>>Hi, this is Dave Volonte. We're winding down Day two of the Cubes coverage of Vim on 2022. We're here at the area in Las Vegas. Myself and Dave Nicholson had been going for two days. Everybody's excited about the VM on party tonight. It's It's always epic, and, uh, it's a great show in terms of its energy. Danny Allen is here. He's cto of in his back. He gave the keynote this morning. I say, Danny, you know, you look pretty good up there with two hours of sleep. I >>had three. >>Look, don't look that good, but your energy was very high. And I got to tell you the story you told was amazing. It was one of the best keynotes I've ever seen. Even even the technology pieces were outstanding. But you weaving in that story was incredible. I'm hoping that people will go back and and watch it. We probably don't have time to go into it, but wow. Um, can you give us the the one minute version of that >>long story? >>Sure. Yeah. I read a book back in 2013 about a ship that sank off Portsmouth, Maine, and I >>thought, I'm gonna go find that >>ship. And so it's a long, >>complicated process. Five >>years in the making. But we used data, and the data that found the ship was actually from 15 years earlier. >>And in 20 >>18, we found the bow of the ship. We found the stern of the ship, but what we were really trying to answer was torpedoed. Or did the boilers explode? Because >>the navy said the boilers exploded >>and two survivors said, No, it was torpedoed or there was a German U boat there. >>And so >>our goal was fine. The ship find the boiler. >>So in 20 >>19, Sorry, Uh, it was 2018. We found the bow and the stern. And then in 2019, we found both boilers perfectly intact. And in fact, the rear end of that torpedo wasn't much left >>of it, of course, but >>data found that wreck. And so it, um, it exonerated essentially any implication that somebody screwed >>up in >>the boiler system and the survivors or the Children of the survivors obviously appreciated >>that. I'm sure. Yes, Several >>outcomes to it. So the >>chief engineer was one >>of the 13 survivors, >>and he lived with the weight of this for 75 years. 49 sailors dead because of myself. But I had the opportunity of meeting some of the Children of the victims and also attending ceremonies. The families of those victims received purple hearts because they were killed due to enemy action. And then you actually knew how to do this. I wasn't aware you had experience finding Rex. You've >>discovered several of >>them prior to this one. But >>the interesting connection >>the reason why this keynote was so powerful as we're a >>team, it's a data conference. >>You connected that to data because you you went out and bought a How do you say this? Magnanimous magnetometer. Magnetometer, Magnetometer. I don't know what that >>is. And a side >>scan Sonar, Right? I got that right. That was >>easy. But >>then you know what this stuff is. And then you >>built the model >>tensorflow. You took all the data and you found anomalies. And then you went right to that spot. Found the >>wreck with 12 >>£1000 of dynamite, >>which made your heart >>beat. But >>then you found >>the boilers. That's incredible. And >>but the point was, >>this is data >>uh, let's see, >>a lot of years after, >>right? >>Yeah. Two sets of data were used. One was the original set of side scan sonar >>data by the historian >>who discovered there was a U boat in the area that was 15 years old. >>And then we used, of >>course, the wind and weather and wave pattern data that was 75 years old to figure out where the boiler should be because they knew that the ship had continued to float for eight minutes. And so you had to go back and determine the models of where should the boilers >>be if it exploded and the boilers >>dropped out and it floated along >>for eight minutes and then sank? Where was >>that data? >>It was was a scanned was an electronic was a paper. How did you get that data? So the original side scan sonar data was just hard >>drive >>data by the historian. >>I wish I could say he used them to >>back it up. But I don't know that I can say that. But he still had >>the data. 15 years later, the >>weather and >>wind and wave data, That was all public information, and we actually used that extensively. We find other wrecks. A lot of wrecks off Boston Sunken World War Two. So we were We were used to that model of tracking what happened. Wow. So, yes, imagine if that data weren't available >>and it >>probably shouldn't have been right by all rights. So now fast forward to 2022. We've got Let's talk about just a cloud >>data. I think you said a >>couple of 100 >>petabytes in the >>cloud 2019. 500 in, Uh, >>no. Yeah. In >>20 2200 and 42. Petabytes in 20 2500 Petabytes last year. And we've already done the same as 2020. So >>240 petabytes >>in Q one. I expect >>this year to move an exhibit of >>data into the public cloud. >>Okay, so you got all that data. Who knows what's in there, right? And if it's not protected, who's going to know in 50 60 7100 years? Right. So that was your tie in? Yes. To the to the importance of data protection, which was just really, really well done. Congratulations. Honestly, one of the best keynotes I've ever seen keynotes often really boring, But you did a great job again on two hours. Sleep. So much to unpack here. The other thing that really is. I mean, we can talk about the demos. We can talk about the announcements. Um, so? Well, yeah, Let's see. Salesforce. Uh, data protection is now public. I almost spilled the beans yesterday in the cube. Caught myself the version 12. Obviously, you guys gave a great demo showing the island >>cloud with I think it >>was just four minutes. It was super fast. Recovery in four minutes of data loss was so glad you didn't say zero minutes because that would have been a live demos which, Okay, which I appreciate and also think is crazy. So some really cool demos, Um, and some really cool features. So I have so much impact, but the the insights that you can provide through them it's VM one, uh, was actually something that I hadn't heard you talk about extensively in the past. That maybe I just missed it. But I wonder if you could talk about that layer and why it's critical differentiator for Wien. It's >>the hidden gem >>within the Wien portfolio because it knows about absolutely >>everything. >>And what determines the actions >>that we take is the >>context in which >>data is surviving. So in the context of security, which we are showing, we look for CPU utilisation, memory utilisation, data change rate. If you encrypt all of the data in a file server, it's going to blow up overnight. And so we're leveraging heuristics in their reporting. But even more than that, one of the things in Wien one people don't realise we have this concept of the intelligent diagnostics. It's machine learning, which we drive on our end and we push out as packages intervene one. There's up to 200 signatures, but it helps our customers find issues before they become issues. Okay, so I want to get into because I often time times, don't geek out with you. And don't take advantage of your your technical knowledge. And you've you've triggered a couple of things, >>especially when the >>analysts call you said it again today that >>modern >>data protection has meaning to you. We talked a little bit about this yesterday, but back in >>the days of >>virtualisation, you shunned agents >>and took a different >>approach because you were going for what was then >>modern. Then you >>went to bare metal cloud hybrid >>cloud containers. Super Cloud. Using the analyst meeting. You didn't use the table. Come on, say Super Cloud and then we'll talk about the edge. So I would like to know specifically if we can go back to Virtualised >>because I didn't know >>this exactly how you guys >>defined modern >>back then >>and then. Let's take that to modern today. >>So what do you >>do back then? And then we'll get into cloud and sure, So if you go back to and being started, everyone who's using agents, you'd instal something in the operating system. It would take 10% 15% of your CPU because it was collecting all the data and sending it outside of the machine when we went through a virtual environment. If you put an agent inside that machine, what happens is you would have 100 operating systems all on the same >>server, consuming >>resources from that hyper visor. And so he said, there's a better way of capturing the data instead of capturing the data inside the operating system. And by the way, managing thousands of agents is no fun. So What we did is we captured a snapshot of the image at the hyper visor level. And then over time, we just leverage changed block >>tracking from the hyper >>visor to determine what >>had changed. And so that was modern. Because no more >>managing agents >>there was no impact >>on the operating system, >>and it was a far more >>efficient way to store >>data. You leverage CBT through the A P. Is that correct? Yeah. We used the VCR API >>for data protection. >>Okay, so I said this to Michael earlier. Fast forward to today. Your your your data protection competitors aren't as fat, dumb and happy as they used to be, so they can do things in containers, containers. And we talked about that. So now let's talk about Cloud. What's different about cloud data protection? What defines modern data protection? And where are the innovations that you're providing? >>Let me do one step in >>between those because one of the things that happened between hypervisors and Cloud was >>offline. The capture of the data >>to the storage system because >>even better than doing it >>at the hyper visor clusters >>do it on the storage >>array because that can capture the >>data instantly. Right? So as we go to the cloud, we want to do the same thing. Except we don't have access to either the hyper visor or the storage system. But what they do provide is an API. So we can use the API to capture all of the blocks, all of the data, all of the changes on that particular operating system. Now, here's where we've kind of gone full circle on a hyper >>visor. You can use the V >>sphere agent to reach into the operating system to do >>things like application consistency. What we've done modern data protection is create specific cloud agents that say Forget >>about the block changes. Make sure that I have application consistency inside that cloud operating >>system. Even though you don't have access to the hyper visor of the storage, >>you're still getting the >>operating system consistency >>while getting the really >>fast capture of data. So that gets into you talking on stage about how synapse don't equal data protection. I think you just explained it, but explain why, but let me highlight something that VM does that is important. We manage both snapshots and back up because if you can recover from your storage array >>snapshot. That is the best >>possible thing to recover from right, But we don't. So we manage both the snapshots and we converted >>into the VM portable >>data format. And here's where the super cloud comes into play because if I can convert it into the VM portable data format, I can move >>that OS >>anywhere. I can move it from >>physical to virtual to cloud >>to another cloud back to virtual. I can put it back on physical if I want to. It actually abstracts >>the cloud >>layer. There are things >>that we do when we go >>between clouds. Some use bio, >>some use, um, fee. >>But we have the data in backup format, not snapshot format. That's theirs. But we have been in backup format that we can move >>around and abstract >>workloads across. All of the infrastructure in your >>catalogue is control >>of that. Is that Is >>that right? That is about >>that 100%. And you know what's interesting about our catalogue? Dave. The catalogue is inside the backup, and so historically, one of the problems with backup is that you had a separate catalogue and if it ever got corrupted. All of your >>data is meaningless >>because the catalogue is inside >>the backup >>for that unique VM or that unique instance, you can move it anywhere and power it on. That's why people said were >>so reliable. As long >>as you have the backup file, you can delete our >>software. You can >>still get the data back, so I love this fast paced so that >>enables >>what I call Super Cloud we now call Super Cloud >>because now >>take that to the edge. >>If I want to go to the edge, I presume you can extend that. And I also presume the containers play a role there. Yes, so here's what's interesting about the edge to things on the edge. You don't want to have any state if you can help it, >>and so >>containers help with that. You can have stateless environment, some >>persistent data storage, >>but we not only >>provide the portability >>in operating systems. We also do this for containers, >>and that's >>true if you go to the cloud and you're using SE CKs >>with relational >>database service is already >>asked for the persistent data. >>Later, we can pick that up and move it to G K E or move it to open shift >>on premises. And >>so that's why I call this the super cloud. We have all of this data. Actually, I think you termed the term super thank you for I'm looking for confirmation from a technologist that it's technically feasible. It >>is technically feasible, >>and you can do it today and that's a I think it's a winning strategy. Personally, Will there be >>such a thing as edge Native? You know, there's cloud native. Will there be edge native new architectures, new ways of doing things, new workloads use cases? We talk about hardware, new hardware, architectures, arm based stuff that are going to change everything to edge Native Yes and no. There's going to be small tweaks that make it better for the edge. You're gonna see a lot of iron at the edge, obviously for power consumption purposes, and you're also going to see different constructs for networking. We're not going to use the traditional networking, probably a lot more software to find stuff. Same thing on the storage. They're going to try and >>minimise the persistent >>storage to the smallest footprint possible. But ultimately I think we're gonna see containers >>will lead >>the edge. We're seeing this now. We have a I probably can't name them, but we have a large retail organisation that is running containers in every single store with a small, persistent footprint of the point of sale and local data, but that what >>is running the actual >>system is containers, and it's completely ephemeral. So we were >>at Red Hat, I was saying >>earlier last week, and I'd say half 40 50% of the conversation was edge open shift, obviously >>playing a big role there. I >>know doing work with Rancher and Town Zoo. And so there's a lot of options there. >>But obviously, open shift has >>strong momentum in the >>marketplace. >>I've been dominating. You want to chime in? No, I'm just No, >>I yeah, I know. Sometimes >>I'll sit here like a sponge, which isn't my job absorbing stuff. I'm just fascinated by the whole concept of of a >>of a portable format for data that encapsulates virtual machines and or instances that can live in the containerised world. And once you once you create that common denominator, that's really that's >>That's the secret sauce >>for what you're talking about is a super club and what's been fascinating to watch because I've been paying attention since the beginning. You go from simply V. M. F s and here it is. And by the way, the pitch to E. M. C. About buying VM ware. It was all about reducing servers to files that can be stored on storage arrays. All of a sudden, the light bulbs went off. We can store those things, and it just began. It became it became a marriage afterwards. But to watch that progression that you guys have gone from from that fundamental to all of the other areas where now you've created this common denominator layer has has been amazing. So my question is, What's the singer? What doesn't work? Where the holes. You don't want to look at it from a from a glass half empty perspective. What's the next opportunity? We've talked about edge, but what are the things that you need to fill in to make this truly ubiquitous? Well, there's a lot of services out there that we're not protecting. To be fair, right, we do. Microsoft 3 65. We announced sales for us, but there's a dozen other paths services that >>people are moving data >>into. And until >>we had data protection >>for the assassin path services, you know >>you have to figure out how >>to protect them. Now here's the kicker about >>those services. >>Most of them have the >>ability to dump date >>out. The trick is, do they have the A >>P? I is needed to put data >>back into it right, >>which is which is a >>gap. As an industry, we need to address this. I actually think we need a common >>framework for >>how to manage the >>export of data, but also the import of data not at a at a system level, but at an atomic level of the elements within those applications. >>So there are gaps >>there at the industry, but we'll fill them >>if you look on the >>infrastructure side. We've done a lot with containers and kubernetes. I think there's a next wave around server list. There's still servers and these micro services, but we're making things smaller and smaller and smaller, and there's going to be an essential need to protect those services as well. So modern data protection is something that's going to we're gonna need modern data protection five years from now, the modern will just be different. Do you ever see the day, Danny, where governance becomes an >>adjacency opportunity for >>you guys? It's clearly an opportunity even now if you look, we spent a lot of time talking about security and what you find is when organisations go, for example, of ransomware insurance or for compliance, they need to be able to prove that they have certifications or they have security or they have governance. We just saw transatlantic privacy >>packed only >>to be able to prove what type of data they're collecting. Where are they storing it? Where are they allowed to recovered? And yes, those are very much adjacency is for our customers. They're trying to manage that data. >>So given that I mean, >>am I correct that architecturally you are, are you location agnostic? Right. We are a location agnostic, and you can actually tag data to allowable location. So the big trend that I think is happening is going to happen in in this >>this this decade. >>I think we're >>scratching the surface. Is this idea >>that, you know, leave data where it is, >>whether it's an S three >>bucket, it could be in an Oracle >>database. It could be in a snowflake database. It can be a data lake that's, you know, data, >>bricks or whatever, >>and it stays where >>it is. And it's just a note on the on the call of the data >>mesh. Not my term. Jim >>Octagon coined that term. The >>problem with that, and it puts data in the hands of closer to the domain experts. The problem with that >>scenario >>is you need self service infrastructure, which really doesn't exist today anyway. But it's coming, and the big problem is Federated >>computational >>governance. How do I automate that governance so that the people who should have access to that it can have access to that data? That, to me, seems to be an adjacency. It doesn't exist except in >>a proprietary >>platform. Today. There needs to be a horizontal >>layer >>that is more open than anybody >>can use. And I >>would think that's a perfect opportunity for you guys. Just strategically it is. There's no question, and I would argue, Dave, that it's actually >>valuable to take snapshots and to keep the data out at the edge wherever it happens to be collected. But then Federated centrally. It's why I get so excited by an exhibit of data this year going into the cloud, because then you're centralising the aggregation, and that's where you're really going to drive the insights. You're not gonna be writing tensorflow and machine learning and things on premises unless you have a lot of money and a lot of GPS and a lot of capacity. That's the type of thing that is actually better suited for the cloud. And, I would argue, better suited for not your organisation. You're gonna want to delegate that to a third party who has expertise in privacy, data analysis or security forensics or whatever it is that you're trying to do with the data. But you're gonna today when you think about AI. We talked about A. I haven't had a tonne of talk about AI some >>appropriate >>amount. Most of the >>AI today correct me if you think >>this is not true is modelling that's done in the cloud. It's dominant. >>Don't >>you think that's gonna flip when edge >>really starts to take >>off where it's it's more real time >>influencing >>at the edge in new use cases at the edge now how much of that data >>is going to be >>persisted is a >>point of discussion. But what >>are your thoughts on that? I completely agree. So my expectation of the way >>that this will work is that >>the true machine learning will happen in the centralised location, and what it will do is similar to someone will push out to the edge the signatures that drive the inferences. So my example of this is always the Tesla driving down the road. >>There's no way that that >>car should be figuring it sending up to the cloud. Is that a stop sign? Is it not? It can't. It has to be able to figure out what the stop sign is before it gets to it, so we'll do the influencing at the edge. But when it doesn't know what to do with the data, then it should send it to the court to determine, to learn about it and send signatures back out, not just to that edge location, but all the edge locations within the within the ecosystem. So I get what you're saying. They might >>send data back >>when there's an anomaly, >>or I always use the example of a deer running in front of the car. David Floyd gave me that one. That's when I want to. I do want to send the data back to the cloud because Tesla doesn't persist. A tonne of data, I presume, right, right less than 5% of it. You know, I want to. Usually I'm here to dive into the weeds. I want kind of uplevel this >>to sort of the >>larger picture. From an I T perspective. >>There's been a lot of consolidation going on if you divide the >>world into vendors >>and customers. On the customer side, there are only if there's a finite number of seats at the table for truly strategic partners. Those get gobbled up often by hyper >>scale cloud >>providers. The challenge there, and I'm part of a CEO accreditation programme. So this >>is aimed at my students who >>are CEOs and CIOs. The challenge is that a lot of CEOs and CIOs on the customer side don't exhaustively drag out of their vendor partners like a theme everything that Saveem >>can do for >>them. Maybe they're leveraging a point >>solution, >>but I guarantee you they don't all know that you've got cast in in the portfolio. Not every one of them does yet, let alone this idea of a super >>cloud and and and >>how much of a strategic role you can play. So I don't know if it's a blanket admonition to folks out there, but you have got to leverage the people who are building the solutions that are going to help you solve problems in the business. And I guess, as in the form of >>a question, >>uh, do you Do you see that as a challenge? Now those the limited number of seats at >>the Table for >>Strategic Partners >>Challenge and >>Opportunity. If you look at the types of partners that we've partnered with storage partners because they own the storage of the data, at the end of the day, we actually just manage it. We don't actually store it the cloud partners. So I see that as the opportunity and my belief is I thought that the storage doesn't matter, >>but I think the >>organisation that can centralise and manage that data is the one that can rule the world, and so >>clearly I'm a team. I think we can do amazing things, but we do have key >>strategic partners hp >>E Amazon. You heard >>them on stage yesterday. >>18 different >>integrations with AWS. So we have very strategic partners. Azure. I go out there all the time. >>So there >>you don't need to be >>in the room at the table because your partners are >>and they have a relationship with the customer as well. Fair enough. But the key to this it's not just technology. It is these relationships and what is possible between our organisations. So I'm sorry to be >>so dense on this, but when you talk about >>centralising that data you're talking about physically centralising it or can actually live across clouds, >>for instance. But you've got >>visibility and your catalogues >>have visibility on >>all that. Is that what you mean by centralised obliterated? We have understanding of all the places that lives, and we can do things with >>it. We can move it from one >>cloud to another. We can take, you know, everyone talks about data warehouses. >>They're actually pretty expensive. >>You got to take data and stream it into this thing, and there's a massive computing power. On the other hand, we're >>not like that. You've storage on there. We can ephemeral e. Spin up a database when you need it for five minutes and then destroy it. We can spin up an image when you need it and then destroy it. And so on your perspective of locations. So irrespective of >>location, it doesn't >>have to be in a central place, and that's been a challenge. You extract, >>transform and load, >>and moving the data to the central >>location has been a problem. We >>have awareness of >>all the data everywhere, >>and then we can make >>decisions as to what you >>do based >>on where it is and >>what it is. And that's a metadata >>innovation. I guess that >>comes back to the catalogue, >>right? Is that correct? >>You have data >>about the data that informs you as to where it is and how to get to it. And yes, so metadata within the data that allows you to recover it and then data across the federation of all that to determine where it is. And machine intelligence plays a role in all that, not yet not yet in that space. Now. I do think there's opportunity in the future to be able to distribute storage across many different locations and that's a whole conversation in itself. But but our machine learning is more just on helping our customers address the problems in their infrastructures rather than determining right now where that data should be. >>These guys they want me to break, But I'm >>refusing. So your >>Hadoop back >>in their rooms via, um that's >>well, >>that scale. A lot of customers. I talked to Renee Dupuis. Hey, we we got there >>was heavy lift. You >>know, we're looking at new >>ways. New >>approaches, uh, going. And of course, it's all in the cloud >>anyway. But what's >>that look like? That future look like we haven't reached bottle and X ray yet on our on our Hadoop clusters, and we do continuously examine >>them for anomalies that might happen. >>Not saying we won't run into a >>bottle like we always do at some >>point, But we haven't yet >>awesome. We've covered a lot of We've certainly covered extensively the research that you did on cyber >>security and ransomware. Um, you're kind of your vision for modern >>data protection. I think we hit on that pretty well casting, you know, we talked to Michael about that, and then, you know, the future product releases the Salesforce data protection. You guys, I think you're the first there. I think you were threatened at first from Microsoft. 3 65. No, there are other vendors in the in the salesforce space. But what I tell people we weren't the first to do data capture at the hyper >>visor level. There's two other >>vendors I won't tell you they were No one remembers them. Microsoft 3 65. We weren't the first one to for that, but we're now >>the largest. So >>there are other vendors in the salesforce space. But we're looking at We're going to be aggressive. Danielle, Thanks >>so much for coming to Cuba and letting us pick your brain like that Really great job today. And congratulations on >>being back >>in semi normal. Thank you for having me. I love being on all right. And thank you for watching. Keep it right there. More coverage. Day volonte for Dave >>Nicholson, By >>the way, check out silicon angle dot com for all the written coverage. All the news >>The cube dot >>net is where all these videos We'll we'll live. Check out wiki bond dot com I published every week. I think I'm gonna dig into the cybersecurity >>research that you guys did this week. If I can >>get a hands my hands on those charts which Dave Russell promised >>me, we'll be right back >>right after this short break. Mm.