>>Hi, everyone. Welcome to ASML day. My name is Yasmin Joffey. I'm the director of systems engineering for ASML at HPE. Today. We're here and joined by my colleague, Don wake, who is a technical marketing engineer who will talk to us about the date and the life of an it administrator through the lens of ASML container platform. We'll be answering your questions real time. So if you have any questions, please feel free to put your questions in the chat, and we should have some time at the end for some live Q and a. Don wants to go ahead and kick us off. >>All right. Thanks a lot, Yasir. Yeah, my name is Don wake. I'm the tech marketing guy and welcome to asthma all day, day in the life of an it admin and happy St. Patrick's day. At the same time, I hope you're wearing green virtual pinch. If you're not wearing green, don't have to look that up if you don't know what I'm scouting. So we're just going to go through some quick things. Talk about discussion of modern business. It needs to kind of set the stage and go right into a demo. Um, so what is the need here that we're trying to fulfill with, uh, ASML container platform? It's, it's all rooted in analytics. Um, modern businesses are driven by data. Um, they are also application centric and the separation of applications and data has never been more important or, or the relationship between the two applications are very data hungry. >>These days, they consume data in all new ways. The applications themselves are, are virtualized, containerized, and distributed everywhere, and optimizing every decision and every application is, is become a huge problem to tackle for every enterprise. Um, so we look at, um, for example, data science, um, as one big use case here, um, and it's, it's really a team sport and I'm today wearing the hat of perhaps, you know, operations team, maybe software engineer, guy working on, you know, continuous integration, continuous development integration with source control, and I'm supporting these data scientists, data analysts. And I also have some resource control. I can decide whether or not the data science team gets a, a particular cluster of compute and storage so that they can do their work. So this is the solution that I've been given as an it admin, and that is the ASML container platform. >>And just walking through this real quick, at the top, I'm trying to, as wherever possible, not get involved in these guys' lives. So the data engineers, scientists, app developers, dev ops guys, they all have particular needs and they can access their resources and spin up clusters, or just do work with the Jupiter notebook or run spark or Kafka or any of the, you know, popular analytics platforms by just getting in points that we can provide to them web URLs and their self service. But in the backend, I can then as the it guy makes sure the Kubernetes clusters are up and running, I can assign particular access to particular roles. I can make sure the data's well protected and I can connect them. I can import clusters from public clouds. I can, uh, you know, put my like clusters on premise if I want to. >>And I can do all this through this centralized control plane. So today I'm just going to show you I'm supporting some data scientists. So one of our very own guys is actually doing a demo right now as well, called the a day in the life of the data scientist. And he's on the opposite side, not caring about all the stuff I'm doing in the backend and he's training models and registering the models and working with data, uh, inside his, you know, Jupiter notebook, running inferences, running postman scripts. And so I'm in the background here, making sure that he's got access to his cluster storage protected, make sure it's, um, you know, his training models are up, he's got service endpoints, connecting him to, um, you know, his source control and making sure he's got access to all that stuff. So he's got like a taxi ride prediction model that he's working on and he has a Jupiter notebook and models. So why don't we, um, get hands on and I'll just jump right over it. >>It was no container platform. So this is a web UI. So this is the interface into the container platform. Our centralized control plane, I'm using my active directory credentials to log in here. >>And >>When I log in, I've also been assigned a particular role, uh, with regard to how much of the resources I can access. Now, in my case, I'm a site admin you can see right up here in the upper right hand, I'm a site admin and I have access to lots and lots of resources. And the one I'm going to be focusing on today is a Kubernetes cluster. Um, so I have a cluster I can go in here and let's say, um, we have a new data scientists come on board one. I can give him his own resources so he can do whatever he wants, use some GPU's and not affect other clusters. Um, so we have all these other clusters already created here. You can see here that, um, this is a very busy, um, you know, production system. They've got some dev clusters over here. >>I see here, we have a production cluster. So he needs to produce something for data scientists to use. It has to be well protected and, and not be treated like a development resource. So under his production cluster, I decided to create a new Kubernetes cluster. And literally I just push a button, create Kubernetes cluster once I've done that. And I'll just show you some of the screens and this is a live environment. So this is, I could actually do it all my hosts are used up right now, but I wouldn't be able to go in here and give it a name, just select, um, some hosts to use as the primary master controller and some workers answer a few more questions. And then once that's done, I have now created a special, a whole nother Kubernetes cluster, um, that I could also create tenants from. >>So tenants are really Kubernetes. Uh namespaces so in addition to taking hosts and Kubernetes clusters, I can also go to that, uh, to existing clusters and now carve out a namespace from that. So I look at some of the clusters that were already created and, um, let's see, we've got, um, we've got this year is an example of a tenant that I could have created from that production cluster. And to do that here in the namespace, I just hit create and similar to how you create a cluster. You can now carve down from a given cluster and we'll say the production cluster and give it a name and a description. I can even tell it, I want this specific one to be an AI ML project, um, which really is our ML ops license. So at the end of the day, I can say, okay, I'm going to create an ML ops tenant from that cluster that I created. >>And so I've already created it here for this demo. And I'm going to just go into that Kubernetes namespace now that we also call it tenant. I mean, it's like, multitenancy the name essentially means we're carving out resources so that somebody can be isolated from another environment. First thing I typically do. Um, and at this point I could also give access to this tenant and only this tenant to my data scientist. So the first thing I typically do is I go in here and you can actually assign users right here. So right now it's just me. But if I want it to, for example, give this, um, to Terry, I could go in here and find another user and assign him from this lead, from this list, as long as he's got the proper credentials here. So you can see here, all these other users have active directory credentials, and they, uh, when we created the cluster itself, we also made sure it integrated with our active directory, so that only authorized users can get in there. >>Let's say the first thing I want to do is make sure when I do Jupiter notebook work, or when Terry does, I'm going to connect him up straight up to the get hub repository. So he gives me a link to get hub and says, Hey man, this is all of my cluster work that I've been doing. I've got my source control there. My scripts, my Python notebooks, my Jupiter notebooks. So when I create that, I simply give him, you know, he gives me his, I create a configuration. I say, okay, here's a, here's a get repo. Here's the link to it. I can use a token, here's his username. And I can now put in that token. So this is actually a private repo and using a token, you know, standard get interface. And then the cool thing after that, you can go in here and actually copy the authorization secret. >>And this gets into the Kubernetes world. Um, you know, if you want to make sure you have secure integration with things like your source control or perhaps your active directory, that's all maintained in secrets. So you can take that secret. And when I then create his notebook, I can put that secret right in here in this, uh, launch Yammel. And I say, Hey, connect this Jupiter notebook up with this secret so he can log in. And when I've launched this Jupiter notebook cluster, this is actually now, uh, within my, my, uh, Kubernetes tenant. It is now really a pod. And if I want to, I can go right into a terminal for that, uh, Kubernetes tenant and say, coop CTL, these are standard, you know, CNCF certified Kubernetes get pods. And when I do this, it'll tell me all of the active pods and within those positive containers that I'm running. >>So I'm running quite a few pods and containers here in this, uh, artificial intelligence machine learning, um, tenant. So that's kind of cool. Also, if I wanted to, I could go straight and I can download the config for Kubernetes, uh, control. Uh well, and then I can do something like this, where on my own system where I'm more comfortable, perhaps coop CTL get pods. So this is running on my laptop and I just had to do a coop CTL refresh and give the IP address and authorization, um, information in order to connect from my laptop to that end point. So from a CIC D perspective from, you know, an it admin guides, he usually wants to use tools right on his, uh, desktop. So here am I back in my web browser, I'm also here on the dashboard of this, uh, Kubernetes, um, tenant, and I can see how it's doing. >>It looks like it's kind of busy here. I can focus specifically on a pod if I want to. I happen to know this pod is my Jupiter notebook pod. So aren't, I show how, you know, I could enable my data scientists by just giving him the, uh, URL or what we call a notebook service end points or notebook end point. And just by clicking on this URL or copying it, copying, you know, it's a link, uh, and then emailing it to them and say, okay, here's your, uh, you know, here's your duper notebook. And I say, Hey, just log in with your credentials. I've already logged in. Um, and so then he's got his Jupiter notebook here and you can see that he's connected to his GitHub repo directly. He's got all of the files that he needs to run his data science project and within here, and this is really in the data science realm, data scientists realm. >>He can see that he can have access to centralized storage and he can copy the files from his GitHub repo to that centralized storage. And, you know, these, these commands, um, are kind of cool. They're a little Jupiter magic commands, and we've got some of our own that showed that attachment to the cluster. Um, but you can see here if you run these commands, they're actually looking at the shared project repository managed by the container platform. So, you know, just to show you that again, I'll go back to the container platform. And in fact, the data scientist, uh, could do the same thing. Attitude put a notebook back to platform. So here's this project repository. So this is other big point. So now putting on my storage admin hat, you know, I've got this shared, um, storage, um, volume that is managed for me by the ESMO data fabric. >>Um, in, in here, you can see that the data scientist, um, from his get repo is able to through Jupiter notebook directly, uh, copy his code. He was able to run as Jupiter notebook and create this XG boost, uh, model. So this file can then be registered in this AIML tenant. So he can go in here and register his model. So this is, you know, this is really where the data scientist guy can self-service kick off his notebooks, even get a deployment end point so that he can then inference his cluster. So here again, another URL that you could then take this and put it into like a postman rest URL and get answers. Um, but let's say he wants to, um, he's been doing all this work and I want to make sure that his, uh, data's protected, uh, how about creating a mirror. >>So if I want to create a mirror of that data, now I go back to this other, uh, and this is the, the, uh, data fabric embedded in a very special cluster called the Picasso cluster. And it's a version of the ASML data fabric that allows you to launch what was formerly called Matt bar as a Kubernetes cluster. And when you create this special cluster, every other cluster that you create is automatically, uh, gets things like that. Tenant storage. I showed you to create a shared workspace, and it's automatically managed by this, uh, data fabric. Uh, and you're even given an end point to go into the data fabric and then use all of the awesome features of ASML data fabric. So here I can just log in here. And now I'm at the, uh, data fabric, web UI to do some data protection and mirroring. >>So >>Let's go over here. Let's say I want to, uh, create a mirror of that tenant. So I forgot to note what the name of my tenant was. I'm going to go back to my tenant, the name of the volume that I'm playing with here. So in my AIML tenant, I'm going to go to my source, control my project repository that I want to protect. And I see that the ESMO data fabric has created 10 and 30 as a volume. So I'll go back to my, um, data fabric here, and I'm going to look for 10 and 30. And if I want to, I can go into tenant 30, >>Okay. >>Down here, I can look at the usage. I can look at all of the, you know, I've used very little of the, uh, allocated storage that I want, but let's, uh, you know what, let's go ahead and create a volume to mirror that one. So very simple web UI that has said create volume. I go in here and I say, I want to do a, a tenant 30 mirror. And I say, mirror the mirror volume. Um, I want to use my Picasso cluster. I want to use tenant 30. So now that's actually looking up in the data fabric, um, database there's 10 and 30 K. So it knows exactly which one I want to use. I can go in here and I can say, you know, ext HCP, tenant, 30 mirror, you know, I can give it whatever name I want and this path here. >>And that's a whole nother, uh, demo is this could be in Tokyo. This could be mirrored to all kinds of places all over the world, because this is truly a global name, split namespace, which is a huge differentiator for us in this case, I'm creating a local mirror and that can go down here and, um, I can add, uh, audit and encryptions. I can do, um, access control. I can, you know, change permissions, you know, so full service, um, interactivity here. And of course this is using the web UI, but there's also rest API interfaces as well. So that is pretty much the, the brunt of what I wanted to show you in the demo. Um, so we got hands on and I'm just going to throw this up real quick and then come back to Yasser. See if he's got any questions he has received from anybody watching, if you have any new questions. >>Yeah. We've got a few questions. Um, we can, uh, just take some time to go, hopefully answer a few. Um, so it, it does look like you can integrate or incorporate your existing get hub, uh, to be able to, um, extract, uh, shared code or repositories. Correct? >>Yeah. So we have that built in and can either be, um, get hub or bit bucket it's, you know, pretty standard interface. So just like you can go into any given, get hub and do a clone of a, of a repo, pull it into your local environment. We integrated that directly into the gooey so that you can, uh, say to your, um, AIML tenant, uh, to your Jupiter notebook. You know, here's, here's my GitHub repo. When you open up my notebook, just connect me straight up. So it saves you some, some steps there because Jupiter notebook is designed to be integrated with get hub. So we have get hub integrated in as well or bit bucket. Right. >>Um, another question around the file system, um, has the map, our file system that was carried over, been modified in any way to run on top of Kubernetes. >>So yeah, I would say that the map, our file system data fabric, what I showed here is the Kubernetes version of it. So it gives you a lot of the same features, but if you need, um, perhaps run it on bare metal, maybe you have performance, um, concerns, um, you know, you can, uh, you can also deploy it as a separate bare metal instance of data fabric, but this is just one way that you can, uh, use it integrated directly into Kubernetes depends really the needs of, of the, uh, the user and that a fabric has a lot of different capabilities, but this is, um, it has a lot of the core file system capabilities where you can do snapshots and mirrors, and it it's of course, striped across multiple, um, multiple disks and nodes. And, uh, you know, Matt BARR data fabric has been around for years. It's, uh, and it's designed for integration with these, uh, analytic type workloads. >>Great. Um, you showed us how you can manage, um, Kubernetes clusters through the ASML container platform you buy. Um, but the question is, can you, uh, control who accesses, which tenant, I guess, namespace that you created, um, and also can you restrict or, uh, inject resource limitations for each individual namespace through the UI? >>Oh yeah. So that's, that's a great question. Yes. To both of those. So, um, as a site admin, I had lots of authority to create clusters, to go into any cluster I wanted, but typically for like the data scientist example I used, I would give him, I would create a user for him. And there's a couple of ways you can create users. Um, and it's all role-based access control. So I could create a local user and have container platform authenticate him, or I can say integrate directly with, uh, active directory or LDAP, and then even including which groups he has access to. And then in the user interface for the site admin, I could say he gets access to this tenant and only this tenant. Um, another thing you asked about is his limitations. So when you create the tenant to prevent that noisy neighbor problem, you can, um, go in and create quotas. >>So I didn't show the process of actually creating a Quentin, a tenant, but integral to that, um, flow is okay, I've defined which cluster I want to use. I defined how much memory I want to use. So there's a quota right there. You could say, Hey, how many CPU's am I taking from this pool? And that's one of the cool things about the platform is that it abstracts all that away. You don't have to really know exactly which host, um, you know, you can create the cluster and select specific hosts, but once you've created the cluster, it's not just a big pool of resources. So you can say Bob, over here, um, he's only going to get 50 of the a hundred CPU's available and he's only going to get X amount of gigabytes of memory. And he's only going to get this much storage that he can consume. So you can then safely hand off something and know they're not going to take all the resources, especially the GPU's where those will be expensive. And you want to make sure that one person doesn't hog all the resources. And so that absolutely quotas are built in there. >>Fantastic. Well, we, I think we are out of time. Um, we have, uh, a list of other questions that we will absolutely reach out and, um, get all your questions answered, uh, for those of you who ask questions in the chat. Um, Don, thank you very much. Thanks everyone else for joining Don, will this recording be made available for those who couldn't make it today? >>I believe so. Honestly, I'm not sure what the process is, but, um, yeah, it's being recorded so they must've done that for a reason. >>Fantastic. Well, Don, thank you very much for your time and thank everyone else for joining. Thank you.

>> live from San Francisco, celebrating 10 years of high tech coverage. It's the Cube covering Veum, World 2019 brought to you by the M Wear and its ecosystem partners. >> Welcome back to San Francisco. Day three of our coverage here on the Cube Of'em world 2019. I'm John Wall's Glad to have you here aboard for our continuing coverage here Day Volonte is also joining me, as is the sartorially resplendent Eric Herzog, cm of and vice president. Global storage channels that IBM storage. Eric, good to see you and love the shirt. Very >> nice. Thank you. Well, always have a wine shirts when I'm on the Cube >> I love in a long time Cuba to we might say, I'm sure he's got the record. Yeah, might pay. Well, >> you and pattern, neck and neck. We'll go to >> the vault. And well, >> since Pat used to be my boss, you know, couch out a path. >> Well, okay. Let the little show what IBM think. Maybe. Well, that's OK. Let's just start off a big picture. We're in all this, you know. Hybrid. Multilingual. This discussion went on this week. Obviously, just your thoughts about general trends and where the business is going now supposed to wear? Maybe we're 23 years ago. Well, the >> good thing is for IBM storage, and we actually came to your partner and titty wiki Bond when our new general manager, Ed Walsh, joined. And we came and we saw Dave and John at the old office are at your offices, and we did a pitch about hybrid multi cloud. Remember that gave us some feedback of how to create a new slide. So we created a slide based on Dave's input, and we were doing that two and 1/2 years ago. So we're running around telling the storage analyst Storage Press about hybrid multi cloud based on IBM storage. How weaken transparently move data, things we do with backup, Of course. An archive. You've got about 450 small and medium cloud providers. Their backup is a service engine. Is our spectrum protect? And so we talked about that. So Dave helped us craft the slide to make it better, because he said, we left a couple things >> out that Eric >> owes you. There were a few other analysts I'm sure you talked to and got input, but but us really were the first toe to combine those things in your in your marketing presentations. But >> let's I'd love to get >> an update on the business. Yes, help people understand the IBM storage organization. You guys created the storage business, you know, years and years and years ago. It's a it's a you know you've got your core business, which is column arms dealers. But there's a lot of Regent IBM, the Cloud Division. You've got the service's division, but so help us understand this sort of organizational structure. So >> the IBM story division's part of IBM Systems, which includes both the mainframe products Z and the Power Server entities. So it's a server in storage division. Um, the Easy guys in particular, have a lots of software that they sell and not just mainframe. So they have a very, very large software business, as do we. As you know, from looking at people that do the numbers, We're the second largest storage software company in the world, and the bulk of that software's not running on IBM gear. So, for example, spectrum protect will back up anyone's array spectrum scale and our IBM Cloud Object storage are sold this software only software defined as the spectrum virtualized. You could basically create a J. Bader Jabo after your favorite distributor or reseller and create your honor. Rates are software, but the all of the infrastructure would actually not be ours, not branded by us. And you call us for tech support for the software side. But if you had a bad power supplier fan, you'd have to call, you know, the reseller distributor said this very robust storage software business. Obviously you make sure that was compatible with the other server elements of IBM systems. But the bulk of our storage is actually sitting connect to some server that doesn't have an IBM logo on it. So that's the bulk of our business connected to Intel servers of all types that used to include, of course, IBM Intel Server division, which was sold off to Lenovo. So we still have a very robust business in the array space that has nothing to do with working on a power machine are working on a Z machine, although we clearly worked very heavily with them and have a number of things going with him, including something that's coming very shortly in the middle of September on some new high end products that we're going to dio >> went 90 Sea Counts All this stuff. Do they >> count to give IBM credit for all the storage that lives inside of the IBM Cloud? Do you get you get credit for that or >> not get credit for that? So when they count our number, it's only the systems that we sell and the storage software that we sell. So if you look at if we were a standalone company, which would include support service made everything, some of which we don't get credit for, right, the support and service is a different entity at IBM that does that, UM, the service's group, the tech support that all goes to someone else. We don't have a new credit >> so hypothetical I don't I don't think this is the case, but let's say hypothetically, if pure storage sold an array into IBM Cloud, they would get credit for it. But if you're array and I'm sure this happens is inside of the IBM, you don't get credit for it. >> That's true interesting, so it's somewhat undercounts. Part of that is the >> way we internally count because we're selling it to ourselves. >> But that's it. >> It's not. It's more of an accounting thing, but it's different when we sell the anybody else. So, for example, we sell the hundreds of cloud providers who in theory compete with the IBM Cloud Division >> to you Get credit for that. You get credit for your own away. That's way work. But if we were standing >> on coming for, say, government, we were Zog in store and I bought the company away, we would be about a $6.3 billion standalone storage software company. That's what we would be if we were all in because support service manes. If we were our own company with our own right legal entity, just like net app or the other guys, we'd be Stanley would be in that, you know, low $6 billion range, counting everything all in. When we do report publicly, we only report our storage system because we don't report our storage software business. And as you notice a few times, our CFO has made comments. If we did count, the storage software visit would be ex, and he's publicly stated that price at least two times. Since I've been an idea when he talks about the software on, but legally we only talk about IBM storage systems. When he publicly state our numbers out onto Wall Street, that's all >> we publicly report. So, um, you're like, you're like a walking sheet of knowledge here, but I wonder if you could take the audience through the portfolio. Oh, it's vast. How should we think about it? And the names have changed. You talk about, you know, 250 a raise, whatever it is the old sand volume control. And now it's a spectrum virtualized, >> right? So take us to the portfolio. What's the current? It's free straight for. >> We have really three elements in the portfolio, all built around, if you will, solution plays. But the three real elements in the portfolio our storage arrays, storage systems, we have entry mid range and high end, just like our competitors do. We lead with all flash, but we still sell hybrid and obviously, for backup, an archive. We still sell all hard drive right for those workloads. So and we have filed blocking object just like most other guys do, Um, for an array, then we have a business built around software, and we have two key elements. Their software defined storage, and we saw that software completely stand alone. It happens, too, by the way, be embedded on the arrays. So, for example, Dave, you mentioned Spectrum virtualized that ship's on flash systems and store wise. But if you don't want our raise, we will sell you just spectrum virtualized alone for block spectrum scale for Big Big Data A. I file Workloads and IBM caught object storage, which could all of them could be bought on an array. But they also could be bought. Itjust Standalone component. Yes, there's a software so part of the advantage we feel that delivers. It's some of the people that have software defined storage, that air raid guys. It's not the same software, so for us, it's easier for us to support and service. It's easier for a stack developing have leading it. Features is not running two different pieces of software running, one that happens to have a software on Lee version or an array embedded version. So we've got that, and then the third is around modern data protection, and that's really it. So a modern data protection portfolio built around spectrum, protect and Protect Plus and some other elements. A software to find storage where we sell the software only, and then arrays. That's it. It's really three things and not show. Now they're all kinds components underneath the hood. But what we really do is we sell. We don't really run around and talk about off last race. We talk about hybrid multi cloud. Now all of our flash raise and a lot of our software defined storage will automatically tear data out, too. Hybrid multi cloud configurations. We just So we lead with that same thing. We have one around cyber resiliency. Now, the one thing that spans the whole portfolio of cyber resiliency way have cyber rebellion see and a raise. We have some softer on the mainframe called Safeguarded Copy that creates immutable copies and has extra extra security for the management rights. You've got management control, and if you have a malware ransomware attack, you couldn't recover to these known good copies. So that's a piece of software that we sell on the mainframe on >> how much growth have you seen in that in? Because he's never reveals if you've got it resonating pervasive, right, Pervasive. So >> we've got, for example, malware and ransomware detection. Also, Inspector protect. So it's taken example. So I'm going to steal from the Cube and I'm gonna ask Dave and for you, I want a billion dollars and Dave's gonna laugh at me because he used a spectrum protect. He's gonna start laughing. But if I'm the ransomware guy, what do I do? I go after your snapshots, your replicas and your backup data sets. First, I make sure I've got those under control. And then when I tell you I'm holding you for ransom, you can't go back to a known good copy. So Ransomware goes after backup snaps and replicas first. Then it goes half your primary storage. So what we do, inspector protect, for example, is we know that at Weeki Bond and the Cube, you back up every night from 11 32 1 30 takes two hours to back you up every night. It's noon. There's tons of activity in the backup data sets. What the heck is going on? We send it out to the admin, So the admin for the Cube wicky bond takes a look and says, No server failure. So you can't be doing a lot of recovery because of a bad server. No storage failures. What the heck is going on? It could be a possible mount where ransomware attack. So that type of technology, we encrypt it, rest on all of our store to raise. We have both tape and tape and cloud air gapping. I'm gonna ask you about that. We've got both types of air gapped >> used to hate tape. Now he loves my love, right? No, I used to hate it, But now I love it because it's like the last resort, just in case. And you do air gapping when you do a WR gapping with customers, Do you kind of rotate the You know, it's like, uh, you know, the Yasser Arafat used to move every night. You sleep in a different place, right? You gonna rotate the >> weird analogy? You do >> some stuff. There's a whole strategy >> of how we outlined how you would do a tape air gap, you a cloud air gap. Of course you're replicating or snapping out to the cloud anyway, so they can't get to that. So if you have a failure, we haven't known good copy, depending on what time that is, right. And then you just recover. Cover back to that and even something simple. We have data rest, encryption. Okay. A lot of people don't use it or won't use it on storage because it's often software based, and so is permanent. Well, in our D s platform on the mainframe, we can encrypt with no performance hit on our flash system products we can encrypt with no performance it on our high end store. Wise, we have four models on the two high end stores models we could encrypt with no performance penalty. So why would you not encrypt all your debt? When there's a performance penalty, you have to sort of pick and choose. My God, I got to encrypt this valuable financial data, but, boy, I really wish it wasn't so slow with us. There is no performance it when you encrypt. So we have encryption at rest, encryption at flight malware and ran somewhere detection. We've got worm, which is important, obviously, doesn't mean I can't steal from wicked Bond Cube, but I certainly can't go change all your account numbers for all your vendors. For sake. of argument, right? So and there's obviously heavily regulated industries that still require worm technology, right? Immutable on the fine, by the way, you could always if it's wormed, you could encrypt it if you want to write. Because Worm just means it's immutable. It doesn't. It's not a different data type. It's just a mutable version of that data. >> So the cyber resiliency is interesting, and it leads me to another question I have around just are, indeed so A lot of companies in this industry do a lot of D developing next generation products. I think, you know, look a t m c when you were there, you know, this >> was a lot of there. Wasn't a ton, >> of course, are a lot of patents and stuff like that. IBM does corps are a lot of research and research facilities, brainiac scientists, I want if you could talk about how the storage division takes advantage of that, either specifically, is it relates to cyber resiliency. But generally, >> yes, so as you know, IBM has got, I think it's like 12 12 or 15 research on Lee sites that that's all they do, and everyone there is, in fact, my office had to be. Akiyama didn't labs, and there's two labs actually hear. The AMA didn't research lab and the Silicon Valley lab, which is very close about five miles away. Beautiful. Almost everything. There is research. There's a few product management guys I happen, Navid desk there every once. Well, see a sales guy or two. But essentially, they're all Richard with PhDs from the leading inverse now at Al Madden and many sites, all the divisions have their own research teams there. There's a heavy storage contingent at Al Midan as an example. Same thing in Zurich. So, for example, we just announced last week, as you know, stuff that will work with Quantum on the tape side. So you don't have to worry about because one of things, obviously, that people complain about quantum computing, whether it's us or anyone else, the quantum computing you can crack basically any encryption. Well, guess what? IBM research has developed tape that can be encrypted. So if using quantum computer, whether it be IBM or someone else's when you go with quantum computing, you can have secured data because the quantum computer can't actually cracked the encryption that we just put into that new tape that was done at IBM Research. How >> far away are we from From Quantum, actually being ableto be deployed and even minor use cases. >> Well, we've got available right now in ibm dot com for Betas. So we've got several 1000 people who have been accidents in it. And entities, we've been talking publicly in the 3 to 7 year timeframe for quantum computer crap out. Should it? Well, no, because if you do the right sort of security, you don't but the power. So if you're envisioning one of my favorite movies, I robot, right where she's doing her talking and that's that would really be quantum in all honesty. But at the same time, you know, the key thing IBM is all about ethics and all about how we do things, whether it be what we do with our diversity programs and hiring. And IBM is always, you know, at the forefront of doing and promoting ethical this and ethical. Then >> you do a customer data is huge. >> Yeah, and what we do with the customer data sets right, we do. GDP are, for example, all over the world were not required by law to do it really Only in Europe we do it everywhere. And so if you're not, if you're in California, if you happen to be in Zimbabwe or you're in Brazil, you get the same protection of GDP are even though we're not legally required to do it. And why are we doing that? Because they're always concerned about customers data, and we know they're paranoid about it. We want to make sure people feel comfortable with IBM. We do. Quantum computing will end up in that same vein. >> But you know, I don't worry about you guys. I were about the guys on the other side of the fence, the ones that I worry about, the same thing Capabilities knew that was >> on, of course. And you know, he talked about it in his speech, and he talked about action on the Cube yesterday about some of his comments on the point, and he mentioned that was based on Blockchain. What he said was Blockchain is a great technology. They've got Blockchain is no. IBM is a big believer in Blockchain. We promoted all over the place and in fact we've done all kinds of different Blockchain things we just did. One announced it last week with Australia with the Australian. I think it is with their equivalent of Wall Street. We've done some stuff with Merrick, the big shipping container thing, and it's a big consortium. That's all legal stuff that was really talking about someone using it the wrong way. And he's very specific point out that Blockchain is a great technology if used ethically, and IBM is all about how we do it. So we make sure whether be quantum computing, Blockchain, et cetera, that everything we do at IBM is about helping the end users, making sure that we're making, for example, open source. As you know. Well, the number one provider of open source technology pre read had acquisition is IBM. We submit Maur into the open community. Renounce Now are we able to make some money off of that? Sure we are, but we do it for a reason, because IBM believes as day point out in this core research. Open computing is court research, and we just join the Open Foundation last week as well. So we're really big on making sure that what we do ourselves is Ethel now We try to make sure that what happens in the hands of people who buy our technology, which we can always track, is also done ethically. And we go out of our way to join the right industry. Associations work with governments, work with whatever we need to do to help make sure that technology could really be iRobot. Anyone who thinks that's not true. If you talk to your grandparent's goto, go to the moon. What are you talking about? >> What Star Trek. It's always >> come to me. Oh, yeah, >> I mean, if you're your iPhone is basically the old community. Transport is the only thing I wish I could have the transfer. Aziz. You know, >> David has the same frame us up. I'm afraid of flying, and I I felt like two million miles on United and David. He's laughs about flowers, so I'm waiting for the transport. I know that's why anymore there's a cone over here. Go stand. Or maybe maybe with a little bit of like, I'm selling my Bitcoin. No, hang on, just hold on. There's always a comeback. Not always. There could be a comeback because Derek always enjoy it as always. Thanks for the good seeing you. All right, Back with more Veum. World 2019 The Cube live in San Francisco.