as we introduce new functionality. And one of the key things that we're able to do, as Shannon mentioned, is to be able to leapfrog releases and get you to that next validated state. We've got about 100 engineers just working on creating and executing those test cases on a continuous basis and obviously, a huge amount of automation. And we've talked about that investment to execute those tests. That's one worth of $60 million of investment in our lab. In fact, we've got just over 2000 VxRail units in our testbed across the US, Shanghai, China and Cork, Ireland. So a massive amount of testing of each of those components to make sure that they operate together in a validated state. >> Yeah, well, absolutely, it's super important not only for the day one, but the day two deployments. But I think this actually a great place for us to bring in that customer that Dell gave me access to. So we've got the CIO of Amarillo, Texas, he was an existing VxRail customer. And he's going to explain what happened as to how he needed to react really fast to support the work-from-home initiative, as well as we get to hear in his words the value of what Lifecycle Management means. So Andrew, if we could queue up that customer segment, please? >> It's been massive and it's been interesting to see the IT team absorb it. As we mature, I think they embrace the ability to be innovative and to work with our departments. But this instance, really justified why I was driving progress. So fervently why it was so urgent today. Three years ago, the answer would have been no. We wouldn't have been in a place where we could adapt With VxRail in place, in a week we spun up hundreds of instant balls. We spun up a 75-person call center in a day and a half, for our public health. We rolled out multiple applications for public health so they could do remote clinics. It's given us the flexibility to be able to roll out new solutions very quickly and be very adaptive. And it's not only been apparent to my team, but it's really made an impact on the business. And now what I'm seeing is those of my customers that work, a little lagging or a little conservative, or understanding the impact of modernizing the way they do business because it makes them adaptable as well. >> Alright, so great, Richard, you talked a bunch about the the efficiencies that that the IT put in place, how about that, that overall just managed, you talked about how fast you spun up these new VDI instances. need to be able to do things much simpler? So how does the overall Lifecycle Management fit into this discussion? >> It makes it so much easier. And in the old environment, one, It took a lot of man hours to make change. It was very disruptive, when we did make change, it overburdened, I guess that's the word I'm looking for. It really overburdened our staff to cause disruption to business. That wasn't cost efficient. And then simple things like, I've worked for multi billion dollar companies where we had massive QA environments that replicated production, simply can't afford that at local government. Having this sort of environment lets me do a scaled down QA environment and still get the benefit of rolling out non disruptive change. As I said earlier, it's allowed us to take all of those cycles that we were spending on Lifecycle Management because it's greatly simplified, and move those resources and rescale them in other areas where we can actually have more impact on the business. It's hard to be innovative when 100% of your cycles are just keeping the ship afloat. >> All right, well, nothing better than hearing it straight from the end user, public sector reacting very fast to the COVID-19. And, if you heard him he said, if this is his, before he had run this project, he would not have been able to respond. So I think everybody out there understands, if I didn't actually have access to the latest technology, it would be much harder. All right, I'm looking forward to doing the CrowdChat letting everybody else dig in with questions and get follow up but a little bit more, I believe one more announcement he can and got for us though. Let's roll the final video clip. >> In our latest software release VxRail 4.7.510, We continue to add new automation and self service features. New functionality enables you to schedule and run upgrade health checks in advance of upgrades, to ensure clusters are in a ready state for the next upgrade or patch. This is extremely valuable for customers that have stringent upgrade windows, as they can be assured the clusters will seamlessly upgrade within that window. Of course, running health checks on a regular basis also helps ensure that your clusters are always ready for unscheduled patches and security updates. We are also offering more flexibility and getting all nodes or clusters to a common release level with the ability to reimage nodes or clusters to a specific VxRail version, or down rev one or more nodes that may be shipped at a higher rate than the existing cluster. This enables you to easily choose your validated state when adding new nodes or repurposing nodes in a cluster. To sum up all of our announcements, whether you are accelerating data sets modernization extending HCI to harsh Edge environments, deploying an on-premises Dell Technologies Cloud platform to create a developer ready Kubernetes infrastructure. VxRail is there delivering a turn-key experience that enables you to continuously innovate, realize operational freedom and predictably evolve. VxRail provides an extensive breadth of platform configurations, automation and Lifecycle Management across the integrated hardware and software full stack and consistent hybrid Cloud operations to address the broadest range of traditional and modern applications across Core, Edge and Cloud. I now invite you to engage with us. First, the virtual passport program is an opportunity to have some fun while learning about VxRail new features and functionality and sCore some sweet digital swag while you're at it. Delivered via an augmented reality app. All you need is your device. So go to vxrail.is/passport to get started. And secondly, if you have any questions about anything I talked about or want a deeper conversation, we encourage you to join one of our exclusive VxRail Meet The Experts sessions available for a limited time. First come first served, just go to vxrail.is/expertsession to learn more. >> All right, well, obviously, with everyone being remote, there's different ways we're looking to engage. So we've got the CrowdChat right after this. But Jon, give us a little bit more as to how Dell's making sure to stay in close contact with customers and what you've got for options for them. >> Yeah, absolutely. So as Shannon said, so in lieu of not having done Tech World this year in person, where we could have those great in-person interactions and answer questions, whether it's in the booth or in meeting rooms, we are going to have these Meet The Experts sessions over the next couple weeks, and we're going to put our best and brightest from our technical community and make them accessible to everyone out there. So again, definitely encourage you. We're trying new things here in this virtual environment to ensure that we can still stay in touch, answer questions, be responsive, and really looking forward to, having these conversations over the next couple of weeks. >> All right, well, Jon and Chad, thank you so much. We definitely look forward to the conversation here and continued. If you're here live, definitely go down below and do it if you're watching this on demand. You can see the full transcript of it at crowdchat.net/vxrailrocks. For myself, Shannon on the video, Jon, Chad, Andrew, man in the booth there, thank you so much for watching, and go ahead and join the CrowdChat.

>> Announcer: From the Cube studios in Palo Alto in Boston, connecting with thought leaders all around the world, this is theCube Conversation. >> Hi, I'm Stu Miniman. And welcome to this special presentation. We have a launch from Dell Technologies updates from the VxRail family. We're going to do things a little bit different here. We actually have a launch video Shannon Champion, of Dell Technologies. And the way we do things a lot of times, is, analysts get a little preview or when you're watching things. You might have questions on it. So, rather than me just wanting it, or you wanting yourself I actually brought in a couple of Dell Technologies expertS two of our Cube alumni, happy to welcome you back to the program. Jon Siegal, he is the Vice President of Product Marketing, and Chad Dunn, who's the Vice President of Product Management, both of them with Dell Technologies. Gentlemen, thanks so much for joining us. >> Good to see you Stu. >> Great to be here. >> All right, and so what we're going to do is we're going to be rolling the video here. I've got a button I'm going to press, Andrew will stop it here and then we'll kind of dig in a little bit, go into some questions when we're all done. We're actually holding a crowd chat, where you will be able to ask your questions, talk to the experts and everything. And so a little bit different way to do a product announcement. Hope you enjoy it. And with that, it's VxRail. Taking HCI to the extremes is the theme. We'll see what that means and everything. But without any further ado, let's let Shannon take the video away. >> Hello, and welcome. My name is Shannon Champion, and I'm looking forward to taking you through what's new with VxRail. Let's get started. We have a lot to talk about. Our launch covers new announcements addressing use cases across the Core, Edge and Cloud and spans both new hardware platforms and options, as well as the latest in software innovations. So let's jump right in. Before we talk about our announcements, let's talk about where customers are adopting VxRail today. First of all, on behalf of the entire Dell Technologies and VxRail teams, I want to thank each of our over 8000 customers, big and small in virtually every industry, who've chosen VxRail to address a broad range of workloads, deploying nearly 100,000 nodes today. Thank you. Our promise to you is that we will add new functionality, improve serviceability, and support new use cases, so that we deliver the most value to you, whether in the Core, at the Edge or for the Cloud. In the Core, VxRail from day one has been a catalyst to accelerate IT transformation. Many of our customers started here and many will continue to leverage VxRail to simply extend and enhance your VMware environment. Now we can support even more demanding applications such as In-Memory databases, like SAP HANA, and more AI and ML applications, with support for more and more powerful GPUs. At the Edge, video surveillance, which also uses GPUs, by the way, is an example of a popular use case leveraging VxRail alongside external storage. And right now we all know the enhanced role that IT is playing. And as it relates to VDI, VxRail has always been a great option for that. In the Cloud, it's all about Kubernetes, and how Dell Technologies Cloud platform, which is VCF on VxRail can deliver consistent infrastructure for both traditional and Cloud native applications. And we're doing that together with VMware. VxRail is the only jointly engineered HCI system built with VMware for VMware environments, designed to enhance the native VMware experience. This joint engineering with VMware and investments in software innovation together deliver an optimized operational experience at reduced risk for our customers. >> Alright, so Shannon talked a bit about, the important role of IT Of course right now, with the global pandemic going on. It's really, calling in, essential things, putting, platforms to the test. So, I really love to hear what both of you are hearing from customers. Also, VDI, of course, in the early days, it was, HCI-only-does-VDI. Now, we know there are many solutions, but remote work is putting that back front and center. So, Jon, why don't we start with you as the what is (muffled speaking) >> Absolutely. So first of all, Stu, thank you, I want to do a shout out to our VxRail customers around the world. It's really been humbling, inspiring, and just amazing to see The impact of our VxRail customers around the world and what they're having on on human progress here. Just for a few examples, there are genomics companies that we have running VxRail that have rolled out testing at scale. We also have research universities out in the Netherlands, doing the antibody detection. The US Navy has stood up a floating hospital to of course care for those in need. So we are here to help that's been our message to our customers, but it's amazing to see how much they're helping society during this. So just just a pleasure there. But as you mentioned, just to hit on the VDI comments, so to your points too, HCI, VxRail, VDI, that was an initial use case years ago. And it's been great to see how many of our existing VxRail customers have been able to pivot very quickly leveraging VxRail to add and to help bring their remote workforce online and support them with their existing VxRail. Because VxRail is flexible, it is agile, to be able to support those multiple workloads. And in addition to that, we've also rolled out some new VDI bundles to make it simpler for customers more cost effective cater to everything from knowlEdge workers to multimedia workers. You name it, you know from 250, desktops up to 1000. But again, back to your point VxRail, HCI, is well beyond VDI, it crossed the chasm a couple years ago actually. And VDI now is less than a third of the typical workloads, any of our customers out there, it supports now a range of workloads that you heard from Shannon, whether it's video surveillance, whether it's general purpose, all the way to mission critical applications now with SAP HAN. So, this has changed the game for sure. But the range of work loads and the flexibility of the actual rules which really helping our existing customers during this pandemic. >> Yeah, I agree with you, Jon, we've seen customers really embrace HCI for a number of workloads in their environments, from the ones that we sure all knew and loved back in the initial days of HCI. Now, the mission critical things now to Cloud native workloads as well, and the sort of the efficiencies that customers are able to get from HCI. And specifically, VxRail gives them that ability to pivot. When these, shall we say unexpected circumstances arise? And I think that that's informing their their decisions and their opinions on what their IP strategies look like as they move forward. They want that same level of agility, and ability to react quickly with their overall infrastructure. >> Excellent. Now I want to get into the announcements. What I want my team actually, your team gave me access to the CIO from the city of Amarillo, so maybe they can dig up that footage, talk about how fast they pivoted, using VxRail to really spin up things fast. So let's hear from the announcement first and then definitely want to share that that customer story a little bit later. So let's get to the actual news that Shannon's going to share. >> Okay, now what's new? I am pleased to announce a number of exciting updates and new platforms, to further enable IT modernization across Core, Edge and Cloud. I will cover each of these announcements in more detail, demonstrating how only VxRail can offer the breadth of platform configurations, automation, orchestration and Lifecycle Management, across a fully integrated hardware and software full stack with consistent, simplified operations to address the broadest range of traditional and modern applications. I'll start with hybrid Cloud and recap what you may have seen in the Dell Technologies Cloud announcements just a few weeks ago, related to VMware Cloud foundation on VxRail. Then I'll cover two brand new VxRail hardware platforms and additional options. And finally circle back to talk about the latest enhancements to our VxRail HCI system software capabilities for Lifecycle Management. Let's get started with our new Cloud offerings based on VxRail. VxRail is the HCI foundation for Dell Technologies, Cloud Platform, bringing automation and financial models, similar to public Cloud to On-premises environments. VMware recently introduced Cloud foundation for Delta, which is based on vSphere 7.0. As you likely know by now, vSphere 7.0 was definitely an exciting and highly anticipated release. In keeping with our synchronous release commitment, we introduced VxRail 7.0 based on vSphere 7.0 in late April, which was within 30 days of VMware's release. Two key areas that VMware focused on we're embedding containers and Kubernetes into vSphere, unifying them with virtual machines. And the second is improving the work experience for vSphere administrators with vSphere Lifecycle Manager or VLCM. I'll address the second point a bit in terms of how VxRail fits in in a moment for VCF 4 with Tom Xu, based on vSphere 7.0 customers now have access to a hybrid Cloud platform that supports native Kubernetes workloads and management, as well as your traditional VM-based workloads. So containers are now first class citizens of your private Cloud alongside traditional VMs and this is now available with VCF 4.0, on VxRail 7.0. VxRail's tight integration with VMware Cloud foundation delivers a simple and direct path not only to the hybrid Cloud, but also to deliver Kubernetes at Cloud scale with one complete automated platform. The second Cloud announcement is also exciting. Recent VCF for networking advancements have made it easier than ever to get started with hybrid Cloud, because we're now able to offer a more accessible consolidated architecture. And with that Dell Technologies Cloud platform can now be deployed with a four-node configuration, lowering the cost of an entry level hybrid Cloud. This enables customers to start smaller and grow their Cloud deployment over time. VCF and VxRail can now be deployed in two different ways. For small environments, customers can utilize a consolidated architecture which starts with just four nodes. Since the management and workload domains share resources in this architecture, it's ideal for getting started with an entry level Cloud to run general purpose virtualized workloads with a smaller entry point. Both in terms of required infrastructure footprint as well as cost, but still with a Consistent Cloud operating model. For larger environments where dedicated resources and role-based access control to separate different sets of workloads is usually preferred. You can choose to deploy a standard architecture which starts at eight nodes for independent management and workload domains. A standard implementation is ideal for customers running applications that require dedicated workload domains that includes Horizon, VDI, and vSphere with Kubernetes. >> Alright, Jon, there's definitely been a lot of interest in our community around everything that VMware is doing with vSphere 7.0. understand if you wanted to use the Kubernetes piece, it's VCF as that so we've seen the announcements, Dell, partnering in there it helps us connect that story between, really the VMware strategy and how they talk about Cloud and where does VxRail fit in that overall, Delta Cloud story? >> Absolutely. So first of all Stu, the VxRail course is integral to the Delta Cloud strategy. it's been VCF on VxRail equals the Delta Cloud platform. And this is our flagship on prem Cloud offering, that we've been able to enable operational consistency across any Cloud, whether it's On-prem, in the Edge or in the public Cloud. And we've seen the Dell tech Cloud Platform embraced by customers for a couple key reasons. One is it offers the fastest hybrid Cloud deployment in the market. And this is really, thanks to a new subscription offer that we're now offering out there where in less than 14 days, it can be still up and running. And really, the Dell tech Cloud does bring a lot of flexibility in terms of consumption models, overall when it comes to VxRail. Secondly, I would say is fast and easy upgrades. This is what VxRail brings to the table for all workloads, if you will, into especially critical in the Cloud. So the full automation of Lifecycle Management across the hardware and software stack across the VMware software stack, and in the Dell software and hardware supporting that, together, this enables essentially the third thing, which is customers can just relax. They can be rest assured that their infrastructure will be continuously validated, and always be in a continuously validated state. And this is the kind of thing that those three value propositions together really fit well, with any on-prem Cloud. Now you take what Shannon just mentioned, and the fact that now you can build and run modern applications on the same VxRail infrastructure alongside traditional applications. This is a game changer. >> Yeah, I love it. I remember in the early days talking with Dunn about CI, how does that fit in with Cloud discussion and the line I've used the last couple years is, modernize the platform, then you can modernize the application. So as companies are doing their full modernization, then this plays into what you're talking about. All right, we can let Shannon continue, we can get some more before we dig into some more analysis. >> That's good. >> Let's talk about new hardware platforms and updates. that result in literally thousands of potential new configuration options. covering a wide breadth of modern and traditional application needs across a range of the actual use cases. First up, I am incredibly excited to announce a brand new Dell EMC VxRail series, the D series. This is a ruggedized durable platform that delivers the full power of VxRail for workloads at the Edge in challenging environments or for space constrained areas. VxRail D series offers the same compelling benefits as the rest of the VxRail portfolio with simplicity, agility and lifecycle management. But in a lightweight short depth at only 20 inches, it's adorable form factor that's extremely temperature-resilient, shock resistant, and easily portable. It even meets milspec standards. That means you have the full power of lifecycle automation with VxRail HCI system software and 24 by seven single point of support, enabling you to rapidly react to business needs, no matter the location or how harsh the conditions. So whether you're deploying a data center at a mobile command base, running real-time GPS mapping on the go, or implementing video surveillance in remote areas, you can ensure availability, integrity and confidence for every workload with the new VxRail ruggedized D series. >> All right, Chad we would love for you to bring us in a little bit that what customer requirement for bringing this to market. I remember seeing, Dell servers ruggedized, of course, Edge, really important growth to build on what Jon was talking about, Cloud. So, Chad, bring us inside, what was driving this piece of the offering? >> Sure Stu. Yeah, yeah, having been at the hardware platforms that can go out into some of these remote locations is really important. And that's being driven by the fact that customers are looking for compute performance and storage out at some of these Edges or some of the more exotic locations. whether that's manufacturing plants, oil rigs, submarine ships, military applications, places that we've never heard of. But it's also about extending that operational simplicity of the the sort of way that you're managing your data center that has VxRails you're managing your Edges the same way using the same set of tools. You don't need to learn anything else. So operational simplicity is absolutely key here. But in those locations, you can take a product that's designed for a data center where definitely controlling power cooling space and take it some of these places where you get sand blowing or seven to zero temperatures, could be Baghdad or it could be Ketchikan, Alaska. So we built this D series that was able to go to those extreme locations with extreme heat, extreme cold, extreme altitude, but still offer that operational simplicity. Now military is one of those applications for the rugged platform. If you look at the resistance that it has to heat, it operates at a 45 degrees Celsius or 113 degrees Fahrenheit range, but it can do an excursion up to 55 C or 131 degrees Fahrenheit for up to eight hours. It's also resistant to heat sand, dust, vibration, it's very lightweight, short depth, in fact, it's only 20 inches deep. This is a smallest form factor, obviously that we have in the VxRail family. And it's also built to be able to withstand sudden shocks certified to withstand 40 G's of shock and operation of the 15,000 feet of elevation. Pretty high. And this is sort of like wherever skydivers go to when they want the real thrill of skydiving where you actually need oxygen to, to be for that that altitude. They're milspec-certified. So, MIL-STD-810G, which I keep right beside my bed and read every night. And it comes with a VxRail stick hardening package is packaging scripts so that you can auto lock down the rail environment. And we've got a few other certifications that are on the roadmap now for naval shock requirements. EMI and radiation immunity often. >> Yeah, it's funny, I remember when we first launched it was like, "Oh, well everything's going to white boxes. "And it's going to be massive, "no differentiation between everything out there." If you look at what you're offering, if you look at how public Clouds build their things, but I called it a few years or is there's a pure optimization. So you need to scale, you need similarities but you know you need to fit some, very specific requirements, lots of places, so, interesting stuff. Yeah, certifications, always keep your teams busy. Alright, let's get back to Shannon to view on the report. >> We are also introducing three other hardware-based additions. First, a new VxRail E Series model based on where the first time AMD EPYC processors. These single socket 1U nodes, offer dual socket performance with CPU options that scale from eight to 64 Cores, up to a terabyte of memory and multiple storage options making it an ideal platform for desktop VDI analytics and computer aided design. Next, the addition of the latest Nvidia Quadro RTX GPUs brings the most significant advancement in computer graphics in over a decade to professional work flows. Designers and artists across industries can now expand the boundary of what's possible, working with the largest and most complex graphics rendering, deep learning and visual computing workloads. And Intel Optane DC persistent memory is here, and it offers high performance and significantly increased memory capacity with data persistence at an affordable price. Data persistence is a critical feature that maintains data integrity, even when power is lost, enabling quicker recovery and less downtime. With support for Intel obtain DC persistent memory customers can expand in memory intensive workloads and use cases like SAP HANA. Alright, let's finally dig into our HCI system software, which is the Core differentiation for VxRail regardless of your workload or platform choice. Our joining engineering with VMware and investments in VxRail HCI system software innovation together deliver an optimized operational experience at reduced risk for our customers. Under the covers, VxRail offers best in class hardware, married with VMware HCI software, either vSAN or VCF. But what makes us different stems from our investments to integrate the two. Dell Technologies has a dedicated VxRail team of about 400 people to build market sell and support a fully integrated hyper converged system. That team has also developed our unique VxRail HCI system software, which is a suite of integrated software elements that extend VMware native capabilities to deliver seamless, automated operational experience that customers cannot find elsewhere. The key components of VxRail HCI system software shown around the arc here that include the extra manager, full stack lifecycle management, ecosystem connectors, and support. I don't have time to get into all the details of these elements today, but if you're interested in learning more, I encourage you to meet our experts. And I will tell you how to do that in a moment. I touched on the LCM being a key feature to the vSphere 7.0 earlier and I'd like to take the opportunity to expand on that a bit in the context of VxRail Lifecycle Management. The LCM adds valuable automation to the execution of updates for customers, but it doesn't eliminate the manual work still needed to define and package the updates and validate all of the components prior to applying them. With VxRail customers have all of these areas addressed automatically on their behalf, freeing them to put their time into other important functions for their business. Customers tell us that Lifecycle management continues to be a major source of the maintenance effort they put into their infrastructure, and then it tends to lead to overburden IT staff, that it can cause disruptions to the business if not managed effectively, and that it isn't the most efficient economically. Automation of Lifecycle Management and VxRail results in the utmost simplicity from a customer experience perspective, and offers operational freedom from maintaining infrastructure. But as shown here, our customers not only realize greater IT team efficiencies, they have also reduced downtime with fewer unplanned outages, and reduced overall cost of operations. With VxRail HCI system software, intelligent Lifecycle Management upgrades of the fully integrated hardware and software stack are automated, keeping clusters and continuously validated states while minimizing risks and operational costs. How do we ensure Continuously validated states for VxRail. VxRail labs execute an extensive, automated, repeatable process on every firmware and software upgrade and patch to ensure clusters are in continuously validated states of the customers choosing across their VxRail environment. The VxRail labs are constantly testing, analyzing, optimizing, and sequencing all of the components in the upgrade to execute in a single package for the full stack. All the while VxRail is backed by Dell EMC's world class services and support with a single point of contact for both hardware and software. IT productivity skyrockets with single click non disruptive upgrades of the fully integrated hardware and software stack without the need to do extensive research and testing. taking you to the next VxRail version of your choice, while always in a continuously validated state. You can also confidently execute automated VxRail upgrades. No matter what hardware generation or node types are in the cluster. They don't have to all be the same. And upgrades with VxRail are faster and more efficient with leapfrogging simply choose any VxRail version you desire. And be assured you will get there in a validated state while seamlessly bypassing any other release in between. Only VxRail can do that. >> All right, so Chad, the lifecycle management piece that Shannon was just talking about is, not the sexiest, it's often underappreciated. There's not only the years of experience, but the continuous work you're doing, reminds me back the early vSAN deployments versus VxRail jointly developed, jointly tested between Dell and VMware. So bring us inside why, 2020 Lifecycle Management still, a very important piece, especially in the VM family line. >> Yes, Stu, I think it's sexy, but, I'm pretty big nerd. (all laughing) Yeah, this is really always been our bread and butter. And in fact, it gets even more important, the larger the deployments come, when you start to look at data centers full of VxRails and all the different hardware software, firmware combinations that could exist out there. It's really the value that you get out of that VxRail HCI system software that Shannon was talking about and how it's optimized around the VMware use case. Very tightly integrated with each VMware component, of course, and the intelligence of being able to do all the firmware, all of the drivers, all the software all together in tremendous value to our customers. But to deliver that we really need to make a fairly large investment. So as Shannon mentioned, we run about 25,000 hours of testing across Each major release for patches, express patches, that's about 7000 hours for each of those. So, obviously, there's a lot of parallelism. And we're always developing new test scenarios for each release that we need to build in as we as we introduce new functionality. And one of the key things that we're able to do, as Shannon mentioned, is to be able to leapfrog releases and get you to that next validated state. We've got about 100 engineers just working on creating and executing those test cases on a continuous basis and obviously, a huge amount of automation. And we've talked about that investment to execute those tests. That's one worth of $60 million of investment in our lab. In fact, we've got just over 2000 VxRail units in our testbed across the US, Shanghai, China and Cork, Ireland. So a massive amount of testing of each of those components to make sure that they operate together in a validated state. >> Yeah, well, absolutely, it's super important not only for the day one, but the day two deployments. But I think this actually a great place for us to bring in that customer that Dell gave me access to. So we've got the CIO of Amarillo, Texas, he was an existing VxRail customer. And he's going to explain what happened as to how he needed to react really fast to support the work-from-home initiative, as well as we get to hear in his words the value of what Lifecycle Management means. So Andrew, if we could queue up that customer segment, please? >> It's been massive and it's been interesting to see the IT team absorb it. As we mature, I think they embrace the ability to be innovative and to work with our departments. But this instance, really justified why I was driving progress. So fervently why it was so urgent today. Three years ago, the answer would have been no. We wouldn't have been in a place where we could adapt With VxRail in place, in a week we spun up hundreds of instant balls. We spun up a 75-person call center in a day and a half, for our public health. We rolled out multiple applications for public health so they could do remote clinics. It's given us the flexibility to be able to roll out new solutions very quickly and be very adaptive. And it's not only been apparent to my team, but it's really made an impact on the business. And now what I'm seeing is those of my customers that work, a little lagging or a little conservative, or understanding the impact of modernizing the way they do business because it makes them adaptable as well. >> Alright, so great, Richard, you talked a bunch about the the efficiencies that that the IT put in place, how about that, that overall just managed, you talked about how fast you spun up these new VDI instances. need to be able to do things much simpler? So how does the overall Lifecycle Management fit into this discussion? >> It makes it so much easier. And in the old environment, one, It took a lot of man hours to make change. It was very disruptive, when we did make change, it overburdened, I guess that's the word I'm looking for. It really overburdened our staff to cause disruption to business. That wasn't cost efficient. And then simple things like, I've worked for multi billion dollar companies where we had massive QA environments that replicated production, simply can't afford that at local government. Having this sort of environment lets me do a scaled down QA environment and still get the benefit of rolling out non disruptive change. As I said earlier, it's allowed us to take all of those cycles that we were spending on Lifecycle Management because it's greatly simplified, and move those resources and rescale them in other areas where we can actually have more impact on the business. It's hard to be innovative when 100% of your cycles are just keeping the ship afloat. >> All right, well, nothing better than hearing it straight from the end user, public sector reacting very fast to the COVID-19. And, if you heard him he said, if this is his, before he had run this project, he would not have been able to respond. So I think everybody out there understands, if I didn't actually have access to the latest technology, it would be much harder. All right, I'm looking forward to doing the CrowdChat letting everybody else dig in with questions and get follow up but a little bit more, I believe one more announcement he can and got for us though. Let's roll the final video clip. >> In our latest software release VxRail 4.7.510, We continue to add new automation and self service features. New functionality enables you to schedule and run upgrade health checks in advance of upgrades, to ensure clusters are in a ready state for the next upgrade or patch. This is extremely valuable for customers that have stringent upgrade windows, as they can be assured the clusters will seamlessly upgrade within that window. Of course, running health checks on a regular basis also helps ensure that your clusters are always ready for unscheduled patches and security updates. We are also offering more flexibility and getting all nodes or clusters to a common release level with the ability to reimage nodes or clusters to a specific VxRail version, or down rev one or more nodes that may be shipped at a higher rate than the existing cluster. This enables you to easily choose your validated state when adding new nodes or repurposing nodes in a cluster. To sum up all of our announcements, whether you are accelerating data sets modernization extending HCI to harsh Edge environments, deploying an on-premises Dell Technologies Cloud platform to create a developer ready Kubernetes infrastructure. VxRail is there delivering a turn-key experience that enables you to continuously innovate, realize operational freedom and predictably evolve. VxRail provides an extensive breadth of platform configurations, automation and Lifecycle Management across the integrated hardware and software full stack and consistent hybrid Cloud operations to address the broadest range of traditional and modern applications across Core, Edge and Cloud. I now invite you to engage with us. First, the virtual passport program is an opportunity to have some fun while learning about VxRail new features and functionality and sCore some sweet digital swag while you're at it. Delivered via an augmented reality app. All you need is your device. So go to vxrail.is/passport to get started. And secondly, if you have any questions about anything I talked about or want a deeper conversation, we encourage you to join one of our exclusive VxRail Meet The Experts sessions available for a limited time. First come first served, just go to vxrail.is/expertsession to learn more. >> All right, well, obviously, with everyone being remote, there's different ways we're looking to engage. So we've got the CrowdChat right after this. But Jon, give us a little bit more as to how Dell's making sure to stay in close contact with customers and what you've got for options for them. >> Yeah, absolutely. So as Shannon said, so in lieu of not having done Tech World this year in person, where we could have those great in-person interactions and answer questions, whether it's in the booth or in meeting rooms, we are going to have these Meet The Experts sessions over the next couple weeks, and we're going to put our best and brightest from our technical community and make them accessible to everyone out there. So again, definitely encourage you. We're trying new things here in this virtual environment to ensure that we can still stay in touch, answer questions, be responsive, and really looking forward to, having these conversations over the next couple of weeks. >> All right, well, Jon and Chad, thank you so much. We definitely look forward to the conversation here and continued. If you're here live, definitely go down below and do it if you're watching this on demand. You can see the full transcript of it at crowdchat.net/vxrailrocks. For myself, Shannon on the video, Jon, Chad, Andrew, man in the booth there, thank you so much for watching, and go ahead and join the CrowdChat.

(upbeat music) >> Announcer: From theCUBE studios in Palo Alto in Boston, connecting with thought leaders all around the world, this is a CUBE conversation. >> Everyone, welcome to this CUBE conversation. I'm John Furrier with theCUBE, host of theCUBE here in our Palo Alto office for remote interviews during this time of COVID-19. We're here with the quarantine crew here in our studio. We've got a great guest here from Google, Will Grannis, managing director, head of the office of the CTO with Google Cloud. Thanks for coming on, Will. Appreciate you spending some time with me. >> Oh, John, it's great to be with you. And as you said, in these times, more important than ever to stay connected. >> Yeah, and I'm really glad you came on because a couple of things. One, congratulations to Google Cloud for the success you guys had. Saw a lot of big wins under your belt, both on the momentum side, on the business side, but also on the technical side. Meet is available now for folks. Anthos is doing very, very well. Partner ecosystem's developing. Got some nice use cases in vertical markets, so I want to get in and unpack with you. But really, the bigger story here is that the world has seen the future before it was ready for it. And that is the at-scale challenge that the COVID-19 has shown everyone. We're seeing the future has been pulled forward. We're living in a virtualized environment. It's funny to say that, virtualization (laughs). Server virtualization is a tech term, but that enabled a lot of things. We're living in a virtualized world now 'cause we have to, but this is going to set in motion a series of new realities that you guys have been experiencing and supporting for many, many years. But now as a provider of Google Cloud, you guys have to operate at scale, you have. And now the whole world realizes that scale is a big deal. And so you guys have had some successes. I want to get your thoughts on the this at scale problem that the world now realizes. I mean, everyone's at home. That's a disruption that was unforecasted. Whether it's under-provisioning VPNs in IT to a surface area for security, to just work and play. And activities are now confined, so people aren't convening anymore and it's a huge issue. What's your take on all this? >> Well, I mean, to your point just now, the fact that we can have this conversation and we can have it fluidly from our respective remote locations just goes to show you the power of information technology that underlies so many of the things that we do today. And for Google Cloud, this is not a new thing. And for Google, this is not a new thing. For Google Cloud, we had a mission of trying to help companies accelerate their transformation and enable them in these new digital environments. And so many companies that we've been working with, they've already been on the path to operating in environments that are digital, that are fluid. And when you think about the cloud, that's one of the great benefits of cloud, is that scalability in common with the business demand. And it also helps the scale situation without having to do the typical, "Oh wait, "you need to find the procurement people. "We need to find the server vendors. "We need to get the storage lined up." It really allows a much more fluid response to unexpected and unforecasted situations. Whether that's customer demand or in this case a global pandemic. >> Yeah, one of the things I want to get in with you on, you have explained what your job is there 'cause obviously Google's got a new CEO now for over a year. Thomas Kurian came from Oracle, knows the enterprise up and down. You had Diane Greene before that. Again, another enterprise leader. Google Cloud has essentially rebuilt itself from the original Google Cloud to be very enterprise centric. You guys have great momentum, and this is a world where cloud-native is going to be required. I mean, everyone now sees it. The tide has been pulled out, everything's exposed, all the gaps in business from a tech standpoint is kind of exposed. And so the smart managers and companies are looking at things and saying, "Double down on that. "Let's kill that. "We don't want to pay that supplier. "They're not core to our business." This is going to be a very rapid acceleration of what I call a vetting of the new set of players that are going to emerge because the folks who don't adapt to this new cloud-native reality, whether it's app workloads for banking to whatever are going to have to reinvent themselves now and reset and tweak to come out of this crisis. So it's going to be very cloud-native. This is a big deal. Can you share your reaction to that? >> Absolutely. And so as you pointed out, there are kind of two worlds that exist right now. Companies that are moving to become more digital and transform, and you mentioned the momentum in Google Cloud just over the last year, greater than 50% revenue growth. And in a greater than $10 billion run rate business and adding customers at a really quick clip, including just yesterday, Splunk, and along the way, Telecom Italia, Major League Baseball, Vodafone, Lowe's, Wayfair, Activision Blizzard. This transformation and this digitization is not just for a few or just for any one industry. It's happening across the board. And then you add that to the implementations that have been happening across Shopify and the Spotify and HSBC, which was a early customer of ours in the cloud and it already has a little bit of a headstart into this transformation. So you see these new companies coming in and seeing the value of digital transformation. And then these other companies that have kind of lit the path for others to consider. And Shopify is a really good example of how seeing drastic uptick in demand, they're able to respond and keep roughly half a million shops up and running during a period of time where many retailers are trying to figure out how to stay online or even get online. >> Well, what is your role at Google? Obviously, you're the managing director. Title is managing director, head of the office of the CTO. We've seen these roles before, head of the CTO, obviously a technical role. Is it partnering with the CEO on strategy? Is it you're tire kicking new things? Are you overseeing any strategic initiatives? What is your role? >> So a little bit of all of those things combined into one. So I spent the first couple of decades of my career on the other side of the fence in the non-tech community, both in the enterprise. But we were still building technology and we were still digitally minded. But not the way that people view technology in Silicon Valley. And so spending a couple of decades in that environment really gave me insights into how to take technology and apply them to a specific problem. And when I came to Google five years ago, selfishly, it was because I knew the potential of Google's technology having been on the other side. And I was really interested in forming a better bridge between Google's technology and people like me who were CTOs of public companies and really wanted to leverage that technology for problems that I was solving. Whether it was aerospace, public sector, manufacturing, what have you. And so it's been great. It's the role of a lifetime. I've been able to build the team that I wanted as an enterprise technologist for decades and the entire span of technologies at our disposal. And we do two things. One is we help our most strategic customers accelerate their path to cloud. And two, we create these signals by working with the top companies moving to the cloud and digitally transforming. We learned so much, John, about what we need to build as an organization. So it also helps balance out the Google driven innovation with our customer driven innovation. >> Yeah, and I can attest. I've been watching you guys from day one. Hired a lot of great enterprise people that I personally know. So you get in the enterprise chops and stuff and you've seen some progress. I have to ask you though, because first of all, big fan of Google at scale from knowing them from when they were just a little search engine to what they are now. There was an expression a few years ago I heard from enterprise customers. It goes along the lines like this. "I want to be like Google," because you guys had a great network, you had large scale. You had all these things that were like awesome. And then they realized, "Well, we can't be like Google. "We don't have SREs. "We don't have large scale data centers." So there was a little bit of a translation, and I want to say a little bit of a overplay of the Google hand, and you guys had since realized that it wasn't just people are going to bang at your doorstep and be adopting Google Cloud because there was a little bit of a cultural disconnect from wanting to be like Google, then leveraging Google in their business as they transform. So as you guys have moved from that, what's changed? They still want to be like Google in the sense you have great security, got a great network, and you've got that scale. Enterprises are a little bit slower to adopt that, which you're focused on now. What is the story there? Because I think that's kind of the theme that I'm hearing. Okay, Google now understands me. They know I'm not as fast as Google. They got super great people (laughs). We are training our people. We're retraining them. This is the transformation that they're going through. So you might be a little bit ahead of them certainly, but now they need to level up. How do you respond to that? >> Well, a lot of this is the transformation that Thomas has been enacting over the last year plus. And it comes in kind of three very operational or tactical pillars that I think of. First, we expanded our customer and we continue to expand our customer facing teams. Three times what they were before because we need to be there. We need to be in those situations. We need to hear from the customer. We need to learn more about the problems they're trying to solve. So we don't just take a theoretical principle and try to overlay it onto a problem. We actually get very visceral understanding of what they're trying to solve. But you have to be there to gain that empathy and that understanding. And so one is showing up, and that has been mobilizing a much larger engine of customer facing personnel from Google. Second, it's also been really important that we evolve our own. Just as Google brought SRE principles and principles of distributed systems and software design out to the world, we also had a little bit to learn about transitioning from typical customer support and moving to more customer experience. So you've seen that evolution under Thomas as well with cloud changing... Moving from talking about support to talking about customer experience, that white glove experience that our customers get and our partners get from the beginning of their journey with us all the way through. And then finally making sure that our product roadmap has the solutions that are relevant across key priority industries for us. Again, that only comes from being present from having a focus in those industries and then developing the solutions that progress those companies. This isn't about taking a principle and trying to apply it blindly. This is about adding that connection, that really deep connection to our customers and our partners and letting that connection manifest the things that we have to do as a product company to best support them over a long period of time. I mean, look at some of these deals we've been announcing. These are 10-year, five-year, multi-year strategic partnerships that go across the canvas of all of Google. And those are the really exciting scaled partnerships. But to your point, you can't just take SRE from Google and apply it to company X, but you can things like error budgets or how we think about the principles of SRE, and you can apply them over the course of developing technology, collaborating, innovating together. >> Yeah, and I think cloud-native is going to be a key thing. It's just my opinion, but I think one of those situations where the better mouse trap will win. If you're cloud-native and you have APIs and you have the kind of services, people will beat it to your doorstep. So I got to ask you, with Thomas Kurian on board, obviously, we've been following his career as well at Oracle. He knows what he's doing. Comes into Google, it's being built out. It's like a rocket ship at this point. What bet is he making and what bet are you guys making on behalf of your customers? If you had to boil it down to Google Cloud's big bet, what is the bet on the technology side? And what's the bet on the business side? >> Sure. Well, I've already mentioned... I've already hinted at the big strategy that Thomas has brought in. And that's, again, those three pillars. Making sure that we show up and that we're present by having a scaled customer facing organization. Again, making sure that we transition from a typical support mindset into more of a customer experience mindset and then making sure that those solutions are tailored and available for our priority industries. If I was to add more color to that, I think one of the most important changes that Thomas has personally been driving is he's been converting us to a partner-led business and a partner-led organization. And this means a lot of investments in large global systems integrators like Accenture and Deloitte. But this also means that... Like the Splunk announcement from yesterday, that isn't just a sell to. This is a partnership that goes deep across go-to market product and sell to. And then we also bring in very specific partners like Temenos in Europe for financial services or a CETA or a Rackspace for migrations. And as a result, already, we're seeing really incredible lifts. So for example, nearly 200% year over year increase in partner influenced revenue in Google Cloud and almost like a 13X year over year increase in new customers won by partners. That's the kind of engine that builds a real hyper-scale business. >> Interesting you mentioned Splunk. I want to get to that in a second, but I also noticed there was a deal with TELUS Group on eSIM subscriptions, which kind of leads me into the edge piece. There's a real edge component here with Google Cloud, and I think I had a conversation with Jennifer Lynn a few years ago, really digging into the built-in security and the value of the Google network. I mean, a lot of the scuttlebutt around the Valley and the industry is Google's got an amazing network. Software-defined networking is going to be a hot programmable area. So you got programmable networking and you got edge and edge security. These are killer areas that need innovation. Could you comment on what you guys are doing there and do you agree? Obviously, you have a killer network and you're leveraging it. Can you just give some insight into what's going on in those two areas? Network and then the edge. >> Yeah, I think what you're seeing is the manifestation of the progression of cloud generally. And what do I mean by that? It started out as like get everything to the data center. We kind of had this thought that maybe we could take all the workloads and we could get them to these centralized hubs and that we could redistribute out the results and drive the latency down over time so we can expand the portfolio of applications and services that would become relevant over time. And what we've seen over the last decade really in cloud is an evolution to more of a layered architecture. And that layered architecture includes kind of core data centers. It includes CDN capacity, points of presence, it includes edge. And just in that list of customers over the last year I mentioned, there were at least three or four telcos in there. And you've also probably heard and seen quite a bit of telco momentum coming from us in recent announcements. I think that's an indication that a lot of us are thinking about, how can we take technology like Anthos, for example, and how could we orchestrate workloads, create a common control plane, manage services across those three shells, if you will, of the architecture? And that's a very strategic and important area for us. And I think generally for the cloud industry, is expanding beyond the data center as the place where everything happens. And you can look at Google Fi, you can look at Stadia. You can look at examples within Google that go well beyond cloud as to how we think about new ways to leverage that kind of criteria. >> All right, so we saw some earnings come out on Amazon side as Google, both groups and Microsoft as well, all three clouds are crushing it on the cloud side. That's a tailwind, I get that. But as it continues, we're expecting post-COVID some redistribution of development dollars in projects. Whether it's IT going cloud-native or whatever new workloads. We are predicting a Cambrian explosion of new things from core to edge. And this is going to create some lifts. So I want to get your thoughts on you guys' strategy with go-to market, as well as your customers as they now have the ability to build workloads and apps with AI and data. There seems to be a trend towards the verticalization of whether it's sales and go-to market and/or specialism because you have horizontal scalability with cloud and you now have data that has distinct (chuckles) value in these verticals. So it's really seems to be... I won't say ratification, but in a way, that seems to be the norm. Whether you come into a market and you have specialization, but the data is there so apps can be more agile. Are you guys seeing that? And is that something that you guys are considering from an organization standpoint? And how do customers think about targeting vertical industries and their customers? >> Yeah, I bring this to... And where you started going there at the end of the question is exactly the way that we think about it as well. Which is we've moved from, "Here are storage offers for everybody, "and here's basic infrastructure for everybody." And now we've said, "How can we make sure "that we have solutions that are tailored "to the very specific problems that customers "are trying to solve?" And we're getting to the point now where performance and variety of technologies are available to be able to impose very specific solutions. And if you think about the substrate that has to be there, we mentioned you have to have some really great partners, and you have to have a roadmap that is focused on priority solution. So for example, at Google Cloud, we're very focused on six priority vertical areas. So retail, financial services, healthcare, manufacturing and industrials, healthcare life sciences, public sector. And as a result of being very focused in those areas, we can make more targeted investments and also align our entire go-to market system and our entire partner ecosystem... Excuse me, ecosystem around those bare specific priority areas. So for example, we work with CETA and HDA Healthcare very recently to develop and maintain a national response portal for COVID-19. And that's to help better inform communities and hospitals. We can use Looker to help with like a Commonwealth Care Alliance nonprofit and that helps monitor patient symptoms and risk factors. So we're using a very specific focus in healthcare and a partner ecosystem to develop very tailored solutions. You can also look at... I mentioned Shopify earlier. That's another great example of how in retail, they can use something like Google Meet, inherent reliability, scalability, security, to connect their employees during these interesting times. But then they can also use GCP, Google Cloud Platform to scale out. And as they come up with new apps and experiences for their shoppers, for their shops, they can rapidly deploy, to your point. And those solutions and how the database performs and how those tiers perform, that's a very tight-knit feedback loop with our engineering teams. >> Yeah, one of the things I'm seeing obviously with the virtualization of the COVID is that when the world gets back to normal, it'll be a hybrid. And it'll be a hybrid between reality, not physical and a hundred percent virtual, hybrid. And that's going to impact events too, media, to everything. Every vertical will be impacted. And I want to point out the Splunk deal and bring that back in because I want you to comment on the relevance of the Splunk deal in context to Splunk has a cloud. And they've got a great slogan, "Data for everywhere." "Data to everywhere," I think it is. But theCUBE, we have a cloud. Every company will have a cloud scale. At some level, we'll progress to having some sort of cloud because they have data. How are you guys powering those clouds? Because I think the Splunk deal is interesting. Their partner, their stock price was up out on the news of the deal. Nice bump there for Splunk, shout out to those guys. But they're a data company and now they're cross-platform. But they're not Google, but they have a cloud. So you know what I'm saying? So they need to play in all the clouds, but they need infrastructure (laughs), they need support. So how do you guys talk to that customer that says, "Hey, the next pandemic that comes, "the next crisis that's going to cause some "either social disruption or workflow disruption "or supply chain disruption. "I need to be agile. "I need to have full cloud scale. "And so I need to talk to Google." What do you say to them? What's the pitch? And does the Splunk deal mirror some of those capabilities? Or tie that together for us, the Splunk deal and how it relates to how to proof themselves for the future. Sorry. >> For example, with the Splunk cloud deal, if you take a look at what Google is already really good at, data processing at scale, log analytics, and you take a look at what Splunk is doing with their events and security incident monitoring and the rest, it's a really great mashup because they see by platforming on Google Cloud, not only do they get highly performing infrastructure. But they also get the opportunity to leverage data tools, data analytics tools, machine learning and AI that can help them provide enhanced services. So not just about capacity going up and down through periods of demand, but also enhancing services and continuing to offer more value to their customers. And we see that as a really big trend. And this gets at something, John, a little bit bigger, which is kind of the two views of the world. And we talked about very tailored, focused solutions. Splunk is an example of taking a very methodical approach to a partnership, building a solution specifically with partners. And in this case, Splunk on the security event management side. But we're always going to provide our data processing platform, our infrastructure for companies across many different industries. And I think that addresses one part of the topic, which is, how do we make sure that in periods of demand rapidly changing, and this goes back to the foundational elements of infrastructure as a service and elasticity. We're going to provide a platform and infrastructure that can help companies move through periods of... It's hard to forecast, and/or demand may rise and fall in very interesting ways. But then there's going to be times where we... Because we're not necessarily a focused use case where it may just be generalized platform versus a focused solution. So for example, in the oil and gas industry, we don't develop custom AI, ML solutions that facilitate upstream extraction, for example. But what we do do is work with renewable energy companies to figure out how they might be able to leverage some of our AI machine learning algorithms from our own data centers to make their operations more efficient and to help those renewable energy companies learn from what we've learned building out what I consider to be a world leading renewable energy strategy and infrastructure. >> It's a classic enablement model where you're enabling your platform for your customers. Okay, so I've got to ask the question. I asked this to the Microsoft guys as well because Amazon has their own SaaS stuff. But really more of end to end. The better product's usually on the ecosystem side. You guys have some killer SaaS. G Suite, we're a customer. We use the G Suite really deeply. We also use some Bigtable as well. I want to build a cloud, we have a cloud, CUBE cloud. But you guys have Meet. So I want to build my product on Google Cloud. How do I know you're not going to compete with me? Do you guys have those conversations around the trade-off between the pure Google services, which provide great value for the areas where the ecosystem needs to develop those new areas that are going to be great markets, potentially huge markets that are out there. >> Well, this is the power of partnership. I mentioned earlier that one of the really big moves that Thomas has made has been developing a sense of partners. And it kind of blurs the line between traditional, what you would call a customer and what you would call a partner. And so having a really strong sense of which industries we're in, which we prioritize, plus having a really strong sense of where we want to add value and where our customers and partners want to add that value. That's the foundational, that's the beginning of that conversation that you just mentioned. And it's important that we have an ability to engage not just in a, "Here's the cloud infrastructure piece of the puzzle." But one of the things Thomas has also done and a key strategy of his has been to make sure that the Google Cloud relationship is also a way to access all amazing innovation happening across all of Google. And also help bring a strategic conversation in that includes multiple properties from across Google so that an HSBC and Google and have a conversation about how to move forward together that is comprehensive rather than having to wonder and have that uncertainty sit behind the projects that we're trying to get out and have high velocity on because they offer so much to retail bank, for example. >> Well, I've got a couple more questions and then I'll let you go. I know you got some other things going on. I really appreciate you taking the time, sharing this great insight and updates. As a builder, you've been on the other side of the table. Now you're at Google heading up the CTO. Also working with Thomas, understanding the go-to market across the board and the product mix. As you talk to customers and they're thinking... The good customers are thinking, "Hey, "I want to come out of this COVID on an upward trajectory "and I want to use this opportunity "to reset and realign for the future." What advice do you have for those enterprises? They could be small, medium-sized enterprises to the full large big guys. And obviously, cloud-native, we've talked some of that already, but what advice would you have for them as they start to really prioritize, as some things are now exposed? The collaboration, the tooling, the scale, all these things are out there. What have you seen and what advice would you give a CXO or CSO or a leader in the industry to think about and how they should come out of this thing, how they should plan, execute, and move forward? >> Well, I appreciate the question because this is the crux of most of my day job, which is interacting with the C-suite and boards of companies and partners around the world. And they're obviously very interested to learn or get a data point from someone at Google. And the advice generally goes in a couple of different directions. One, collaboration is part of the secret sauce that makes Google what it is. And I think you're seeing this right now across every industry, and whether you're a small, medium-sized business or you're a large company, the ability to connect people with each other to collaborate in very meaningful ways, to share information rapidly, to do it securely with high reliability, that's the foundation that enables all of the projects that you might choose to... Applications to build, services to enable, to actually succeed in production and over the long haul. Is that culture of innovation and collaboration. So absolutely number one is having a really strong sense of what they want to achieve from a cultural perspective and collaboration perspective and the people because that's the thing that fuels everything else. Second piece of advice, especially in these times where there's so much uncertainty, is where can you buy down uncertainty with...? You can learn without a high penalty. This is why cloud I think is really, really finding super scale. It was already on the rise, but what you're seeing now as you've laid back to me during this conversation, we're seeing the same thing, which is a high increase in demand of, "Let's get this implemented now. "How can we do this more? "This is clearly one way to move through uncertainty." And so look for those opportunities. I'll give you a really good example. Mainframes, (chuckles) one of the classic workloads of the on-premise enterprise. There are all sorts of potential magic solves for getting mainframes to the cloud and getting out of mainframes. But a practical consideration might be maybe you just front-end it with some Java. Or maybe you just get closer to other data centers within a certain amount of milliseconds that's required to have a performant workload. Maybe you start chunking at art and treat the workload a little bit differently rather than just one thing. But there are a lot of years and investments in our workload that might run on a mainframe. And that's a perfect example of how biting off too much might be a little bit dangerous, but there is a path to... So for example, we brought in a company called Cornerstone to help with those migrations. But we also have partnerships with data center providers and others globally plus our own built infrastructure to allow even a smaller step per se for more close proximity location of the workload. >> It's great. Everything kind of has a technical metaphor connection these days when you have a internet, digitally connected world. We're living in the notion of a digital business, was a research buzzword that's been kicked around for years. But I think now COVID-19, you're seeing the virtual or digital, it's really digital, but virtual reality, augmented reality is going to come fast too. Really get people to go, "Wow. "Virtualization of my business." So we've been kind of kicking around this term business virtualization just almost as a joke, but it's really more about, okay, this is about a new world, new opportunity to think about when we come out of this, we're going to still go back to our physical world. Now, the hybrid now kicks in. This kind of connects all aspects of business in every vertical. It's not like, "Hey, I'm targeting this industry." So there might be unique solutions in those industries, but now the world is virtualized. It's connected, it's a digital environment. These are huge concepts that I think has kind of been a lunatic fringe idea, but now it's brought mainstream. This is going to be a huge tailwind for you guys as well as developers and entrepreneurs and application software. This is going to be, we think, a big thing. What's your reaction to that? Based on your experience, what do you see happening? Do you agree with it? And do you have anything you might want to add to that? >> Maybe one kind of philosophical statement and then one more... I bruised my shins a lot in this world and maybe share some of the black and blue coloration. First from a philosophical standpoint, the greater the crisis, the more open-minded people become and the more creative people get. And so I'm really excited about the creativity that I'm seeing with all of the customers that I work with directly, plus our partners, Googlers. Everybody is rallying together to think about this world differently. So to your point, a shift in mindset, there are very few moments where you get this pronounced change and everyone is going through it all at the same time. So that creates an opportunity, a scenario where you're bold thinking new strategies, creativity. Bringing people in in new ways, collaborating in new ways and offer a lot of benefits. More practically speaking and from my experience, building technology for a couple decades, it has an interesting parallel to building tightly coupled, really large maybe monoliths versus microservices and the debate around, "Do we build small things "that can be reconfigured and built out by others "or built upon by others more easily? "Or do we create a golden path and a more understood development environment?" And I'm not here to answer the question of which one's better because that's still a raging debate. But I can tell you that the process of going through and taking a service or an application or a thing that we want to deliver to a customer, that one of our customers wants to deliver to their customer. And thinking about it so comprehensively that you're able to think about it in, what are its core functions? And then thinking methodically about how to enable those core functions. That's a real opportunity, and I think technology to your point is getting to the place where if you want to run across multiple clouds, this is the Anthos conversation were recently GA'ed. Global scale platform, multicloud platform, that's a pretty big moment in technology. And that opens up the aperture to think differently about architectures and that process of taking an application service and making it real. >> Well, I think you're right on the money. I think philosophically, it's a flashpoints opportunity. I think that's going to prove to be accelerating and to see people win faster and lose faster. You're going to to see that quickly happen. But to your point about the monolith versus service or decoupled based systems, I think we now live in a world where it's a systems view now. You can have a monolith combined with decoupled systems. That's distributed computing. I think this is the trend, it's a system. It's not one thing or the other. So I think the debate will continue just like VI versus Emacs (chuckles). We don't know, right? People are going to have the debate, but if you think about it as a system, the use case defines your architecture. That's the beautiful thing about the cloud. So great insight, I really appreciate it. And how's everything going over there at Google Cloud? You've got Meet that's available. How's your staff? What's it like inside the Googleplex and the Google Cloud team? Tell us what's going on over there. People still working, working remote? How's everyone doing? >> Well, as you can tell from my scenario here, my backdrop, yes, still part at work. And we take this as a huge responsibility. These moments as a huge responsibility because there are educators, loved ones, medical professionals, critical life services that run on services that Google provides. And so I can tell you we're humbled by the opportunity to provide the backbone and the platform and the people and the curiosity and the sincere desire to help. And I mentioned a couple of ways already just in this conversation where we've been able to leverage some of our investments technology to help form people that really gets at the root of who we are. So while we just like any other humans are going through a process of understanding our new reality, what really fires us up and what really charges us up is because this is a moment where what we do really well is very, very important for the world in every geo, in every vertical, in every use case, in every solution type. We're taking that responsibility very seriously. And at the same time, we're trying to make sure that all of our teams as well as all of the teams that we work with and our customers and partners are making it through the human moment, not just the technology moment. >> Well, congratulations and thanks for spending the time. Great insight, Will. Appreciate, Will Grannis, managing director, head of technology office of the CTO at Google Cloud. This certainly brings to the mainstream what we've been in the industry been into for a long time, which is DevOps, large scale, role of data and technology. Now we think it's going to be even more acute around societal benefits. And thank God we have all those services for the frontline workers. So thank you so much for all that effort and thanks for spending the time here in theCUBE Conversation. Appreciate it. >> Thanks for having me, John. >> Okay, I'm John Furrier here in Palo Alto studios for remote CUBE Conversation with Google Cloud, getting the update. Really looking at the future as it unfolds. We are going to see this moment in time as an opportunity to move to the next level, cloud-native and change not only the tech industry but society. I'm John Furrier, thanks for watching. (upbeat music)

>>It's the queue covering the virtual vertical Big Data Conference 2020. Brought to you by vertical. >>Hello, everybody. Welcome to the new Normal. You're watching the Cube, and it's remote coverage of the vertical big data event on digital or gone Virtual. My name is Dave Volante, and I'm here with Colin Mahoney, who's a senior vice president at Micro Focus and the GM of Vertical Colin. Well, strange times, but the show goes on. Great to see you again. >>Good to see you too, Dave. Yeah, strange times indeed. Obviously, Safety first of everyone that we made >>a >>decision to go Virtual. I think it was absolutely the right all made it in advance of how things have transpired, but we're making the best of it and appreciate your time here, going virtual with us. >>Well, Joe and we're super excited to be here. As you know, the Cube has been at every single BDC since its inception. It's a great event. You just you just presented the key note to your to your audience, You know, it was remote. You didn't have that that live vibe. And you have a lot of fans in the vertical community But could you feel the love? >>Yeah, you know, it's >>it's hard to >>feel the love virtually, but I'll tell you what. The silver lining in all this is the reach that we have for this event now is much broader than it would have been a Z you know, you know, we brought this event back. It's been a few years since we've done it. We're super excited to do it, obviously, you know, in Boston, where it was supposed to be on location, but there wouldn't have been as many people that could participate. So the silver lining in all of this is that I think there's there's a lot of love out there we're getting, too. I have a lot of participants who otherwise would not have been able to participate in this. Both live as well. It's a lot of these assets that we're gonna have available. So, um, you know, it's out there. We've got an amazing customers and of practitioners with vertical. We've got so many have been with us for a long time. We've of course, have a lot of new customers as well that we're welcoming, so it's exciting. >>Well, it's been a while. Since you've had the BDC event, a lot of transpired. You're now part of micro focus, but I know you and I know the vertical team you guys have have not stopped. You've kept the innovation going. We've been following the announcements, but but bridge the gap between the last time. You know, we had coverage of this event and where we are today. A lot has changed. >>Oh, yeah, a lot. A lot has changed. I mean, you know, it's it's the software industry, right? So nothing stays the same. We constantly have Teoh keep going. Probably the only thing that stays the same is the name Vertical. Um and, uh, you know, you're not spending 10 which is just a phenomenal released for us. So, you know, overall, the the organization continues to grow. The dedication and commitment to this great form of vertical continues every single release we do as you know, and this hasn't changed. It's always about performance and scale and adding a whole bunch of new capabilities on that front. But it's also about are our main road map and direction that we're going towards. And I think one of the things have been great about it is that we've stayed true that from day one we haven't tried to deviate too much and get into things that are barred to outside your box. But we've really done, I think, a great job of extending vertical into places where people need a lot of help. And with vertical 10 we know we're going to talk more about that. But we've done a lot of that. It's super exciting for our customers, and all of this, of course, is driven by our customers. But back to the big data conference. You know, everybody has been saying this for years. It was one of the best conferences we've been to just so really it's. It's developers giving tech talks, its customers giving talks. And we have more customers that wanted to give talks than we had slots to fill this year at the event, which is another benefit, a little bit of going virtually accommodate a little bit more about obviously still a tight schedule. But it really was an opportunity for our community to come together and talk about not just America, but how to deal with data, you know, we know the volumes are slowing down. We know the complexity isn't slowing down. The things that people want to do with AI and machine learning are moving forward in a rapid pace as well. There's a lot talk about and share, and that's really huge part of what we try to do with it. >>Well, let's get into some of that. Um, your customers are making bets. Micro focus is actually making a bet on one vertical. I wanna get your perspective on one of the waves that you're riding and where are you placing your bets? >>Yeah, No, it's great. So, you know, I think that one of the waves that we've been writing for a long time, obviously Vertical started out as a sequel platform for analytics as a sequel, database engine, relational engine. But we always knew that was just sort of takes that we wanted to do. People were going to trust us to put enormous amounts of data in our platform and what we owe everyone else's lots of analytics to take advantage of that data in the lots of tools and capabilities to shape that data to get into the right format. The operational reporting but also in this day and age for machine learning and from some pretty advanced regressions and other techniques of things. So a huge part of vertical 10 is just doubling down on that commitment to what we call in database machine learning and ai. Um, And to do that, you know, we know that we're not going to come up with the world's best algorithms. Nor is that our focus to do. Our advantage is we have this massively parallel platform to ingest store, manage and analyze the data. So we made some announcements about incorporating PM ML models into the product. We continue to deepen our python integration. Building off of a new open source project we started with uber has been a great customer and partner on This is one of our great talks here at the event. So you know, we're continuing to do that, and it turns out that when it comes to anything analytics machine learning, certainly so much of what you have to do is actually prepare the big shape the data get the data in the right format, apply the model, fit the model test a model operationalized model and is a great platform to do that. So that's a huge bet that were, um, continuing to ride on, taking advantage of and then some of the other things that we've just been seeing. You continue. I'll take object. Storage is an example on, I think Hadoop and what would you point through ultimately was a huge part of this, but there's just a massive disruption going on in the world around object storage. You know, we've made several bets on S three early we created America Yang mode, which separates computing story. And so for us that separation is not just about being able to take care of your take advantage of cloud economics as we do, or the economics of object storage. It's also about being able to truly isolate workloads and start to set the sort of platform to be able to do very autonomous things in the databases in the database could actually start self analysing without impacting many operational workloads, and so that continues with our partnership with pure storage. On premise, we just announced that we're supporting beyond Google Cloud now. In addition to Amazon, we supported on we've got a CFS now being supported by are you on mode. So we continue to ride on that mega trend as well. Just the clouds in general. Whether it's a public cloud, it's a private cloud on premise. Giving our customers the flexibility and choice to run wherever it makes sense for them is something that we are very committed to. From a flexibility standpoint. There's a lot of lock in products out there. There's a lot of cloud only products now more than ever. We're hearing our customers that they want that flexibility to be able to run anywhere. They want the ease of use and simplicity of native cloud experiences, which we're giving them as well. >>I want to stay in that architectural component for a minute. Talk about separating compute from storage is not just about economics. I mean apart Is that you, you know, green, really scale compute separate from storage as opposed to in chunks. It's more efficient, but you're saying there's other advantages to operational and workload. Specificity. Um, what is unique about vertical In this regard, however, many others separate compute from storage? What's different about vertical? >>Yeah, I think you know, there's a lot of differences about how we do it. It's one thing if you're a cloud native company, you do it and you have a shared catalog. That's key value store that all of your customers are using and are on the same one. Frankly, it's probably more of a security concern than anything. But it's another thing. When you give that capability to each customer on their own, they're fully protected. They're not sharing it with any other customers. And that's something that we hear a lot of insights from our customers. They want to be able to separate compute and storage. But they want to be able to do this in their own environment so that they know that in their data catalog there's no one else is. You share in that catalog, there's no single point of failure. So, um, that's one huge advantage that we have. And frankly, I think it just comes from being a company that's operating on premise and, uh, up in the cloud. I think another huge advantages for us is we don't know what object storage platform is gonna win, nor do we necessarily have. We designed the young vote so that it's an sdk. We started with us three, but it could be anything. It's DFS. That's three. Who knows what what object storage formats were going to be there and then finally, beyond just the object storage. We're really one of the only database companies that actually allows our customers to natively operate on data in very different formats, like parquet and or if you're familiar with those in the Hadoop community. So we not only embrace this kind of object storage disruption, but we really embrace the different data formats. And what that means is our customers that have data pipelines that you know, fully automated, putting this information in different places. They don't have to completely reload everything to take advantage of the Arctic analytics. We can go where the data is connected into it, and we offer them a lot of different ways to take advantage of those analytics. So there are a couple of unique differences with verdict, and again, I think are really advance. You know, in many ways, by not being a cloud native platform is that we're very good at operating in different environments with different formats that changing formats over time. And I don't think a lot of the other companies out there that I think many, particularly many of the SAS companies were scrambling. They even have challenges moving from saying Amazon environment to a Microsoft azure environment with their office because they've got so much unique Band Aid. Excuse me in the background. Just holding the system up that is native to any of those. >>Good. I'm gonna summarize. I'm hearing from you your Ferrari of databases that we've always known. Your your object store agnostic? Um, it's any. It's the cloud experience that you can bring on Prem to virtually any cloud. All the popular clouds hybrid. You know, aws, azure, now Google or on Prem and in a variety of different data formats. And that is, I think, you know, you need the combination of those I think is unique in the marketplace. Um, before we get into the news, I want to ask you about data silos and data silos. You mentioned H DFs where you and I met back in the early days of big data. You know, in some respects, you know, Hadoop help break down the silos with distributing the date and leave it in place, and in other respects, they created Data Lakes, which became silos. And so we have. Yet all these other sales people are trying to get to, Ah, digital transformation meeting, putting data at their core virtually obviously, and leave it in place. What's your thoughts on that in terms of data being a silo buster Buster, How does verdict of way there? >>Yeah, so And you're absolutely right, I think if even if you look at his due for all the new data that gets into the do. In many ways, it's created yet another large island of data that many organizations are struggling with because it's separate from their core traditional data warehouse. It's separate from some of the operational systems that they have, and so there might be a lot of data in there, but they're still struggling with How do I break it out of that large silo and or combine it again? I think some some of the things that verdict it doesn't part of the announcement just attend his migration tools to make it really easy. If you do want to move it from one platform to another inter vertical, but you don't have to move it, you can actually take advantage of a lot of the data where it resides with vertical, especially in the Hadoop brown with our external table storage with our building or compartment natively. So we're very pragmatic about how our customers go about this. Very few customers, Many of them tried it with Hadoop and realize that didn't work. But very few customers want a wholesale. Just say we're going to throw everything out. We're gonna get rid of our data warehouse. We're gonna hit the pause button and we're going to go from there. Just it's not possible to do that. So we've spent a lot of time investing in the product, really work with them to go where the data is and then seamlessly migrate. And when it makes sense to migrate, you mentioned the performance of America. Um, and you talked about it is the variety. It definitely is. And one other thing that we're really proud of this is that it actually is not a gas guzzler. Easy either One of the things that we're seeing, a lot of the other cloud databases pound for pound you get on the 10th the hardware vertical running up there. You get over 10 x performance. We're seeing that a lot, so it's Ah, it's not just about the performance, but it's about the efficiency as well. And I think that efficiency is really important when it comes to silos. Because there's there's just only so much horsepower out there. And it's easier for companies to play tricks and lots of servers environment when they start up for so many organizations and cloud and frankly, looking at the bills they're getting from these cloud workloads that are running. They really conscious of that. >>Yeah. The big, big energy companies love the gas guzzlers. A lot of a lot of cloud. Cute. But let's get into the news. Uh, 10 dot io you shared with your the audience in your keynote. One of the one of the highlights of data. What do we need to know? >>Yeah, so, you know, again doubling down on these mega trends, I'll start with Machine Learning and ai. We've done a lot of work to integrate so that you can take native PM ml models, bring them into vertical, run them massively parallel and help shape you know your data and prepare it. Do all the work that we know is required true machine learning. And for all the hype that there is around it, this is really you know, people want to do a lot of unsupervised machine learning, whether it's for healthcare fraud, detection, financial services. So we've doubled down on that. We now also support things like Tensorflow and, you know, as I mentioned, we're not going to come up with the best algorithms. Our job is really to ensure that those algorithms that people coming up with could be incorporated, that we can run them against massive data sets super efficiently. So that's that's number one number two on object storage. We continue to support Mawr object storage platforms for ya mode in the cloud we're expanding to Google G CPI, Google's cloud beyond just Amazon on premise or in the cloud. Now we're also supporting HD fs with beyond. Of course, we continue to have a great relationship with our partners, your storage on premise. Well, what we continue to invest in the eon mode, especially. I'm not gonna go through all the different things here, but it's not just sort of Hey, you support this and then you move on. There's so many different things that we learn about AP I calls and how to save our customers money and tricks on performance and things on the third areas. We definitely continue to build on that flexibility of deployment, which is related to young vote with. Some are described, but it's also about simplicity. It's also about some of the migration tools that we've announced to make it easy to go from one platform to another. We have a great road map on these abuse on security, on performance and scale. I mean, for us. Those are the things that we're working on every single release. We probably don't talk about them as much as we need to, but obviously they're critically important. And so we constantly look at every component in this product, you know, Version 10 is. It is a huge release for any product, especially an analytic database platform. And so there's We're just constantly revisiting you know, some of the code base and figuring out how we can do it in new and better ways. And that's a big part of 10 as well. >>I'm glad you brought up the machine Intelligence, the machine Learning and AI piece because we would agree that it is really one of the things we've noticed is that you know the new innovation cocktail. It's not being driven by Moore's law anymore. It's really a combination of you. You've collected all this data over the last 10 years through Hadoop and other data stores, object stores, etcetera. And now you're applying machine intelligence to that. And then you've got the cloud for scale. And of course, we talked about you bringing the cloud experience, whether it's on Prem or hybrid etcetera. The reason why I think this is important I wanted to get your take on this is because you do see a lot of emerging analytic databases. Cloud Native. Yes, they do suck up, you know, a lot of compute. Yeah, but they also had a lot of value. And I really wanted to understand how you guys play in that new trend, that sort of cloud database, high performance, bringing in machine learning and AI and ML tools and then driving, you know, turning data into insights and from what I'm hearing is you played directly in that and your differentiation is a lot of the things that we talk about including the ability to do that on from and in the cloud and across clouds. >>Yeah, I mean, I think that's a great point. We were a great cloud database. We run very well upon three major clouds, and you could argue some of the other plants as well in other parts of the world. Um, if you talk to our customers and we have hundreds of customers who are running vertical in the cloud, the experience is very good. I think it would always be better. We've invested a lot in taking advantage of the native cloud ecosystem, so that provisioning and managing vertical is seamless when you're in that environment will continue to do that. But vertical excuse me as a cloud platform is phenomenal. And, um, you know, there's a There's a lot of confusion out there, you know? I think there's a lot of marketing dollars spent that won't name many of the companies here. You know who they are, You know, the cloud Native Data Warehouse and it's true, you know their their software as a service. But if you talk to a lot of our customers, they're getting very good and very similar. experiences with Bernie comic. We stopped short of saying where software is a service because ultimately our customers have that control of flexibility there. They're putting verdict on whichever cloud they want to run it on, managing it. Stay tuned on that. I think you'll you'll hear from or more from us about, you know, that going going even further. But, um, you know, we do really well in the cloud, and I think he on so much of yang. And, you know, this has really been a sort of 2.5 years and never for us. But so much of eon is was designed around. The cloud was designed around Cloud Data Lakes s three, separation of compute and storage on. And if you look at the work that we're doing around container ization and a lot of these other elements, it just takes that to the next level. And, um, there's a lot of great work, so I think we're gonna get continue to get better at cloud. But I would argue that we're already and have been for some time very good at being a cloud analytic data platform. >>Well, since you open the door I got to ask you. So it's e. I hear you from a performance and architectural perspective, but you're also alluding two. I think something else. I don't know what you can share with us. You said stay tuned on that. But I think you're talking about Optionality, maybe different consumption models. That am I getting that right and you share >>your difficult in that right? And actually, I'm glad you wrote something. I think a huge part of Cloud is also has nothing to do with the technology. I think it's how you and seeing the product. Some companies want to rent the product and they want to rent it for a certain period of time. And so we allow our customers to do that. We have incredibly flexible models of how you provision and purchase our product, and I think that helps a lot. You know, I am opening the door Ah, a little bit. But look, we have customers that ask us that we're in offer them or, you know, we can offer them platforms, brawl in. We've had customers come to us and say please take over systems, um, and offer something as a distribution as I said, though I think one thing that we've been really good at is focusing on on what is our core and where we really offer offer value. But I can tell you that, um, we introduced something called the Verdict Advisor Tool this year. One of the things that the Advisor Tool does is it collects information from our customer environments on premise or the cloud, and we run through our own machine learning. We analyze the customer's environment and we make some recommendations automatically. And a lot of our customers have said to us, You know, it's funny. We've tried managed service, tried SAS off, and you guys blow them away in terms of your ability to help us, like automatically managed the verdict, environment and the system. Why don't you guys just take this product and converted into a SAS offering, so I won't go much further than that? But you can imagine that there's a lot of innovation and a lot of thoughts going into how we can do that. But there's no reason that we have to wait and do that today and being able to offer our customers on premise customers that same sort of experience from a managed capability is something that we spend a lot of time thinking about as well. So again, just back to the automation that ease of use, the going above and beyond. Its really excited to have an analytic platform because we can do so much automation off ourselves. And just like we're doing with Perfect Advisor Tool, we're leveraging our own Kool Aid or Champagne Dawn. However you want to say Teoh, in fact, tune up and solve, um, some optimization for our customers automatically, and I think you're going to see that continue. And I think that could work really well in a bunch of different wallets. >>Welcome. Just on a personal note, I've always enjoyed our conversations. I've learned a lot from you over the years. I'm bummed that we can't hang out in Boston, but hopefully soon, uh, this will blow over. I loved last summer when we got together. We had the verdict throwback. We had Stone Breaker, Palmer, Lynch and Mahoney. We did a great series, and that was a lot of fun. So it's really it's a pleasure. And thanks so much. Stay safe out there and, uh, we'll talk to you soon. >>Yeah, you too did stay safe. I really appreciate it up. Unity and, you know, this is what it's all about. It's Ah, it's a lot of fun. I know we're going to see each other in person soon, and it's the people in the community that really make this happen. So looking forward to that, but I really appreciate it. >>Alright. And thank you, everybody for watching. This is the Cube coverage of the verdict. Big data conference gone, virtual going digital. I'm Dave Volante. We'll be right back right after this short break. >>Yeah.