(upbeat music) >> Welcome back to San Francisco, "theCUBE" is live, our day two coverage of VMware Explore 2022 continues. Lisa Martin with Dave Nicholson. Dave and I are pleased to welcome Jason Collier, principal member of technical staff at AMD to the program. Jason, it's great to have you. >> Thank you, it's great to be here. >> So what's going on at AMD? I hear you have some juicy stuff to talk about. >> Oh, we've got a ton of juicy stuff to talk about. Clearly the Project Monterey announcement was big for us, so we've got that to talk about. Another thing that I really wanted to talk about was a tool that we created and we call it, it's the VMware Architecture Migration Tool, call it VAMT for short. It's a tool that we created and we worked together with VMware and some of their professional services crew to actually develop this tool. And it is also an open source based tool. And really the primary purpose is to easily enable you to move from one CPU architecture to another CPU architecture, and do that in a cold migration fashion. >> So we're probably not talking about CPUs from Tandy, Radio Shack systems, likely this would be what we might refer to as other X86 systems. >> Other X86 systems is a good way to refer to it. >> So it's interesting timing for the development and the release of a tool like this, because in this sort of X86 universe, there are players who have been delayed in terms of delivering their next gen stuff. My understanding is AMD has been public with the idea that they're on track for by the end of the year, Genoa, next gen architecture. So can you imagine a situation where someone has an existing set of infrastructure and they're like, hey, you know what I want to get on board, the AMD train, is this something they can use from the VMware environment? >> Absolutely, and when you think about- >> Tell us exactly what that would look like, walk us through 100 servers, VMware, 1000 VMs, just to make the math easy. What do you do? How does it work? >> So one, there's several things that the tool can do, we actually went through, the design process was quite extensive on this. And we went through all of the planning phases that you need to go through to do these VM migrations. Now this has to be a cold migration, it's not a live migration. You can't do that between the CPU architectures. But what we do is you create a list of all of the virtual machines that you want to migrate. So we take this CSV file, we import this CSV file, and we ask for things like, okay, what's the name? Where do you want to migrate it to? So from one cluster to another, what do you want to migrate it to? What are the networks that you want to move it to? And then the storage platform. So we can move storage, it could either be shared storage, or we could move say from VSAN to VSAN, however you want to set it up. So it will do those storage migrations as well. And then what happens is it's actually going to go through, it's going to shut down the VM, it's going to take a snapshot, it is going to then basically move the compute and/or storage resources over. And once it does that, it's going to power 'em back up. And it's going to check, we've got some validation tools, where it's going to make sure VM Tools comes back up where everything is copacetic, it didn't blue screen or anything like that. And once it comes back up, then everything's good, it moves onto the next one. Now a couple of things that we've got feature wise, we built into it. You can parallelize these tasks. So you can say, how many of these machines do you want to do at any given time? So it could be, say 10 machines, 50 machines, 100 machines at a time, that you want to go through and do this move. Now, if it did blue screen, it will actually roll it back to that snapshot on the origin cluster. So that there is some protection on that. A couple other things that are actually in there are things like audit tracking. So we do full audit logging on this stuff, we take a snapshot, there's basically kind of an audit trail of what happens. There's also full logging, SYS logging, and then also we'll do email reporting. So you can say, run this and then shoot me a report when this is over. Now, one other cool thing is you can also actually define a change window. So I don't want to do this in the middle of the afternoon on a Tuesday. So I want to do this later at night, over the weekend, you can actually just queue this up, set it, schedule it, it'll run. You can also define how long you want that change window to be. And what it'll do, it'll do as many as it can, then it'll effectively stop, finish up, clean up the tasks and then send you a report on what all was successfully moved. >> Okay, I'm going to go down the rabbit hole a little bit on this, 'cause I think it's important. And if I say something incorrect, you correct me. >> No problem. >> In terms of my technical understanding. >> I got you. >> So you've got a VM, essentially a virtual machine typically will consist of an entire operating system within that virtual machine. So there's a construct that containerizes, if you will, the operating system, what is the difference, where is the difference in the instruction set? Where does it lie? Is it in the OS' interaction with the CPU or is it between the construct that is the sort of wrapper around the VM that is the difference? >> It's really primarily the OS, right? And we've not really had too many issues doing this and most of the time, what is going to happen, that OS is going to boot up, it's going to recognize the architecture that it's on, it's going to see the underlying architecture, and boot up. All the major operating systems that we test worked fine. I mean, typically they're going to work on all the X86 platforms. But there might be instruction sets that are kind of enabled in one architecture that may not be in another architecture. >> And you're looking for that during this process. >> Well usually the OS itself is going to kind of detect that. So if it pops up, the one thing that is kind of a caution that you need to look for. If you've got an application that's explicitly using an instruction set that's on one CPU vendor and not the other CPU vendor. That's the one thing where you're probably going to see some application differences. That said, it'll probably be compatible, but you may not get that instruction set advantage in it. >> But this tool remediates against that. >> Yeah, and what we do, we're actually using VM Tools itself to go through and validate a lot of those components. So we'll look and make sure VM Tools is enabled in the first place, on the source system. And then when it gets to the destination system, we also look at VM Tools to see what is and what is not enabled. >> Okay, I'm going to put you on the spot here. What's the zinger, where doesn't it work? You already said cold, we understand, you can schedule for cold migrations, that's not a zinger. What's the zinger, where doesn't it work? >> It doesn't work like, live migrations just don't work. >> No live, okay, okay, no live. What about something else? What's the oh, you've got that version, you've got that version of X86 architecture, it-won't work, anything? >> A majority of those cases work, where it would fail, where it's going to kick back and say, hey, VM Tools is not installed. So where you would see this is if you're running a virtual appliance from some vendor, like insert vendor here that say, got a firewall, or got something like that, and they don't have VM Tools enabled. It's going to fail it out of the gate, and say, hey, VM Tools is not on this, you might want to manually do it. >> But you can figure out how to fix that? >> You can figure out how to do that. You can also, and there's a flag in there, so in kind of the options that you give it, you say, ignore VM Tools, don't care, move it anyway. So if you've got less, some VMs that are in there, but they're not a priority VM, then it's going to migrate just fine. >> Got It. >> Can you elaborate a little bit on the joint development work that AMD and VMware are doing together and the value in it for customers? >> Yeah, so it's one of those things we worked with VMware to basically produce this open source tool. So we did a lot of the core component and design and we actually engaged VMware Professional Services. And a big shout out to Austin Browder. He helped us a ton in this project specifically. And we basically worked, we created this, kind of co-designed, what it was going to look like. And then jointly worked together on the coding, of pulling this thing together. And then after that, and this is actually posted up on VMware's public repos now in GitHub. So you can go to GitHub, you can go to the VMware samples code, and you can download this thing that we've created. And it's really built to help ease migrations from one architecture to another. So if you're looking for a big data center move and you got a bunch of VMs to move. I mean, even if it's same architecture to same architecture, it's definitely going to ease the pain of going through and doing a migration of, it's one thing when you're doing 10 machines, but when you're doing 10,000 virtual machines, that's a different story. It gets to be quite operationally inefficient. >> I lose track after three. >> Yeah. >> So I'm good for three, not four. >> I was going to ask you what your target market segment is here. Expand on that a little bit and talk to me about who you're working with and those organizations. >> So really this is targeted toward organizations that have large deployments in enterprise, but also I think this is a big play with channel partners as well. So folks out there in the channel that are doing these migrations and they do a lot of these, when you're thinking about the small and mid-size organizations, it's a great fit for that. Especially if they're kind of doing that upgrade, the lift and shift upgrade, from here's where you've been five to seven years on an architecture and you want to move to a new architecture. This is really going to help. And this is not a point and click GUI kind of thing. It's command line driven, it's using PowerShell, we're using PowerCLI to do the majority of this work. And for channel partners, this is an excellent opportunity to put the value and the value add and VAR, And there's a lot of opportunity for, I think, channel partners to really go and take this. And once again, being open source. We expect this to be extensible, we want the community to contribute and put back into this to basically help grow it and make it a more useful tool for doing these cold migrations between CPU architectures. >> Have you seen any in the last couple of years of dynamics, obviously across the world, any industries in particular that are really leading edge for what you guys are doing? >> Yeah, that's really, really interesting. I mean, we've seen it, it's honestly been a very horizontal problem, pretty much across all vertical markets. I mean, we've seen it in financial services, we've seen it in, honestly, pretty much across the board. Manufacturing, financial services, healthcare, we have seen kind of a strong interest in that. And then also we we've actually taken this and presented this to some of our channel partners as well. And there's been a lot of interest in it. I think we presented it to about 30 different channel partners, a couple of weeks back about this. And I got contact from 30 different channel partners that said they're interested in basically helping us work on it. >> Tagging on to Lisa's question, do you have visibility into the AMD thought process around the timing of your next gen release versus others that are competitors in the marketplace? How you might leverage that in terms of programs where partners are going out and saying, hey, perfect time, you need a refresh, perfect time to look at AMD, if you haven't looked at them recently. Do you have any insight into that in what's going on? I know you're focused on this area. But what are your thoughts on, well, what's the buzz? What's the buzz inside AMD on that? >> Well, when you look overall, if you look at the Gartner Hype Cycle, when VMware was being broadly adopted, when VMware was being broadly adopted, I'm going to be blunt, and I'm going to be honest right here, AMD didn't have a horse in the race. And the majority of those VMware deployments we see are not running on AMD. Now that said, there's an extreme interest in the fact that we've got these very cored in systems that are now coming up on, now you're at that five to seven year refresh window of pulling in new hardware. And we have extremely attractive hardware when it comes to running virtualized workloads. The test cluster that I'm running at home, I've got that five to seven year old gear, and I've got some of the, even just the Milan systems that we've got. And I've got three nodes of another architecture going onto AMD. And when I got these three nodes completely maxed to the number of VMs that I can run on 'em, I'm at a quarter of the capacity of what I'm putting on the new stuff. So what you get is, I mean, we worked the numbers, and it's definitely, it's like a 30% decrease in the amount of resources that you need. >> That's a compelling number. >> It's a compelling number. >> 5%, 10%, nobody's going to do anything for that. You talk 30%. >> 30%. It's meaningful, it's meaningful. Now you you're out of Austin, right? >> Yes. >> So first thing I thought of when you talk about running clusters in your home is the cost of electricity, but you're okay. >> I'm okay. >> You don't live here, you don't live here, you don't need to worry about that. >> I'm okay. >> Do you have a favorite customer example that you think really articulates the value of AMD when you're in customer conversations and they go, why AMD and you hit back with this? >> Yeah. Actually it's funny because I had a conversation like that last night, kind of random person I met later on in the evening. We were going through this discussion and they were facing exactly this problem. They had that five to seven year infrastructure. It's funny, because the guy was a gamer too, and he's like, man, I've always been a big AMD fan, I love the CPUs all the way since back in basically the Opterons and Athlons right. He's like, I've always loved the AMD systems, loved the graphics cards. And now with what we're doing with Ryzen and all that stuff. He's always been a big AMD fan. He's like, and I'm going through doing my infrastructure refresh. And I told him, I'm just like, well, hey, talk to your VAR and have 'em plug some AMD SKUs in there from the Dells, HPs and Lenovos. And then we've got this tool to basically help make that migration easier on you. And so once we had that discussion and it was great, then he swung by the booth today and I was able to just go over, hey, this is the tool, this is how you use it, here's all the info. Call me if you need any help. >> Yeah, when we were talking earlier, we learned that you were at Scale. So what are you liking about AMD? How does that relate? >> The funny thing is this is actually the first time in my career that I've actually had a job where I didn't work for myself. I've been doing venture backed startups the last 25 years and we've raised couple hundred million dollars worth of investment over the years. And so one, I figured, here I am going to AMD, a larger corporation. I'm just like, am I going to be able to make it a year? And I have been here longer than a year and I absolutely love it. The culture at AMD is amazing. We still have that really, I mean, almost it's like that underdog mentality within the organization. And the team that I'm working with is a phenomenal team. And it's actually, our EVP and our Corp VP, were actually my executive sponsors, we were at a prior company. They were one of my executive sponsors when I was at Scale. And so my now VP boss calls me up and says, hey, I'm putting a band together, are you interested? And I was kind of enjoying a semi-retirement lifestyle. And then I'm just like, man, because it's you, yes, I am interested. And the group that we're in, the work that we're doing, the way that we're really focusing on forward looking things that are affecting the data center, what's going to be the data center like three to five years from now. It's exciting, and I am having a blast, I'm having the time of my life. I absolutely love it. >> Well, that relationship and the trust that you will have with each other, that bleeds into the customer conversations, the partner conversations, the employee conversations, it's all inextricably linked. >> Yes it is. >> And we want to know, you said three to five years out, like what? Like what? Just general futurist stuff, where do you think this is going. >> Well, it's interesting. >> So moon collides with the earth in 2025, we already know that. >> So we dialed this back to the Pensando acquisition. When you look at the Pensando acquisition and you look at basically where data centers are today, but then you look at where basically the big hyperscalers are. You look at an AWS, you look at their architecture, you specifically wrap Nitro around that, that's a very different architecture than what's being run in the data center. And when you look at what Pensando does, that's a lot of starting to bring what these real clouds out there, what these big hyperscalers are running into the grasps of the data center. And so I think you're going to see a fundamental shift. The next 10 years are going to be exciting because the way you look at a data center now, when you think of what CPUs do, what shared storage, how the networking is all set up, it ain't going to look the same. >> Okay, so the competing vision with that, to play devil's advocate, would be DPUs are kind of expensive. Why don't we just use NICs, give 'em some more bandwidth, and use the cheapest stuff. That's the competing vision. >> That could be. >> Or the alternative vision, and I imagine everything else we've experienced in our careers, they will run in parallel paths, fit for function. >> Well, parallel paths always exist, right? Otherwise, 'cause you know how many times you've heard mainframe's dead, tape's dead, spinning disk is dead. None of 'em dead, right? The reality is you get to a point within an industry where it basically goes from instead of a growth curve like that, it goes to a growth curve of like that, it's pretty flat. So from a revenue growth perspective, I don't think you're going to see the revenue growth there. I think you're going to see the revenue growth in DPUs. And when you actually take, they may be expensive now, but you look at what Monterey's doing and you look at the way that those DPUs are getting integrated in at the OEM level. It's going to be a part of it. You're going to order your VxRail and VSAN style boxes, they're going to come with them. It's going to be an integrated component. Because when you start to offload things off the CPU, you've driven your overall utilization up. When you don't have to process NSX on basically the X86, you've just freed up cores and a considerable amount of them. And you've also moved that to where there's a more intelligent place for that pack to be processed right, out here on this edge. 'Cause you know what, that might not need to go into the host bus at all. So you have just alleviated any transfers over a PCI bus, over the PCI lanes, into DRAM, all of these components, when you're like, but all to come with, oh, that bit needs to be on this other machine. So now it's coming in and it's making that decision there. And then you take and integrate that into things like the Aruba Smart Switch, that's running the Pensando technology. So now you got top of rack that is already making those intelligent routing decisions on where packets really need to go. >> Jason, thank you so much for joining us. I know you guys could keep talking. >> No, I was going to say, you're going to have to come back. You're going to have to come back. >> We've just started to peel the layers of the onion, but we really appreciate you coming by the show, talking about what AMD and VMware are doing, what you're enabling customers to achieve. Sounds like there's a lot of tailwind behind you. That's awesome. >> Yeah. >> Great stuff, thank you. >> It's a great time to be at AMD, I can tell you that. >> Oh, that's good to hear, we like it. Well, thank you again for joining us, we appreciate it. For our guest and Dave Nicholson, I'm Lisa Martin. You're watching "theCUBE Live" from San Francisco, VMware Explore 2022. We'll be back with our next guest in just a minute. (upbeat music)

>> TheCUBE presents HPE Discover 2022 brought to you by HPE. >> Welcome back to theCUBE's coverage of HPE Discover 2022. We're here at the Venetian convention center in Las Vegas Dave Vellante for John Furrier. Cam Amirs here is the director of technical alliances at Cribl'. Cam, good to see you. >> Good to see you too. >> Cribl'. Cool name. Tell us about it. >> So let's see. Cribl' has been around now for about five years selling products for the last two years. Fantastic company, lots of growth, started there 2020 and we're roughly 400 employees now. >> And what do you do? Tell us more. >> Yeah, sure. So I run the technical alliances team and what we do is we basically look to build integrations into platforms such as HPE GreenLake and Ezmeral. And we also work with a lot of other companies to help get data from various sources into their destinations or, you know other enrichments of data in that data pipeline. >> You know, you guys have been on theCUBE. Clint's been on many times, Ed Bailey was on our startup showcase. You guys are successful in this overfunded observability space. So, so you guys have a unique approach. Tell us about why you guys are successful in the product and some of the things you've been doing there. >> Yeah, absolutely. So our product is very complimentary to a lot of the technologies that already exist. And I used to joke around that everyone has these like pretty dashboards and reports but they completely glaze over the fact that it's not easy to get the data from those sources to their destinations. So for us, it's this capability with Cribl' Stream to get that data easily and repeatably into these destinations. >> Yeah. You know, Cam, you and I are both at the Snowflake Summit to John's point. They were like a dozen observability companies there. >> Oh yeah. >> And really beginning to be a crowded space. So explain what value you bring to that ecosystem. >> Yeah, sure. So the ecosystem that we see there is there are a lot of people that are kind of sticking to like effectively getting data and showing you dashboards reports about monitoring and things of that sort. For us, the value is how can we help customers kind of accelerate their adoption of these platforms, how to go from like your legacy SIM or your legacy monitoring solution to like the next-gen observability platform or next-gen security platform >> and what you do really well is the integration and bringing those other toolings to, to do that? >> Correct, correct. And we make it repeatable. >> How'd you end up here? >> HP? So we actually had a customer that actually deployed our software on the HPS world platform. And it was kind of a light bulb moment that, okay this is actually a different approach than going to your traditional, you know, AWS, Google, et cetera. So we decided to kind of hunt this down and figure out how we could be a bigger player in this space. >> You saw the data fabric announcement? I'm not crazy about the term, data fabric is an old NetApp term, and then Gartner kind of twisted it. I like data mesh, but anyway, it doesn't matter. We kind of know what it is, but but when you see an announcement like that how do you look at it? You know, what does it mean to to Cribl' and your customers? >> Yeah. So what we've seen is that, so we work with the data fabric team and we're able to kind of route our data to their, as a data lake, so we can actually route the data from, again all these very sources into this data lake and then have it available for whatever customers want to do with it. So one of the big things that I know Clint talks about is we give customers this, we sell choice. So we give them the ability to choose where they want to send their data, whether that's, you know HP's data lake and data fabric or some other object store or some other destination. They have that choice to do so. >> So you're saying that you can stream with any destination the customer wants? What are some examples? What are the popular destinations? >> Yeah so a lot of the popular destinations are your typical object stores. So any of your cloud object stores, whether it be AWS three, Google cloud storage or Azure blob storage. >> Okay. And so, and you can pull data from any source? >> Laughter: I'd be very careful, but absolutely. What we've seen is that a lot of people like to kind of look at traditional data sources like Syslog and they want to get it to us, a next-gen SIM, but to do so it needs to be converted to like a web hook or some sort of API call. And so, or vice versa, they have this brand new Zscaler for example, and they want to get that data into their SIM but there's no way to do it 'cause a SIM only accepts it as a Syslog event. So what we can do is we actually transform the data and make it so that it lands into that SIM in the format that it needs to be and easily make that a repeatable process >> So, okay. So wait, so not as a Syslog event but in whatever format the destination requires? >> Correct, correct. >> Okay. What are the limits on that? I mean, is this- >> Yeah. So what we've seen is that customers will be able to take, for example they'll take this Syslog event, it's unstructured data but they need to put it into say common information model for Splunk or Elastic common schema for Elastic search or just JSON format for Elastic. And so what we can do is we can actually convert those events so that they land in that transformed state, but we can also route a copy of that event in unharmed fashion, to like an S3 bucket for object store for that long term compliance user >> You can route it to any, basically any object store. Is that right? Is that always the sort of target? >> Correct, correct. >> So on the message here at HPE, first of all I'll get to the marketplace point in a second, but it's cloud to edge is kind of their theme. So data streaming sounds expensive. I mean, you know so how do you guys deal with the streaming egress issue? What does that mean to customers? You guys claim that you can save money on that piece. It's a hotly contested discussion point. >> Laughter: So one of the things that we actually just announced in our 350 release yesterday is the capability of getting data from Windows events, or from Windows hosts, I'm sorry. So a product that we also have is called Cribl' Edge. So our capability of being able to collect data from the edge and then transit it out to whether it be an on-prem, or self-hosted deployment of Cribl', or or maybe some sort of other destination object store. What we do is we actually take the data in in transit and reduce the volume of events. So we can do things like remove white space or remove events that are not really needed and compress or optimize that data so that the egress cost to your point are actually lowered. >> And your data reduction approach is, is compression? It's a compression algorithm? >> So it is a combination, yeah, so it's a combination. So there's some people what they'll do is they'll aggregate the events. So sometimes for example, VPC flow logs are very chatty and you don't need to have all those events. So instead you convert those to metrics. So suddenly you reduced those events from, you know high volume events to metrics that are so small and you still get the same value 'cause you still see the trends and everything. And if later on down the road, you need to reinvestigate those events, you can rehydrate that data with Cribl' replay >> And you'll do the streaming in real time, is that right? >> Yeah. >> So Kafka, is that what you would use? Or other tooling? >> Laughter: So we are complimentary to a Kafka deployment. Customer's already deployed and they've invested in Kafka, We can read off of Kafka and feed back into Kafka. >> If not, you can use your tooling? >> If not, we can be replacing that. >> Okay talk about your observations in the multi-cloud hybrid world because hybrid obviously everyone knows it's a steady state now. On public cloud, on premise edge all one thing, cloud operations, DevOps, data as code all the things we talk about. What's the customer view? You guys have a unique position. What's going on in the customer base? How are they looking at hybrid and specifically multi-cloud, is it stitching together multiple hybrids? Or how do you guys work across those landscapes? >> So what we've seen is a lot of customers are in multiple clouds. That's, you know, that's going to happen. But what we've seen is that if they want to egress data from say one cloud to another the way that we've architected our solution is that we have these worker nodes that reside within these hybrid, these other cloud event these other clouds, I should say so that transmitting data, first egress costs are lowered, but being able to have this kind of, easy way to collect the data and also stitch it back together, join it back together, to a single place or single location is one option that we offer customers. Another solution that we've kind of announced recently is Search. So not having to move the data from all these disparate data sources and data lakes and actually just search the data in place. That's another capability that we think is kind of popular in this hybrid approach. >> And talk about now your relationship with HPE you guys obviously had customers that drove you to Greenlake, obviously what's your experience with them and also talk about the marketplace presence. Is that new? How long has that been going on? Have you seen any results? >> Yeah, so we've actually just started our, our journey into this HPE world. So the first thing was obviously the customer's bringing us into this ecosystem and now our capabilities of, I guess getting ready to be on the marketplace. So having a presence on the marketplace has been huge giving us kind of access to just people that don't even know who we are, being that we're, you know a five year old company. So it's really good to have that exposure. >> So you're going to get customers out of this? >> That's the idea. [Laughter] >> Bring in new market, that's the idea of their GreenLake is that partners fill in. What's your impression so far of GreenLake? Because there seems to be great momentum around HP and opening up their channel their sales force, their customer base. >> Yeah. So it's been very beneficial for us, again being a smaller company and we are a channel first company so that obviously helps, you know bring out the word with other channel partners. But HP has been very, you know open arm kind of getting us into the system into the ecosystem and obviously talking, or giving the good word about Cribl' to their customers. >> So, so you'll be monetizing on GreenLake, right? That's the, the goal. >> That's the goal. >> What do you have to do to get into a position? Obviously, you got a relationship you're in the marketplace. Do you have to, you know, write to their API's or do you just have to, is that a checkbox? Describe what you have to do to monetize. >> Sure. So we have to first get validated on the platform. So the validation process validates that we can work on the Ezmeral GreenLake platform. Once that's been completed, then the idea is to have our logo show up on the marketplace. So customers say, Hey, look, I need to have a way to get transit data or do stuff with data specifically around logs, metrics, and traces into my logging solution or my SIM. And then what we do with them on the back end is we'll see this transaction occur right to their API to basically say who this customer is. 'Cause again, the idea is to have almost a zero touch kind of involvement, but we will actually have that information given to us. And then we can actually monetize on top of it. >> And the visualization component will come from the observability vendor. Is that right? Or is that somewhat, do you guys do some of that? >> So the visualization is right now we're basically just the glue that gets the data to the visualization engine. As we kind of grow and progress our search product that's what will probably have more of a visualization component. >> Do you think your customers are going to predominantly use an observability platform for that visualization? I mean, obviously you're going to get there. Are they going to use Grafana? Or some other tool? >> Or yeah, I think a lot of customers, obviously, depending on what data and what they're trying to accomplish they will have that choice now to choose, you know Grafana for their metrics, logs, et cetera or some sort of security product for their security events but same data, two different kind of use cases. And we can help enable that. >> Cam, I want to ask you a question. You mentioned you were at Splunk and Clint, the CEO and co-founder, was at Splunk too. That brings up the question I want to get your perspective on, we're seeing a modern network here with HPE, with Aruba, obviously clouds kind of going next level you got on premises, edge, all one thing, distributed computing basically, cyber security, a data problem that's solved a lot by you guys and people in this business, making sure data available machine learnings are growing and powering AI like you read about. What's changed in this business? Because you know, Splunking logs is kind of old hat you know, and now you got observability. Unification is a big topic. What's changed now? What's different about the market today around data and these platforms and, and tools? What's your perspective on that? >> I think one of the biggest things is people have seen the amount of volume of data that's coming in. When I was at Splunk, when we hit like a one terabyte deal that was a big deal. Now it's kind of standard. You're going to do a terabyte of data per day. So one of the big things I've seen is just the explosion of data growth, but getting value out of that data is very difficult. And that's kind of why we exist because getting all that volume of data is one thing. But being able to actually assert value from it, that's- >> And that's the streaming core product? That's the whole? >> Correct. >> Get data to where it needs to be for whatever application needs whether it's cyber or something else. >> Correct, correct. >> What's the customer uptake? What's the customer base like for you guys now? How many, how many customers you guys have? What are they doing with the data? What are some of the common things you're seeing? >> Yeah. I mean, it's, it's the basic blocking and tackling, we've significantly grown our customer base and they all have the same problem. They come to us and say, look, I just need to get data from here to there. And literally the routing use case is our biggest use case because it's simple and you take someone that's a an expensive engineer and operations engineer instead of having them going and doing the plumbing of data of just getting logs from one source to another, we come in and actually make that a repeatable process and make that easy. And so that's kind of just our very basic value add right from the get go. >> You can automate that, automate that, make it repeatable. Say what's in the name? Where'd the name come from? >> So Cribl', if you look it up, it's actually kind of an old shiv to get to siphon dirt from gold, right? So basically you just, that's kind of what we do. We filter out all the dirt and leave you the gold bits so you can get value. >> It's kind of what we do on theCUBE. >> It's kind of the gold nuggets. Get all these highlights, hitting Twitter, the golden, the gold nuggets. Great to have you on. >> Cam, thanks for, for coming on, explaining that sort of you guys are filling that gap between, Hey all the observability claims, which are all wonderful but then you got to get there. They got to have a route to get there. That's what got to do. Cribl' rhymes with tribble. Dave Vellante for John Furrier covering HPE Discover 2022. You're watching theCUBE. We'll be right back.

(upbeat music) >> theCUBE presents KubeCon and CloudNativeCon Europe 22, brought to you by the Cloud Native Computing Foundation. >> Valencia, Spain, a KubeCon, CloudNativeCon Europe 2022. I'm Keith Towns along with Paul Gillon, Senior Editor Enterprise Architecture for Silicon Angle. Welcome Paul. >> Thank you Keith, pleasure to work with you. >> We're going to have some amazing people this week. I think I saw stat this morning, 65% of the attendees, 7,500 folks. First time KubeCon attendees, is this your first conference? >> It is my first KubeCon and it is amazing to see how many people are here and to think of just a couple of years ago, three years ago, we were still talking about, what the Cloud was, what the Cloud was going to do and how we were going to integrate multiple Clouds. And now we have this whole new framework for computing that is just rifled out of nowhere. And as we can see by the number of people who are here this has become the dominant trend in Enterprise Architecture right now how to adopt Kubernetes and containers, build microservices based applications, and really get to that transparent Cloud that has been so elusive. >> It has been elusive. And we are seeing vendors from startups with just a few dozen people, to some of the traditional players we see in the enterprise space with 1000s of employees looking to capture kind of lightning in a bottle so to speak, this elusive concept of multicloud. >> And what we're seeing here is very typical of an early stage conference. I've seen many times over the years where the floor is really dominated by companies, frankly, I've never heard of that. The many of them are only two or three years old, you don't see the big dominant computing players with the presence here that these smaller companies have. That's very typical. We saw that in the PC age, we saw it in the early days of Unix and it's happening again. And what will happen over time is that a lot of these companies will be acquired, there'll be some consolidation. And the nature of this show will change, I think dramatically over the next couple or three years but there is an excitement and an energy in this auditorium today that is really a lot of fun and very reminiscent of other new technologies just as they requested. >> Well, speaking of new technologies, we have Dave Cole, CRO, Chief Revenue Officer. >> That's right. >> Chief Marketing Officer of Spectrum Cloud. Welcome to the show. >> Thank you. It's great to be here. >> So let's talk about this big ecosystem, Kubernetes. >> Yes. >> Solve problem? >> Well the dream is... Well, first of all applications are really the lifeblood of a company, whether it's our phone or whether it's a big company trying to connect with its customers about applications. And so the whole idea today is how do I build these applications to build that tight relationship with my customers? And how do I reinvent these applications rapidly in along comes containerization which helps you innovate more quickly? And certainly a dominant technology there is Kubernetes. And the question is, how do you get Kubernetes to help you build applications that can be born anywhere and live anywhere and take advantage of the places that it's running? Because everywhere has pluses and minuses. >> So you know what, the promise of Kubernetes from when I first read about it years ago is, runs on my laptop? >> Yeah. >> I can push it to any Cloud, any platforms. >> That's right, that's right. >> Where's the gap? Where are we in that phase? Like talk to me about scale? Is it that simple? >> Well, that is actually the problem is that today, while the technology is the dominant containerization technology in orchestration technology, it really still takes a power user, it really hasn't been very approachable to the masses. And so was these very expensive highly skilled resources that sit in a dark corner that have focused on Kubernetes, but that now is trying to evolve to make it more accessible to the masses. It's not about sort of hand wiring together, what is a typical 20 layer stack, to really manage Kubernetes and then have your engineers manually can reconfigure it and make sure everything works together. Now it's about how do I create these stacks, make it easy to deploy and manage at scale? So we've gone from sort of DIY Developer Centric to all right, now how do I manage this at scale? >> Now this is a point that is important, I think is often overlooked. This is not just about Kubernetes. This is about a whole stack of Cloud Native Technologies. And you who is going to integrate that all that stuff, piece that stuff together? Obviously, you have a role in that. But in the enterprise, what is the awareness level of how complex this stack is and how difficult it is to assemble? >> We see a recognition of that we've had developers working on Kubernetes and applications, but now when we say, how do we weave it into our production environments? How do we ensure things like scalability and governance? How do we have this sort of interesting mix of innovation, flexibility, but with control? And that's sort of an interesting combination where you want developers to be able to run fast and use the latest tools, but you need to create these guardrails to deploy it at scale. >> So where do the developers fit in that operation stack then? Is Kubernetes an AIOps or an ops task or is it sort of a shared task across the development spectrum? >> Well, I think there's a desire to allow application developers to just focus on the application and have a Kubernetes related technology that ensures that all of the infrastructure and related application services are just there to support them. And because the typical stack from the operating system to the application can be up to 20 different layers, components, you just want all those components to work together, you don't want application developers to worry about those things. And the latest technologies like Spectra Cloud there's others are making that easy application engineers focus on their apps, all of the infrastructure and the services are taken care of. And those apps can then live natively on any environment. >> So help paint this picture for us. I get AKS, EKS, Anthos, all of these distributions OpenShift, the Tanzu, where's Spectra Cloud helping me to kind of cobble together all these different distros, I thought distro was the thing just like Linux has different distros, Randy said different distros. >> That actually is the irony, is that sort of the age of debating the distros largely is over. There are a lot of distros and if you look at them there are largely shades of gray in being different from each other. But the Kubernetes distribution is just one element of like 20 elements that all have to work together. So right now what's happening is that it's not about the distribution it's now how do I again, sorry to repeat myself, but move this into scale? How do I move it into deploy at scale to be able to manage ongoing at scale to be able to innovate at-scale, to allow engineers as I said, use the coolest tools but still have technical guardrails that the enterprise knows, they'll be in control of. >> What does at-scale mean to the enterprise customers you're talking to now? What do they mean when they say that? >> Well, I think it's interesting because we think scale's different because we've all been in the industry and it's frankly, sort of boring old word. But today it means different things, like how do I automate the deployment at-scale? How do I be able to make it really easy to provision resources for applications on any environment, from either a virtualized or bare metal data center, Cloud, or today Edge is really big, where people are trying to push applications out to be closer to the source of the data. And so you want to be able to deploy it-scale, you want to manage at-scale, you want to make it easy to, as I said earlier, allow application developers to build their applications, but ITOps wants the ability to ensure security and governance and all of that. And then finally innovate at-scale. If you look at this show, it's interesting, three years ago when we started Spectra Cloud, there are about 1400 businesses or technologies in the Kubernetes ecosystem, today there's over 1800 and all of these technologies made up of open source and commercial all version in a different rates, it becomes an insurmountable problem, unless you can set those guardrails sort of that balance between flexibility, control, let developers access the technologies. But again, manage it as a part of your normal processes of a scaled operation. >> So Dave, I'm a little challenged here, because I'm hearing two where I typically consider conflicting terms. Flexibility, control. >> Yes. >> In order to achieve control, I need complexity, in order to choose flexibility, I need t-shirt, one t-shirt fits all and I get simplicity. How can I get both that just doesn't compute. >> Well, that's the opportunity and the challenge at the same time. So you're right. So developers want choice, good developers want the ability to choose the latest technology so they can innovate rapidly. And yet ITOps, wants to be able to make sure that there are guardrails. And so with some of today's technologies, like Spectra Cloud, it is, you have the ability to get both. We actually worked with dimensional research, and we sponsor an annual state of Kubernetes survey. We found this last summer, that two out of three IT executives said, you could not have both flexibility and control together, but in fact they want it. And so it is this interesting balance, how do I give engineers the ability to get anything they want, but ITOps the ability to establish control. And that's why Kubernetes is really at its next inflection point. Whereas I mentioned, it's not debates about the distro or DIY projects. It's not big incumbents creating siloed Kubernetes solutions, but in fact it's about allowing all these technologies to work together and be able to establish these controls. And that's really where the industry is today. >> Enterprise , enterprise CIOs, do not typically like to take chances. Now we were talking about the growth in the market that you described from 1400, 1800 vendors, most of these companies, very small startups, our enterprises are you seeing them willing to take a leap with these unproven companies? Or are they holding back and waiting for the IBMs, the HPS, the MicrosoftS to come in with the VMwares with whatever they solution they have? >> I think so. I mean, we sell to the global 2000. We had yesterday, as a part of Edge day here at the event, we had GE Healthcare as one of our customers telling their story, and they're a market share leader in medical imaging equipment, X-rays, MRIs, CAT scans, and they're starting to treat those as Edge devices. And so here is a very large established company, a leader in their industry, working with people like Spectra Cloud, realizing that Kubernetes is interesting technology. The Edge is an interesting thought but how do I marry the two together? So we are seeing large corporations seeing so much of an opportunity that they're working with the smaller companies, the latest technology. >> So let's talk about the Edge a little, you kind of opened it up there. How should customers think about the Edge versus the Cloud Data Center or even bare metal? >> Actually it's a... Well bare metal is fairly easy is that many people are looking to reduce some of the overhead or inefficiencies of the virtualized environment. But we've had really sort of parallel little white tornadoes, we've had bare metal as infrastructure that's been developing, and then we've had orchestration developing but they haven't really come together very well. Lately, we're finally starting to see that come together. Spectra Cloud contributed to open source a metal as a service technology that finally brings these two worlds together, making bare metal much more approachable to the enterprise. Edge is interesting, because it seems pretty obvious, you want to push your application out closer to your source of data, whether it's AI inferencing, or IoT or anything like that, you don't want to worry about intermittent connectivity or latency or anything like that. But people have wanted to be able to treat the Edge as if it's almost like a Cloud, where all I worry about is the app. So really, the Edge to us is just the next extension in a multi-Cloud sort of motif where I want these Edge devices to require low IT resources, to automate the provisioning, automate the ongoing version management, patch management, really act like a Cloud. And we're seeing this as very popular now. And I just used the GE Healthcare example of that, imagine a CAT scan machine, I'm making this part up in China and that's just an Edge device and it's doing medical imagery which is very intense in terms of data, you want to be able to process it quickly and accurately, as close to the endpoint, the healthcare provider is possible. >> So let's talk about that in some level of details, we think about kind of Edge and these fixed devices such as imaging device, are we putting agents on there, or we looking at something talking back to the Cloud? Where does special Cloud inject and help make that simple, that problem of just having dispersed endpoints all over the world simpler? >> Sure. Well we announced our Edge Kubernetes, Edge solution at a big medical conference called HIMMS, months ago. And what we allow you to do is we allow the application engineers to develop their application, and then you can de you can design this declarative model this cluster API, but beyond Cluster profile which determines which additional application services you need and the Edge device, all the person has to do with the endpoint is plug in the power, plug in the communications, it registers the Edge device, it automates the deployment of the full stack and then it does the ongoing versioning and patch management, sort of a self-driving Edge device running Kubernetes. And we make it just very easy. No IT resources required at the endpoint, no expensive field engineering resources to go to these endpoints twice a year to apply new patches and things like that, all automated. >> But there's so many different types of Edge devices with different capabilities, different operating systems, some have no operating system. I mean that seems, like a much more complex environment, just calling it the Edge is simple, but what you're really talking about is 1000s of different devices, that you have to run your applications on how are you dealing with that? >> So one of the ways is that we're really unbiased. In other words, we're OS and distro agnostic. So we don't want to debate about which distribution you like, we don't want to debate about which OS you want to use. The truth is, you're right. There's different environments and different choices that you'll want to make. And so the key is, how do you incorporate those and also recognize everything beyond those, OS and Kubernetes and all of that and manage that full stack. So that's what we do, is we allow you to choose which tools you want to use and let it be deployed and managed on any environment. >> And who's... >> So... >> I'm sorry Keith, who's responsible for making Kubernetes run on the Edge device. >> We do. We provision the entire stack. I mean, of course the company does using our product, but we provision the entire Kubernetes infrastructure stack, all the application services and the application itself on that device. >> So I would love to dig into like where pods happen and all that. But, provisioning is getting to the point that is a solve problem. Day two. >> Yes. >> Like you just mentioned HIMMS, highly regulated environments. How does Spectra Cloud helping with configuration management, change control, audit, compliance, et cetera, the hard stuff. >> Yep. And one of the things we do, you bring up a good point is we manage the full life cycle from day zero, which is sort of create, deploy, all the way to day two, which is about access control, security, it's about ongoing versioning in a patch management. It's all of that built into the platform. But you're right, like the medical industry has a lot of regulations. And so you need to be able to make sure that everything works, it's always up to the latest level have the highest level of security. And so all that's built into the platform. It's not just a fire and forget it really is about that full life cycle of deploying, managing on an ongoing basis. >> Well, Dave, I'd love to go into a great deal of detail with you about kind of this day two ops and I think we'll be covering a lot more of that topic, Paul, throughout the week, as we talk about just as we've gotten past, how do I deploy Kubernetes pod, to how do I actually operate IT? >> Absolutely, absolutely. The devil is in the details as they say. >> Well, and also too, you have to recognize that the Edge has some very unique requirements, you want very small form factors, typically, you want low IT resources, it has to be sort of zero touch or low touch because if you're a large food provider with 20,000 store locations, you don't want to send out field engineers two or three times a year to update them. So it really is an interesting beast and we have some exciting technology and people like GE are using that. >> Well, Dave, thanks a lot for coming on theCUBE, you're now KubeCon, you've not been on before? >> I have actually, yes its... But I always enjoy it. >> Great conversation. From Valencia, Spain. I'm Keith Towns, along with Paul Gillon and you're watching theCUBE, the leader in high tech coverage. (upbeat music)

>>The cube presents, Coon and cloud native con Europe 22 brought to you by the cloud native computing foundation. >>Lisia Spain, a cuon cloud native con Europe 2022. I'm Keith towns, along with Paul Gillon, senior editor, enterprise architecture for Silicon angle. Welcome Paul, >>Thank you, Keith pleasure to work >>With you. You know, we're gonna have some amazing people this week. I think I saw stat this morning, 65% of the attendees, 7,500 folks. First time Q con attendees. This is your first conference. >>It is my first cubic con and it is amazing to see how many people are here and to think of, you know, just a couple of years ago, three years ago, we were still talking about what the cloud was and what the cloud was gonna do and how we were gonna integrate multiple clouds. And now we have this whole new framework for computing that is just rifled out of, out of nowhere. And as we can see by the number of people who are here, this has become a, a, this is the dominant trend in enterprise architecture right now, how to adopt Kubernetes and containers, build microservices based applications, and really get to that, that transparent cloud that has been so elusive. >>It has been elusive. And we are seeing vendors from startups with just a, a few dozen people to some of the traditional players we see in the enterprise space with thousands of employees looking to capture kind of lightning in a bottle, so to speak this elusive concept of multi-cloud. >>And what we're seeing here is very typical of an early stage conference. I've seen many times over the years where the, the floor is really dominated by companies, frankly, I've never heard of that. Many of them are only two or three years old, and you don't see the big, the big dominant computing players with, with the presence here that these smaller companies have. That's very typical. We saw that in the PC age, we saw it in the early days of Unix and, and it's happening again. And what will happen over time is that a lot of these companies will be acquired. There'll be some consolidation. And the nature of this show will change, I think, dramatically over the next couple or three years, but there is an excitement and an energy in this auditorium today that is, is really a lot of fun and very reminiscent of other new technologies just as they press it. >>Well, speaking of new technologies, we have Dave Cole, CR O chief revenue officer that's right. Chief marketing officer that's right of spec cloud. Welcome to the show. Thank >>You. It's great to be here. >>So let's talk about this big ecosystem. Okay. Kubernetes. Yes. Solve problem. >>Well, you know, the, the dream is, well, first of all, applications are really the lifeblood of a company, whether it's our phone or whether it's a big company trying to connect with its customer, it's about applications. And so the whole idea today is how do I build these applications to build that tight relationship with my customers? And how do I reinvent these applications rapidly in, along comes containerization, which helps you innovate more quickly. And certainly a dominant technology. There is Kubernetes. And the, the question is how do you get Kubernetes to help you build applications that can be born anywhere and live anywhere and take advantage of the places that it's running, cuz everywhere has pluses and minuses. >>So you know what the promise of Kubernetes from when I first read about it years ago is runs on my laptop. Yep. I can push it to any cloud, any platform that's that's right. Where's the gap. Where are we in that, in that phase? Like talk to me about scale. Is that, is that, is it that simple? >>Well, that act is actually the problem is that date while the technology is the dominant containerization technology and orchestration technology, it really still takes a power user. It really hasn't been very approachable to the masses. And so it was these very expensive, highly skilled resources that sit in a dark corner that have focused on Kubernetes, but that, that now is trying to evolve to make it more accessible to the masses. It's not about sort of hand wiring together. What is a typical 20 layer stack to really manage Kubernetes and then have your engineers manually can reconfigure it and make sure everything works together. Now it's about how do I create these stacks, make it easy to deploy and manage at scale. So we've gone from sort of DIY developer centric to all right, now, how do I manage this at scale? >>Now this is a point that is important, I think is often overlooked. This is not just about Kubernetes. This is about a whole stack of cloud native technologies. Yes. And you who is going to, who is going to integrate that, all that stuff, piece that stuff together, right? Obviously you have a, a role in that. Yes. But in the enterprise, what is the awareness level of how complex this stack is and how difficult it is to assemble? >>We, we see a recognition of that, that we've had developers working on Kubernetes and applications, but now when we say, how do we weave it into our production environments? How do we ensure things like scalability and governance? How do we have this sort of interesting mix of innovation, flexibility, but with control. And that's sort of an interesting combination where you want developers to be able to run fast and use the latest tools, but you need to create these guardrails to deploy it at scale. >>So where do the developers fit in that operation stack then? Is this, is Kubernetes an AI ops or an ops a task, or is it sort of a shared task across the development spectrum? >>Well, I think there's a desire to allow application developers, to just focus on the application and have a Kubernetes related technology that ensures that all of the infrastructure and related application services are just there to support them. And because the typical stack from the operating system to the application can be up to 20 different layers components. You just want all those components to work together. You don't want application developers to worry about those things. And the latest technologies like spectra cloud there's others are making that easy application engineers focus on their apps, all of the infrastructure and the services are taken care of. And those apps can then live natively on any environment. >>So help paint this picture for us. You know, I get got AKs ETS and those, all of these distributions OpenShift, the tan zoo, where is spec cloud helping me to kind of cobble together all these different distros I thought distro was the, was the thing like, just like Lennox has different distros, you know, right. Randy said different distros >>That actually is the irony. Is that sort of the age of debating, the distros largely is over. There are a lot of distros and if you look at them, there are largely shades of gray in being different from each other. But the Kubernetes distribution is just one element of like 20 elements that all have to work together. So right now what's what's happening is that it's not about the distribution it's now, how do I, again, sorry to repeat myself, but move this into a, into scale. How do I move it into deploy at scale, to be able to manage ongoing at scale, to be able to innovate at scale, to allow engineers, as I said, use the coolest tools, but still have technical guardrails that the, the enterprise knows they'll be in control of what, >>What does at scale mean to the enterprise customers you're talking to now? What do they mean when they say that? >>Well, I think it's interesting cuz we think scale's different cuz we've all been in the industry and it's frankly sort of boring old wor word, but today it means different things. Like how do I automate the deployment at scale? How do I be able to make it really easy to provision resources for applications on any environment from either a virtualized or bare metal data center cloud or today edge is really big where people are trying to push applications out to be closer to this source of the data. And so you want to be able to deploy it scale you wanna manage at scale, you wanna make it easy to, as I said earlier, allow application developers to build their applications, but it ops wants the ability to ensure security and governance and all of that. And then finally innovate at scale. If you look at this show, it's interesting, three years ago, when we started spectra cloud, there are about 1400 businesses or technologies in the Kubernetes ecosystem today there's over 1800 and all of these technologies made up of open source and commercial, all versioning at different rates. It becomes an insurmountable problem unless you can set those guardrails sort of that balance between flexibility and control, let developers access the technologies. But again, manage it as a part of your normal processes of a, of a scale of operation. >>So, so Dave, I'm a little challenged here cuz I'm hearing two where I typically consider conflicting terms. Okay. Flexibility control. Yes. In order to achieve control, I need complexity in order to choose flexibility. I need t-shirt one t-shirt fits all right. To and I, and I, and I get simplicity. How can I get both that just doesn't you know, compute >>Well thus the opportunity and the challenge at the same time. So you're right. So developers want choice, good developers want the ability to choose the latest technology so they can innovate rapidly. And yet it ops wants to be able to make sure that there are guard rails. And so with some of today's technologies like spectral cloud, it is you have the ability to get both. We actually worked with dimensional research and we sponsor an annual state of Kubernetes survey. We found this last summer, that two out of three, it executives said you could not have both flexibility and control together, but in fact they want it. And so it is this interesting balance. How do I give engineers the ability to get anything they want, but it ops the ability to establish control. And that's why Kubernetes is really at its next inflection point. Whereas I mentioned, it's not debates about the distro or DIY projects. It's not big incumbents creating siloed Kubernetes solutions. But in fact it's about allowing all these technologies to work together and be able to establish these controls. And that's, that's really where the industry is today. >>Enterprise enterprise CIOs do not typically like to take chances. Now we were talking about the growth in the market that you described from 1400, 1800 vendors. Most of these companies, very small startups are, are enterprises. Are you seeing them willing to take a leap with these unproven companies or are they holding back and waiting for the IBMs, the HPS, the Microsofts to come in with the VMwares with whatever they solution they have? >>I, I think so. I mean, we sell to the global 2000. We had yesterday as a part of edge day here at the event, we had GE healthcare as one of our customers telling their story. And they're a market share leader in medical imaging equipment. X-rays MRIs, cat scans, and they're, they're starting to treat those as edge devices. And so here is a very large established company, a leader in their industry, working with people like spectral cloud, realizing that Kubernetes is interesting technology. The edge is an interesting thought, but how do I marry the two together? So we are seeing large corporations seeing so much of an opportunity that they're working with the smaller companies, the latest technology. >>So let's talk about the edge a little. You kind of opened it up there. Yeah. How should customers think about the edge versus the cloud data center or even bare metal? >>Actually it's a well bare bare metal is fairly easy is that many people are looking to reduce some of the overhead or inefficiencies of the virtualized environment. And, but we've had really sort of parallel little white tornadoes. We've had bare metal as infrastructure that's been developing and then we've had orchestration technology's developing, but they haven't really come together very well lately. We're finally starting to see that come together. Spectra cloud contributed to open source a metal as a service technology that finally brings these two worlds together. Making bare metal much more approachable to the inters enterprise edge is interesting because it seems pretty obvious. You wanna push your application out closer to your source of data, whether it's AI in fencing or O T or anything like that, you don't wanna worry about intermittent connectivity or latency or anything like that. But people have wanted to be able to treat the edge as if it's almost like a cloud where all I worry about is the app. >>So really the edge to us is just the next extension in a multi-cloud sort of motif where I want these edge devices to require low it resources to automate the provisioning, automate the ongoing version management patch management really act like a cloud. And we're seeing this as very, very popular now. And I just used the GE healthcare example of that. Imagine a cat scan machine, I'm making this part up in China and that's just an edge device. And it's, it's doing medical imagery, which is very intense in terms of data. You want to be able to process it quickly and accurately as close to the endpoint, the healthcare provider as possible. >>So let's talk about that in some level of detail, as we think about kind of edge and you know, these fixed devices such as imaging device, are we putting agents on there? Are we looking at something talking back to the cloud, where does special cloud inject and help make that simple, that problem of just having dispersed endpoints all over the world? Simpler? >>Sure. Well we announced our edge Kubernetes edge solution at a big medical conference called, called hymns months ago. And what we allow you to do is we allow the application engineers to develop their application. And then you can de you can design this declarative model, this cluster API, but beyond cluster profile, which determines which additional application services you need and the edge device, all the person has to do with the endpoint is plug in the power plug in the communications. It registers the edge device. It automates the deployment of the full stack. And then it does the ongoing versioning and patch management, sort of a self-driving edge device running Kubernetes. And we make it just very, very easy. No, it resources required at the endpoint, no expensive field engineering resources to go to these endpoints twice a year to apply new patches and things like that, all >>Automated, but there's so many different types of edge devices with different capabilities, different operating systems, some have no operating system. Yeah. I mean, what, that seems like a much more complex environment, just calling it, the edge is simple, but what you're really talking about is thousands of different devices, right? That you have to run your applications on how, how are you dealing with that? >>So one of the ways is that we're really unbiased. In other words, we're OS and distro agnostic. So we don't want to debate about which distribution you like. We don't want to debate about, you know, which OS you want to use. The truth is you're right. There's different environments and different choices that you'll wanna make. And so the key is, is how do you incorporate those and also recognize everything beyond those, you know, OS and Kubernetes and all of that and manage that full stack. So that's what we do is we allow you to choose which tools you want to use and let it be deployed and managed on any environment. >>And who's respo, I'm sorry, key. Who's responsible for making Kubernetes run on the edge device. >>We do. We provision the entire stack. I mean, of course the company does using our product, but we provision the entire Kubernetes infrastructure stack all the application services and the application itself on that device. >>So I would love to dig into like where pods happen and all that, but provisioning is getting to the point that it's a solve problem. Day two. Yes. Like we, you know, you just mentioned hymns, highly regulated environments. How does spec cloud helping with configuration management change control, audit, compliance, et cetera, the hard stuff. >>Yep. And one of the things we do, you bring up a good point is we manage the full life cycle from day zero, which is sort of create, deploy all the way to day two, which is about, you know, access control, security. It's about ongoing versioning and patch management. It's all of that built into the platform. And, but you're right. Like the medical industry has a lot of regulations. And so you need to be able to make sure that everything works. It's always up to the latest level, have the highest level of security. And so all that's built into the platform. It's not just a fire and forget it really is about that full life cycle of deploying, managing on an ongoing basis. >>Well, Dave, I'd love to go into a great deal of detail with you about kind of this day two option. I think we'll be covering a lot more of that topic, Paul, throughout the week, as we talk about just, you know, as we've gotten past, you know, how do I deploy Kubernetes pod to how do I actually operate it? >>Absolutely, absolutely. The devil is in the details as they say, >>Well, and also too, you have to recognize that the edge has some very unique requirements. You want very small form factors. Typically you want low it resources. It has to be sort of zero touch or low touch because if you're a large food provider with 20,000 store locations, you don't wanna send out field engineers two or three times a year to update them. So it really is an interesting beast and we have some exciting technology and people like GE are using that. >>Well, Dave, thanks a lot for coming on to Q you're now Cub Alon. You've not been on before. >>I have actually. Yes. Oh. But I always enjoy it. >>It's great conversation. Foria Spain. I'm Keith towns along with Paul Gillon and you're watching the cue, the leader in high tech coverage.

(upbeat music) >> We're back at VeeamON 2022. We're here at the Aria in Las Vegas Dave Vellante with Dave Nicholson. Bill Andrews is here. He's the president and CEO of ExaGrid, mass boy. Bill, thanks for coming on theCUBE. >> Thanks for having me. >> So I hear a lot about obviously data protection, cyber resiliency, what's the big picture trends that you're seeing when you talk to customers? >> Well, I think clearly we were talking just a few minutes ago, data's growing like crazy, right This morning, I think they said it was 28% growth a year, right? So data's doubling almost just a little less than every three years. And then you get the attacks on the data which was the keynote speech this morning as well, right. All about the ransomware attacks. So we've got more and more data, and that data is more and more under attack. So I think those are the two big themes. >> So ExaGrid as a company been around for a long time. You've kind of been the steady kind of Eddy, if you will. Tell us about ExaGrid, maybe share with us some of the differentiators that you share with customers. >> Sure, so specifically, let's say in the Veeam world you're backing up your data, and you really only have two choices. You can back that up to disc. So some primary storage disc from a Dell, or a Hewlett Packard, or an NetApp or somebody, or you're going to back it up to what's called an inline deduplication appliance maybe a Dell Data Domain or an HPE StoreOnce, right? So what ExaGrid does is we've taken the best of both those but not the challenges of both those and put 'em together. So with disc, you're going to get fast backups and fast restores, but because in backup you keep weekly's, monthly's, yearly retention, the cost of this becomes exorbitant. If you go to a deduplication appliance, and let's say the Dell or the HPs, the data comes in, has to be deduplicated, compare one backup to the next to reduce that storage, which lowers the cost. So fixes that problem, but the fact that they do it inline slows the backups down dramatically. All the data is deduplicated so the restores are slow, and then the backup window keeps growing as the data grows 'cause they're all scale up technologies. >> And the restores are slow 'cause you got to rehydrate. >> You got to rehydrate every time. So what we did is we said, you got to have both. So our appliances have a front end disc cache landing zone. So you're right directed to the disc., Nothing else happens to it, whatever speed the backup app could write at that's the speed we take it in at. And then we keep the most recent backups in that landing zone ready to go. So you want to boot a VM, it's not an hour like a deduplication appliance it's a minute or two. Secondly, we then deduplicate the data into a second tier which is a repository tier, but we have all the deduplicated data for the long term retention, which gets the cost down. And on top of that, we're scale out. Every appliance has networking processor memory end disc. So if you double, triple, quadruple the data you double, triple, quadruple everything. And if the backup window is six hours at 100 terabyte it's six hours at 200 terabyte, 500 terabyte, a petabyte it doesn't matter. >> 'Cause you scale out. >> Right, and then lastly, our repository tier is non-network facing. We're the only ones in the industry with this. So that under a ransomware attack, if you get hold of a rogue server or you hack the media server, get to the backup storage whether it's disc or deduplication appliance, you can wipe out all the backup data. So you have nothing to recover from. In our case, you wipe it out, our landing zone will be wiped out. We're no different than anything else that's network facing. However, the only thing that talks to our repository tier is our object code. And we've set up security policies as to how long before you want us to delete data, let's say 10 days. So if you have an attack on Monday that data doesn't get deleted till like a week from Thursday, let's say. So you can freeze the system at any time and do restores. And then we have immutable data objects and all the other stuff. But the culmination of a non-network facing tier and the fact that we do the delayed deletes makes us the only one in the industry that can actually truly recover. And that's accelerating our growth, of course. >> Wow, great description. So that disc cache layer is a memory, it's a flash? >> It's disc, it's spinning disc. >> Spinning disc, okay. >> Yeah, no different than any other disc. >> And then the tiered is what, less expensive spinning disc? >> No, it's still the same. It's all SaaS disc 'cause you want the quality, right? So it's all SaaS, and so we use Western Digital or Seagate drives just like everybody else. The difference is that we're not doing any deduplication coming in or out of that landing zone to have fast backups and fast restores. So think of it like this, you've got disc and you say, boy it's too expensive. What I really want to do then is put maybe a deduplication appliance behind it to lower the cost or reverse it. I've got a deduplication appliance, ugh, it's too slow for backups and restores. I really want to throw this in front of it to have fast backups first. Basically, that's what we did. >> So where does the cost savings, Bill come in though, on the tier? >> The cost savings comes in the fact that we got deduplication in that repository. So only the most recent backup >> Ah okay, so I get it. >> are the duplicated data. But let's say you had 40 copies of retention. You know, 10 weekly's, 36 monthly's, a few yearly. All of that's deduplicated >> Okay, so you're deduping the stuff that's not as current. >> Right. >> Okay. >> And only a handful of us deduplicate at the layer we do. In other words, deduplication could be anywhere from two to one, up to 50 to one. I mean it's all over the place depending on the algorithm. Now it's what everybody's algorithms do. Some backup apps do two to one, some do five to one, we do 20 to one as well as much as 50 to one depending on the data types. >> Yeah, so the workload is going to largely determine the combination >> The content type, right. with the algos, right? >> Yeah, the content type. >> So the part of the environment that's behind the illogical air gap, if you will, is deduped data. >> Yes. >> So in this case, is it fair to say that you're trading a positive economic value for a little bit longer restore from that environment? >> No, because if you think about backup 95% of the customers restores are from the most recent data. >> From the disc cache. >> 95% of the time 'cause you think about why do you need fast restores? Somebody deleted a file, somebody overwrote a file. They can't go work, they can't open a file. It's encrypted, it's corrupted. That's what IT people are trying to keep users productive. When do you go for longer-term retention data? It's an SEC audit. It's a HIPAA audit. It's a legal discovery, you don't need that data right away. You have days and weeks to get that ready for that legal discovery or that audit. So we found that boundary where you keep users productive by keeping the most recent data in the disc cache landing zone, but anything that's long term. And by the way, everyone else is long term, at that point. >> Yeah, so the economics are comparable to the dedupe upfront. Are they better, obviously get the performance advance? >> So we would be a lot looped. The thing we replaced the most believe it or not is disc, we're a lot less expensive than the disc. I was meeting with some Veeam folks this morning and we were up against Cisco 3260 disc at a children's hospital. And on our quote was $500,000. The disc was 1.4 million. Just to give you an example of the savings. On a Data Domain we're typically about half the price of a Data Domain. >> Really now? >> The reason why is their front end control are so expensive. They need the fastest trip on the planet 'cause they're trying to do inline deduplication. >> Yeah, so they're chasing >> They need the fastest memory >> on the planet. >> this chips all the time. They need SSD on data to move in and out of the hash table. In order to keep up with inline, they've got to throw so much compute at it that it drives their cost up. >> But now in the case of ransomware attack, are you saying that the landing zone is still available for recovery in some circumstances? Or are you expecting that that disc landing zone would be encrypted by the attacker? >> Those are two different things. One is deletion, one is encryption. So let's do the first scenario. >> I'm talking about malicious encryption. >> Yeah, absolutely. So the first scenario is the threat actor encrypts all your primary data. What's does he go for next? The backup data. 'Cause he knows that's your belt and suspend is to not pay the ransom. If it's disc he's going to go in and put delete commands at the disc, wipe out the disc. If it's a data domain or HPE StoreOnce, it's all going to be gone 'cause it's one tier. He's going to go after our landing zone, it's going to be gone too. It's going to wipe out our landing zone. Except behind that we have the most recent backup deduplicate in the repository as well as all the other backups. So what'll happen is they'll freeze the system 'cause we weren't going to delete anything in the repository for X days 'cause you set up a policy, and then you restore the most recent backup into the landing zone or we can restore it directly to your primary storage area, right? >> Because that tier is not network facing. >> That's right. >> It's fenced off essentially. >> People call us every day of the week saying, you saved me, you saved me again. People are coming up to me here, you saved me, you saved me. >> Tell us a story about that, I mean don't give me the names but how so. >> I'll actually do a funnier story, 'cause these are the ones that our vendors like to tell. 'Cause I'm self-serving as the CEO that's good of course, a little humor. >> It's your 15 minutes of job. >> That is my 15 minutes of fame. So we had one international company who had one ExaGrid at one location, 19 Data Domains at the other locations. Ransomware attack guess what? 19 Data Domains wiped out. The one ExaGrid, the only place they could restore. So now all 20 locations of course are ExaGrids, China, Russia, Mexico, Germany, US, et cetera. They rolled us out worldwide. So it's very common for that to occur. And think about why that is, everyone who's network facing you can get to the storage. You can say all the media servers are buttoned up, but I can find a rogue server and snake my way over the storage, I can. Now, we also of course support the Veeam Data Mover. So let's talk about that since we're at a Veeam conference. We were the first company to ever integrate the Veeam Data Mover. So we were the first actually ever integration with Veeam. And so that Veeam Data Mover is a protocol that goes from Veeam to the ExaGrid, and we run it on both ends. So that's a more secure protocol 'cause it's not an open format protocol like SaaS. So with running the Veeam Data Mover we get about 30% more performance, but you do have a more secure protocol layer. So if you don't get through Veeam but you get through the protocol, boom, we've got a stronger protocol. If you make it through that somehow, or you get to it from a rogue server somewhere else we still have the repository. So we have all these layers so that you can't get at it. >> So you guys have been at this for a while, I mean decade and a half plus. And you've raised a fair amount of money but in today's terms, not really. So you've just had really strong growth, sequential growth. I understand it, and double digit growth year on year. >> Yeah, about 25% a year right now >> 25%, what's your global strategy? >> So we have sales offices in about 30 countries already. So we have three sales teams in Brazil, and three in Germany, and three in the UK, and two in France, and a lot of individual countries, Chile, Argentina, Columbia, Mexico, South Africa, Saudi, Czech Republic, Poland, Dubai, Hong Kong, Australia, Singapore, et cetera. We've just added two sales territories in Japan. We're adding two in India. And we're installed in over 50 countries. So we've been international all along the way. The goal of the company is we're growing nicely. We have not raised money in almost 10 years. >> So you're self-funding. You're cash positive. >> We are cash positive and self-funded and people say, how have you done that for 10 years? >> You know what's interesting is I remember, Dave Scott, Dave Scott was the CEO of 3PAR, and he told me when he came into that job, he told the VCs, they wanted to give him 30 million. He said, I need 80 million. I think he might have raised closer to a hundred which is right around what you guys have raised. But like you said, you haven't raised it in a long time. And in today's terms, that's nothing, right? >> 100 is 500 in today's terms. >> Yeah, right, exactly. And so the thing that really hurt 3PAR, they were public companies so you could see all this stuff is they couldn't expand internationally. It was just too damn expensive to set up the channels, and somehow you guys have figured that out. >> 40% of our business comes out of international. We're growing faster internationally than we are domestically. >> What was the formula there, Bill, was that just slow and steady or? >> It's a great question. >> No, so what we did, we said let's build ExaGrid like a McDonald's franchise, nobody's ever done that before in high tech. So what does that mean? That means you have to have the same product worldwide. You have to have the same spares model worldwide. You have to have the same support model worldwide. So we early on built the installation. So we do 100% of our installs remotely. 100% of our support remotely, yet we're in large enterprises. Customers racks and stacks the appliances we get on with them. We do the entire install on 30 minutes to about three hours. And we've been developing that into the product since day one. So we can remotely install anywhere in the world. We keep spares depots all over the world. We can bring 'em up really quick. Our support model is we have in theater support people. So they're in Europe, they're in APAC, they're in the US, et cetera. And we assign customers to the support people. So they deal with the same support person all the time. So everything is scalable. So right now we're going to open up India. It's the same way we've opened up every other country. Once you've got the McDonald's formula we just stamp it all over the world. >> That's amazing. >> Same pricing, same product same model, same everything. >> So what was the inspiration for that? I mean, you've done this since day one, which is what like 15, 16 years ago. Or just you do engineering or? >> No, so our whole thought was, first of all you can't survive anymore in this world without being an international company. 'Cause if you're going to go after large companies they have offices all over the world. We have companies now that have 17, 18, 20, 30 locations. And there were in every country in the world, you can't go into this business without being able to ship anywhere in the world and support it for a single customer. You're not going into Singapore because of that. You're going to Singapore because some company in Germany has offices in the U.S, Mexico Singapore and Australia. You have to be international. It's a must now. So that was the initial thing is that, our goal is to become a billion dollar company. And we're on path to do that, right. >> You can see a billion. >> Well, I can absolutely see a billion. And we're bigger than everybody thinks. Everybody guesses our revenue always guesses low. So we're bigger than you think. The reason why we don't talk about it is we don't need to. >> That's the headline for our writers, ExaGrid is a billion dollar company and nobody's know about it. >> Million dollar company. >> On its way to a billion. >> That's right. >> You're not disclosing. (Bill laughing) But that's awesome. I mean, that's a great story. I mean, you kind of are a well kept secret, aren't you? >> Well, I dunno if it's a well kept secret. You know, smaller companies never have their awareness of big companies, right? The Dells of the world are a hundred billion. IBM is 70 billion, Cisco is 60 billion. Easy to have awareness, right? If you're under a billion, I got to give a funny story then I think we got to close out here. >> Oh go ahead please. >> So there's one funny story. So I was talking to the CIO of a super large Fortune 500 company. And I said to him, "Just so who do you use?" "I use IBM Db2, and I use, Cisco routers, and I use EMC primary storage, et cetera. And I use all these big." And I said, "Would you ever switch from Db2?" "Oh no, the switching costs would kill me. I could never go to Oracle." So I said to him, "Look would you ever use like a Pure Storage, right. A couple billion dollar company." He says, "Who?" >> Huh, interesting. >> I said to him, all right so skip that. I said, "VMware, would you ever think about going with Nutanix?" "Who?" Those are billion dollar plus companies. And he was saying who? >> Public companies. >> And he was saying who? That's not uncommon when I talk to CIOs. They see the big 30 and that's it. >> Oh, that's interesting. What about your partnership with Veeam? Tell us more about that. >> Yeah, so I would actually, and I'm going to be bold when I say this 'cause I think you can ask anybody here at the conference. We're probably closer first of all, to the Veeam sales force than any company there is. You talk to any Veeam sales rep, they work closer with ExaGrid than any other. Yeah, we are very tight in the field and have been for a long time. We're integrated with the Veeam Data Boomer. We're integrated with SOBR. We're integrated with all the integrations or with the product as well. We have a lot of joint customers. We actually do a lot of selling together, where we go in as Veeam ExaGrid 'cause it's a great end to end story. Especially when we're replacing, let's say a Dell Avamar to Dell Data Domain or a Dell Network with a Dell Data Domain, very commonly Veeam ExaGrid go in together on those types of sales. So we do a lot of co-selling together. We constantly train their systems engineers around the world, every given week we're training either inside sales teams, and we've trained their customer support teams in Columbus and Prague. So we're very tight with 'em we've been tight for over a decade. >> Is your head count public? Can you share that with us? >> So we're just over 300 employees. >> Really, wow. >> We have 70 open positions, so. >> Yeah, what are you looking for? Yeah, everything, right? >> We are looking for engineers. We are looking for customer support people. We're looking for marketing people. We're looking for inside sales people, field people. And we've been hiring, as of late, major account reps that just focus on the Fortune 500. So we've separated that out now. >> When you hire engineers, I mean I think I saw you were long time ago, DG, right? Is that true? >> Yeah, way back in the '80s. >> But systems guy. >> That's how old I am. >> Right, systems guy. I mean, I remember them well Eddie Castro and company. >> Tom West. >> EMV series. >> Tom West was the hero of course. >> The EMV 4000, the EMV 20,000, right? >> When were kids, "The Soul of a New Machine" was the inspirational book but anyway, >> Yeah Tracy Kidder, it was great. >> Are you looking for systems people, what kind of talent are you looking for in engineering? >> So it's a lot of Linux programming type stuff in the product 'cause we run on a Linux space. So it's a lot of Linux programs so its people in those storage. >> Yeah, cool, Bill, hey, thanks for coming on to theCUBE. Well learned a lot, great story. >> It's a pleasure. >> That was fun. >> Congratulations. >> Thanks. >> And good luck. >> All right, thank you. >> All right, and thank you for watching theCUBE's coverage of VeeamON 2022, Dave Vellante for Dave Nicholson. We'll be right back right after this short break, stay with us. (soft beat music)

>>Welcome back to Los Angeles, Lisa Martin and Dave Nicholson here on day three of the cubes, coverage of coop con and cloud native con north America, 21, Dave, we've had a lot of great conversations. The last three days it's been jam packed. Yes, it has been. And yes, it has been fantastic. And it's been live. Did we mention that it's inline live in Los Angeles and we're very pleased to welcome one of our alumni back to the program. David Stephanie is here. The CEO of Trulio David. Welcome back. It's good to see you. >>Thanks for having me. It's good to be here. Isn't it great to be in person? Oh man. It's been a reunion. >>It hasn't been a reunion and they have Ubered been talking about these great little, have you seen these wristbands that they have? I actually asked >>For two, cause I'm a big hugger, so >>Excellent. So, so here we are day three of coupon. That's actually probably day five, our third day of coverage. I'm losing track to it's Friday. I know that, that I can tell you, you guys announced two dot five a couple of weeks ago. Tell us what's in that. What's exciting. Before we crack open Twilio, uh, choy. >>Sure, sure. Well, it's been exciting to be here. Look, the theme right of resiliency realize has been it's right up our wheelhouse, right? To signal that more people are getting into production type of environments. More people require data protection for cloud native applications, right? And, uh, there's two dot five releases. It is as an answer to what we're seeing in the market. It really is centered predominantly around, uh, ransomware protection. And uh, you know, for us, when we look at this, I I've done a lot of work in, in cybersecurity, my career. And we took a hard look about a year ago around this area. How do we do this? How do we participate? How do we protect and help people recover? Because recovery that's part of the security conversation. You can talk about all the other things, but recovery is just as important. And we look at, uh, everything from a zero trust architecture that we provide now to adhering, to NIST standards and framework that's everything from immutability. Uh, so you can't touch the backups now, right? Uh, th that's fine to encryption, right? We'll encrypt from the application all the way to that, to the storage repository. And we'll leverage Keem in that system. So it's kind of like Bitcoin, right? You need a key to get your coin. You as an end-user only have your key to your data alone. And that's it. So all these things become more and more important as we adopt more cloud native technology. And >>As the threat landscape changes dramatically. >>Oh yeah. I got to tell you right. Every time we, you, you publish an application into another cloud, it's a new vector, right? So now I'm living in a multi-cloud world where multiple applications in my data now lives, right? So people are trying to attack backups through, uh, consoles and the ministry of consoles to the actual back of themselves. So new vectors, new problems need new solutions. >>And you mentioned, you mentioned something, you, you, you asked the question, how do we participate? And we are here at KU con uh, w uh, cloud native foundation. So what about, what's your connection to the open source community and efforts there? How do you participate in that? >>Yeah, so it's a really great question because, you know, uh, we are a closed source solution that focuses all of our efforts on the open source community and protecting cloud native applications. Our roots have been protecting cloud native applications since 2013, 2014, and with a lot of very large logos. And, um, you know, through time there are open source projects that do emerge, you know, in this community. And for example, Valero is an open source data protection platform, um, for all of its goodness, as a, as a community-based project, they're also deficiencies, right? So Valero in itself is, uh, focuses only on label based applications. It doesn't really scale. It doesn't have a UI it's really CLI driven, which is good for some people and it's free. But you know, if you need to really talk about an enterprise grade platform, this is where we pick up, you know, we, in our last release, we gave you the ability to capture your Valero based backups. And now you want to be an adult with an enterprise caliber, you know, backup solution and continue to protect your environment and have compliance and governance needs all satisfied. That's where, that's where we really stand out. >>Well, when you're talking to customers in any industry, what are the things that you talk about in terms of relief, categorizing the key differentiators that really make Trulia stand out above the competition? >>Yeah. Cause there, there a bunch of, they're a bunch of great competitors out there. There's no doubt about it. A lot of the legacy folks that you do see perhaps on those show floor, they do tuck in Valero and under the, under the covers, they can check a box or you can set aside some customer needs some of the pure play people that, that we do see out there, great solutions too. But really where we shine is, you know, we are the most flexible agnostic solution that there is in this market. And we've had people like red hat and Susa and verandas, digital ocean and HPS morale. And the list goes on, certify, say, Trulio is the solution of choice. And now no matter where you are in this journey or who you're using, we have your back. So there's a lot of flexibility. There we are complete storage agnostic. >>We are cloud agnostic in going back to how you want to build our architecture application. People are in various phases in their, in their journey. A lot of times, many moons ago, you may have started with just a label based application. Then you have another department that has a new technique and they want to use helm, or you may be adopting open shift and you're using operators to us. It doesn't matter. You have peace of mind. So whether you have, you have to protect multiple departments or you as an end user, as one single tenant are using various techniques, we'll discover or protect and we can move forward. >>So if you looked at, if you look at it from a workload basis, um, and you look at your customers are the workloads that you're protecting. What's, what's the mix of what you think of as legacy virtualized things versus containerized things. And then, and then, and then the other kind of follow on to that is, um, are you seeing a lot of modernization and migration or are you seeing people leave the legacy things alone and then develop net new in sort of separate silos? >>Yeah. So that's a great question. And I, to tell you the answer varies, that's, that's the honest answer, right? You end up having, you may have a group or a CIO that says, look, your CTO says, we're moving to this new architecture. The water's great, bring your applications in. And so either it's, we're going to lift and shift an application and then start to break it apart over time and develop microservices, or we're gonna start net new. And it really does run, run the gambit. And so, you know, as we look at, for some of those people, they have peace of mind that they can bring their two on applications in and we can recover. And for some people that say, look, I'm going to start brand new, and these are gonna be stateless applications. Um, we've seen this story before, right? Our, our, uh, uh, I joke around, it's kinda like the movie Groundhog's day. >>Uh, you know, we, we started many moons ago within the OpenStack world and we started with stateless to stateful. Always, always, always finds a way, but for the stateless people, um, when you start thinking about security, I've had conversations with CSOs around the world who say, I'm going to publish a stainless application. What I'm concerned about things like drift, you know, what's happening in runtime may be completely different than what I intended. So now we give you the ability to capture that runtime state compare. The two things identify what's changed. If you don't like what you see, and you can take that point in time recovery into a sandbox and forensically take it apart. You know, one of our superpowers, if you will, is the, our point in time, backups are all in an open format. Everyone else has proprietary Schemos. So the benefit of an open format is you have the ability to leverage a lot of third party tooling. So take a point in time, run scanners across it. And it, God forbid Trulio goes away. You still have access and you can recreate a point in time. So when you start thinking about compliance, heavy environments, think about telcos, right? Or financial institutions. They have to keep things for 15 years, right? Technologies change, architectures change. You can't have that lock-in >>So we continue to thrive. And on that front, one of the marketing terms that we hear a lot, and I want to get your opinion on this as a feature proofing, how do you, what does, what does it mean to you and Trillium and how do you enable that for organizations, like you said, for the FSI is I have to keep data for 15 years and other industries that have to keep it for maybe even longer. >>I mean, right. The future proof, uh, you know, terminology, that's part of our mantra actually, when I talked about, you know, a superpower being as agnostic and flexible as can be right, as long as you adhere to standards, right? The standards that are out here, we have that agnostic play. And then again, not just capturing an applications, metadata data, but that open format, right? Giving you that open capability to unpack something. So you're not, there is no, there is no vendor lock-in with us at all. So all these things play a part into, into future-proofing yourself. And because we live and breathe cloud native applications, you know, it's not just Kubernetes right? Over the course of time, there'll be other things, right. You're going to see mixed workloads too. They're gonna be VM based in the cloud and container based in the cloud and server lists as well. But you, as long as you have that framework to continuously build off of it, that's, that's where we go. You know, uh, it shouldn't matter where your application lives, right? At the end of the day, we will protect the application and its data. It can live anywhere. So conversations around multi-cloud change, we start to think and talk across cloud, right? The ability to move your application, your data, wherever it, wherever it needs to be to. >>Well, you talked about recoverability and that is the whole point of backing up video. You have to be able to recover something that we've seen in the last 18, 19 months. Anyone can backup >>Data. >>That's right. That's right. If you can't recover it, or if you can't recover it in time. Yeah. We're talking like going on a business potential and we've seen the massive changes in the security landscape in the last 18, 19 months ransomware. I was looking at some, some cybersecurity data that showed that just in the first half of this calendar year, January one to June 30, 20, 21, ransomware was up nearly 11 X DDoS attacks are up. We've got this remote workforce. That's going to probably persist for a while. So the ability to recover data from not if we get hit by ransomware, but when we get hit by ransomware is >>When you're, you're absolutely right. And, and, and to your plate anyway. So anyone can back up anything. When you look at it, it's at its highest form. We talk about point time where you orchestration, right. Backup is a use case. Dr. Is a use case, right? How do you, reorchestrate something that's complex, right? The containers, these applications in the cloud native space, there are morphous, they're living things, right? The metadata is different from one day to the next, the data itself is different from when one day the net to the next. So that's, what's so great about Trillium. It's such an elegant solution. It allows your, reorchestrate a point in time when and where you need it. So yes. You have to be able to recover. Yes. It's not a matter of if, but when. Right. And that's why recovery is part of that security conversation. Um, you know, I I've seen insurance companies, right? They want to provide insurance for ransomware. Well, you're gonna have enough attacks where they don't want to provide that insurance anymore. It costs too much. The investment that you make with, with Trulio will save you so much more money down the road. Right. Uh, who's our product manager actually gave a talk about that yesterday and the economics were really interesting. >>Hmm. So how has the recovery methodology who participates in that changed over time? As, as we, you know, as we are in this world of developer operators who take on greater responsibility for infrastructure things. Yeah. Who's, who's responsible for backup and recovery today and how, how has that changed >>Everyone? Everyone's responsible. So, you know, we rewind however many years, right? And it used predominantly CIS admin that was in charge of backup administrator, but a ticket in your backup administrator, right. Cloud native space and application lifecycle management is a team sport. Security is a team sport. It's a holistic approach. Right? So when you think about the, the team that you put out on the field, whether your DevOps, your SRE dev sec ops it ops, you're all going to have a need for point in time, we orchestration for various things and the term may not be backup. Right? It's something else. And maybe for test dev purposes, maybe for forensic purposes, maybe for Dr. Right. So I say it's a team sport and security as a holistic thing that everyone has to get on board with >>The three orchestration is exactly the right way to talk about absolute these processes. It's not just recovery, you're rebuilding >>Yeah. A complex environment. It's always changing. >>That's one of the guarantees. It's always going to be changing >>That much. >>Can you give us a, leave us with a customer example that you think really articulates the value of what Trulio delivers? >>Yeah. So it's interesting. I won't say who the customer is, but I'll tell you it's in the defense agency, it's a defense agency. Uh, they have developers all over the place. Uh, they need self-service capabilities for the tenants to mind their own backups. So you don't need to contact someone, right. They can build, they have one >>Dashboard, single pane of glass or truth to manage all their Corinthians applications. And it gives them that infrastructure to progress whether your dev ops or not your it ops, uh, this, this group has rolled it out across the nation and they're using in their work with very sensitive environments. So now we have they're back. And what are some of the big business outcomes that they're achieving already? >>The big business outcomes? Well, so operational efficiencies are definitely first and foremost, right? Empowering the end user with more tools, right? Because we've seen this shift left and people talking about dev ops, right. So how do I empower them to do more? So I see that operational efficiency, the recoverability aspect, God forbid, something goes wrong. How do you, how do you do that in the cost of that? Um, and then also, um, being native to the environment, the Trillium solution is built for Kubernetes. It is built on go. It is a Qubit stateless Kubernetes application. So you have to have seamless integration into these environments. And then going back to what I was saying before, knowing peace of mind, the credibility aspect, that it is blessed by, you know, red hat and suicide Mirandas and all these other, other folks in the field, um, that you can guarantee it's going to work >>Well, that helps to give your customers the confidence that there, and that confidence might sound trivial. It's not, especially when we're talking about security, it's not at all that, that's a, that's a big business outcome for you guys. When a customer says, I'm confident I have the right solution, we're going to be able to recover when things happen, we try, we fully trust in the solution that we're, >>And we'll bring more into production faster that helps everyone out here too. Right? It feels good. You have that credibility. You have that assurance that I can move faster and I can move into different clouds faster. And that's, we're gonna continue to put, we're gonna continue to push the envelope there. You know, coming a, as we look into, you know, going forward, we're going to come out with other capabilities. That's going to continue to differentiate ourselves from, from folks. Uh, we'll, we'll talk about in time, the ability to propagate data across multiple clouds simultaneously. So making RTOs look at the split seconds and minutes. And so I hope that we can have that conversation next time we were together, because it's really exciting. >>Any, any CTA that you want to give to the audience, any, any, uh, like upcoming or recent webinars that you think they would be really benefit from? >>I guess one thing I put out there is that, um, I understand that people need to continuously learn. There is a skillset hole in, in this market. We can, we understand that, you know, and people look to us as not just a vendor, but a partner. And a lot of the questions that we do get are how do I do this? Or how do I do that? Engage us, ask us to consume our product is really, really easy. You can download from the website or go to an, you know, red hats operator hub, or go to the marketplace over at Susa, and let's begin to begin and we're here to help. And so reach out, right? We want everyone to be successful. >>Awesome. trillium.io. David, thank you for joining us. This has been an exciting conversation. Good >>To see you all. >>Likewise. Good to see you in person take care. We look forward to the next time we see you when unpacking what other great things are going on on Trulia. We appreciate your >>Time. Thank you so much. Good to be here >>For David's fie and David Nicholson, the two Davids I'm going to sandwich. I'm Lisa Martin, you we're coming to you live from Los Angeles. This is Q con cloud native con north America, 2021. Stick around our next guest joins us momentarily.

>>We are coming out of a year, like none other and organizations of all types of pressing forward with planning for the future now in the realm of it. And really every industry, no single topic is getting as much attention as digital transformation. Every organization and industry defines digital transformation differently based on the outcomes that they're looking for from creating a digital first business models to driving greater operational efficiency or accelerating innovation by extracting better insights from their data, regardless of how they define their next stage of business. They must all pursue a path of infrastructure, hardware, and software modernization with trusted partners that have the technology and expertise to deliver successful outcomes at HPS accelerating next event. On April 21st, we have a really compelling lineup of industry luminaries. Pat Gelsinger is setting a new and bold direction for Intel. John Chambers is now investing in game changing and society changing tech, Dr. >>Lisa SU who's the CEO of AMD. That's a company that completely transformed itself and become a critical technology supplier for compute solutions. And of course, HPS CEO, Antonio Neary. These execs will be sharing their perspectives on what's next in the market. We'll also have HPE leaders and experts providing details on new requirements, being driven by the defining workloads of the digital era and what capabilities and expertise are needed to enable great future outcomes. We'll also hear directly from some of HP's customers that are on their own path to transformation and how they are accelerating next. This is Dave Volante, inviting you to join us on the 21st of April at 11:00 AM. Eastern time, 8:00 AM Pacific and join the conversation. We'll see you there.

>>Welcome everyone to a day in the life of data with HPE as well. Data fabric, the session is being recorded and will be available for replay at a later time. When you want to come back and view it again, feel free to add any questions that you have into the chat. And Chad and I joined stark. We'll, we'll be more than willing to answer your questions. And now let me turn it over to Jimmy Bates. >>Thanks. Uh, let me go ahead and share my screen here and we'll get started. >>Hey everyone. Uh, once again, my name is Jimmy Bates. I'm a director of solutions architecture here for HPS Merle in the Americas. Uh, today I'd like to walk you through a journey on how our everyday life is evolving, how everything about our world continues to grow more connected about, and about how here at HPE, how we support the data that represents that digital evolution for our customers, with the HPE as rural data fabric to start with, let's define that term data. The concept of that data can be simplified to a record of life's events. No matter if it's personal professional or mechanical in nature, data is just records that represent and describe what has happened, what is happening or what we think will happen. And it turns out the more complete record we have of these events, the easier it is to figure out what comes next. >>Um, I like to refer to that as the omnipotence protocol. Um, let's look at this from a personal perspective of two very different people. Um, let me introduce you to James. He's a native citizen of the digital world. He's, he's been, he's been a citizen of this, uh, an a career professional in the it world for years. He's always on always connected. He loves to get all the information he needs on a smartphone. He works constantly with analytics. He predicts what his customers need, what they want, where they are, uh, and how best to reach them. Um, he's fully embraced the use of data in his life. This is Sue SCA. She's, she's a bit of a, um, of an opposite to James. She's not yet immigrated to our digital world. She's been dealing with the changes that are prevalent in our times. And she started a new business that allows her customers, the option of, um, of expressing their personalities and the mask that they wear. She wants to make sure her customers can upload images, logos, and designs in order to deliver that customized mask, uh, to brighten their interactions with others while being safe as they go about their day. But she needs a crash course in digital and the digital journey. She's recently as, as most of us have as transitioned from an office culture to a work from home culture, and she wants to continue to grow that revenue venture on the side >>At the core of these personalities is a journey that is, that is representative common challenge that we're all facing today. Our world has been steadily shrinking as our ability to reach out to one another has steadily increased. We're all on that journey together to know more about what is happening to be connected to what our business is doing to be instantly responsive to our customer needs and to deliver that personalized service to every individual. And it as moral, we see this across every industry, the challenge of providing tailored experiences to potential customers in a connected world to provide constant information on deliveries that we requested or provide an easier commute to our destination to, to change the inventories, um, to the just-in-time arrival for our fabrications to identify quality issues in real time to alter the production of each product. So it's tailored to the request of the end user to deliver energy in, in smarter, more efficient ways, uh, without injury w while protecting the environment and to identify those, those, uh, medical emerging threats, and to deliver those personalized treatments safely. >>And at the core of all of these changes, all of these different industries is data. Um, if you look at the major technology trends, um, they've been evolving down this path for some time now, we're we're well into our cloud journey. The mobile platform world is, is now just part of our core strategies. IOT is feeding constant streams of data often over those mobile, uh, platforms. And the edge is increasingly just part of our core, all of this combined with the massive amounts of data that's becoming, becoming available through it is driving autonomous solutions with machine learning and AI. Uh, this is, this is just one aspect of this, this data journey that we're on, but for success, it's got, uh, sorry for success. It's got to be paired. Um, it's gotta be paired with action. >>Um, >>Well, when you look at the, uh, um, if we take a look at James and Cisco, right, we can start to see, um, with the investments in those actions, um, how their travel they're realizing >>Their goals, >>Services, efforts, you know, uh, focused, deliver new data-driven applications are done in new ways that are smaller in nature and kind of rapidly iterate, um, to respond to the digital needs of, of our new world, um, containerization to deploy and manage those apps anywhere in our connected world, they need to be secure we'll time streaming architecture, um, from, from the, from the beginning to allow for continual interactions with our changing customer demands and all of this, especially in our current environment, while running cost reduction initiatives. This is just the current world that, that our solutions must live in. Um, with that framework in mind, um, I'd like to take the remainder of our time and kind of walk through some of the use cases where, where we at HPE helped organizations through this journey with, with, with the ASML data fabrics, >>Let's >>Start with what's happening in the mobile world. In fact, the HPE as moral data fabric is being used by a number of companies to provide infinitely personalized experiences. In this case, it could be James could be sushi. It could be anyone that opens up their smartphone in the morning, uh, quickly checking what's transpiring in the world with a selection of curated, relative relevant articles, images, and videos provided by data-driven algorithm workloads, all that data, the logs, the recommendations, and the delivery of those recommendations are done through a variety of companies using HP as rural software, um, that provides a very personalized experience for our users. In addition, other companies monitor the service quality of those mobile devices to ensure optimize connectivity as they move throughout their day. The same is true for digital communication for that video communication, what we're doing right now, especially in these days where it's our primary method of connecting as we deal with limited physical engagements. Um, there's been a clear spike in the usage of these types of services. HPE, as Merle is helping a number of these companies deliver on real time telemetry analysis, predicting demand, latency, monitoring, user experience, and analyzing in real time, responding with autonomous adjustments to maintain pleasant experiences for all participants involved. >>Um, >>Another area, um, we're eight or HBS ML data fabric is playing a crucial role in the daily experience inside our automobiles. We invest a lot of ourselves in our cars. We expect tailored experiences that help us stay safe and connected as we move from one destination to another, in the areas of autonomous driving connected car, a number of major car companies in the world are using our data fabric to take autonomous driving to the next level where it should be effectively collecting all data from sensors and cameras, and then feeding that back into a global data fabric. So that engineers that develop cars can train next generation, future driving algorithms that make our driving experience safer and more autonomy going forward. >>Now let's take a look at a different mode of travel. Uh, the airline industry is being impaired. Varied is being impacted very differently today from, from the car companies, with our software, uh, we help airlines travel agencies, and even us as consumers deal with pricing, calculations and challenges, uh, with, um, air traffic services. We, we deal with, um, um, uh, delivering services around route predictions on time arrivals, weather patterns, and tagging and tracking luggage. We help people with flight connections and finding out what the figuring out what the best options are for your, for your travel. Uh, we collect mountains of data, secure it in a global data fabric, so it can provide, be provided back in an analyzed form with it. The stressed industry can contain some very interesting insights, provide competitive offerings and better services to us as travelers. >>This is also true for powering biometrics. At scale, we work with the biggest biometrics databases in the world, providing the back end for their enormous biometric authentication pursuit. Just to kind of give you a rough idea. A biometric authentication is done with a number of different data points from fingerprints. I re scans numerous facial features. All of these data points are captured for every individual and uploaded into the database, such that when the user is requesting services, their biometric metrics can be pooled and validated in seconds. From a scale perspective, they're onboarding 1 million people a day more than 200 million a year with a hundred percent business continuity and the options do multi-master and a global data fabric as needed ensuring that users will have no issues in securely accessing their pension payouts medical services or what other types of services. They may be guaranteed >>Pivoting >>To a very different industry. Even agriculture was being impacted in digital ways. Using HPE as well, data fabric, we help farmers become more digital. We help them predict weather patterns, optimize sea production. We even helped see producers create custom seed for very specific weather and ground conditions. We combine all of these things to help optimize production and ensure we can feed future generations. In some cases, all of these data sources collected at the edge can be provided back to insurance companies to help farmers issue claims when micro patterns affect farmers in negative ways, we all benefit from optimized farming and the HBS Modena fabric is there to assist in that journey. We provide the framework and the workload guidance to collect relevant data, analyze it and optimize food production. Our customers demonstrate the agricultural industry is most definitely my immigrating to our digital world. >>Now >>That we've got the food, we need to ship it along with everything else, all over the world, as well as offer can be found in action in many of the largest logistics companies in the world. I mean, just tracking things with greater efficiency can lead to astounding insights. What flights and ships did the package take? What Hans held it along its journey, what weather conditions did it encounter? What, what customs office did it go through and, and how much of it's requested and being delivered this along with hundreds of other telemetry points can be used to provide very accurate trade and economic predictions around what's going on with trade in the world. These data sets are being used very intensively to understand economy conditions and plan for future event consequences. We also help answer, uh, questions for shipping containers that are, that are more basic. Uh, like where is my container located at is my container still on the correct ship? Uh, surprisingly, uh, this helps cut down on those pesky little events like lost containers. >>Um, it's astounding the amount of data that's in DNA, and it's not just the pairs. It's, it's the never ending patterns found with other patterns that none of it can be fully understood unless the micro is maintained in context to the macro. You can't really understand these small patterns unless you maintain that overall understanding of the entire DNA structure to help the HVS mold data fabric can be found across every aspect of the medical field. Most recently was there providing the software framework to collect genomic sequencing, landing it in the data fabric, empowering connected availability for analysis to predict and find patterns of significance to shorten the effort it takes to identify those potential triggers and make things like vaccines become becoming available. In record time. >>Data is about people at HPE asthma. We keep people connected all around the world. We do this in a variety of ways. We we've already looked at several of the ways that that happens. We help you find data. You need, we help you get from point a to point B. We help make sure those birthday gifts show up on time. Some other interesting ways we connect people via recipes, through social platforms and online services. We help people connect to that new recipe that is unexpected, but may just be the kind of thing you need for dinner tonight at HPDs where we provide our customers with the power to deliver services that are tailored to the individual from edge to core, from containers to cloud. Many of the services you encounter everyday are delivered to you through an HV as oral global data fabric. You may not see it, but we're there in the morning in the morning when you get up and we're there in the evening. Um, when you wind down, um, at HPE as role, we make data globally available across everywhere that your business needs to go. Um, I'd like to thank everyone, uh, for the time that you've given us today. And I'd like to turn it back over and open up the floor for questions at this time, >>Jimmy, here's a question. What are the ways consumers can get started with HPS >>The fabric? Well, um, uh, there's several ways to get started, right? We, we, uh, first off we have software available that you can download that there's extensive documentation and use cases posted on our website. Um, uh, we have services that we offer, like, um, assessment services that can come in and help you assess the, the data challenges that you're having, whether you're, you're just dealing with a scale issue, a security issue, or trying to migrate to a more containerized approach. We have a services to help you come in, assess that aspect. Um, we have a getting started bundles, um, and we have, um, so there's all kinds of services that, that help you get started on your journey. So what >>Does a typical first deployment look like? >>Well, that's, that's a very, very interesting question. Um, a typical first deployment, it really kind of varies depending on where you're at in the material. Are you James? Are you, um, um, Cisco, right? It really depends on, on where you're at in your journey. Um, but a typical deployment, um, is, is, is involved. Uh, we, we like to come in, we we'd like to do workshops, really understand your specific challenges and problems so that we can determine what solutions are best for you. Um, that to take a look at when we kind of settle on that we, we, um, the first deployment, uh, is, um, there's typically, um, a deployment of, uh, a, uh, a service offering, um, w with a software to kind of get you started along the way we kind of bundle that aspect. Um, as you move forward, if you're more mature and you already have existing container solutions, you already have existing, large scale data aspects of it. Um, it's really about the specific use case of your current problem that you're dealing with. Um, every solution, um, is tailored towards the individual challenges and problems that, that each one of us are facing. >>I break, they mentioned as part of the asthma family. So how does data fabric pair with the other solutions within Israel? >>Well, so I like to say there's, um, there, there's, there's three main areas, um, from a software standpoint, um, for when you count some of our, um, offerings with the GreenLake solution, but there are, so there are really four main areas with ESMO. There's the data fabric offering, which is really focused on, on, on, on delivering that data at scale for AI ML workloads for big data workloads for containerized workloads. There is the ESMO container platform, which really solves a lot of, um, some of the same problems, but really focus more on a compute delivery, uh, and a hundred percent Kubernetes environment. We also have security offerings, um, which, which help you take in this containerized world, uh, that help you take the different aspects of, um, securing those applications. Um, so that when the application, the containerized applications move from one framework or one infrastructure from one to the other, it really helps those, the security go with those applications so that they can operate in a zero trust environment. And of course, all of this, uh, options of being available to you, where everything has a service, including the hardware through some of our GreenLake offerings. So those are kind of the areas that, uh, um, that pair with the HPE, um, data fabric, uh, when you look at the entire ESMO pro portfolio. >>Well, thanks, Jimmy really appreciate it. That's all the questions we have right now. So is there anything that you'd like to close with? >>Uh, you know, the, um, I I'm, I find it I'm very, uh, I'm honored to be here at HPE. Um, I, I really find it, it's amazing. Uh, as we work with our customers solving some really challenging problems that are core to their business, um, it's, it's always an interesting, um, interesting, um, day in the office because, uh, every problem is different because every problem is tailored to the specific challenges that our customers face. Um, while they're all will well, we will, what we went over today is a lot of the general areas and the general concepts that we're all on together in a journey, but the devil's always in the details. It's about understanding the specific challenges in the organization and, and as moral software is designed to help adapt, um, and, and empower your growth in your, in your company. So that you're focused on your business, in the complexity of delivering services across this connected world. That's what as will takes off your plate so that you don't have to worry about that. It just works, and you can focus on the things that impact your business more directly. >>Okay. Well, we really thank everyone for coming today and hope you learned, uh, an idea about how data fabric can begin to help your business with it. All of a sudden analytics, thank you for coming. Thanks.

>> Narrator: From around the globe, it's theCUBE, covering HPE Discover Virtual Experience brought to you by HPE. >> Hi, and welcome back to theCUBE's coverage of HPE Discover 2020 the virtual experience. I'm your host Stu Miniman. I'm really happy to be joined on the program two of our CUBE alumni, we have the Daves from Hewlett Packard labs. Sitting in the screen next to me is Dave Husak he is a fellow and general manager for the Cloudless Initiative. And on the other side of the screen, we have Dave Larson, vice president and CTO of the Cloudless Initiative. Dave and Dave, thank you so much for joining us again. >> Delighted to be here. >> All right, so specifically we're going to be talking a bit about security, obviously, you know, very important in the cloud era. And as we build our native architect, you know, Dave Husak, I guess, why don't you set the stage for us a little bit, of you know, where security fits into, you know, HPE overall and, you know, the mission that you know, last year a lot of buzz and discussion and interest around Cloudless. So just put that as a start and then we'll, get into a lot of discussion about security. >> Right yeah, last year we did, you know, launch the initiative and, you know, we framed it as, it composed of three components, one of which in fact, the most important aspect of which it was the trust fabric Cloudless Trust Fabric, which was you know, built on the idea of intrinsic security for all workload end points, right. And this is a theme that you see playing out, you know, a year later playing out, I think across the industry. You hear that language and that, you know, that kind of idea of being promoted in the context of zero trust, you know, new capabilities being launched by VMware and other kinds of runtime environments, right. And you know, the way I like to say it is that we have entered an era of security first in IT infrastructure. It's no longer going to be practical to build IT infrastructure and then, you know, have products that secure it, right. You know, build perimeters, do micro-segment or anything like that. Workload end points need to be intrinsically secure. And you know, the upshot of that really at this point is that all IT infrastructure companies are security companies now. The you know it, acknowledge it, like it or not, we're all security companies now. And so, you know, a lot of the principles applying in the Cloudless Trust Fabric are those zero trust principles are based on cryptographic, workload, identity, leverage unique aspects of HPs products and infrastructure that we've already been delivering with hardware and Silicon root of trust built into our reliance servers and other capabilities like that. And you know, our mission, my mission is to propel that forward and ensure that HP is, you know, at the forefront of securing everything. >> Yeah, excellent definitely, you know love the security first discussion. Every company we've talked to absolutely security is not only a sea level, but you know, typically board level discussion, I guess my initial feedback, as you would say, if every company today is a security company, many of them might not be living up to the expectation just yet So Dave Larson, let's say, you know, applications are, you know, at the core of what we've look at it in cloud native. It's new architectures, new design principles. So give us some, what is HPE thoughts and stuff, how security fits into that, and what's different from how we might've thought about security in the past the applications? Well, I think Dave touched on it, right? From a trust fabric perspective, we have to think of moving to something where the end points themselves, whether their workloads or services are actually intrinsically secure and that we can instantiate some kind of a zero trust framework that really benefits the applications. It really isn't sufficient to do intermediate inspection. In fact, the real, the primary reason why that's no longer possible is that the world is moving too encryption everywhere. And as soon as all packets are encrypted in flight, not withstanding claims to the contrary, it's virtually impossible to do any kind of inference on the flows to apply any meaningful security. But the way we see it is that the transition is moving to a modality where all services, all workloads, all endpoints can be mutually attested, cryptographically identified in a way that allows a zero trust model to emerge so that all end points can know what they are speaking to on the remote end and by authorization principals determine whether or not they're allowed to speak to those. So from a HPE perspective, the area where we build is from the bottom up, we have a Silicon root of trust in our server platform. It's part of our ILO five Integrated lights out baseboard management controller. We can actually deliver a discreet and measurable identity for the hardware and projected up into the workload, into the software realm. >> Excellent, Ty I heard you mentioned identity makes me think of the Cytel acquisition that the HPE made early this year, people in the cloud native community into CubeCon you know, SPIFFE of course, is a project that had gotten quite a bit of attention. Can give us a little bit as to how that acquisition fits into this overall discussion we were just having? >> Oh yeah, so we acquired Cytel into the initiative, beginning of this year. As you, understand Stu, right. Cryptographic identity is fundamental to zero trust security because we're no longer, like Dave pointed out we're no longer relying, on intermediary devices, firewalls, or other kinds of functions to manage, you know, authorize those communications. So the idea of building cryptographic identity into all workload endpoints, devices and data is sort of a cornerstone of any zero trust security strategy. We were delighted to bring the team on board. Not only from the standpoint that they are the world's experts, original contributors, and moderators and committers in the stewardship of SPIFFE and SPIRE the two projects in the CNCF. But you know, the impact they're going to have on the HPs product development, hardware and software is going to be outsized. And it also, you know, as a, I'll have to point this out as well, you know, It is the, this is the most prominent open source project that HP is now stewarding, right. In terms of its acceptance, of SPIFFE and SPIRE, or both poised to be I have an announcement here shortly, probably. But we expect they're going to be promoted to the incubating phase of CNCF maturity from the Sandbox is actually one of the first Sandbox projects in the CNCF. And so it's going to join that Pantheon of know, you know, top few dozen out of I think 1,390 projects in the CNCF. So like you pointed out Stu you know, SPIFFE and SPIRE are right now, you know, the world's leading candidate as, you know, sort of the certificate standard for cryptographic workload endpoint identity. And we're looking at that as a very fundamental enabling technology for this transformation, that the industry is going to go through. >> Yeah, it's really interesting if we pull on that open source thread a little bit more, you know, I think back to earlier in my career, you know, 15, 20 years ago, and if you talk to a CIO, you know, security might be important to them, but they keep what they're building and how their IT infrastructure, is something that they keep very understood. And if you were a vendor supplying to them, you had to be under NDA to understand, because that was a differentiation. Now we're talking about lifting cloud, we're talking about open source, you know, even when I talked to the financial institutions, they're all talking amongst themselves the how do we share best practices because it's not, am I secure? It's we all need to be secure. I wonder if you can comment a little bit on that trend, you know, how the role of open source. Yeah, this is an extension of Kerckhoffs's principle, right? The idea that a security system has to be secure, even if you know the system, right. That's it's only the contents of the ease in the communication letter, that are important. And that is playing out, at the highest level in our industry now, right. So it is, like I said, cryptographic identity and identity based encryption are the cornerstones of building a zero trust fabric. You know, one of the other things is, cause you mentioned that, we also observed is that the CNCF, the Apache foundation. The other thing that's, I think a contrast to 15 years ago, right back 15, 20 years ago, open source was a software development phenomenon, right. Where, you know, the usual idea, you know, there's repositories of code, you pull them down, you modify them for your own particular purposes and you upstream this, the changes and such, right. It's less about that now. It is much more a model for open source operations than it is a model for open source development. Most of the people that are pulling down those repositories unless they are using them, they're not modifying them, right. And as you also, I think understand, right. The framework of the CNCF landscape comprehensive, right? You can build an entire IT infrastructure operations environment by you know, taking storage technologies, security technologies, monitoring management, you know, it's complete, right. And it is, you know, becoming really, you know, a major operational discipline out there in the world to harness all of that development harness, the open source communities. Not only in the software, not only in the security space, but I think you know comprehensively and that engine of growth and development is I think probably the largest, you know manpower and brainpower, and you know, operational kind of active daily users model out there now, right. And, it's going to be critical. I think for the decade, this decade that's coming. That the successful IT infrastructure companies have to be very tightly engaged with those communities in that process, because open source operations is the new thing. It's like, you know DevOps became OpsDev or something like that is the trend. >> Yeah, and I'm glad you brought that up you know I think about the DevOps movement, really fused security, it can't be a bolt on it can't be an afterthought. The mantra I've heard over the last few years, is security is everyone's responsibility. Dave Larson, you know, the question I have for you is, how do we make sure, you know, policy is enforced you know, even I think about an organization everyone's responsible for it, you know, who's actually making sure that things happen because, you know, if everybody's looking after it, it should be okay. But, you know, bring us down a little bit from the application standpoint. >> Well, I would say, you know, first of all, you have to narrow the problem down, right? The more we try to centralize security with discreet appliances, that's some kind of a choke point, the explosion, the common editorial explosion of policy declaratives that are necessary in order to achieve that problem to achieve the solution becomes untenable, right? There is no way to achieve the right kind of policy enforcement unless we get as close to the actual workloads themselves, unless we implement a zero trust model where only known and authorized end points are allowed to communicate with each other, you know. We've lived with a really unfortunate situation in the internet at large, for the last couple of decades where an IP address is both a location and an identifier. This is problem because that can be abused. it's something that can be changed. It's something that is easily spoofed, and frankly the nature of that element of the way we connect applications together is the way that almost virtually all exploits, get into the environment and cause problems. If we move to a zero trust model where the individual end points will only speak with only respond to something that is authorized and only things that are authorized and they trust nothing else, we eliminate 95 to 99% of them problem. And we are in an automated stance that will allow us to have much better assurance of the security of the connections between the various endpoints and services. >> Excellent, so, you know, one of the questions that always comes up, some of the pieces we're talking about here are open source. You talk about security and trust across multiple environments. How does HPE differentiate from, you know, everything else out there and, you know, how are you taking the leadership position? I'd love to hear both of your commentary on that. >> Yeah, well, like I said, initially, the real differentiation for us is that HPE was the market leader for industry standard servers, from a security perspective. Three years ago in our ProLiant gen 10 servers, when we announced them, they had the Silicon root of trust and we've shipped more than a million and a half servers into the market with this capability that is unique in the market. And we've been actively extending that capability so that we can project the identity, not just to the actual hardware itself, but that we can bind it in a multi-factor sense, the individual software components that are hosted on that server, whether it's the operating system, a hypervisor, a VM, a container framework, or an actual container, or a piece of it code from a serverless perspective. All of those things need to be able to be identified and we can bring a multi-factor identity capability to individual workloads that can be the underpinning for this zero across connection capability. >> Great and David, anything you'd like to add there? >> No, like what he said I think HP is uniquely positioned you know, the depth and the breadth of our installed base of platforms that are already zero trust ready, if you will, right. Coupled with the identity technology that we're developing in the context of the Cytel acquisition and David, my work in a building, the cloudless trust fabric, you know, are the, like I said, the cornerstones of these architectures, right? And HP has a couple of unfair advantages here you know, okay breadth and depth of our, the customer base and the installed base of the system is already put out there. While the world is transitioning, you know, inevitably to these, you know, these kinds of security architectures, these kinds of IT infrastructure architectures, HP has a, you know, a leadership team position by default here that we can take advantage of. And our customers can reap the benefits of without, well, you know, without you know, rebuilding forklift upgrading, or otherwise, you know, it is, yeah as Dave talked about, you know, a lot will change, right. There's more to do, right? As we move from, you know, IP addresses and port numbers, as identities for security, because we know that perimeter security, network security like that is busted, right. It is, you know, every headline making, you know, kind of advanced persistent threat kind of vulnerabilities it's all at the root of all those problems, right. There are technologies like OPA, right you know, policy has to be reframed in the context of workload identity, not in network identity know. Like call this legal sort of the microsegmentation fallacy, right. You know that, you know, perimeters are broken, not a valid security strategy anymore. So the answer can't be, let's just draw smaller perimeters, especially since we're now filling them up with evermore, you know, dynamic evanescent kind of workload endpoints, you know, containers coming and going at a certain pace. And serverless instances, right. All of those things springing up and, and being torn down, you know, on, you know, very short life cycle that's right. It is inconceivable that traditional, you know perimeter based micro-segmentation based security frameworks can keep up with the competent tutorial explosion and the pace with which we are going to be where, you know, orchestration frameworks are going to be deploying these end points. There are, you know, there's a lot more to do, you know, but this is, the transformation story. This is of the 2020s, you know, infrastructure, IT infrastructure school is very different in two, five, 10 years from now than it does today. And you know that's you know we believe HP has, like I said, a few unfair advantages to lead the world in terms of those transformations. >> Excellent, well, appreciate the look towards the future as well as where we are today. Dave and Dave, thanks so much for joining. Thank you, Stu. >> Thanks, dude, pleasure. >> All right, we'll be back with lots more coverage. HPE Discover 2020 the Virtual Experience. I'm Stu Miniman and thank you for watching theCUBE. (upbeat music)

(orchestral music) >> Hi, I'm Peter Burris and welcome to another digital community event. As we do with all digital community events, we're gonna start off by having a series of conversations with real thought leaders about a topic that's pressing to today's enterprises as they try to achieve new classes of business outcomes with technology. At the end of that series of conversations, we're gonna go into a crowd chat and give you an opportunity to voice your opinions and ask your questions. So stay with us throughout. So, what are we going to be talking about today? We're going to be talking about the challenge that businesses face as they try to apply AI, ML, and new classes of analytics to their very challenging, very difficult, but nonetheless very value-producing outcomes associated with data. The challenge that all these businesses have is that often, you spend too much time in the infrastructure and not enough time solving the problem. And so what's required is new classes of technology and new classes of partnerships and business arrangements that allow for us to mask the underlying infrastructure complexity from data science practitioners, so that they can focus more time and attention on building out the outcomes that the business wants and a sustained business capability so that we can continue to do so. Once again, at the end of this series of conversations, stay with us, so that we can have that crowd chat and you can, again, ask your questions, provide your insights, and participate with the community to help all of us move faster in this crucial direction for better AI, better ML and better analytics. So, the first conversation we're going to have is with Anant Chintamaneni. Anant's the Vice President of Products at BlueData. Anant, welcome to theCUBE. >> Hi Peter, it's great to be here. I think the topic that you just outlined is a very fascinating and interesting one. Over the last 10 years, data and analytics have been used to create transformative experiences and drive a lot of business growth. You look at companies like Uber, AirBnB, and you know, Spotify, practically, every industry's being disrupted. And the reason why they're able to do this is because data is in their DNA; it's their key asset and they've leveraged it in every aspect of their product development to deliver amazing experiences and drive business growth. And the reason why they're able to do this is they've been able to leverage open-source technologies, data science techniques, and big data, fast data, all types of data to extract that business value and inject analytics into every part of their business process. Enterprises of all sizes want to take advantage of that same assets that the new digital companies are taking and drive digital transformation and innovation, in their organizations. But there's a number of challenges. First and foremost, if you look at the enterprises where data was not necessarily in their DNA and to inject that into their DNA, it is a big challenge. The executives, the executive branch, definitely wants to understand where they want to apply AI, how to kind of identify which huge cases to go after. There is some recognition coming in. They want faster time-to-value and they're willing to invest in that. >> And they want to focus more on the actual outcomes they seek as opposed to the technology selection that's required to achieve those outcomes. >> Absolutely. I think it's, you know, a boardroom mandate for them to drive new business outcomes, new business models, but I think there is still some level of misalignment between the executive branch and the data worker community which they're trying to upgrade with the new-age data scientists, the AI developer and then you have IT in the middle who has to basically bridge the gap and enable the digital transformation journey and provide the infrastructure, provide the capabilities. >> So we've got a situation where people readily acknowledge the potential of some of these new AI, ML, big data related technologies, but we've got a mismatch between the executives that are trying to do evidence-based management, drive new models, the IT organization who's struggling to deal with data-first technologies, and data scientists who are few and far between, and leave quickly if they don't get the tooling that they need. So, what's the way forward, that's the problem. How do we move forward? >> Yeah, so I think, you know, I think we have to double-click into some of the problems. So the data scientists, they want to build a tool chain that leverages the best in-class, open source technologies to solve the problem at hand and they don't want, they want to be able to compile these tool chains, they want to be able to apply and create new algorithms and operationalize and do it in a very iterative cycle. It's a continuous development, continuous improvement process which is at odds with what IT can deliver, which is they have to deliver data that is dispersed all over the place to these data scientists. They need to be able to provide infrastructure, which today, they're not, there's an impotence mismatch. It takes them months, if not years, to be able to make those available, make that infrastructure available. And last but not the least, security and control. It's just fundamentally not the way they've worked where they can make data and new tool chains available very quickly to the data scientists. And the executives, it's all about faster time-to-value so there's a little bit of an expectation mismatch as well there and so those are some of the fundamental problems. There's also reproducibility, like, once you've created an analytics model, to be able to reproduce that at scale, to be then able to govern that and make sure that it's producing the right results is fundamentally a challenge. >> Audibility of that process. >> Absolutely, audibility. And, in general, being able to apply this sort of model for many different business problems so you can drive outcomes in different parts of your business. So there's a huge number of problems here. And so what I believe, and what we've seen with some of these larger companies, the new digital companies that are driving business valley ways, they have invested in a unified platform where they've made the infrastructure invisible by leveraging cloud technologies or containers and essentially, made it such that the data scientists don't have to worry about the infrastructure, they can be a lot more agile, they can quickly create the tool chains that work for the specific business problem at hand, scale it up and down as needed, be able to access data where it lies, whether it's on-prem, whether it's in the cloud or whether it's a hybrid model. And so that's something that's required from a unified platform where you can do your rapid prototyping, you can do your development and ultimately, the business outcome and the value comes when you operationalize it and inject it into your business processes. So, I think fundamentally, this start, this kind of a unified platform, is critical. Which, I think, a lot of the new age companies have, but is missing with a lot of the enterprises. >> So, a big challenge for the enterprise over the next few years is to bring these three groups together; the business, data science world and infrastructure world or others to help with those problems and apply it successfully to some of the new business challenges that we have. >> Yeah, and I would add one last point is that we are on this continuous journey, as I mentioned, this is a world of open source technologies that are coming out from a lot of the large organizations out there. Whether it's your Googles and your Facebooks. And so there is an evolution in these technologies much like we've evolved from big data and data management to capture the data. The next sort of phase is around data exploitation with artificial intelligence and machine learning type techniques. And so, it's extremely important that this platform enables these organizations to future proof themselves. So as new technologies come in, they can leverage them >> Great point. >> for delivering exponential business value. >> Deliver value now, but show a path to delivery value in the future as all of these technologies and practices evolve. >> Absolutely. >> Excellent, all right, Anant Chintamaneni, thanks very much for giving us some insight into the nature of the problems that enterprises face and some of the way forward. We're gonna be right back, and we're gonna talk about how to actually do this in a second. (light techno music) >> Introducing, BlueData EPIC. The leading container-based software platform for distributed AI, machine learning, deep learning and analytics environments. Whether on-prem, in the cloud or in a hybrid model. Data scientists need to build models utilizing various stacks of AI, ML and DL applications and libraries. However, installing and validating these environments is time consuming and prone to errors. BlueData provides the ability to spin up these environments on demand. The BlueData EPIC app store includes, best of breed, ready to run docker based application images. Like TensorFlow and H2O driverless AI. Teams can also add their own images, to provide the latest tools that data scientists prefer. And ensure compliance with enterprise standards. They can use the quick launch button. which provides pre configured templates with the appropriate application image and resources. For example, they can instantly launch a new Sandbox environment using the template for TensorFlow with a Jupyter Notebook. Within just a few minutes, it'll be automatically configured with GPUs and easy access to their data. Users can launch experiments and make GPUs automatically available for analysis. In this case, the H2O environment was set up with one GPU. With BlueData EPIC, users can also deploy end points with the appropriate run time. And the inference run times can use CPUs or GPUs. With a container based BlueData Platform, you can deploy fully configured distributed environments within a matter of minutes. Whether on-prem, in the public cloud, or in a hybrid a architecture. BlueData was recently acquired by Hewlett Packward Enterprise. And now, HPE and BlueData are joining forces to help you on your AI journey. (light techno music) To learn more, visit www.BlueData.com >> And we're back. I'm Peter Burris and we're continuing to have this conversation about how businesses are turning experience with the problems of advance analytics and the solutions that they seek into actual systems that deliver continuous on going value and achieve the business capabilities required to make possible these advanced outcomes associated with analytics, AI and ML. And to do that, we've got two great guests with us. We've got Kumar Sreekanti, who is the co-founder and CEO of BlueData. Kumar, welcome back to theCUBE. >> Thank you, it is nice to be here, back again. >> And Kumar, you're being joined by a customer. Ramesh Thyagarajan, is the executive director of the Advisory Board Company which is part of Optum now. Ramesh, welcome to theCUBE. >> Great to be here. >> Alright, so Kumar let's start with you. I mentioned up front, this notion of turning technology and understanding into actual business capabilities to deliver outcomes. What has been BlueData's journey along, to make that happen? >> Yeah, it all started six years ago, Peter. It was a bold vision and a big idea and no pun intended on big data which was an emerging market then. And as everybody knows, the data was enormous and there was a lot of innovation around the periphery. but nobody was paying attention to how to make the big data consumable in enterprise. And I saw an enormous opportunity to make this data more consumable in the enterprise and to give a cloud-like experience with the agility and elasticity. So, our vision was to build a software infrastructure platform like VMware, specially focused on data intensity distributed applications and this platform will allow enterprises to build cloud like experiences both on enterprise as well as on hybrid clouds. So that it pays the journey for their cloud experience. So I was very fortunate to put together a team and I found good partners like Intel. So that actually is the genesis for the BlueData. So, if you look back into the last six years, big data itself has went through a lot of evolution and so the marketplace and the enterprises have gone from offline analytics to AI, ML based work loads that are actually giving them predictive and descriptive analytics. What BlueData has done is by making the infrastructure invisible, by making the tool set completely available as the tool set itself is evolving and in the process, we actually created so many game changing software technologies. For example, we are the first end-to-end content-arised enterprise solution that gives you distributed applications. And we built a technology called DataTap, that provides computed data operation so that you don't have to actually copy the data, which is a boom for enterprises. We also actually built multitenancy so those enterprises can run multiple work loads on the same data and Ramesh will tell you in a second here, in the healthcare enterprise, the multitenancy is such a very important element. And finally, we also actually contributed to many open source technologies including, we have a project called KubeDirector which is actually is our own Kubernetes and how to run stateful workloads on Kubernetes. which we have actually very happy to see that people like, customers like Ramesh are using the BlueData. >> Sounds like quite a journey and obviously you've intercepted companies like the advisory board company. So Ramesh, a lot of enterprises have mastered or you know, gotten, understood how to create data lakes with a dupe but then found that they still weren't able to connect to some of the outcomes that they saw. Is that the experience that you had. >> Right, to be precise, that is one of the kind of problems we have. It's not just the data lake that we need to be able to do the workflows or other things, but we also, being a traditional company, being in the business for a long time, we have a lot of data assets that are not part of this data lake. We're finding it hard to, how do we get the data, getting them and putting them in a data lake is a duplication of work. We were looking for some kind of solutions that will help us to gather the benefits of leaving the data alone but still be able to get into it. >> This is where (mumbles). >> This is where we were looking for things and then I was lucky and fortunate to run into Kumar and his crew in one of the Hadoop conferences and then they demonstrated the way it can be done so immediately hit upon, it's a big hit with us and then we went back and then did a POC, very quickly adapt to the technology and that is also one of the benefits of corrupting this technology is the level of contrary memorization they are doing, it is helping me to address many needs. My data analyst, the data engineers and the data scientists so I'm able to serve all of them which otherwise wouldn't be possible for me with just this plain very (mumbles). >> So it sounds as though the partnership with BlueData has allowed you to focus on activities and problems and challenges above the technology so that you can actually start bringing data science, business objectives and infrastructure people together. Have I got that right? >> Absolutely. So BlueData is helping me to tie them all together and provide an excess value to my business. We being in the healthcare, the importance is we need to be able to look at the large data sets for a period of time in order to figure out how a patient's health journey is happening. That is very important so that we can figure out the ways and means in which we can lower the cost of health care and also provide insights to the physician, they can help get people better at health. >> So we're getting great outcomes today especially around, as you said that patient journey where all the constituents can get access to those insights without necessarily having to learn a whole bunch of new infrastructure stuff but presumably you need more. We're talking about a new world that you mentioned before upfront, talking about a new world, AI, ML, a lot of changes. A lot of our enterprise customers are telling us it's especially important that they find companies that not only deliver something today but demonstrate a commitment to sustain that value delivery process especially as the whole analytics world evolves. Are you experiencing that as well? >> Yes, we are experiencing and one of the great advantage of the platform, BlueData platform that gave me this ability to, I had the new functionality, be it the TensorFlow, be it the H2O, be it the heart studio, anything that I needed, I call them, they give me the images that are plug-and-play, just put them and all the prompting is practically transparent to nobody need to know how it is achieved. Now, in order to get to the next level of the predictive and prescriptive analytics, it is not just you having the data, you need to be able to have your curated data asset set process on top of a platform that will help you to get the data scientists to make you. One of the biggest challenges that are scientist is not able to get their hands on data. BlueData platform gives me the ability to do it and ensure all the security meets and all the compliances with the various other regulated compliances we need to make. >> Kamar, congratulations. >> Thank you. >> Sounds like you have a happy customer. >> Thank you. >> One of the challenges that every entrepreneur faces is how did you scale the business. So talk to us about where you are in the decisions that you made recently to achieve that. >> As an entrepreneur, when you start a company, odds are against you, right? You're always worried about it, right. You make so many sacrifices, yourself and your team and all that but the the customer is the king. The most important thing for us to find satisfied customers like Rameshan so we were very happy and BlueData was very successful in finding that customer because i think as you pointed out, as Ramesh pointed out, we provide that clean solution for the customer but as you go through this journey as a co-founder and CEO, you always worry about how do you scale to the next level. So we had partnerships with many companies including HPE and we found when this opportunity came in front of me with myself and my board, we saw this opportunity of combining the forces of BlueData satisfied customers and innovative technology and the team with the HPs brand name, their world-class service, their investment in R&D and they have a very long, large list of enterprise customers. We think putting these two things together provides that next journey in the BlueData's innovation and BlueData's customers. >> Excellent, so once again Kumar Sreekanti, co-founder and CEO of BlueData and Ramesh Thyagarajan who is the executive director of the advisory board company and part of Optum, I want to thank both of you for being on theCUBE. >> Thank you >> Thank you, great to be here. >> Now let's hear a little bit more about how this notion of bringing BlueData and HPE together is generating new classes of value that are making things happen today but are also gonna make things happen for customers in the future and to do that we've got Dave Velante who's with Silicon Angle Wiki Bond joined by Patrick Osbourne who's with HPE in our Marlborough studio so Dave over to you. >> Thanks Peter. We're here with Patrick Osbourne, the vice president and general manager of big data and analytics at Hewlett Packard Enterprise. Patrick, thanks for coming on. >> Thanks for having us. >> So we heard from Kumar, let's hear from you. Why did HPE purchase, acquire BlueData? >> So if you think about it from three angles. Platform, people and customers, right. Great platform, built for scale addressing a number of these new workloads and big data analytics and certainly AI, the people that they have are amazing, right, great engineering team, awesome customer success team, team of data scientists, right. So you know, all the folks that have some really, really great knowledge in this space so they're gonna be a great addition to HPE and also on the customer side, great logos, major fortune five customers in the financial services vertical, healthcare, pharma, manufacturing so a huge opportunity for us to scale that within HP context. >> Okay, so talk about how it fits into your strategy, specifically what are you gonna do with it? What are the priorities, can you share some roadmap? >> Yeah, so you take a look at HPE strategy. We talk about hybrid cloud and specifically edge to core to cloud and the common theme that runs through that is data, data-driven enterprises. So for us we see BlueData, Epic platform as a way to you know, help our customers quickly deploy these new mode to applications that are fueling their digital transformation. So we have some great plans. We're gonna certainly invest in all the functions, right. So we're gonna do a force multiplier on not only on product engineering and product delivery but also go to market and customer success. We're gonna come out in our business day one with some really good reference architectures, with some of our partners like Cloud Era, H2O, we've got some very scalable building block architectures to marry up the BlueData platform with our Apollo systems for those of you have seen that in the market, we've got our Elastic platform for analytics for customers who run these workloads, now you'd be able to virtualize those in containers and we'll have you know, we're gonna be building out a big services practice in this area. So a lot of customers often talk to us about, we don't have the people to do this, right. So we're gonna bring those people to you as HPE through Point Next, advisory services, implementation, ongoing help with customers. So it's going to be a really fantastic start. >> Apollo, as you mentioned Apollo. I think of Apollo sometimes as HPC high performance computing and we've had a lot of discussion about how that's sort of seeping in to mainstream, is that what you're seeing? >> Yeah absolutely, I mean we know that a lot of our customers have traditional workloads, you know, they're on the path to almost completely virtualizing those, right, but where a lot of the innovation is going on right now is in this mode two world, right. So your big data and analytics pipeline is getting longer, you're introducing new experiences on top of your product and that's fueling you know, essentially commercial HPC and now that folks are using techniques like AI and modeling inference to make those services more scalable, more automated, we're starting to bringing these more of these platforms, these scalable architectures like Apollo. >> So it sounds like your roadmap has a lot of integration plans across the HPE portfolio. We certainly saw that with Nimble, but BlueData was working with a lot of different companies, its software, is the plan to remain open or is this an HPE thing? >> Yeah, we absolutely want to be open. So we know that we have lots of customers that choose, so the HP is all about hybrid cloud, right and that has a couple different implications. We want to talk about your choice of on-prem versus off-prem so BlueData has a great capability to run some of these workloads. It essentially allows you to do separation of compute and storage, right in the world of AI and analytics we can run it off-prem as well in the public cloud but then we also have choice for customers, you know, any customer's private cloud. So that means they want to run on other infrastructure besides HPE, we're gonna support that, we have existing customers that do that. We're also gonna provide infrastructure that marries the software and the hardware together with frameworks like Info Site that we feel will be a you know, much better experience for the customers but we'll absolutely be open and absolutely have choice. >> All right, what about the business impact to take the customer perspective, what can they expect? >> So I think from a customer perspective, we're really just looking to accelerate deployment of AI in the enterprise, right and that has a lot of implications for us. We're gonna have very scalable infrastructure for them, we're gonna be really focused on this very dynamic AI and ML application ecosystems through partnerships and support within the BlueData platform. We want to provide a SAS experience, right. So whether that's GPUs or accelerators as a service, analytics as a service, we really want to fuel innovation as a service. We want to empower those data scientists there, those are they're really hard to find you know, they're really hard to retain within your organization so we want to unlock all that capability and really just we want to focus on innovation of the customers. >> Yeah, and they spend a lot of time wrangling data so you're really going to simplify that with the cloud (mumbles). Patrick thank you, I appreciate it. >> Thank you very much. >> Alright Peter, back to you in Palo Alto. >> And welcome back, I'm Peter Burris and we've been talking a lot in the industry about how new tooling, new processes can achieve new classes of analytics, AI and ML outcomes within a business but if you don't get the people side of that right, you're not going to achieve the full range of benefits that you might get out of your investments. Now to talk a little bit about how important the data science practitioner is in this equation, we've got two great guests with us. Nanda Vijaydev is the chief data scientists of BlueData. Welcome to theCUBE. >> Thank you Peter, happy to be here. >> Ingrid Burton is the CMO and business leader at H2O.AI, Ingrid, welcome to the CUBE. >> Thank you so much for having us. >> So Nanda Vijaydev, let's start with you. Again, having a nice platform, very, very important but how does that turn into making the data science practitioner's life easier so they can deliver more business value. >> Yeah thank you, it's a great question. I think end of the day for a data scientist, what's most important is, did you understand the question that somebody asked you and what is expected of you when you deliver something and then you go about finding, what do I need for them, I need data, I need systems and you know, I need to work with people, the experts in the process to make sure that the hypothesis I'm doing is structured in a nice way where it is testable, it's modular and I have you know, a way for them to go back to show my results and keep doing this in an iterative manner. That's the biggest thing because the satisfaction for a data scientist is when you actually take this and make use of it, put it in production, right. To make this whole thing easier, we definitely need some way of bringing it all together. That's really where, especially compared to the traditional data science where everything was monolithic, it was one system, there was a very set way of doing things but now it is not so you know, with the growing types of data, with the growing types of computation algorithms that's available, there's a lot of opportunity and at the same time there is a lot of uncertainty. So it's really about putting that structure and it's really making sure you get the best of everything and still deliver the results, that is the focus that all data scientists strive for. >> And especially you wanted, the data scientists wants to operate in the world of uncertainty related to the business question and reducing uncertainty and not deal with the underlying some uncertainty associated with the infrastructure. >> Absolutely, absolutely you know, as a data scientist a lot of time used to spend in the past about where is the data, then the question was, what data do you want and give it to you because the data always came in a nice structured, row-column format, it had already lost a lot of context of what we had to look for. So it is really not about you know, getting the you know, it's really not about going back to systems that are pre-built or pre-processed, it's getting access to that real, raw data. It's getting access to the information as it came so you can actually make the best judgment of how to go forward with it. >> So you describe the world with business, technology and data science practitioners are working together but let's face it, there's an enormous amount of change in the industry and quite frankly, a deficit of expertise and I think that requires new types of partnerships, new types of collaboration, a real (mumbles) approach and Ingrid, I want to talk about what H2O.AI is doing as a partner of BlueData, HPE to ensure that you're complementing these skills in pursuit or in service to the customer's objectives. >> Absolutely, thank you for that. So as Nanda described, you know, data scientists want to get to answers and what we do at H2O.AI is we provide the algorithms, the platforms for data scientist to be successful. So when they want to try and solve a problem, they need to work with their business leaders, they need to work with IT and they actually don't want to do all the heavy lifting, they want to solve that problem. So what we do is we do automatic machine learning platforms, we do that with optimizing algorithms and doing all the kind of, a lot of the heavy lifting that novice data scientists need and help expert data scientists as well. I talk about it as algorithms to answers and actually solving business problems with predictions and that's what machine learning is really all about but really what we're seeing in the industry right now and BlueData is a great example of kind of taking away some of the hard stuff away from a data scientist and making them successful. So working with BlueData and HPE, making us together really solve the problems that businesses are looking for, it's really transformative and we've been through like the digital transformation journey, all of us have been through that. We are now what I would term an AI transformation of sorts and businesses are going to the next step. They had their data, they got their data, infrastructure is kind of seamlessly working together, the clusters and containerization that's very important. Now what we're trying to do is get to the answers and using automatic machine learning platforms is probably the best way forward. >> That's still hard stuff but we're trying to get rid of data science practitioners, focusing on hard stuff that doesn't directly deliver value. >> It doesn't deliver anything for them, right. They shouldn't have to worry about the infrastructure, they should worry about getting the answers to the business problems they've been asked to solve. >> So let's talk a little bit about some of the new business problems that are going to be able to be solved by these kinds of partnerships between BlueData and H2O.AI. Start, Nanda, what do you, what gets you excited when we think about the new types of business problems that customers are gonna be able to solve. >> Yeah, I think it is really you know, the question that comes to you is not filtered through someone else's lens, right. Someone is trying an optimization problem, someone is trying to do a new product discovery so all this is based on a combination of both data-driven and evidence-based, right. For us as a data scientist, what excites me is that I have the flexibility now that I can choose the best of the breed technologies. I should not be restricted to what is given to me by an IT organization or something like that but at the same time, in an organization, for things to work, there has to be some level of control. So it is really having this type of environments or having some platforms where some, there is a team that can work on the control aspect but as a data scientist, I don't have to worry about it. I have my flexibility of tools of choice that I can use. At the same time, when you talk about data, security is a big deal in companies and a lot of times data scientists don't get access to data because of the layers and layers of security that they have to go through, right. So the excitement of the opportunity for me is if someone else takes care of the problem you know, just tell me where is the source of data that I can go to, don't filter the data for me you know, don't already structure the data for me but just tell me it's an approved source, right then it gives me more flexibility to actually go and take that information and build. So the having those controls taken care of well before I get into the picture as a data scientist, it makes it extremely easy for us to focus on you know, to her point, focus on the problem, right, focus on accessing the best of the breed technology and you know, give back and have that interaction with the business users on an ongoing basis. >> So especially focus on, so speed to value so that you're not messing around with a bunch of underlying infrastructure, governance remaining in place so that you know what are the appropriate limits of using the data with security that is embedded within that entire model without removing fidelity out of the quality of data. >> Absolutely. >> Would you agree with those? >> I totally agree with all the points that she brought up and we have joint customers in the market today, they're solving very complex problems. We have customers in financial services, joint customers there. We have customers in healthcare that are really trying to solve today's business problems and these are everything from, how do I give new credit to somebody? How do I know what next product to give them? How do I know what customer recommendations can I make next? Why did that customer churn? How do I reach new people? How do I do drug discovery? How do I give a patient a better prescription? How do I pinpoint disease than when I couldn't have seen it before? Now we have all that data that's available and it's very rich and data is a team sport. It takes data scientists, it takes business leaders and it takes IT to make it all work together and together the two companies are really working to solve problems that our customers are facing, working with our customers because they have the intellectual knowledge of what their problems are. We are providing the tools to help them solve those problems. >> Fantastic conversation about what is necessary to ensure that the data science practitioner remains at the center and is the ultimate test of whether or not these systems and these capabilities are working for business. Nanda Vijaydev, chief data scientist of BlueData, Ingrid Burton CMO and business leader, H2O.AI, thank you very much for being on theCUBE. >> Thank you. >> Thank you so much. >> So let's now spend some time talking about how ultimately, all of this comes together and what you're going to do as you participate in the crowd chat. To do that let me throw it back to Dave Velante in our Marlborough studios. >> We're back with Patrick Osbourne, alright Patrick, let's wrap up here and summarize. We heard how you're gonna help data science teams, right. >> Yup, speed, agility, time to value. >> Alright and I know a bunch of folks at BlueData, the engineering team is very, very strong so you picked up a good asset there. >> Yeah, it means amazing technology, the founders have a long lineage of software development and adoption in the market so we're just gonna, we're gonna invested them and let them loose. >> And then we heard they're sort of better together story from you, you got a roadmap, you're making some investments here, as I heard. >> Yeah, I mean so if we're really focused on hybrid cloud and we want to have all these as a services experience, whether it's through Green Lake or providing innovation, AI, GPUs as a service is something that we're gonna be you know, continuing to provide our customers as we move along. >> Okay and then we heard the data science angle and the data science community and the partner angle, that's exciting. >> Yeah, I mean, I think it's two approaches as well too. We have data scientists, right. So we're gonna bring that capability to bear whether it's through the product experience or through a professional services organization and then number two, you know, this is a very dynamic ecosystem from an application standpoint. There's commercial applications, there's certainly open source and we're gonna bring a fully vetted, full stack experience for our customers that they can feel confident in this you know, it's a very dynamic space. >> Excellent, well thank you very much. >> Thank you. Alright, now it's your turn. Go into the crowd chat and start talking. Ask questions, we're gonna have polls, we've got experts in there so let's crouch chat.

(lively orchestral music) >> Hello, everyone. Welcome to this special CUBE Conversation. We're here in Palo Alto, California, theCUBE headquarters. I'm John Furrier, the cofounder of SiliconANGLE Media, cohost of theCUBE. We're here with fellow cloud influencer, friend of theCUBE, Sarbjeet Johal, who's always on Twitter. If you check out my Twitter stream, you'll find out we've always got some threads. He's always jumping in the CrowdChat and I think was in the leaderboard for our last CrowdChat on multi-cloud Kubernetes. Thanks for coming in. >> Yeah, thank you for having me here. >> Thanks for coming in. So you're very prolific on Twitter. We love the conversations. We're gettin' a lot of energy around some of the narratives that have been flowing around, obviously helped this week by the big news of IBM acquiring Red Hat for, what was it, 30, what was the number, 34? >> 34, yeah. >> $34 billion, huge premium, essentially changing the game in open source, some think, some don't, but it begs the question, you know, cloud obviously is relevant. Ginni Rometty, the CEO of IBM, actually now saying cloud is where it's at, 20% have been on the cloud, 80% have not yet moved over there, trillion-dollar market which we called, actually, I called, a few years ago when I wrote my Forbes story about Amazon, the Trillion Dollar Baby I called it. This is real. >> Yeah. So apps are moving to the cloud, value for businesses on the cloud, people are seeing accelerated timelines for shipping. Software. >> Yeah. >> Software offer is eating the world. Cloud is eating software, and data's at the center of it. So I want to get your thoughts on this, because I know that you've been talking a lot about technical debt, you know, the role of developer, cloud migration. The reality is, this is not easy. If you're doin' cloud native, it's pretty easy. >> Still pretty easy, yeah. >> If that's all you got, right, so if you're a startup and/or built on the cloud, you really got the wind at your back, and it's lookin' really good. >> Yeah. >> If you're not born in the cloud, you're an IT shop, they've been consolidating for years, and now told to jump to a competitive advantage, you literally got to make a pivot overnight. >> Yeah, actually, at high level, I think cloud consumption you can divide into two buckets, right? One is the greenfield which, as you said, it's not slam dunk, all these startups are born in cloud, and all these new projects, systems of innovation what I usually refer to those, are born in cloud, and they are operated in cloud, and at some point they will sort of fade away or die in cloud, but the hard part is the legacy applications sitting in the enterprise, right? So those are the trillion dollar sort of what IBM folks are talking about. That's a messy problem to tackle. Within that, actually, there are some low-hanging fruits. Of course, we can move those workloads to the cloud. I usually don't refer the application, the workloads as applications because people are sort of religiously attached to the applications. They feel like it's their babies, right? >> Yeah. >> So I usually say workload, so some workloads are ripe for the cloud. It's data mining, BI, and also the AI part of it, right? So but some other workloads which are not right for the cloud right now or they're hard to move or the ERP system, systems of record and systems of engagement or what we call CRMs and marketing sort of applications which are legacy ones. >> Yeah, hard-coded operationalized software frameworks and packages and vendors like Oracle. >> Yes. >> They're entrenched. >> Oracle SAP, and there's so many other software vendors that have provided tons of software to the data centers that they're sitting there, and the hard part is that nobody wants to pull the plug on the existing applications. I've seen that time and again. I have done, my team has done more than 100 data center audits from EMC and VMware days. We have seen that time and again. Nobody wants to pull the plug on the application. >> 'Cause they're runnin' in production! (laughs) >> They are running in production. And it's hard to measure the usage of those applications, also, that's a hard part of the sort of old stack, if you will. >> Yeah. So the reality is, this is kind of getting to the heart of what we wanted to talk about which is, you know, vendor hype and market realities. >> Yeah. >> The market reality is, you can't unplug legacy apps overnight, but you got a nice thing called containers and Kubernetes emerging, that's nice. >> Yeah. >> Okay, so check, I love that, but still, the reality is, is okay, then who does it? >> Yeah. >> Do I add more complexity? We just had Jerry Chen and hot startup Rockset on, they're trying to reduce the complexity by just having a more simple approach. This is a hard architectural challenge. >> It is. >> So that's one fundamental thing I want to discuss with you. And then there's the practical nature of saying assuming you get the architecture right, migrating and operating. Let's take those as separate, let's talk architecture, then we'll talk operating and migrating. >> Okay. >> Architecturally, what do people do, what are people doing, what you're seeing, what do you think is the right architecture for cloud architects, because that's a booming position. >> Yeah. >> There's more and more cloud architects out there, and the openings for cloud architects is massive. >> Yeah, I think in architecture, the microservices are on the rise. There are enabling technologies behind it. It doesn't happen sort of magically overnight. We have had some open source sort of development in that area the, the RESTful APIs actually gave the ports to the microservices. Now we can easily inter-operate between applications, right? So and our sort of, sorry I'm blanking out, so our way to divide the compute at the sort of micro-chunks from VM, virtual machine, to the container to the next level is the serverless, right? So that is giving ports to the microservices, and the integration technologies are improving at the same time. The problem of SEL lies in the data, which is the storage part and the data part and the network, and the network is closely associated with security. So security and network are two messy parts. They are in the architecture, even in the pure cloud architecture in the Kubernete world, those are two sort of hard parts. And Cisco is trying to address the network part. I speak, I spoke to some folks there, and what they are doing in that space, they are addressing the network and SCODI part, sort of deepening-- >> And it's a good time for them to do that. >> Yeah. >> Because, I mean, you go back, and you know, we covered DevNet Create, which is Susie Wee, she's a rising star at Cisco, and now she's running all of DevNet. So the developer network within Cisco's has a renaissance because, you know, you go back 20 years ago, if you were a network guy, you ran the show, I mean, everything ran the network. The network was everything. The network dictated what would happen. Then it kind of went through a funk of like now cloud native's hot and serverless, but now that programability's hitting the network because remember the holy trinity of transformation is compute, storage, and networking. (laughs) >> Yeah. >> Those aren't going away. >> Yeah, they aren't going away. >> Right, so networking now is seeing some, you know, revitalization because you can program it, you can automate it, you can throw DevOps to it. This is kind of changing the game a little bit. So I'm intrigued by the whole network piece of it because if you can automate some network with containers and Kubernetes and, say, service meshes, then it's become programmable, then you can do the automation, then it's infrastructure, it's code. >> Yeah, exactly. >> Infrastructure is code. It has to cover all three of those things. >> That is true, and another aspect is that we talk about multi-cloud all the time, which Cisco is focusing on also, like IBM, like VMware, like many other players who talk about multi-cloud, but problem with the multi-cloud right now is that you cannot take your security policies from one cloud provider to another and then just say, okay, just run there, right? So you can do the compute easy, containers, right, or Kubernetes are there, but you can't take the network as is, you cannot, you can still take the storage but not storage policies, so the policy-driven computing is still not there. >> Yeah. >> So we need, I think, more innovation in that area. >> Yeah, there's some technical issues. I talk a lot of startups, and they're jumpin' around from Azure to Amazon, and everyone comes back to Amazon because they say, and I'm not going to name names, but I'll just categorically say with what's going on is when they get to Microsoft and Oracle and IBM, the old kind of guards is they come in and they find that they check the boxes on the literature, oh, they do this, that, and that, but it's really just a lot of reverse proxies, there's a lot of homegrown stuff in there-- >> Yeah. >> That are making it work and hang together but not purely built from the ground up. >> Exactly, yeah, so they're actually sort of re-bottling the old sort of champagne kind of stuff, like they re-label old stuff and put layers of abstraction on top of it and that's why we're having those problems with the sort of legacy vendors. >> So let's get into some of the things that I know you're talking about a lot on Twitter, we're engaging on with with the community is migration, and so I want to kind of put a context to the questions so we can riff together on it. Let's just say that you and I were hired by the the CIO of a huge enterprise, financial services, pick your vertical. >> Yeah. >> Hey, Sarbjeet and John, fix my problems, and they give us the keys to the kingdom, bag of money, whatever it takes, go make it happen. What do we do, what's the first things that we do? Because they got a legacy, we know what it looks like, you got the networks, you're racking stack, top-of-rack switches, you got perimeter-based security. We got to go in and kind of level the playing field. What's our strategy, what do we what do we recommend? >> Yeah, the first thing first, right? So first, we need to know the drivers for the migration, right, what is it? Is it a cost-cutting, is it the agility, is it mergers and acquisitions? So what are the, what is the main driver? So that knowing that actually will help us like divvy up the problem, actually divide it up. The next thing, the next best practice is, I always suggest, I've done quite a few migrations, is that do the application portfolio analysis first. You want to find that low-hanging fruit which can be moved to the cloud first. The reason, main reason behind that is that your people and processes need to ease into using the cloud. I use consumption term a lot, actually on Twitter you see that, so I'm a big fan of consumption economics. So your people and processes need to adapt, like your change control, change management, ITSM, the old stuff still is valid, actually. We're giving it a new name, but those problems don't go away, right? How you log a ticket, how you how the support will react and all that stuff, so it needs to map to the cloud. SLA is another less talked about topic in our circles on Twitter, and our industry partners don't talk about, but that's another interesting part. Like what are the SLAs needed for, which applications and so forth. So first do the application profiling, find the low-hanging fruit. Go slow in the beginning, create the phases, like phase one, phase two, phase three, phase four. And it also depends number, on the number of applications, right? IBM folks were talking about that thousand average number of applications per enterprise. I think it's more than thousand, I've seen it. And that, just divvy up the problem. And then another best practice I've learned is migrate as is, do not transform and migrate, because then you're at, if something is not working over there or the performance problem or any latency problem, you will blame it on your newer architecture, if you will. Move as is, then then transform over there. And if you want me to elaborate a little more on the transformation part, I usually divide transformation into three buckets, actually this is what I tell the CIOs and CTOs and CEOs, that transformation is of three types. Well, after you move, transformation, first it is the infrastructure-led transformation. You can do the platforming and go from Windows to Linux and Linux to AIX and all that stuff, like you can go from VM to container kind of stuff, right? And the second is a process-led transformation, which is that you change your change control, change management, policy-driven computing, if you will, so you create automation there. The third thing is the application where you open the hood of the application and refactor the code and do the Web service enablement of your application so that you can weave in the systems of innovation and plug those into the existing application. So you want to open your application. That's the whole idea behind all this sort of transformation is your applications are open so you can bring in the data and take out the data as you weave. >> From your conversations and analysis, how does cloud, once migrations happen in cloud operations, how does that impact traditional network, network architecture, network security, and application performance? >> On the network side, actually, how does it, let me ask you a question, what do you mean by how does it-- >> In the old days, used a provisional VLAN. >> The older stuff? >> So I got networks out there, I got a big enterprise, okay, we know how to run the networks, but now I'm movin' to the cloud. >> Yeah. >> I'm off premises, I'm on premise, now I'm in the cloud. >> Yeah. >> How do I think about the network's differently? Whose provisioning the subnets, who's doing the VPNs? You know, where's the policy, all these policy-based things that we're startin' to see at Kubernetes. >> Yeah. >> They were traditionally like networks stuff-- >> You knew what it was. >> That's now happening at the microservices level. >> Yeah. >> So new paradigm. >> The new paradigm, actually, the whole idea is that your network folks, your storage folks, your server folks, like what they were used to be in-house, they need to be able to program, right? That's the number one thing. So you need to retrain your workforce, right? If you don't have the, you cannot retrain people overnight, and then you bring in some folks who know how to program networks and then bring those in. There's a big misconception about, from people, that the service, sorry, the service provider, which is called cloud service provider, is it responsible for the security of your applications or for the network, sort of segmentation of your network. They are not, actually, they don't have any liability over security if you read the SLAs. It's your responsibility to have the sort of right firewalling, right checks and balances in place for the network for storage, for compute, right policies in place. It's your responsibility. >> So let's talk about the, some tweets you've been doin' 'cause I've been wanting to pull the ones that I like. You tweeted a couple days ago, we don't know how to recycle failed startups. >> Yeah. (chuckles) >> Okay, and I said open source. And you picked up and brought up another image, is open source a dumping ground for failed startups? And it was interesting because what I love about open source is, in the old days of proprietary software, if the company went under, the code went under with it, but at least now, with open source, at least something can survive. But you bring up this dumping concept, that also came up in an interview earlier today with another guest which was with all this contribution coming in from vendors, it's almost like there's a dumping going on into open source in general, and you can't miss a beat without five new announcements per day that's, you know, someone's contributing their software from this project or a failed, even failed startup, you know, last hope, let's open source it. Is that good or bad, I mean, what's your take on that, what was your posture or thinking around this conversation? It is good, is it bad? >> Yeah, I believe it's, it's a economic problem, economics thing, right? So when somebody's like proprietary model doesn't work, they say, okay, let me see if this works, right? Actually, they always go first with like, okay let me sell-- >> Make money. >> Let me make money, right? A higher margin, right, everybody loves that, right? But then, if they cannot penetrate the market, they say, okay, let me make it open source, right? And then I will get the money from the support, or my own distro, like, distros are a big like open source killer, I said that a few times. Like the vendor-specific distributions of open source, they kill open source like nothing else does. Because I was at Rackspace when we open-sourced OpenStack, and I saw what happened to OpenStack. It was like eye-opening, so everybody kind of hijacked OpenStack and started putting their own sort of flavors in place. >> Yeah, yeah, we saw the outcome of that. >> Yeah. >> It niched into infrastructures of service, kind of has a special purpose-built view. >> And when I-- >> And that it comes cloud native didn't help either. Cloud grew at that time, too, talking about the 2008 timeframe. >> Yeah, yeah, and exactly. And another, why I said that was, it was in a different context, actually, I invested some money into an incubator in Berkeley, The Batchery, so we have taken what, 70-plus startups through that program so far, and I've seen that pattern there. So I will interview the people who want to bring their startup to our incubator and all that, and then after, most of them fail, right? >> Yeah. >> They kind of fade away or they leave, they definitely leave our incubator after a certain number of weeks, but then you see like what happens to them, and now also living in the Valley, you can't avoid it. I worked with 500 Startups a little bit and used to go to their demo days from the Rackspace days because we used to have a deal with them, a marketing deal, so the pattern I saw that was, there's a lot of innovation, there was a lot of brain power in these startups that we don't know what, these people just fade away. We don't have a mechanism to say, okay, hey you are doing this, and we are also doing similar stuff, we are a little more successful than, let's merge these two things and make it work. So we don't know how to recycle the startups. So that's what was on it. >> It's almost a personal network of intellectual capital. >> Yeah. >> Kind of, there needs to be a new way to network in the IP that's in people's heads. Or in this case, if it's open source, that's easy there, too, so being inaccessible. >> So there's no startup, there's no Internet of startups, if you will. >> Yeah, so there's no-- >> Hey, you start a CUBE group. (Sarbjeet laughing) You'll do it, start a CrowdChat. All right, I want to ask you about this consumption economics. >> Yeah. >> I like this concept. Can you take a minute to explain what you mean by consumption economics? You said you're all over it. I know you talk a lot about it on Twitter. >> Yes. >> What is it about, why is it important? >> Actually, the pattern I've seen in tech industry for last 25, 24 years in Silicon Valley, so the pattern I've seen is that everybody focuses on the supply side, like we do this, we like, we're going to change the way you work and all that stuff, but people usually do not focus on the consumption side of things, like people are consuming things. I'm a great fan of a theory called Jobs to Be Done theory. If you get a time, take a look at that. So what jobs people are trying to do and how you can solve that problem. Actually, if you approach your products, services from that angle, that goes a long way. Another aspect I talk about, the consumption economics, is age of micro-consumption, and again, there are reasons behind it. The main reason is there's so much thrown at us individually and and also enterprise-wise, like so much technology is thrown at us, if we try to batch, like if were ready to say, okay, we're not going to consume the technology now, and we're going to do every six months, like we're going to release every six months, or new software or new packages, and also at the same time, we will consume every six months, that doesn't work. So the whole notion when I talk about the micro-consumption is that you keep bringing the change in micro-chunks. And I think AWS has mastered the game of micro-supply, as a micro-supplier of that micro-change. >> Yeah. >> If you will. So they release-- >> And by the way, they're very customer-centric, so listening to the demand side. >> Exactly. So they kind of walk hand in hand with the customer in a way that customer wants this, so they're needing this, so let us release it. They don't wait for like old traditional model of like, okay, every year there's a new big release and there are service packs and patches and all that stuff, even though other vendors have moved along the industry. But they still have longer cycles, they still release like 10 things at a time. I think that doesn't work. So you have to give, as a supplier, to the masses of the workers of the world in HPs and IBMs, give the change in smaller chunks, don't give them monolithic. When you're marketing your stuff, even marketing message should be in micro-chunks, like or even if you created like five sort of features and sort of, let's, say in Watson, right, just give them one at a time. Be developer-friendly because developers are the people who will consume that stuff. >> Yeah, and then making it more supply, less supply side but micro-chunks or microservices or micro-supply. >> Yeah. >> Having a developer piece also plays well because they're also ones who can help assemble the micro, it's in a LEGO model of composeability. >> Yeah, exactly. >> And so I think that's definitely right. The other thing I wanted to get your thoughts on is validated by Jerry Chen at Greylock and his hot startups and a few others is my notion of stack overhaul. The changes in the stack are significant. I tweeted, and you commented on it, on the Red Hat IBM deal 'cause they were talkin' about, oh, the IBM stack is going to be everywhere, and they're talking about the IBM stack and the old full-stack developer model, but if you look at the consumption economics, you look at horizontally scalable cloud, native serverless and all those things goin' on with Kubernetes, the trend is a complete radical shifting of the stack where now the standardization is the horizontally scalable, and then the differentiations at the top of the stack, so the stack has tweaked and torqued it a little bit. >> Yeah. >> And so this is going to change a lot. Your thoughts and reaction to that concept of stack, not a complete, you know, radical wholesale change, but a tweak. >> Actually our CTO at Rackspace, John Engates, gave us a sort of speech at one of the kind of conferences here in Bay Area, the title of that was Stack, What Stack, right? So the point he was trying to make was like stack is like, we are not in the blue stack, red stack anymore, so we are a cross-stack, actually. There are a lot of the sort of small LEGO pieces, we're trying to put those together. And again, the reason behind that is because there's some enabling technology like Web services in RESTful APIs, so those have enabled us to-- >> And new kinds of glue layers, if you will. >> Yeah, yeah. >> Abstraction layers. >> Yeah, I call it digital glue. There's a new type of digital glue, and now we have, we are seeing the emergence of low code, no code sort of paradigms coming into the play, which is a long debate in itself. So they are changing the stack altogether. So everything is becoming kind of lightweight, if you will, again-- >> And more the level of granularity is getting, you know, thinner and thinner, not macro. So you know, macroservices doesn't exist. That was my, I think, my tweet, you know, macroservices or microservices? >> Yeah. >> Which one you think's better? And we know what's happening with microservices. That is the trend. >> That is the trend. >> So that is that antithesis of macro. >> Yeah. >> Or monolithic. >> Yeah, so there's a saying in tech, actually I will rephrase it, I don't know exactly how that is, so we actually tend to overestimate the impact of a technology in the short run and underestimate in the long term, right? So there's a famous saying somebody, said that, and that's, I think that's so true. What we actually wanted to do after the dot-com bust was the object-oriented, like the sort of black box services, it as, we called them Web services back then, right? >> Yeah. >> There were books written by IBM-- >> Service-oriented architecture-- >> Yeah, SOA. >> Web services, RSS came out of that. >> Yes. >> I mean, a lot of good things that are actually in part of what the vision is happening today. >> It's happening now actually, it just happening today. And mobile has changed everything, I believe, not only on the consumer side, even on the economic side. >> I mean, that's literally 16, 17 years later. >> Yes, exactly, it took that long. >> It's the gestation period. >> Yes. >> Bitcoin 10 years ago yesterday, the white paper was built. >> Yeah. >> So the acceleration's certainly happening. I know you're big fan of blockchain, you've been tweeting about it lately. Thoughts on blockchain, what's your view on blockchain? Real, going to have a big impact? >> I think it will have huge impact, actually. I've been studying on it, actually. I was light on it, now I'm a little bit, I'm reading on it this and I understand. I've talked to people who are doing this work. I think it will have a huge impact, actually. The problem right now with blockchain is that, the speed, right? >> It's slow, yeah. So yeah, it's very slow, doc slow, if you will. But I think that is a technical problem, we can solve that. There's no sort of functional problem with the blockchain. Actually, it's a beautiful thing. Another aspect which come into play is the data sovereignty. So blockchains actually are replicated throughout the world if you want the worldwide money exchange and all that kind of stuff going around. We will need to address that because the data in Switzerland needs to sit there, and data in the U.S. needs to stay in the U.S. That blockchain actually kind of, it doesn't do that. You have a copy of the same data everywhere. >> Yeah, I mean, you talk about digital software to find money, software to find data center. I mean, it's all digital. I mean, someone once said whatever gets digitized grows exponentially. (Sarbjeet laughing) Oh, that was you! >> Actually I-- >> On October 30th. >> That was, that came from a book, actually. It's called Exponential Organizations. Actually, they're two great books I will recommend for everybody to read, actually there's a third one also. So (laughs) the two are, one is Exponential Organizations. It's a pretty thin book, you should take, pick it up. And it talks about like whatever get digitized grows exponentially, but our organizations are not, like geared towards handling that exponential growth. And the other one is Consumption Economics. The title of the book is Consumption Economics, actually. I saw that book after I started talking about it, consumption economics myself. I'm an economics major, actually, so that's why I talk about that kind of stuff and those kind comments, so. >> Well, and I think one of the things, I mean, we've talked about this privately when we've seen each other at some of theCUBE events, I think economics, the chief economic officer role will be a title that will be as powerful as a CSO, chief security officer, because consumption economics, token economics which is the crypto kind of dynamic of gamification or network effects, you got economics in cloud, you got all kinds of new dynamics that are now instrumented that need, that are, they're throwin' off numbers. So there's math behind things, whether it's cryptocurrency, whether it's math behind reputation, or any anything. >> Yeah. >> Math is driving everything, machine learning, heavy math-oriented algorithms. >> Yeah, actually at the end of the day, economics matters, right? That's what we are all trying to do, right? We're trying to do things faster cheaper, right? That's what automation is all about. >> And simplifying, too. >> And simplifying service. >> You can't throw complexity in, more complexity. >> Yeah. >> That's exponential complexity. >> Sometimes while we are trying to simplify things, and I also said, like many times the tech is like medicine, right? I've said that many times. (laughs) Tech is like medicine, every pill has a side effect. Sometimes when we are trying to simplify stuff, we add more complexity, so. >> Yeah. What's worse, the pain or the side effects? Pick your thing. >> Yeah, you pick your thing. And your goal is to sort of reduce the side effects. They will be there, they will be there. And what is digital transformation? It's all about business. It's not, less about technology, technology's a small piece of that. It's more about business models, right? So we're trying to, when we talk about micro-consumption and the sharing economy, they're kind of similar concepts, right? So Ubers of the world and Airbnbs all over the world, so those new business models have been enabled by technology, and we want to to replicate that with the medicine, with the, I guess, education, autos, and you name it. >> So we obviously believe in microcontent at theCUBE. We've got the Clipper tool, the search engine. >> I love that. >> So the CUBEnomics. It's a book that we should be getting on right away. >> Yeah, we should do that! >> CUBEnomics. >> CUBEnomics, yeah. >> The economics behind theCUBE interviews. Sarbjeet, thank you for coming on. Great to see you, and thank you for your participation-- >> Thanks, John. >> And engagement online in our digital community. We love chatting with you and always great to see you, and let's talk more about economics and digital exponential growth. It's certainly happening. Thanks for coming in, appreciate it. >> It was great having, being here, actually. >> All right, the CUBE Conversation, here in Palo Alto Studios here for theCUBE headquarters. I'm John Furrier, thanks for watching. (lively orchestral music)

>> Announcer: Live, from Copenhagen, Denmark, it's theCUBE. Covering KubeCon and CloudNativeCon Europe 2018. Brought to you by the Cloud Native Computing Foundation and its Ecosystem Partners. >> Well everyone, welcome back to the live coverage of theCUBE here in Copenhagen, Denmark for KubeCon, Kubernetes Con 2018, part of the CNCF, Cloud Native Compute Foundation, part of the Linux Foundation. I'm John Furrier with Lauren Cooney, the founder of Spark Labs, breaking down day two, wrapping up our coverage of KubeCon and all the success that we've seen with Kubernetes, I thought it would be really appropriate to bring on the cofounder of KubeCon originally, Joseph Jacks, known as JJ in the industry, a good friend of theCUBE and part of the early formation of what is now Cloud Native. We were all riffing on that at the time. welcome back to theCUBE, great to see you. >> Thank you for having me John. >> So, for the story, for the folks out there, you know Cloud Native was really seen by the devops community, and infrastructure code was no secret to the insiders in the timeframes from 2010 through 2015, 16 timeframe, but really it was an open stack summit. A lot of people were kind of like, hey, you know, Google's got Kubernetes, they're going to open it up and this could be a real game changer, container, Docker was flying off the shelves. So we just kind of saw, right, and you were there and we were talking so there was a group of us. You were one of them. And you founded KubeCon, and bolted into the, at that time, the satellite Linux Foundation events, and then you pass it off as a good community citizen to the CNCF, so I wanted to just make sure that people knew that. What a great success. What's your impression? I mean, are you blown away? >> I am definitely blown away. I mean I think the size and scale of the European audience is remarkable. We had something like slightly less than half this in Austin last year. So to see more than that come here in Europe I think shows the global kind of growth curve as well as like, I think, Dan and someone else was asking sort of raise your hand if you've been to Kubecon Austin and very few actually, so there's a lot of new people showing up in Europe. I think it just shows the demand-- >> And Dan's been traveling around. I've seen him in China, some events I've been to. >> Joseph: All over. >> He's really working hard so props to him. We gave him some great props earlier. But he also told us Shanghai is coming online. >> Joseph: Yeah. >> So you got Shanghai, you to Barcelona next year for the European show, and of course Seattle. This is a community celebrating right now because there's a lot of high fives going on right now because there's a lot of cool, we've got some sort of core standard, defacto standard, now let's go to work. What are you working on now? You got a stealth startup? Share a little bit about it. I know you don't want to give the details out, but where is it kind of above the stack? Where you going to be playing? >> Sure, so we're not talking too much in terms of specifics and we're pretty stealthy, but I can tell you what I'm personally very excited about in terms of where Kubernetes is going and kind of where this ecosystem is starting to mature for practitioners, for enterprises. So one of the things that I think Kubernetes is starting to bring to bear is this idea of commoditizing distributed systems for everyday developers, for everyday enterprises. And I think that that is sort of the first time in sort of maybe, maybe the history of software development, software engineering and building applications, we're standardizing on a set of primitives, a set of building blocks for distributed system style programming. You know we had in previous eras things like Erlang and fault tolerant programming and frameworks, but those were sort of like pocketed into different programming communities and different types of stacks. I think Kubernetes is the one sort of horizontal technology that the industry's adopting and it's giving us these amazing properties, so I think some of the things that we're focusing on or excited about involve sort of the programming layer on top of Kubernetes in simplifying the experience of kind of bringing all stateful and enterprise workloads and different types of application paradigms natively into Kubernetes without requiring a developer to really understand and learn the Kubernetes primitives themselves. >> That's next level infrastructure as code. Yeah so as Kubernetes becomes more successful, as Kubernetes succeeds at a larger and larger scale, people simply shouldn't have to know or understand the internals. There's a lot of people, I think Kelsey and a few other people, started to talk about Kubernetes as the Linux kernel of distributed computing or distributed systems, and I think that's a really great way of looking at it. You know, do programmers make file system calls directly when they're building their applications? Do they script directly against the kernel for maybe some very high performance things. But generally speaking when you're writing a service or you're writing a microservice or some business logic, you're writing at a higher level of abstraction and a language that's doing some IO and maybe some reading and writing files, but you're using higher level abstractions. So I think by the same token, the focus today with Kubernetes is people are learning this API. I think over time people are going to be programming against that API at a higher level. And what are you doing here, the show? Obviously you're (mumbles) so you're doing some (mumbles) intelligence. Conversations you've been in, can you share your opinion of what's going on here? Your thoughts on the content program, the architecture, the decisions they've made. >> I think we've just, so lots of questions in there. What am I doing here? I just get so energized and I'm so, I just get reinvigorated kind of being here and talking to people and it's just super cool to see a lot of old faces, people who've been here for a while, and you know, one of the things that excites me, and this is just like proof that the event's gotten so huge. I walk around and I see a lot of familiar faces, but more than 80, 90% of people I've never seen before, and I'm like wow this has like gotten really super huge mainstream. Talking with some customers, getting a good sense of kind of what's going on. I think we've seen two really huge kind of trends come out of the event. One is this idea of multicloud sort of as a focus area, and you've talked with Bassam at Upbound and the sort of multicloud control plane, kind of need and demand out there in the community and the user base. I think what Bassam's doing is extremely exciting. The other, so multicloud is a really big paradigm that most companies are sort of prioritizing. Kubernetes is available now on all the cloud providers, but how do we actually adopt it in a way that is agnostic to any cloud provider service. That's one really big trend. The second big thing that I think we're starting to see, just kind of across a lot of talks is taking the Kubernetes API and extending it and wrapping it around stateful applications and stateful workloads, and being able to sort of program that API. And so we saw the announcement from Red Hat on the operator framework. We've seen projects like Kube Builder and other things that are really about sort of building native custom Kubernetes APIs for your applications. So extensibility, using the Kubernetes API as a building block, and then multicloud. I think those are really two huge trends happening here. >> What is your view on, I'm actually going to put you on test here. So Red Hat made a bet on Kubernetes years ago when it was not obvious to a lot of the other big wales. >> Joseph: From the very beginning really. >> Yeah from the very beginning. And that paid off huge for Red Hat as an example. So the question is, what bets should people be making if you had to lay down some thought leadership on this here, 'cause you obviously are in the middle of it and been part of the beginning. There's some bets to be made. What are the bets that the IBMs and the HPs and the Cisco's and the big players have to make and what are the bets the startups have to make? >> Well yeah, there's two angles to that. I mean, I think the investment startups are making, are different set of investments and motivated differently than the multinational, huge, you know, technology companies that have billions of dollars. I think in the startup category, startups just should really embrace Kubernetes for speeding the way they build reliable and scalable applications. I think really from the very beginning Kubernetes is becoming kind of compelling and reasonable even at a very small scale, like for two or three node environment. It's becoming very easy to run and install and manage. Of course it gives you a lot of really great properties in terms of actually running, building your systems, adopting microservices, and scaling out your application. And that's what's sort of like a direct end user use case, startups, kind of building their business, building their stack on Kubernetes. We see companies building products on top of Kubernetes. You see a lot of them here on the expo floor. That's a different type of vendor startup ecosystem. I think there's lots of opportunities there. For the big multinationals, I think one really interesting thing that hasn't really quite been done yet, is sort of treating Kubernetes as a first-class citizen as opposed to a way to commercialize and enter a new market. I think one of the default ways large technology companies tend to look at something hypergrowth like Kubernetes and TensorFlow and other projects is wrapping around it and commercializing in some way, and I think a deeper more strategic path for large companies could be to really embed Kubernetes in the core kind of crown jewel IP assets that they have. So I'll give you an example, like, for let's just take SAP, I'll just pick on SAP randomly, for no reason. This is one of the largest enterprise software companies in the world. I would encourage the co-CEOs of SAP, for example. >> John: There's only one CEO now. >> Is there one CEO now? Okay. >> John: Snabe left. It's now (drowned out by talking). >> Oh, okay, gotcha. I haven't been keeping up on the SAP... But let's just say, you know, a CEO boardroom level discussion of replatforming the entire enterprise application stack on something like Kubernetes could deliver a ton of really core meaningful benefits to their business. And I don't think like deep super strategic investments like that at that level are being made quite yet. I think at a certain point in time in the future they'll probably start to be made that way. But that's how I would like look at smart investments on the bigger scale. >> We're not seeing scale yet with Kubernetes, just the toe is in the water. >> I think we're starting to see scale, John. I think we are. >> John: What's the scale number in clusters? >> I'll give you the best example, which came up today, and actually really surprised me which I think was a super compelling example. The largest retailer in China, so essentially the Amazon of China, JD.com, is running in production for years now at 20,000 compute nodes with Kubernetes, and their largest cluster is a 5,000 node cluster. And so this is pushing the boundary of the sort of production-- >> And I think that may be the biggest one I've heard. >> Yeah, that's certainly, I mean for a disclosed user that's pretty huge. We're starting to see people actually talk publicly about this which is remarkable. And there are huge deployments out there. >> We saw Tyler Jewell come on from WSO2. He's got a new thing called Ballerina. New programming language, have you seen that? >> Joseph: I have, I have. >> Thoughts on that? What's your thoughts on that? >> You know, I think that, so I won't make any particular specific comments on Ballerina, I'm not extremely informed on it. I did play with a little bit, I don't want to give any of my opinions, but what I'd say, and I think Tyler actually mentioned this, one of the things that I believe is going to be a big deal in the coming years, is so, trying to think of Kubernetes as an implementation detail, as the kernel, do you interact directly with that? Do you learn that interface directly? Are you sort of kind of optimizing your application to be sort of natively aware of those abstractions? I think the answer to all of those questions is no, and Kubernetes is sort of delegated as a compiler target, and so frankly like directionally speaking, I think what Ballerina's sort of design is aspiring towards is the right one. Compile time abstraction for building distributed systems is probably the next logical progression. I like to think of, and I think Brendan Burns has started to talk about this over the last year or two. Everyone's writing assembly code 'cause we're swimming yaml and configuration based designs and systems. You know, sort of pseudodeclarative, but more imperative in static configurations. When in reality we shouldn't be writing these assembly artifacts. We should be delegating all of this complexity to a compiler in the same way that you know, we went from assembly to C to higher level languages. So I think over time that starts to make a lot of sense, and we're going to see a lot of innovation here probably. >> What's your take on the community formation? Obviously, it's growing, so, any observations, any insight for the folks watching what's happening in the community, patterns, trends you'd see, like, don't like. >> I think we could do a better job of reducing politics amongst the really sort of senior community leaders, particularly who have incentives behind their sort of agendas and sort of opinions, since they work for various, you know, large and small companies. >> Yeah, who horse in this race. >> Sure, and there's, whether they're perverse incentives or not, I think net the project has such a high quality genuine, like humble, focused group of people leading it that there isn't much pollution and negativity there. But I think there could be a higher standard in some cases. Since the project is so huge and there are so many very fast moving areas of evolution, there tends to be sort of a fast curve toward many cooks being in the kitchen, you know, when new things materialize and I think that could be better handled. But positive side, I think like the project is becoming incredibly diverse. I just get super excited to see Aparna from Google leading the project at Google, both on the hosted Saas offering and the Kubernetes project. People like Liz and others. And I just think it's an awesome, welcoming, super diverse community. And people should really highlight that more. 'Cause I think it's a unique asset of the project. >> Well you're involved in some deep history. I think we're going to be looking this as moment where there was once a KubeCon that was not part of the CNCF, and you know, you did the right thing, did a good thing. You could have kept it to yourself and made some good cash. >> It's definitely gotten really big, and it's way beyond me now at this point. >> Those guys did a good job with CNCF. >> They're doing phenomenal. I think vast majority of the credit, at this scale, goes to Chris Anasik and Dan Conn, and the events team at the Linux Foundation, CNCF, and obviously Kelsey and Liz and Michelle Noorali and many others. But blood, sweat, and tears. It's no small feat pulling off an event like this. You know, corralling the CFP process, coordinating speakers, setting the themes, it's a really huge job. >> And now they got to deal with all the community, licenses, Lauren your thoughts? >> Well they're consistent across Apache v2 I believe is what Dan said, so all the projects under the CNCF are consistently licensed. So I think that's great. I think they actually have it together there. You know, I do share your concerns about the politics that are going on a little bit back and forth, the high level, I tend to look back at history a little bit, and for those of us that remember JBoss and the JBoss fork, we're a little bit nervous, right? So I think that it's important to take a look at that and make sure that that doesn't happen. Also, you know, open stack and the stuff that we've talked about before with distros coming out or too many distros going to be hitting the street, and how do we keep that more narrow focused, so this can go across-- >> Yeah, I started this, I like to list rank and iterate things, and I started with this sheet of all the vendors, you know, all the Kubernetes vendors, and then Linux Foundation, or CNCF took it over, and they've got a phenomenal sort of conformance testing and sort of compliance versioning sheet, which lists all the vendors and certification status and updates and so on and I think there's 50 or 60 companies. On one hand I think that's great, because it's more innovation, lots of service providers and offerings, but there is a concern that there might be some fragmentation, but again, this is a really big area of focus, and I think it's being addressed. Yeah, I think the right ones will end up winning, right? >> Joseph: Right, for sure. >> and that's what's going to be key. >> Joseph: Healthy competition. >> Yes. >> All right final question. Let's go around the horn. We'll start with you JJ, wrapping up KubeCon 2018, your thoughts, summary, what's happened here? What will we talk about next year about what happened this week in Denmark? >> I think this week in Denmark has been a huge turning point for the growth in Europe and sort of proof that Kubernetes is on like this unstoppable inflection, growth curve. We usually see a smaller audience here in Europe, relative to the domestic event before it. And we're just seeing the numbers get bigger and bigger. I think looking back we're also going to see just the quality of end users and the end user community and more production success stories starting to become front and center, which I think is really awesome. There's lots of vendors here. But I do believe we have a huge representation of end users and companies actually sharing what they're doing pragmatically and really changing their businesses from Financial Times to Cern and physics projects, and you know, JD and other huge companies. I think that's just really awesome. That's a unique thing of the Kubernetes project. There's some hugely transformative companies doing awesome things out there. >> Lauren your thoughts, summary of the week in Denmark? >> I think it's been awesome. There's so much innovation happening here and I don't want to overuse that word 'cause I think it's kind of BS at some point, but really these companies are doing new things, and they're taking this to new levels. I think that hearing about the excitement of the folks that are coming here to actually learn about Kubernetes is phenomenal, and they're going to bring that back into their companies, and you're going to see a lot more actually coming to Europe next year. I also true multicloud would be phenomenal. I would love that if you could actually glue those platforms together, per se. That's really what I'm looking for. But also security. I think security, there needs to be a security seg. We talked to customers earlier. That's something they want to see. I think that that needs to be something that's brought to the table. >> That's awesome. My view is very simple. You know I think they've done a good job in CNCF and Linux Foundation, the team, building the ecosystem, keeping the governance and the technical and the content piece separate. I think they did a good job of showing the future state that we'd like to get to, which is true multicloud, workload portability, those things still out of reach in my opinion, but they did a great job of keeping the tight core. And to me, when I hear words like defacto standard I think of major inflection points where industries have moved big time. You think of internetworking, you think of the web, you think of these moments where that small little tweak created massive new brands and created a disruptor enabler that just created, changed the game. We saw Cisco coming out of that movement of IP with routers you're seeing 3Com come out of that world. I think that this change, this new little nuance called Kubernetes is going to be absolutely a defacto standard. I think it's definitely an inflection point and you're going to see startups come up with new ideas really fast in a new way, in a new modern global architecture, new startups, and I think people are going to be blown away. I think you're going to see fast rising growth companies. I think it's going to be an investment opportunity whether it's token economics or a venture backer private equity play. You're going to see people come out of the wood work, real smart entrepreneur. I think this is what people have been waiting for in the industry so I mean, I'm just super excited. And so thanks for coming on. >> Thank you for everything you do for the community. I think you truly extract the signal from the noise. I'm really excited to see you keep coming to the show, so it's really awesome. >> I appreciate your support, and again we're co-developing content in the open. Lauren great to host with you this week. >> Thank you, it's been awesome. >> And you got a great new venture, high five there. High five to the founder of KubeCon. This is theCUBE, not to be confused with KubeCon. And we're theCUBE, C-U-B-E. I'm John Furrier, thanks for watching. It's a wrap of day two global coverage here exclusively for KubeCon 2018, CNCF and the Linux Foundation. Thanks for watching. (techno music)

>> Announcer: Live from Las Vegas, it's theCUBE. Covering Dell Technologies World 2018. Brought to you by Dell EMC and its ecosystem partners. >> Welcome back, it's a beautiful day here in Las Vegas and this is theCUBE's live coverage of Dell Technologies World 2018. I'm Stu Miniman and happy to welcome, fresh off the keynote stage and for the first time on our program Jeff Clark, who is the Vice-Chairman of Products and Operations at Dell Technologies. Jeff, great to see you Thanks for joining us. >> Thanks, Stu. Thanks for having me. >> All right, so first of all Jeff, you know, you'll be a CUBE alum when we finish this, so for our audience that's not familiar-- >> Jeff: Do I get a badge? >> I've got a sticker for you actually. >> A sticker will work. >> Absolutely. Tell us a little bit about your background, you've been at Dell for a number of years. You now own really kind of the client and ISG businesses. >> Jeff: Sure. >> Which is a huge chunk of Michael's business. Give us your background. >> I'm an electrical engineer, by training. I went to the University of Texas at San Antonio. Got my double E degree. Out of school went to work for Motorola. And I joined what was PC's Limited when that was the first private name of Dell in 1987. I've been here for 31 years. And I've done a variety of things all on the engineering and product side. I've had the fortunate opportunity, I started in the factory as a process/test/quality/reliability engineer, we were Jacks of many trades at that time. Went to product development in 1989 and have been in that side ever since. I've worked in every kind of product that we had at the core design roles. I got to start a business, one of the funnest things I've ever done. I started the Precision business in 1997 from ground zero, me and a few of our top engineers and building that into the business that it is today. Expanded responsibilities, had a stint of running our enterprise business back in 2002 through 2005. Actually got to work with EMC back then. Dave Donatelli and many others back in the day. And now I lead a combined products and operations organization that has our CSG PC peripheral portfolio and ISG portfolio, our infrastructure products, as well as the fundamental supply chain that runs the company. >> Yeah, so Jeff, you've done it all and you've seen Michael through well, an amazing journey. >> We've worked together for a long time and it's been a heck of a ride. And to be honest, I think the ride's not over and the ride in front of us I think is more exciting than the past 30 years. >> Yeah, as we always say, it's a good thing, nothing's changing. There's nothing new to get those that love technology excited about, right? >> If there's any constant in our industry, and certainly in our company, it is change. And thinking about what's unfolded in my three plus decades at this is amazing to where we are today. But again, the future, as Bob DeCrescenzo said today, wicked cool. >> Wicked cool, absolutely. When you get up to Boston a little bit more, you can get a Boston accent. Yeah, exactly. Jeff, if we look at the Dell Technologies family, client side of the business is about half, the ISG is another 37%, so you know, you own major, major chunk of what's going on inside. Maybe give us a little bit of how you look at this portfolio. Are there interactions between the client side and the enterprise side? You know, we've seen most of the other big tech players that had both, either shed or split or, you know, kept the HPs and the IBMs of the world, no longer have both of those together. >> Yeah, those are interesting thoughts. You know, for us, our customers are asking us to provide a more set of comprehensive solutions. They want more end to end. And I don't see how you provide an end to end solution if you don't have one of the ends. And as trite as that may sound, I think it's the core fabric of what we're doing and certainly the role I have now leading this organization of being able to cultivate and build, I think, the world's leading and innovative PC products and peripherals around them. Same thing on the infrastructure side, where we have the privilege of being a leader in a number of categories. And then beginning to bring them together in new and unique ways. I referenced in my keynote this morning about how new entrants to the workforce are pressuring conventional definitions of how we do work and we deploy technology. So we have leadership, products, and now you capture or able to tie that together with VMware Workspace ONE or an AirWatch or RSA class of products and you begin to modernize the experience. How could you not do that if you're not integrating the pieces? Or a VDI experience where you take a thin client, or VxRail infrastructure, and some VMware Horizon software and build out a solution set. That's what our customers are asking us to do. And I think we're in a very unique position. In fact, I know we are, 'cause no one else has all of what I just described. >> Jeff, there was a main theme you talked about in your keynote, that IT can drive and change business and it resonated from what I'm hearing with customers. But if you dial back a few years ago, it was IT wasn't getting it done, IT wasn't listening to the business, we had Stealth IT. Why are things different now? What's the role of IT going forward? And how does Dell fit into that big picture? >> You know, Michael touched on it in his opening yesterday about IT and business have become much much more closely integrated to compete in this modern world. And I suspect some of this goes back to we've always thought of IT as a cost center, OPEX. Yet, over the past decade, we've seen some fundamental disruption of business that has been fundamentally IT-led. New technology-led. New business models that have been fueled by new technology. I think that modernization, whether it's modernization of applications, taking advantage of information at your disposal and turning that into useful insights to make better business decisions, is a catalyst for a reframing, if you will, of what IT does. And the role of IT in a business, and a role that IT can help companies be more competitive, or at a minimum, help them not get disrupted by someone who's doing it, as well. So I think that's what's changing and I think you're seeing companies embrace that. And as soon as you do, you begin to I think challenge what have you invested in, where are you going, how am I taking advantage of some of the new trends that I outlined maybe this morning. And it gets I think a pretty interesting time in front of us. >> Yeah, you know, you actually went through immersive and collaborative computing, IOT, multi-clouded options, offer to find anything and AI and ML. So a lot of new things. One area I'd like to touch on, we heard some great side from Allison Dew earlier this week. It's great when we have the new tools and the new technology but sometimes we wonder how does adoption go and how does that impact productivity and people's engagement? And I'm curious how we help the enterprise and help the client side, not just do something new but be more productive and move their business forward. >> Look, if start with the client side, I think it's pretty easy to think about productivity. Particularly if you believe this boundary between work and the workplace is fundamentally changed and think about where people do work. You're actually getting a much more productive workforce by allowing people to work when the want to work, where they want to work. And that traditional boundary of eight to five, whatever it might be, physically in the office. You now have access to all 168 hours in a week and people want to work when they want to work. And we find that the work more, particularly if you put technology in their hand that makes them more productive and they have access to what they need to do their job. You cast that forward into the enterprise and I think, look, at some level IT is hard and we have a huge role in making it much easier. How to simplify. How to make it more automated so IT practitioners can actually migrate to how do I configure this LAN? How do I set up this server? And interesting things and still important things, but can migrate to how do I take this data and turn it into information that helps my business unit, my company win. That's where I think, again, I think this migrates, too and we play a huge role in helping that. >> Yeah, there's a theme that, another thing came up in the keynote, data really at the center of everything and not just talking about storage, but you had McClaren up on stage talking about that. How do you see the role of data changing? How do we capture for companies? How valued data is? >> A tie back to Michael's opening, he talked about data being, if you will, the rocket fuel for this rocket change and digitization of our world, the digital transformation that's underway. And between Michael, Pat, and myself, we all talked about that happening at the edge in a decentralized manner. I tried to build upon that and say you hadn't seen nothing yet, there's a whole lot more coming. Well, if believe that, you have to start preparing today, and anticipating that. And again, I think we play a role in helping companies do that. I think it requires a modern approach. It requires an approach to understand how that information is coming in to be able to do something with it. That's where we're focusing, as I mentioned. In fact, I think I specifically said it's sort of the heart of our vision for IT transformation. The data's the gold. In fact, Pat may have said that yesterday. Now, the challenge will be how do you take all of that data sort through it, figure out which pieces are most valuable and then get them to where they're supposed to go to make decisions. That's yet to be seen how we do that but I'm encouraged, given our track record in this industry. We'll find ways to do that. Engines like AI and machine or capabilities like artificial intelligence and machine learning are certainly a vast step forward of making sense of all that stuff. >> Yeah. Jeff, I wonder if you could bring us inside some of your customers. You know, where do you find some of the strategic discussions happening? I think back to early PC or server days, you know, who bought boxes versus now, it seems like more of a C level discussion for some of these large trends that you're seeing. What are some of the big changes that you're seeing in the customers and what are some of the biggest challenges that they're having today? >> I think you mentioned it. One of the things that I've seen in the customer interactions I've had in this new role and getting to see more and more each and every month. The conversations I have, or participate in, are seldom, if ever, about the speeds and feeds of this, the performance of that. It's about here's my business problem, how do you help me? How do you help me get this done? How do you provide me a set of solutions to get to where I want to go? By the way, if you have advice, recommendation to help us, they want to hear that. So they want to access our technical knowledge base across our organization. But again, I think this theme that I tried to say a couple of times this morning around outcomes, so it's an outcome-driven discussion. It's solutions. It's end to end. And how can you help me? Probably, I guess, I could generalize them to fit those four attributes. >> Great. Last thing, you talked about the modern data center. What's that mean for your customers? >> To me, it's all about putting at the disposal of our customers a set of technologies and infrastructure solutions and services that allows 'em to take advantage of that data. Allow them to have the data services they need and the underlying horsepower to do it in a fairly intelligent way. Hopefully automating a few of those tasks and giving them the agility and flexibility they need. >> Yeah. Jeff, wonder if you could speak to really, the engineering culture inside of Dell. Think back to before Dell made a lot of exhibitions, it's like, oh well Dell was a supply chain company, people would say. And then a number of acquisitions came through, you know, you lived with a lot of the engineers, you've got more engineers through the EMC merger. Sometimes people that don't understand, they're like oh, it's just all going to commodity stuff, software defined anything means that infrastructure doesn't matter. You know, where does the Dell engineering culture differentiate and position you in the market? >> You know, it might not surprise you, given my background, that certainly we are a supply chain company. We were doing hardcore engineering for a long time. I look at some of the advancements we made back in the day in leading the industry. I think we have a long distinguished track record of doing that. And now with the combination of the two companies, I look at this organization and the engineering capability we have, I like my hand, we like our hand. The trick is, is to getting our teams to innovate where we can differentiate, where we can help customers solve problems. And part of what I've been doing across this community of engineers, is doing that. Pivoting resources to the most important things. Pivoting resources to where we can differentiate. Pivoting resources where our innovation can actually distinguish, or shine against the competitive set. We've seen this in every category, PC, server, storage. And many of these cases, we start from the privileged position of being the leader. So think about when we get everything aligned to be able to innovate and differentiate, I like my hand. >> All right. Jeff, I want to give you the final word, coming away from Dell Technologies World this year. There's a lot of product announcements, people are going to learn a lot in the sessions, but what do you want people to come away with? Understanding the Dell portfolio and Dell as a company, as a partner? >> Well, if I could leave any parting statement, and make it very specific to the ISG portfolio, I talked about power, our power brand now being the brand of our future state ISG products, walk away with a commitment to build a power branded portfolio that is going to be innovative, differentiated in the marketplace, and something that helps our customers with. That's our commitment and that's what we'll deliver going forward. >> All right. Jeff Clark, thank you for sharing with us all the information, your update. Your first time on theCUBE, but I'm sure we'll have you on many times in the future. >> My pleasure, thanks for having me. >> All right. We'll be back with lots more coverage here from Dell Technologies World 2018. I'm Stu Miniman and you're watching theCUBE.

>> Announcer: Live from Las Vegas, it's theCUBE, covering HPE Discover 2017. Brought you by Hewlett Packard Enterprise. >> Welcome back, everyone. Live here in Las Vegas, this is theCUBE's exclusive coverage for three days at Hewlett Packard Enterprise Discover 2017. I'm John Furrier with my co-host Dave Vellante. Day two winding down, a lot of action happening, a lot of news, a lot of technology announced with a lot of ground-breaking stuff, and our next guest is Navin Mittal, Director, Products and Solutions Marketing at the Data Center Infrastructure Group. Welcome to theCUBE. Good to see you again. >> Good to see you, John. >> Thanks for coming on, I mean a lot of stuff going on under the hood. We heard from Susan about the servers with the security chip and the silicon. You guys got FlexFabric, you got all this capacity. It's really kind of like the new sports cars coming out with Gen 10, under the hood a lot of action happening. What's going on with the relationships? We're hearing a partner-centric message here at Discover this year. Give us the update. >> Yeah, so first of all, absolutely spot on on the whole Gen 10 servers. We are data crunchers. We will get the market right. But let's talk about networking, because that's something that actually combines everything, when you talk about server storage and networking and our customers as you very well know, can't just give it service alone. So, if you may or may not remember, six months back we announced the strategic relationship with Arista Networks where we basically said that they are our preferred network provider going forward. >> John: Yeah, we had them on in London. >> Okay great, yeah, so it's been going great so far. The giant go-to market has not been just go-to market but it's also been reference architecture designs. It's been creation of reference architectures with our server teams especially mission critical servers, SAP HANA talk about it so. >> John: Give us the update. What's new with the partnership? What's the progress in six months? >> Yeah, so in six months, our sales teams are completely trained and stoked to go out and sell there. Our customers are really excited with the partnership. The are asking for not only HPs servers and storage solutions but of course the Arista products also. 'Cause now they have a choice of products. If they are existing FlexFabric customers, they already worked very well with HPE, but now with the bringing in of the Arista switches, you can get the software to fine layer end-to-end. >> And you get the high end covered. A lot of service provider opportunities. What's the big take away in the marketplace from your standpoint? As you look at what's going on here at Discover 2017, and looking at what you're doing with Arista at the networking layer, a lot of interesting things are going on at the network layer, a lot of open source projects, a lot of new software, what's your take on what's going on at the network layer in the Cloud and whatnot? >> Open source has always been an integral part of HP's DNA, as you very well know, right? We have been a great contributor if you talk about Helion or you talk about OpenSwitch which was happening last year. Customers are looking for business outcomes. They don't really care whether it's open source or closed source at one point. We are all about outcomes and business solutions. So, we bring in the best of breed networking along with best of breed servers and storage, combine them to give a solution that we can offer to our customers whether they are in the Cloud-centric journey, they've already made the transition to Cloud or they trying to tackle with legacy (mumbles) >> So what are some examples of some of the solutions? >> Yeah, the SAP HANA solution architecture that we did recently, not many people know about this, but the HANA Cloud actually runs on the Arista switches already. Now think about power that our customers can get if we can bring that flexibility and agility that SAP uses internally in their Cloud into the Enterprise data centers today. So that's the reference architecture which we already have. >> Okay, and then in that example, so the core switch is Arista, and what do you guys bring to the table, everything else around it? >> Storage, yes. And don't forget the Pointnext consulting, right? So that is the switch, ties everything together so that customers can actually utilize not only our products and solutions, but the entire journey. >> And in that solution, for example, the HANA, when you mentioned Pointnext to consulting. What specifically is the service's organization doing? Is it tuned for SAP HANA? Is there some magic sauce that's sprinkled in? How does that all work? >> Yeah, so great point. And so the Pointnext to consulting of course makes a point to understand where you are currently in your journey, right? Depending on where you are, the SAP HANA Cloud solution may not be a perfect fit. In this example that I mentioned about SAP HANA itself we just wanted to highlight the fact that if you are ready to move to the Cloud like agility into your private data center, we have the solution ready with you, and you can apply it in your private data center. So your journey might begin with Pointnext, it might begin with coming to HPE. >> Alright, so here's the hard billion dollar question, not million, billion dollar question. >> It is a billion dollar question. >> Trillion dollar question. Well true private Cloud TAM is 260 billion. So that's not including hybrid. But Meg's up there too. >> Navin: Well it's 250 billion based on one of the reports that Wikibon put in. >> The true private Cloud. Ground-breaking again, another great Wikibon research that no one else is doing. Again, that number is legit, that's basically saying that On-prem isn't going away any time soon. I think this plays beautifully to what you guys are doing. But the question is this, how are you going to simplify as customers are transforming their operating model to Cloud-like, how are you going to simplify it with these relationships? >> Yeah, so for that, to talk about simplicity I need to take a step up, right? Because you saw Meg talk about the hybrid ID strategy, and then we also talked about the Gen 10 Silver announcement where we talk about control and agility and security. That's where the Arista portfolio fits in squarely across the hybrid ID and the Pointnext to consulting because now you're talking about the security solutions being end-to-end from service, storage, and networking, while giving you the agility that you're already accustomed to in some cases from (mumbles) solutions and having the capacity control from our financial services offering. >> So, from a customer standpoint, no real change, it's kind of like, it's enabling them extracted away, I'm just trying to get on the network side, what's your policy? A lot of policies going, a lot of automation opportunities. >> Yes. >> What's going on there? >> Yeah, so I don't know if you know about the product called the Spirit Cloud networking that we offer, where it is really allowing the policies that are defined at the application level and translating that into the underlying infrastructure level. So think about this, in a typical data center you tend to have silos, where you have a server silo, networking silo, and a storage silo, and from the time the application defines the policies and the requirement from an application standpoint to reach the end customer, you would have to go through these silos in order to provision those. With bringing in distributor Cloud networking, and it's integration with other networks, those policies get automatically deployed. And guess what, it's a heterogeneous environment, so you can actually mix and match existing workloads along with existing infrastructure as well. >> And what happens to the IT pros that used to be associated with those different silos? I mean, what are they all doing today? >> Yeah, they get to do much better things, right? Because IT is now transitioning from a cost center to a revenue generator. And it's not about firing people, right? Let me make sure I clarify this, it's about realizing your resources so that they can now become more productive with the time that they have. I don't know about you, if I'm done at 5 pm, you could either go back to your home, and I'm sure you have families, or you could spend time figuring out the next network problem that you're having in the data center. That's where the true agility comes out, that's where the true economic savings come out. >> That's where software programmable infrastructure works. People can get their weekends back. That's really kind of like, I mean, a lot of time is spend on mundane tasks. Either chasing down some sort of automated provisioning, or I mean, manual provisioning, or configuring stuff. What's the big game-changer? Is it machine-learning that we're seeing there, how do you guys see that technology? What's the enabler? >> Yeah, so I think at the end of the day, customers are looking for a stack, end-to-end stack, that one company can bring to them with the flexibility of choosing every layer within the stack. So we at HP of course are very focused on openness, right? So the HPE stack actually has all the way from applications to computers, to servers, to storage, to networking, whether you're talking about Nimble or the SimpliVity acquisition, or the (mumbles) that we have, to the underlying networking layer. And in this case, we are contending that Arista switching is the fabric which brings in best of breed. But you're free to choose the other layers of the stack as well. >> And how do you differentiate in the marketplace? The competition or the customer says, well I should have you guys HP and Arista instead of whatever, vendor X,Y, or Z. What do you tell them? >> Yeah, so the famous thing that I tell is you are either in the legacy mode and stuck with a typical vendor, you know we all know what the name means but I won't mention it here, where they try to keep selling you newer and newer gear with newer operating systems, or you go with a vendor that is open, has a DNA of being open, will hold your hand until you actually deployed in the data center and give you the choice that you need in the data center to be successful. >> Surely making things easier has been key. Nimble, and SimpliVity really kind of put the design at the center, and then brought software in, that changes the game. That's more Cloud-like. That's certainly very DevOps friendly. >> Absolutely, and it doesn't even stop there, right? If you take the conversation up higher up to the virtualization or the container layer, discussion. When you start talking about digitally the containers bring into the world, then it's a completely game-changer. How do you ensure that the network traffic that and application sitting on a container somewhere in one of the Vms or in Silver, can be translated and traced all the way back to the switchboard. And ensuring that nothing goes down. >> And that's the whole ethos of infrastructure as code, is actually make it programmable. So the app guys don't have to get under the hood. >> Yes, that programmable is taking care of the agility side of the house. What I am talking about is visibility and security so that if something does go wrong, we all are human, something can go wrong, even in programming, you need to pinpoint and detect and create and automate and fix issues as fast as possible. And there are some fundamental underlying tenants of the Arista operating system which allows us to do that, and of course the secret sauce that we add on top of that is the combination with the server and storage. >> Navin, thank you for coming into theCUBE and sharing insights. Final question for you. What's your takeaway from this year at Discover? What's the vibe, what's your personal (mumbles) simplifying, IT, hybrid IT, and intelligent edge, outside of the core things, what's your big takeaway? >> Yeah, I think I am super excited after meeting our customers and partners here. We are back in the game. We are here to take the market by storm and we will be doing it. >> Alright, here breaking it down in the networking Arista relationship and all the great stuff in the networking life. Navin, thank you so much. It's theCUBE live coverage from Las Vegas, in HPE 2017. We'll be back with more live coverage after this short break. (futuristic music)