>>From the Cube Studios in Palo Alto in Boston, bringing you data-driven insights from the cube and E T R. This is breaking analysis with Dave Valante. >>Making technology predictions in 2022 was tricky business, especially if you were projecting the performance of markets or identifying I P O prospects and making binary forecast on data AI and the macro spending climate and other related topics in enterprise tech 2022, of course was characterized by a seesaw economy where central banks were restructuring their balance sheets. The war on Ukraine fueled inflation supply chains were a mess. And the unintended consequences of of forced march to digital and the acceleration still being sorted out. Hello and welcome to this week's weekly on Cube Insights powered by E T R. In this breaking analysis, we continue our annual tradition of transparently grading last year's enterprise tech predictions. And you may or may not agree with our self grading system, but look, we're gonna give you the data and you can draw your own conclusions and tell you what, tell us what you think. >>All right, let's get right to it. So our first prediction was tech spending increases by 8% in 2022. And as we exited 2021 CIOs, they were optimistic about their digital transformation plans. You know, they rushed to make changes to their business and were eager to sharpen their focus and continue to iterate on their digital business models and plug the holes that they, the, in the learnings that they had. And so we predicted that 8% rise in enterprise tech spending, which looked pretty good until Ukraine and the Fed decided that, you know, had to rush and make up for lost time. We kind of nailed the momentum in the energy sector, but we can't give ourselves too much credit for that layup. And as of October, Gartner had it spending growing at just over 5%. I think it was 5.1%. So we're gonna take a C plus on this one and, and move on. >>Our next prediction was basically kind of a slow ground ball. The second base, if I have to be honest, but we felt it was important to highlight that security would remain front and center as the number one priority for organizations in 2022. As is our tradition, you know, we try to up the degree of difficulty by specifically identifying companies that are gonna benefit from these trends. So we highlighted some possible I P O candidates, which of course didn't pan out. S NQ was on our radar. The company had just had to do another raise and they recently took a valuation hit and it was a down round. They raised 196 million. So good chunk of cash, but, but not the i p O that we had predicted Aqua Securities focus on containers and cloud native. That was a trendy call and we thought maybe an M SS P or multiple managed security service providers like Arctic Wolf would I p o, but no way that was happening in the crummy market. >>Nonetheless, we think these types of companies, they're still faring well as the talent shortage in security remains really acute, particularly in the sort of mid-size and small businesses that often don't have a sock Lacework laid off 20% of its workforce in 2022. And CO C e o Dave Hatfield left the company. So that I p o didn't, didn't happen. It was probably too early for Lacework. Anyway, meanwhile you got Netscope, which we've cited as strong in the E T R data as particularly in the emerging technology survey. And then, you know, I lumia holding its own, you know, we never liked that 7 billion price tag that Okta paid for auth zero, but we loved the TAM expansion strategy to target developers beyond sort of Okta's enterprise strength. But we gotta take some points off of the failure thus far of, of Okta to really nail the integration and the go to market model with azero and build, you know, bring that into the, the, the core Okta. >>So the focus on endpoint security that was a winner in 2022 is CrowdStrike led that charge with others holding their own, not the least of which was Palo Alto Networks as it continued to expand beyond its core network security and firewall business, you know, through acquisition. So overall we're gonna give ourselves an A minus for this relatively easy call, but again, we had some specifics associated with it to make it a little tougher. And of course we're watching ve very closely this this coming year in 2023. The vendor consolidation trend. You know, according to a recent Palo Alto network survey with 1300 SecOps pros on average organizations have more than 30 tools to manage security tools. So this is a logical way to optimize cost consolidating vendors and consolidating redundant vendors. The E T R data shows that's clearly a trend that's on the upswing. >>Now moving on, a big theme of 2020 and 2021 of course was remote work and hybrid work and new ways to work and return to work. So we predicted in 2022 that hybrid work models would become the dominant protocol, which clearly is the case. We predicted that about 33% of the workforce would come back to the office in 2022 in September. The E T R data showed that figure was at 29%, but organizations expected that 32% would be in the office, you know, pretty much full-time by year end. That hasn't quite happened, but we were pretty close with the projection, so we're gonna take an A minus on this one. Now, supply chain disruption was another big theme that we felt would carry through 2022. And sure that sounds like another easy one, but as is our tradition, again we try to put some binary metrics around our predictions to put some meat in the bone, so to speak, and and allow us than you to say, okay, did it come true or not? >>So we had some data that we presented last year and supply chain issues impacting hardware spend. We said at the time, you can see this on the left hand side of this chart, the PC laptop demand would remain above pre covid levels, which would reverse a decade of year on year declines, which I think started in around 2011, 2012. Now, while demand is down this year pretty substantially relative to 2021, I D C has worldwide unit shipments for PCs at just over 300 million for 22. If you go back to 2019 and you're looking at around let's say 260 million units shipped globally, you know, roughly, so, you know, pretty good call there. Definitely much higher than pre covid levels. But so what you might be asking why the B, well, we projected that 30% of customers would replace security appliances with cloud-based services and that more than a third would replace their internal data center server and storage hardware with cloud services like 30 and 40% respectively. >>And we don't have explicit survey data on exactly these metrics, but anecdotally we see this happening in earnest. And we do have some data that we're showing here on cloud adoption from ET R'S October survey where the midpoint of workloads running in the cloud is around 34% and forecast, as you can see, to grow steadily over the next three years. So this, well look, this is not, we understand it's not a one-to-one correlation with our prediction, but it's a pretty good bet that we were right, but we gotta take some points off, we think for the lack of unequivocal proof. Cause again, we always strive to make our predictions in ways that can be measured as accurate or not. Is it binary? Did it happen, did it not? Kind of like an O K R and you know, we strive to provide data as proof and in this case it's a bit fuzzy. >>We have to admit that although we're pretty comfortable that the prediction was accurate. And look, when you make an hard forecast, sometimes you gotta pay the price. All right, next, we said in 2022 that the big four cloud players would generate 167 billion in IS and PaaS revenue combining for 38% market growth. And our current forecasts are shown here with a comparison to our January, 2022 figures. So coming into this year now where we are today, so currently we expect 162 billion in total revenue and a 33% growth rate. Still very healthy, but not on our mark. So we think a w s is gonna miss our predictions by about a billion dollars, not, you know, not bad for an 80 billion company. So they're not gonna hit that expectation though of getting really close to a hundred billion run rate. We thought they'd exit the year, you know, closer to, you know, 25 billion a quarter and we don't think they're gonna get there. >>Look, we pretty much nailed Azure even though our prediction W was was correct about g Google Cloud platform surpassing Alibaba, Alibaba, we way overestimated the performance of both of those companies. So we're gonna give ourselves a C plus here and we think, yeah, you might think it's a little bit harsh, we could argue for a B minus to the professor, but the misses on GCP and Alibaba we think warrant a a self penalty on this one. All right, let's move on to our prediction about Supercloud. We said it becomes a thing in 2022 and we think by many accounts it has, despite the naysayers, we're seeing clear evidence that the concept of a layer of value add that sits above and across clouds is taking shape. And on this slide we showed just some of the pickup in the industry. I mean one of the most interesting is CloudFlare, the biggest supercloud antagonist. >>Charles Fitzgerald even predicted that no vendor would ever use the term in their marketing. And that would be proof if that happened that Supercloud was a thing and he said it would never happen. Well CloudFlare has, and they launched their version of Supercloud at their developer week. Chris Miller of the register put out a Supercloud block diagram, something else that Charles Fitzgerald was, it was was pushing us for, which is rightly so, it was a good call on his part. And Chris Miller actually came up with one that's pretty good at David Linthicum also has produced a a a A block diagram, kind of similar, David uses the term metacloud and he uses the term supercloud kind of interchangeably to describe that trend. And so we we're aligned on that front. Brian Gracely has covered the concept on the popular cloud podcast. Berkeley launched the Sky computing initiative. >>You read through that white paper and many of the concepts highlighted in the Supercloud 3.0 community developed definition align with that. Walmart launched a platform with many of the supercloud salient attributes. So did Goldman Sachs, so did Capital One, so did nasdaq. So you know, sorry you can hate the term, but very clearly the evidence is gathering for the super cloud storm. We're gonna take an a plus on this one. Sorry, haters. Alright, let's talk about data mesh in our 21 predictions posts. We said that in the 2020s, 75% of large organizations are gonna re-architect their big data platforms. So kind of a decade long prediction. We don't like to do that always, but sometimes it's warranted. And because it was a longer term prediction, we, at the time in, in coming into 22 when we were evaluating our 21 predictions, we took a grade of incomplete because the sort of decade long or majority of the decade better part of the decade prediction. >>So last year, earlier this year, we said our number seven prediction was data mesh gains momentum in 22. But it's largely confined and narrow data problems with limited scope as you can see here with some of the key bullets. So there's a lot of discussion in the data community about data mesh and while there are an increasing number of examples, JP Morgan Chase, Intuit, H S P C, HelloFresh, and others that are completely rearchitecting parts of their data platform completely rearchitecting entire data platforms is non-trivial. There are organizational challenges, there're data, data ownership, debates, technical considerations, and in particular two of the four fundamental data mesh principles that the, the need for a self-service infrastructure and federated computational governance are challenging. Look, democratizing data and facilitating data sharing creates conflicts with regulatory requirements around data privacy. As such many organizations are being really selective with their data mesh implementations and hence our prediction of narrowing the scope of data mesh initiatives. >>I think that was right on J P M C is a good example of this, where you got a single group within a, within a division narrowly implementing the data mesh architecture. They're using a w s, they're using data lakes, they're using Amazon Glue, creating a catalog and a variety of other techniques to meet their objectives. They kind of automating data quality and it was pretty well thought out and interesting approach and I think it's gonna be made easier by some of the announcements that Amazon made at the recent, you know, reinvent, particularly trying to eliminate ET t l, better connections between Aurora and Redshift and, and, and better data sharing the data clean room. So a lot of that is gonna help. Of course, snowflake has been on this for a while now. Many other companies are facing, you know, limitations as we said here and this slide with their Hadoop data platforms. They need to do new, some new thinking around that to scale. HelloFresh is a really good example of this. Look, the bottom line is that organizations want to get more value from data and having a centralized, highly specialized teams that own the data problem, it's been a barrier and a blocker to success. The data mesh starts with organizational considerations as described in great detail by Ash Nair of Warner Brothers. So take a listen to this clip. >>Yeah, so when people think of Warner Brothers, you always think of like the movie studio, but we're more than that, right? I mean, you think of H B O, you think of t n t, you think of C N N. We have 30 plus brands in our portfolio and each have their own needs. So the, the idea of a data mesh really helps us because what we can do is we can federate access across the company so that, you know, CNN can work at their own pace. You know, when there's election season, they can ingest their own data and they don't have to, you know, bump up against, as an example, HBO if Game of Thrones is going on. >>So it's often the case that data mesh is in the eyes of the implementer. And while a company's implementation may not strictly adhere to Jamma Dani's vision of data mesh, and that's okay, the goal is to use data more effectively. And despite Gartner's attempts to deposition data mesh in favor of the somewhat confusing or frankly far more confusing data fabric concept that they stole from NetApp data mesh is taking hold in organizations globally today. So we're gonna take a B on this one. The prediction is shaping up the way we envision, but as we previously reported, it's gonna take some time. The better part of a decade in our view, new standards have to emerge to make this vision become reality and they'll come in the form of both open and de facto approaches. Okay, our eighth prediction last year focused on the face off between Snowflake and Databricks. >>And we realized this popular topic, and maybe one that's getting a little overplayed, but these are two companies that initially, you know, looked like they were shaping up as partners and they, by the way, they are still partnering in the field. But you go back a couple years ago, the idea of using an AW w s infrastructure, Databricks machine intelligence and applying that on top of Snowflake as a facile data warehouse, still very viable. But both of these companies, they have much larger ambitions. They got big total available markets to chase and large valuations that they have to justify. So what's happening is, as we've previously reported, each of these companies is moving toward the other firm's core domain and they're building out an ecosystem that'll be critical for their future. So as part of that effort, we said each is gonna become aggressive investors and maybe start doing some m and a and they have in various companies. >>And on this chart that we produced last year, we studied some of the companies that were targets and we've added some recent investments of both Snowflake and Databricks. As you can see, they've both, for example, invested in elation snowflake's, put money into Lacework, the Secur security firm, ThoughtSpot, which is trying to democratize data with ai. Collibra is a governance platform and you can see Databricks investments in data transformation with D B T labs, Matillion doing simplified business intelligence hunters. So that's, you know, they're security investment and so forth. So other than our thought that we'd see Databricks I p o last year, this prediction been pretty spot on. So we'll give ourselves an A on that one. Now observability has been a hot topic and we've been covering it for a while with our friends at E T R, particularly Eric Bradley. Our number nine prediction last year was basically that if you're not cloud native and observability, you are gonna be in big trouble. >>So everything guys gotta go cloud native. And that's clearly been the case. Splunk, the big player in the space has been transitioning to the cloud, hasn't always been pretty, as we reported, Datadog real momentum, the elk stack, that's open source model. You got new entrants that we've cited before, like observe, honeycomb, chaos search and others that we've, we've reported on, they're all born in the cloud. So we're gonna take another a on this one, admittedly, yeah, it's a re reasonably easy call, but you gotta have a few of those in the mix. Okay, our last prediction, our number 10 was around events. Something the cube knows a little bit about. We said that a new category of events would emerge as hybrid and that for the most part is happened. So that's gonna be the mainstay is what we said. That pure play virtual events are gonna give way to hi hybrid. >>And the narrative is that virtual only events are, you know, they're good for quick hits, but lousy replacements for in-person events. And you know that said, organizations of all shapes and sizes, they learn how to create better virtual content and support remote audiences during the pandemic. So when we set at pure play is gonna give way to hybrid, we said we, we i we implied or specific or specified that the physical event that v i p experience is going defined. That overall experience and those v i p events would create a little fomo, fear of, of missing out in a virtual component would overlay that serves an audience 10 x the size of the physical. We saw that really two really good examples. Red Hat Summit in Boston, small event, couple thousand people served tens of thousands, you know, online. Second was Google Cloud next v i p event in, in New York City. >>Everything else was, was, was, was virtual. You know, even examples of our prediction of metaverse like immersion have popped up and, and and, and you know, other companies are doing roadshow as we predicted like a lot of companies are doing it. You're seeing that as a major trend where organizations are going with their sales teams out into the regions and doing a little belly to belly action as opposed to the big giant event. That's a definitely a, a trend that we're seeing. So in reviewing this prediction, the grade we gave ourselves is, you know, maybe a bit unfair, it should be, you could argue for a higher grade, but the, but the organization still haven't figured it out. They have hybrid experiences but they generally do a really poor job of leveraging the afterglow and of event of an event. It still tends to be one and done, let's move on to the next event or the next city. >>Let the sales team pick up the pieces if they were paying attention. So because of that, we're only taking a B plus on this one. Okay, so that's the review of last year's predictions. You know, overall if you average out our grade on the 10 predictions that come out to a b plus, I dunno why we can't seem to get that elusive a, but we're gonna keep trying our friends at E T R and we are starting to look at the data for 2023 from the surveys and all the work that we've done on the cube and our, our analysis and we're gonna put together our predictions. We've had literally hundreds of inbounds from PR pros pitching us. We've got this huge thick folder that we've started to review with our yellow highlighter. And our plan is to review it this month, take a look at all the data, get some ideas from the inbounds and then the e t R of January surveys in the field. >>It's probably got a little over a thousand responses right now. You know, they'll get up to, you know, 1400 or so. And once we've digested all that, we're gonna go back and publish our predictions for 2023 sometime in January. So stay tuned for that. All right, we're gonna leave it there for today. You wanna thank Alex Myerson who's on production and he manages the podcast, Ken Schiffman as well out of our, our Boston studio. I gotta really heartfelt thank you to Kristen Martin and Cheryl Knight and their team. They helped get the word out on social and in our newsletters. Rob Ho is our editor in chief over at Silicon Angle who does some great editing for us. Thank you all. Remember all these podcasts are available or all these episodes are available is podcasts. Wherever you listen, just all you do Search Breaking analysis podcast, really getting some great traction there. Appreciate you guys subscribing. I published each week on wikibon.com, silicon angle.com or you can email me directly at david dot valante silicon angle.com or dm me Dante, or you can comment on my LinkedIn post. And please check out ETR AI for the very best survey data in the enterprise tech business. Some awesome stuff in there. This is Dante for the Cube Insights powered by etr. Thanks for watching and we'll see you next time on breaking analysis.

>>Oh, welcome back to the Cube here at aws Reinvent 22. As we continue our coverage here, the AWS Global Showcase, the Startup Showcase, John Wall is here hosting for the Cube as we've been here all week. Hope you're enjoying our coverage here. This is day three, by the way. We're wrapping it up shortly with us to talk about what's going on in the, kind of the hotel world in it and what's going on in the cloud, especially at I hg is Eric Norman, head of infrastructure, architecture, and innovation at I H G Hotels and Resorts. Eric, good to see you, >>Sir. Oh, thank you. And thank you for inviting me. Yeah, >>You bet. Glad to have you board here on the queue. First time, I think too, by the way, right? >>It is. And can I just tell you who IHG is >>Real quick? Yeah, wait a second. First I want another rest. I got Introduc to Rod Stuller, who is the Vice president and of Solutions marketing at Aviatrix and Rod. Good to see you, sir. Thanks a lot. Now let's talk about I ih. >>Great. Well, IHGs a a hospitality company, it's been around for 200 years, that has 17 brands globally in over a hundred countries. We sleek, you know, up could up to 888,000 people a night. So it's a pretty large company that we compete with, you know, all the hotel companies globally. >>So let's talk about your, your footprint right now in, in terms of what your needs are, because you've mentioned obviously a lot of, you have a lot of customers needs, you have a lot of internal stakeholder needs. Yeah. So just from that perspective, how are you balancing out, you know, the products you wanna launch as opposed to the, on the development side and the maintenance side? >>Yeah, I mean we, we have focused our, our attention to our, our guests and our hotels globally and, and taking technology and from a foundation, getting it at, at the edge so that way the consumer and the hotel owner can deliver a quality product to a guest experience. You know, we've have moved larger, a large deployment of our mission critical applications over the last five years really, of moving into more SaaS and infrastructure like AWS and GCP and, and leveraging their global scale to be able to deliver at the edge or get closer to the edge. And so we've, you know, I'm pretty sure you've seen, you know, kind of people building, you know, mission critical apps. You know, probably in the last three years it's probably escalating and more of like a hockey stick of moving stuff. I'd love to hear what AVIA is seeing. Oh >>Yeah. Now we're, we're seeing that quite a bit, right? As people move into the cloud, it's now business critical applications that are going there. So good enough isn't good enough anymore, right? It has to be, you know, a powerful capability that's business critical, can support that, give people the ability to troubleshoot it when something goes wrong. And then multi-cloud, you mentioned a couple different cloud companies, a lot of enterprises are moving to multiple clouds and you don't want to have to do it differently in every cloud. You want a infrastructure management layer that allows you to do that across >>Clouds. So how do you go about that, you know, deciding what goes where. I mean, it sounds like a simple question, but, but if you are dealing in a lot of different kinds of environments, different needs and different requirements, whatever, you know, how are you sorting out, delegating, you know, you know, you're, you're you're gonna be working here, you're gonna be >>Working there. Yeah. So we built some standards base that says, you know, certain types of apps, you know, transactional base, you know, go to this cloud provider and data analytics that's gonna go to another, another cloud provider based on our decision of key capability, native capability, and, and also coverage. You know, cuz we are in China, right? You know, you know, I, I've gotta be able to get into China and, and build not only a network that can support that, but also business apps locally to meet, compete with compliance, regulatory type activities. I mean, even in, in the US market, I got, you know, California privacy laws, you know, you have globally, you've gotta deal with getting data applications into compliance for those globally, right? >>Yeah. So, so you got that compliance slash governance Yeah. Issue. Huge issue. Yeah. I would think for you, you gotta decide who's gonna get to what when, and also we have to meet certain regulatory standards as you pointed out. And not just there, but you got European footprint, right? I mean, you're global. Yeah. So, so you know, handling that kind of scope or scale, what kind of nightmares or challenges does that provide you and how's Aviatrix helping you solve >>That? Yeah, in the early days, you know, we were using cloud native, you know, constructs for networking and a little bit of a security type angle to it. What we found was, you know, you can't get the automation you need. You can't get the, the scalability, you know, cuz we're, we're trying to shift left our, you know, our DevOps and our ability to deploy infrastructure. Aviatrix had come in and, and provided a, a solution that gets us there quicker than anybody else. It's allow us to, you know, build a mesh network across all our regions globally. I'm able to deploy, you know, new landing zones or, you know, public cloud fairly quickly with my, you know, networking construct. We also, we found that because we are a multi hybrid cloud, we, we introduced on the edge a a new network. We had to introduce a performance hub architecture that's using Equinix that sits in every region in every public cloud and partner. Cuz all our partners, you know, we, we've moved a lot of stuff to sas. You know, Amadeus is our centralized reservation system. That's our key, you know? Sure. You know, reservation tool, it's so sourced out. I need to bring them in and I need to get data that's closer to where, in a region to where it needs the land so I can process it. Right. >>And it's a big world out there too. I mean, you're, you're not in your head Rod. So talk about if you would share some of the, the aviatrix experience in that regard. When you have a client like this that has these, you know, multinational locations and, and yet you're looking for some consistency and some uniformity. You don't, you know, you can't be reinventing the wheel every time something pops up, right? >>Right. No. And then, and it's about agility and speed and, you know, being able to do it with less people than you used to have to do things, right? You, you want to be able to give the developers what they need when they need it. There was a time when people were going around it, swiping their credit card and, and saying, it doesn't give me what I need. And so cloud is supposed to change that. So we're trying to deliver the ability to do that for the developers a lot faster than had been done in the past. But at the same time, giving the enterprise the controls, the security, the compliance that they need. And sometimes those things got in the way, but now we're building systems that allow that to happen at, at the piece that developers needed to happen. >>But what Rod said about, you know, one of the big things you sparked my thinking is it also, you know, building a overlay of the cloud native construct allows for visibility that, you know, you didn't have, you know, from a developer or even a operations day two operations, now you get that visibility into the network space and controls and management of that space a lot easier now, you know? >>Yeah. I mean, business critical applications, right? People, the people, the business does not care about networking, right? They see it as electricity and if it's down somebody else's problem to fix it. But the people who do need to keep it up, they need the telemetry. They need the ability to understand, are we trending in the wrong direction? Should we be doing something so that we don't get to the point where it goes down? And that's the kind of information that we're providing in this multi-cloud environment. You mentioned Equinix, we, we just have a partnership with Equinix where we're extending the cloud operational model that Aviatrix delivers all the way out to Equinix and that global fabric that you're talking about. So this is allowing the, the comp companies to have that visibility, that operational ability all the way globally. >>Yeah. Because you know, when you start building all these clouds now and multi regions, multiple AZs or different cloud providers or SaaS providers, you're moving data all over the place. And if you, if you don't have a single pane of glass to see that entire network and be able to route stuff accordingly, it's gonna be a zoo. It's not gonna >>Work. We were, I was talking earlier with, with another guest and we were just talking about companies in your case, I, I IHG kind of knowing what you have and it's not like such a basic thing he said, but yeah, you'd be surprised how many people don't know what they have. Oh, yeah. And so they're trying to provide that visibility and, and, and awareness. So, so I'm kind of curious because you were just the next interview up, so sorry Ken, but, but do you know what you have, I mean, are you learning what you have or is how do you identify, prioritize? How valuable is this asset as opposed to this can wait? I mean, is that still an ongoing process for >>You? It, it's definitely an ongoing process. I mean, we've done over the last three years of constantly assessing all our inventory of what we have, making sure we have the right mo roadmaps for each of the apps and products that we have. Cause we've turned to more of a product driven organization and a DevOps and we're, we're moving more and more product teams onto that DevOps process. Yep. So we can shift left a lot of the activities that developer in the past had to go over a fence to ask for help and, and, you know, kind of the automation of the network and the security built in allows us to be able to shift that left. >>Did that, I, you were saying too three years, right? You've been on, on this path Yep. Going back then to 2019 right. Pandemic hits, right. The world changes. How has that affected this three year period for you? And where are you in terms of where you expected to be and, and Yep. And then what's your, what are your headlights seeing down the road as to what your, your eventual journey, how you want that to end? >>I probably, the biggest story that we have a success story is when the pandemic did happen, you know, all our call centers, all agents had to go home. We were able within 30 days be able to bring up remote desktops, you know, workspaces an a uws and give access to globally in China and in Singapore and in the Americas. There's >>No small task there, >>That's for sure. So we built a desktop, certified it, and, and agents were able to answer calls for guests, you know, you know, so it was a huge success to us. Sure. It did slow down. I mean, during the pandemic it did slow us down from what gets migrated. You know, our focus is, you know, again, back to what I was saying earlier is around our guests and our loyalty and, you know, how do we give value back to our hotel owners and our guests? >>And how do you measure that? I mean, how do you know that what you're doing is working with, with that key audience? >>We'd measured by, you know, one occupa >>There so many, how many people do we have in the rooms? Right? But in terms of the interface, in terms of the effectiveness, the applications, in terms of what you're offering. Yeah. >>It gets back to uptime of our systems and you know, being able to deploy an application in multiple regions elevates the availability of the product to our guest. You know, the longer I'm up, the more revenue I can produce. Right. So, you know, so we, we try to, you know, we measure also guest satisfaction at the properties, you know, them using our tech and that kind of stuff to >>Be so you surveying just to find out what, how they feel about, so some, >>Cause we have a lot of tech inside of our hotels that allow for, we have ISG connect, which allows for people to go from one hotel another and not ask for passwords and, you know, that kind of stuff. >>That would not be made by the way. I'd be begging for help. Let's talk about skills, because I hear that a lot. Talk a lot about that this week. Hearing that, that, you know, the advancement of knowledge is obviously a very powerful thing, but it's also a bit of a shortcoming right now in terms of, of having a need for skills and not having that kind of firepower horsepower on your bench. What, what do you see in that regard? And, and first off, what did you see about it? And then I'll follow >>Up with Yeah, I mean, over our journey, it started off where you didn't have the skills, you know, you didn't have the skill from an operations engineering architecture. So we went on a, you know, you know, how do we build training programs? How do we get, you know, tools to, to either virtual training, bringing teachers, we built, you know, daily, our weekly calls where we bring our experts from our vendors in there to be able to ask questions to help engineering people or architecture people or operations to ask questions and get answers. You know, we, we've been on a role of, you know, upscaling over the last three years and we continue to drive that, you know, we have lunch and learns that we bring people to. Yep. You know, and, and we, and we, we ta tailor the, the content for that training based on what we are consuming and what we're using as opposed to just a, you know, a broad stroke of, of public cloud or, it's >>Almost like you don't have to be holistic about it. You just need to, what do you need to know to >>Make >>Them successful, to be better at what you're doing here? Right. Sure. >>And that's been huge. And, >>And yeah, we, and we have a program called ace, which is AVIATRIX certified engineer. And there's a bunch of different types of classes. So if you're a networking person in the past it's like A C C I E, but we have about 18,000 people over the last three years who have gone through that training. One of them. One of them, right? Is that right? Yeah. Yeah. And, and this is not necessarily about aviatrix. What we're doing is trying to give multi-cloud, you know, networking expertise because a lot of the people that we're talking about are coming from the data center world. And networking is so different in the cloud. We're helping them understand it's not as scary as they might think. Right. If your whole career has been networking in the data center and all of a sudden there's this cloud thing that you don't really understand, you need somebody to help you sort of get there. And we're doing that in a multi-cloud way. And we have all kinds of different levels to teach people how to do, do infrastructure as code. That's another thing, you know, data center guys, they never did infrastructure as code. It was, you had to bolt it in and plug stuff in. Right. But now things are being done much faster with infrastructure as code. And we're teaching people how >>To do that. Yeah. I mean, yesterday, one of the keynotes is about the partner in the, the marketplace. And they use the image imagery of, of marathon runner, you know, a marathon runner. Yeah. You could do a marathon by yourself, but if you want to improve and become a, a great marathon runner, you need a coach, you need nutritionist, you need people running with you to, to make that engine go faster a little bit. Yeah, exactly. And you know, having a partner like Aviatrix helps you know the team to be successful. >>Well, it is, it is a marathon, not a sprint. That's for sure. And you've been on this kind of three year jog. You might feel like you've been running a marathon a little bit, but it sounds like you're really off to a great start and, and have a pretty good partnership here. So thank you. Congratulations on that, Eric. Thank you for being with us. And Rod, same to you. Thank you. Appreciate the time here on the AWS Global Showcase. I'm John Wal, you're watching The Cube. We're out in Las Vegas and of course the cube, as you well know, is the leader in high tech coverage.

>>The Cube Presents UI Path Forward five. Brought to you by UI Path, >>Everybody. We're back in Las Vegas. The cube's coverage we're day one at UI Path forward. Five. Pascal Borne is here. He's an expert and bestselling author in the topic of AI and automation and the book Intelligent Automation. Welcome to the world of Hyper Automation, the first book on the topic. And of course, Ray Wong is back on the cube. He's the founder, chairman and principal analyst, Constellation Reese, also bestselling author of Everybody Wants To Rule the World. Guys, thanks so much for coming on The Cubes. Always a pleasure. Ray Pascal, First time on the Cube, I believe. >>Yes, thank you. Thanks for the invitation. Thank you. >>So what is artificial about artificial intelligence, >>For sure, not people. >>So, okay, so you guys are both speaking at the conference, Ray today. I think you're interviewing the co CEOs. What do you make of that? What's, what are you gonna, what are you gonna probe with these guys? Like, how they're gonna divide their divide and conquer, and why do you think the, the company Danielle in particular, decided to bring in Rob Sland? >>Well, you know what I mean, Like, you know, these companies are now at a different stage of growth, right? There's that early battle between RPA vendors. Now we're actually talking something different, right? We're talking about where does automation go? How do we get the decisioning? What's the next best action? That's gonna be the next step. And to take where UI path is today to somewhere else, You really want someone with that enterprise cred and experience the sales motions, the packages, the partnership capabilities, and who else better than Roblin? He, that's, he's done, he can do that in his sleep, but now he's gotta do that in a new space, taking whole category to another level. Now, Daniel on the other hand, right, I mean, he's the visionary founder. He put this thing from nothing to where he is today, right? I mean, at that point you want your founder thinking about the next set of ideas, right? So you get this interesting dynamic that we've seen for a while with co CEOs, those that are doing the operations, getting the stuff out the door, and then letting the founders get a chance to go back and rethink, take a look at the perspective, and hopefully get a chance to build the next idea or take the next idea back into the organization. >>Right? Very well said. Pascal, why did you write your book on intelligent automation and, and hyper automation, and what's changed since you've written that book? >>So, I, I wrote this book, An Intelligent Automation, two years ago. At that time, it was really a new topic. It was really about the key, the, the key, the key content of the, of the book is really about combining different technologies to automate the most complex end to end business processes in companies. And when I say capabilities, it's, we, we hear a lot about up here, especially here, robotic process automation. But up here alone, if you just trying to transform a company with only up here, you just fall short. Okay? A lot of those processes need more than execution. They need language, they need the capacity to view, to see, they need the capacity to understand and to, and to create insights. So by combining process automation with ai, natural language processing, computer vision, you give this capability to create impact by automating end to end processes in companies. >>I, I like the test, what I hear in the keynote with independent experts like yourself. So we're hearing that that intelligent automation or automation is a fundamental component of digital transformation. Is it? Or is it more sort of a back office sort of hidden in inside plumbing Ray? What do you think? >>Well, you start by understanding what's going on in the process phase. And that's where you see discover become very important in that keynote, right? And that's where process mining's playing a role. Then you gotta automate stuff. But when you get to operations, that's really where the change is going to happen, right? We actually think that, you know, when you're doing the digital transformation pieces, right? Analytics, automation and AI are coming together to create a concept we call decision velocity. You and I make a quick decision, boom, how long does it take to get out? Management committee could free forever, right? A week, two months, never. But if you're thinking about competing with the automation, right? These decisions are actually being done a hundred times per second by machine, even a thousand times per second. That asymmetry is really what people are facing at the moment. >>And the companies that are gonna be able to do that and start automating decisions are gonna be operating at another level. Back to what Pascal's book talking about, right? And there are four questions everyone has to ask you, like, when do you fully intelligently automate? And that happens right in the background when you augment the machine with a human. So we can find why did you make an exception? Why did you break a roll? Why didn't you follow this protocol so we can get it down to a higher level confidence? When do you augment the human with the machine so we can give you the information so you can act quickly. And the last one is, when do you wanna insert a human in the process? That's gonna be the biggest question. Order to cash, incident or resolution, Hire to retire, procure to pay. It doesn't matter. When do you want to put a human in the process? When do you want a man in the middle, person in the middle? And more importantly, when do you want insert friction? >>So Pascal, you wrote your book in the middle of the, the pandemic. Yes. And, and so, you know, pre pandemic digital transformation was kind of a buzzword. A lot of people gave it lip service, eh, not on my watch, I don't have to worry about that. But then it became sort of, you're not a digital business, you're out of business. So, so what have you seen as the catalyst for adoption of automation? Was it the, the pandemic? Was it sort of good runway before that? What's changed? You know, pre isolation, post isolation economy. >>You, you make me think about a joke. Who, who did your best digital transformation over the last years? The ceo, C H R O, the Covid. >>It's a big record ball, right? Yeah. >>Right. And that's exactly true. You know, before pandemic digital transformation was a competitive advantage. >>Companies that went into it had an opportunity to get a bit better than their, their competitors during the pandemic. Things have changed completely. Companies that were not digitalized and automated could not survive. And we've seen so many companies just burning out and, and, and those companies that have been able to capitalize on intelligent automation, digital transformations during the pandemic have been able not only to survive, but to, to thrive, to really create their place on the market. So that's, that has been a catalyst, definitely a catalyst for that. That explains the success of the book, basically. Yeah. >>Okay. Okay. >>So you're familiar with the concept of Stew the food, right? So Stew by definition is something that's delicious to eat. Stew isn't simply taking one of every ingredient from the pantry and throwing it in the pot and stirring it around. When we start talking about intelligent automation, artificial intelligence, augmented intelligence, it starts getting a bit overwhelming. My spy sense goes off and I start thinking, this sounds like mush. It doesn't sound like Stew. So I wanna hear from each of you, what is the methodical process that, that people need to go through when they're going through digital trans transmission, digital transformation, so that you get delicious stew instead of a mush that's just confused everything in your business. So you, Ray, you want, you want to, you wanna answer that first? >>Yeah. You know, I mean, we've been talking about digital transformation since 2010, right? And part of it was really getting the business model, right? What are you trying to achieve? Is that a new type of offering? Are you changing the way you monetize something? Are you taking existing process and applying it to a new set of technologies? And what do you wanna accomplish, right? Once you start there, then it becomes a whole lot of operational stuff. And it's more than st right? I mean, it, it could be like, well, I can't use those words there. But the point being is it could be a complete like, operational exercise. It could be a complete revenue exercise, it could be a regulatory exercise, it could be something about where you want to take growth into the next level. And each one of those processes, some of it is automation, right? There's a big component of it today. But most of it is really rethinking about what you want things to do, right? How do you actually make things to be successful, right? Do I reorganize a process? Do I insert a place to do monetization? Where do I put engagement in place? How do I collect data along the way so I can build better feedback loop? What can I do to build the business graph so that I have that knowledge for the future so I can go forward doing that so I can be successful. >>The Pascal should, should, should the directive be first ia, then ai? Or are these, are these things going to happen in parallel naturally? What's your position on that? Is it first, >>So it, so, >>So AI is part of IA because that's, it's, it's part of the big umbrella. And very often I got the question. So how do you differentiate AI in, I a, I like to say that AI is only the brain. So think of ai cuz I'm consider, I consider AI as machine learning, Okay? Think of AI in a, like a brain near jar that only can think, create, insight, learn, but doesn't do anything, doesn't have any arms, doesn't have any eyes, doesn't not have any mouth and ears can't talk, can't understand with ia, you, you give those capabilities to ai. You, you basically, you create a cap, the capability, technological capability that is able to do more than just thinking, learning and, and create insight, but also acting, speaking, understanding the environment, viewing it, interacting with it. So basically performing these, those end to end processes that are performed currently by people in companies. >>Yeah, we're gonna get to a point where we get to what we call a dynamic scenario generation. You're talking to me, you get excited, well, I changed the story because something else shows up, or you're talking to me and you're really upset. We're gonna have to actually ch, you know, address that issue right away. Well, we want the ability to have that sense and respond capability so that the next best action is served. So your data, your process, the journey, all the analytics on the top end, that's all gonna be served up and changed along the way. As we go from 2D journeys to 3D scenarios in the metaverse, if we think about what happens from a decentralized world to decentralized, and we think about what's happening from web two to web three, we're gonna make those types of shifts so that things are moving along. Everything's a choose your end venture journey. >>So I hope I remember this correctly from your book. You talked about disruption scenarios within industries and within companies. And I go back to the early days of, of our industry and East coast Prime, Wang, dg, they're all gone. And then, but, but you look at companies like Microsoft, you know, they were, they were able to, you know, get through that novel. Yeah. Ibm, you know, I call it survived. Intel is now going through their, you know, their challenge. So, so maybe it's inevitable, but how do you see the future in terms of disruption with an industry, Forget our industry for a second, all industry across, whether it's healthcare, financial services, manufacturing, automobiles, et cetera. How do you see the disruption scenario? I'm pretty sure you talked about this in your book, it's been a while since I read it, but I wonder if you could talk about that disruption scenario and, and the role that automation is going to play, either as the disruptor or as the protector of the incumbents. >>Let's take healthcare and auto as an example. Healthcare is a great example. If we think about what's going on, not enough nurses, massive shortage, right? What are we doing at the moment? We're setting five foot nine robots to do non-patient care. We're trying to capture enough information off, you know, patient analytics like this watch is gonna capture vitals from a going forward. We're doing a lot what we can do in the ambient level so that information and data is automatically captured and decisions are being rendered against that. Maybe you're gonna change your diet along the way, maybe you're gonna walk an extra 10 minutes. All those things are gonna be provided in that level of automation. Take the car business. It's not about selling cars. Tesla's a great example. We talk about this all the time. What Tesla's doing, they're basically gonna be an insurance company with all the data they have. They have better data than the insurance companies. They can do better underwriting, they've got better mapping information and insights they can actually suggest next best action do collision avoidance, right? Those are all the things that are actually happening today. And automation plays a big role, not just in the collection of that, that information insight, but also in the ability to make recommendations, to do predictions and to help you prevent things from going wrong. >>So, you know, it's interesting. It's like you talk about Tesla as the, the disrupting the insurance companies. It's almost like the over the top vendors have all the data relative to the telcos and mopped them up for lunch. Pascal, I wanna ask you, you know, the topic of future of work kind of was a bromide before, but, but now I feel like, you know, post pandemic, it, it actually has substance. How do you see the future of work? Can you even summarize what it's gonna look like? It's, it's, Or are we here? >>It's, yeah, it's, and definitely it's, it's more and more important topic currently. And you, you all heard about the great resignation and how employee experience is more and more important for companies according to have a business review. The companies that take care of their employee experience are four times more profitable that those that don't. So it's a, it's a, it's an issue for CEOs and, and shareholders. Now, how do we get there? How, how do we, how do we improve the, the quality of the employee experience, understanding the people, getting information from them, educating them. I'm talking about educating them on those new technologies and how they can benefit from those empowering them. And, and I think we've talked a lot about this, about the democratization local type of, of technologies that democratize the access to those technologies. Everyone can be empowered today to change their work, improve their work, and finally, incentivization. I think it's a very important point where companies that, yeah, I >>Give that. What's gonna be the key message of your talk tomorrow. Give us the bumper sticker, >>If you will. Oh, I'm gonna talk, It's a little bit different. I'm gonna talk for the IT community in this, in the context of the IT summit. And I'm gonna talk about the future of intelligent automation. So basically how new technologies will impact beyond what we see today, The future of work. >>Well, I always love having you on the cube, so articulate and, and and crisp. What's, what's exciting you these days, you know, in your world, I know you're traveling around a lot, but what's, what's hot? >>Yeah, I think one of the coolest thing that's going on right now is the fact that we're trying to figure out do we go to work or do we not go to work? Back to your other point, I mean, I don't know, work, work is, I mean, for me, work has been everywhere, right? And we're starting to figure out what that means. I think the second thing though is this notion around mission and purpose. And everyone's trying to figure out what does that mean for themselves? And that's really, I don't know if it's a great, great resignation. We call it great refactoring, right? Where you work, when you work, how we work, why you work, that's changing. But more importantly, the business models are changing. The monetization models are changing macro dynamics that are happening. Us versus China, G seven versus bricks, right? War on the dollar. All these things are happening around us at this moment and, and I think it's gonna really reshape us the way that we came out of the seventies into the eighties. >>Guys, always a pleasure having folks like yourself on, Thank you, Pascal. Been great to see you again. All right, Dave Nicholson, Dave Ante, keep it right there. Forward five from Las Vegas. You're watching the cue.

>>Hello and welcome to the power of and where H P E Aruba and Pensando are changing the game the way customers scale at the cloud and what's next in the evolution in switching everyone. I'm john ferrier with the Cuban. I'm here with Shane Corbyn, Director of Technical Product management. Pensando Williams show vice president Product management, Aruba HP Gentlemen, thank you for coming on and doing a deep dive and and going into the big news. So the first question I want to ask you guys is um, what do you guys see from a market customer perspective that kicked this project off? Amazing results over the past year or so. Where did it all come from? >>It's a great question, John So when we were doing our homework, there were actually three very clear customer challenges. First, security threats were largely spawned with from within the perimeter. In fact, four star highlights that 80% of threats originate within the internal network. Secondly, workloads are largely distributed, creating a ton of east west traffic and then lastly, network services such as firewalls load balancers. VPN aggregators are expensive. They're centralized and then ultimately result in service changing complexity. So everyone, >>so go ahead. Change. >>Yeah. Additionally, when we spoke to our customers after launching initially the distributed services platform, these compliance challenges clearly became apparent to us and while they saw the architectural value of adopting what the largest public cloud providers have done by putting a smart making each compute note to provide these state full services. Enterprise customers were still were struggling with the need to upgrade fleets and Brownfield servers and the associated per node cost of adding a spark nick to every compute node. Typically the traffic volumes for on a personal basis within an enterprise data center are significantly lower than cloud. Thus we saw an opportunity here to in conjunction with Aruba developed a new category of switching product um, to share the crossing capabilities of our unique intellectual property around our DPU across a rack of servers that Net Net delivers the same set of services through a new category of platform, enabling a distributed services architecture and ultimately addressing the compliance and uh, TCO generating huge TCO and ri for customers. >>You know, one of the things that we've been reporting on with you guys as well as the cloud scale, this is the volume of data and just the performance and scale I think the timing of the, of this partnership and the product development is right on point. You got the edge right around the corner more, more distributed nature of cloud operations, huge, huge change in the marketplace. So great timing on the origination story there. Great stuff. Tell me more about the platform itself. The details what's under the hood, the hardware. Os, what are the specs? >>Yeah, so we started with a very familiar premise, Ruba customers are already leveraging C X with an edge to cloud, common operating model and deploying Leaf and spy networks. Plus we're excited to introduce the industry's first distributed services switch where the first configuration has 48 25 gig ports with 100 gig uplinks running Aruba C X cloud native operating system. Pensando A six and software inside enabling layer four through seven staple services you want to elaborate on. >>Let me elaborate on that a little further. Um, you know, as we spoke, existing platforms and how customers were seeking to address these challenges were inherently limited by the diocese and that thus limited their scale and performance and ability in traditional switching platforms to deliver truly stable functions in in a switching platform. This was, you know, architecturally from the ground up. When we developed our DPU 1st and 2nd generation, we delivered it or we we we built it with staples services in in mind from the Gecko. We we leverage to clean state designed with RP four program with GPU, we evolved to our seven nanometer based DPU right now, which is essentially enabling software and silicon and this has generated a new level of performance scale flexibility and capability in terms of services this serves as the foundation for or 200 gig card where we're taking the largest cloud providers into production for. And the DPU itself is designed inherently to process state track state connections and state will flow is a very, very large scale without impacting performance. And in fact, the two of these deep you component service, their services foundation of the C X 10-K And this is how we enable states of functions in a switching platform. Functions like stable network network fire walling, stable segmentation, enhance programmable telemetry. Which we believe will bring a whole lot of value to our customers. And this is a, a platform that's inherently programmable from the ground up. We can we can build and and leverages platform to build new use cases around encryption, enabling state for load balancing, stable nash to name a few. But the key message here is this is this is a platform with the next generation of architecture is in mind is programmed but at all levels of the stack and that's what makes it fundamentally different than anything else. >>I want to just double click on that if you don't mind before we get to the competitive question because I think you brought up the state thing, I think this is worth calling out if you guys don't mind commenting more on this state issue because this is big cloud. Native developers right now want speed, they're shifting left at the Ci cd pipeline with program ability. So going down and having the program ability and having state is a really big deal. Can you guys just expand on that a little bit more and why it's important and how hard it really is to pull off. >>I I can start I guess. Well um it's very hard to pull off because of the sheer amount of connections you need to track when you're developing something like a state, full firewall or state from load balancer. A key component of that is managing the connections at very, very large scale and understanding what's happening with those connections at scale without impacting application performance. And this is fundamentally different. A traditional switching platform regardless of how it's deployed today in a six don't typically process and manage state like this. Memory resources within the shape aren't sufficient. Um the policy scale that you can implement on a platform aren't sufficient to address and fundamentally enable deployable fire walling or load balancing or other state services. >>That's exactly right. So the other kind of key point here is that if you think about the sophistication of different security threats, it does really require you to be able to look at the entire packet and more so be able to look at the entire flow and be able to log that history so that you can get much better heuristics around different anomalies. Security threats that are emerging today. >>That's a great great point. Thanks for bringing that extra extra point out, I would just add to this, we're reporting this all the time when silicon angle in the cube is that you know, the you know, the the automation wave that's coming with around data, you know, it's the center of data now, not date as soon as we heard earlier on with the presentation data drives automation having that enabled with state is a real big deal. So I think that's really worth calling out now. I got to ask the competition question, how is this different? I mean this is an evolution, I would say it's a revolution you guys are being humble um but how is this different from what customers can deploy today >>architecturally, if you take a look at it? So we've, we've spoken about the technology and fundamentally in the platform, what's unique in the architecture but foundational e when customers deploy stable services, they're typically deployed leveraging traditional big box appliances for east west or workload based agents which seek to implement stable security for each East west architectural, what we're enabling is staples services like fire walling, segmentation can scale with the fabric and are delivered at the optimal point for east west which is through the Leaf for access their of the network and we do this for any type of workload. Being deployed on a virtualized compute node being deployed on a containerized, our worker node being deployed on bare metal agnostic of topology. It can be in the access layer of a three tier design and a data center. It can be in the leaf layer of the excellent VPN based fabric. But the goal is an all centrally managed to a single point of orchestration control which William we'll talk about shortly. The goal of this is to to drive down the TCO of your data center as a whole by allowing you to retire legacy appliances that are deployed in in east west role, not utilized host based agents and thus save a whole lot of money. And we've modeled on the order of 60 to 70% in terms of savings in terms of the traditional data center pod design of 1000 compute nodes which will be publishing and as as we go forward, additional services as we mentioned like encryption, this platform has the capability to terminate up to 800 gigs of line, right encryption, I P sec VPN per platform state will not load balancing and this is all functionality will be adding to this existing platform because it's programmable as we mentioned from the ground up. >>What are some of the use cases lead and one of the top use case. What's the low hanging fruit? And where does this go? Service providers enterprise, what are the types of customers you guys see implementing? >>Yeah, that's what's really exciting about the C X 10,000 we actually see customer interest from all types of different markets, whether it be higher education service providers to financial services, basically all enterprises verticals with private cloud or edge data centers for example, could be a hospital, a big box retailer or Coehlo. Such as an equity. It's so it's really the 6 10,000 that creates a new switching category enabling staple services in that leaf node, right at the workload, unifying network and security automation policy management. Second, the C X 10,000 greatly improved security posture and eliminates the need for hair pinning east west traffic all the way back to the centralized plants. Lastly, a Shane highlighted there's a 70% Tco savings by eliminating that appliance brawl and ultimately collapsing the network security operations. >>I love the category creation vibe here. Love it. And obviously the technical and the cloud line is great. But how do the customers manage all this? Okay. You got a new category. I just put the box in, throw away some other one. I mean how does this all get down? How does the customers manage all this? >>Yeah. So we're looking to build on top of the ribbon fabric composer. It's another familiar sight for our customers which already provides for compute storage and network automation with a broad ecosystem integrations such as being where the sphere be center as with Nutanix prison And so aligned with the c. x. 10,000 at G. A. now the aruba fabric composer unifies security and policy orchestration and management with the ability to find firewall policies efficiently and provide that telemetry to collectors such a slump. >>So the customer environments right now involve a lot of multi vendor and new frameworks cloud native. How does this fit into the customer's existing environment? The ecosystem. How do they get that get going here? >>Yeah, great question. Um our customers can get going is we we built a flexible platform that can be deployed in either Greenfield or brownfield. Obviously it's a best of breed architecture for distributed services were building in conjunction with the ruble but if customers want to gradually integrate this into their existing environments and they're using other vendors, spines or course this can be inserted seamlessly as a leaf or an access access to your switch to deliver the exact same set of services within that architecture. So it plugs seamlessly in because it supports all the standard control playing protocols, VX, Lenny, VPN and traditional attitude three tier designs easily. Now for any enterprise solution deployment, it's critical that you build a holistic ecosystem around it. It's clear that this will get customer deployments and the ecosystem being diverse and rich is very, very important and as part of our integrations with the controller, we're building a broad suite of integrations across threat detection application dependency mapping, Semen sore develops infrastructure as code tools like ants, Poland to answer the entire form. Um, it's clear if you look at these categories of integrations, you know XDR or threat detection requires full telemetry from within the data center. It's been hard to accomplish to date because you typically need agents on, on your compute nodes to give you the visibility into what's going on or firewalls for east west flaws. Now our platform can natively provide full visibility in dolphins, East west in the data center and this can become the source of telemetry truth that these Ml XT or engines required to work. The other aspects of ecosystem are around application dependency mapping the single core challenge with deploying segmentation. East West is understanding the rules to put in place right first, is how do you insert the service uh service device in such a way that it won't add more complexity. We don't add any complexity because we're in line natively. How do we understand that allow you to build the rules are necessary to do segmentation. We integrate with tools like guard corps, we provide our flow logs a source of data and they can provide rural recommendations and policy recommendations for customers around. We're building integrations around steve and soar with tools like Splunk and elastic elastic search that will allow net hops and sec ops teams to visualize, train and manage the services delivered by the C X 10-K. And the other aspect of ecosystem from a security standpoint is clearly how do I get policy from these traditional appliances and enforce them on this next generation architecture that you've built that can enable state health services. So we're building integrations with tools like toughen analgesic third party sources of policy that we can ingest and enforcing the infrastructure allowing you to gradually migrate to this new architecture over time >>it's really a cloud native switch, you solve people's problems pain points but yet positioned for growth. I mean it sounds that's my takeaway. But I gotta ask you guys both what's the takeaway for the customers because it's not that simple for that. We have a complicated >>Environment. I think, I think it's really simple every 10 years or so. We see major evolutions in the data center in the switching environment. We do believe we've created a new category with the distributed services, distributed services, switch, delivering cloud scale distribute services where the local where the workloads were side greatly simplifying network security provisions and operations with the Yoruba fabric composer while improving security posture and the TCO. But that's not all folks. It's a journey. Right. >>Yeah, it's absolutely a journey. And this is the first step in in a long journey with a great partner like Aruba, there's other platforms, 100 or four gig hardware platforms we're looking at and then there's additional services that we can enable over time allowing customers to drive even more Tco value out of the platform and the architectural services like encryption for securing the cloud on ramp services like state for load balancing to deploy east west in the data center and you know, holistically that's that's the goal, deliver value for customers and we believe we have an architecture and a platform and this is the first step in a long journey. It's >>a great way. I just ask one final final question for both of you. As product leaders, you've got to be excited having a category creation product here in this market, this big wave. What's what's your thoughts? >>Yeah, exactly. Right. It doesn't happen that often. And so we're all in, it's it's exciting to be able to work with a great team like Sandu and chain here. And so we're really excited about this launch. >>Yeah, it's awesome. The team is great. It's a great partnership between and santo and Aruba and you know, we we look forward to delivering value for john customers. >>Thank you both for sharing under the hood and more details on the product. Thanks for coming on. >>Thank you. Okay, >>the next evolution of switching, I'm john furrier here with the power of An HP, Aruba and Pensando, changing the game the way customers scale up in the cloud and networking. Thanks for watching. Mhm.

>>Mhm Welcome back to Los Angeles. The Cubans live, I can't say that enough. The Cubans live. We're at cu con cloud Native Con 21. We've been here all day yesterday and today and tomorrow talking with lots of gas. Really uncovering what's going on in the world of kubernetes, lisa martin here with Dave Nicholson. We've got some folks. Next we're gonna be talking about a customer use case, which is always one of my favorite things to talk about. Please welcome Michael Coletti, the principal platform engineer at CHG Healthcare and then cat from a christian VP of products from port works by pure storage. Guys, welcome to the program, Thank you. Happy to be here. Yeah. So Michael, first of all, let's go ahead and start with you, give the audience an overview of CHG healthcare. >>Yeah, so CHG Healthcare were a staffing company so we sure like a locum pen and so our clients are doctors and hospitals, so we help staff hospitals with temporary doctors or even permanent placing. So we deal with a lot of doctors, a lot of nursing and we're were a combination of multiple companies to see if she is the parents. So and uh yeah, we're known in the industry is one of the leaders in this, this field and providing uh hospitals with high quality uh doctors and nurses and uh you know, our customer services like number one and one of these are Ceos really focused on is now how do we make that more digital, how we provide that same level of quality of service, but a digital experience as rich for >>I can imagine there was a massive need for that in the last 18 months alone. >>Covid definitely really raised that awareness out for us and the importance of that digital experience and that we need to be out there in the digital market. >>Absolutely. So your customer report works by pure storage, we're gonna get into that. But then can talk to us about what's going on. The acquisition of port works by peer storage was about a year ago I talked to us about your VP of product, what's going on? >>Yeah, I mean, you know, first of all, I think I could not say how much of a great fit for a port works to be part of your storage. It's uh uh Pure itself is a very fast moving large start up that's a dominant leader in a flash and data center space. And you know, pure recognizes the fact that Cuban it is is the new operating system of the cloud is now how you know, it's kind of virtualizing the cloud itself and there is a, you know, a big burgeoning need for data management in communities and how you can kind of orchestrate work lords between your on prem data centers in the cloud and back. So port books fits right into the story as complete vision of data management for our customers and uh spend phenomenal or business has grown as part of being part of Pure and uh you know, we're looking at uh launching some new products as well and it's all exciting times. >>So you must have been pretty delighted to be acquired as a startup by essentially a startup because because although pure has reached significant milestones in the storage business and is a leader in flash storage still, that, that startup mindset is there, that's unique, that's not, that's not the same as being acquired by a company that's been around for 100 years seeking to revitalize >>itself. Can >>you talk a little bit about that >>aspect? So I think it will uh, Purest culture is highly innovation driven and it's a very open flat culture. Right? I mean everybody impure is accessible, it can easily have a conversation with folks and everybody has his learning mindset and Port works is and has always been in the same way. Right? So when you put these teams together, if we can create wonders, I mean we, right after that position, just within a few months we announced an integrated solution that Port works orchestrates volumes and she file shares in Pure flash products and then delivers as an integrated solution for our customers. And Pure has a phenomenal uh, cloud based monitoring and management system called Pure one that we integrated well into. Now we're bringing the power of all of the observe ability that Purest customers are used to for all of the partners customers and having super happy, you know, delivering that capability to our customers and our customers are delighted now they can have a complete view all the way from community is an >>app to the >>flash and I don't think any one company on the planet can even climb, they can do that. >>I think, I think it's fair to acknowledge that pure one was observe ability before observe ability was a word. Exactly one used regularly. So that's very interesting. >>I could talk to us about obviously you are a customer CHD as a customer of court works now Port works by peer storage. Talk to us about the use case, what what was the compelling? It was their compelling event and from a storage perspective that that led you to Port works in the >>first so we be, they began this our Ceo basically in the vision, we we need to have a digital presence, we need and hazards and this was even before Covid, so they brought me on board and my my manager read uh glass or he we basically had this task to how are we going to get out into the cloud, how we're going to make that happen And we we chose to follow very much cloud native strategy and the platform of choice. I mean it just made sense with kubernetes and so when we were looking at kubernetes, we're starting to figure out how we're doing, we knew that data is going to be a big factor, you know, um being to provide data, we're very much focused on an event driven, were really pushing to event driven architecture. So we leverage Kafka on top of kubernetes, but at the time we were actually leveraging Kafka with M S K down out in a W S and that was just a huge cost to us. So I came on board, I had experienced with poor works prior company before that and I basically said we need to figure out a great storage away overlay. And the only way to do is we gotta have high performance storage, we've got to have secure, we gotta be able to back up and recover that storage and the poor works was the right match and that allowed us to have a very smooth transition off of M S K onto kubernetes, saving us, it's a significant amount of money per month and just leverage that already existing hardware that are existing, compute memory and just in the and move right to port works, >>leveraging your existing investments. >>Exactly which is key. Very, very key. So, >>so been kept, how common are the challenges that when you guys came together with the HD, how common are the challenges? It's actually, >>that's a great question, you know, this is, I'll tell you the challenges that Michael and his team are running into is what we see a lot in the, in the industry where people pay a ton of money, you know, to, you know, to to other vendors or especially in some cases use some cloud native services, but they want to have control over the data. They want to control the cost and they want higher performance and they want to have, you know, there's also governance and regulatory things that they need to control better. So they want to kind of bring these services and have more control over them. Right? So now we will work very well with all of our partners including the cloud providers as well as uh, you know, an from several vendors and everybody but different customers are different kinds of needs and port works gives them the flexibility if you are a customer who want, you know, have a lot of control over your applications, the performance of the agency and want to control cars very well in leveraging existing investments board works can deliver that for you in your data center right now you can integrate it with pure slash and you get a complete solution or you won't run it in cloud and you still want to have leverage the agility of the cloud and scale for books delivers a solution for you as well. So it kind of not only protects their investment in future proves their architecture, you get future proving your architecture completely. So if you want to tear the cloud or burst the cloud, you have a great solution that you can continue to leverage >>when you hear a future proof and I'm a marketer. So I always go, I love to know what it means to different people, what does that mean to you in your environment? >>My environment. So a future proof means like one of the things we've been addressing lately, that's just a real big challenge and I'm sure it's a challenge in the industry, especially Q and A's is upgrading our clusters ability to actually maintain a consistent flow with how fast kubernetes is growing, you know, they they're out I think yes, we leverage eks so it's like 1 21 or 1 22 now, uh that effort to upgrade a cluster, it can be a daunting one with port works. We actually were able to make that to where we could actually spin up a brand new cluster and with port work shift, all our application services, data migrated completely over poor works, handles all that for us and stand up that new cluster in less than a day. And that effort, it would take us a week, two weeks to do so not even man hours the time spent there, but just the reliability of being able to do that and the cost, you know, instead of standing up a new cluster and configuring it and doing all that and spending all that time, we can just really, we move to what we call blue green cut over strategy and port works is an essential piece of that. >>So is it fair to say that there are a variety of ways that people approach port works from a, from a value perspective in terms of, I I know that one area that you are particularly good in is the area of backups in this environment, but then you get data management and there's a third kind of vector there. What is the third vector? >>Yeah, it's all of the data services. Data services, like for example, database as a service on any kubernetes cluster paid on your cloud or you're on from data centers, which >>data, what kind of databases >>you were talking about? Anything from Red is Kafka Postgres, my sequel, you know, council were supporting, we just announced something called port books, data services offering that essentially delivers all these databases as a service on any kubernetes cluster uh that that a customer can point to unless than kind of get the automated management of the database on day one to day three, the entire life cycle. Um you know, through regular communities, could curdle experience through Api and SDK s and a nice slick ui that they can, you know, just role based access control and all of that, that they can completely control their data and their applications through it. And, you know, that's the third vector of potatoes Africans >>like a question for you. So what works has been a part of peer storage? You've known it since obviously for several years before you were a c h G, you brought up to see H G, you now know it a year into being acquired by a fast paced startup. Talk to me about the relationship and some of the benefits that you're getting with port works as a part of pure storage. >>Well, I mean one of the things, you know, when, when I heard about the accusation, my first thing was I was a little bit concerned is that relationship going to change and when we were acquiring, when we're looking at a doctor and Poor works, One thing I would tell my management is poor works is not just a vendor that wants to throw a solution on you and provide some capability there, partner, they want to partner with you and your success in your journey and this whole cloud native journey to provide this rich digital experience for not only our platform engineering team, but our dev teams, but also be able to really accelerate the development of our services so we can provide that digital portal for our end users and that didn't change. If anything that accelerated that that relationship did not change. You know, I came to the cat with an issue we just, we're dealing with, he immediately got someone on the phone call with me and so that has not changed. So it's really exciting to see that now that they've been acquired that they still are very much invested in the success of their customers and making sure we're successful. You know, it's not all of a sudden I was worried I was gonna have to do a whole different support process and it's gonna go into a black hole didn't happen. They still are very much involved with their customers. And >>that sounds kind of similar to what you talked about with the cultural alignment I've known here for a long time and they're very customer centric. Sounds like one of the areas in which there was a very strong alignment with port works. >>Absolutely important works has always taken pride in being customer. First company. Our founders are heavily customer focused. Uh, you know, they are aligned. They want, they have always aligned uh, the portraits business to our customers needs. Uh Pure is a company that's men. I actually focused on customers, right? I mean, that's all, you know, purist founder cause and everybody care about and so, you know, bringing these companies together and being part of the pure team. I kind of see how synergistic it is. And you know, we have, you know, that has enabled us to serve our customers customers even better than before. >>So, I'm curious about the two of you personally, in terms of your histories, I'm going to assume that you didn't both just bounce out of high school into the world of kubernetes, right? So like lisa and I your spanning the generations between the world of, say, virtualization based on X 86 architecture and virtualization where you can have microservices, you have a full blown operating system that you're working with, that kind of talk about, you know, Michael with you first talk about what that's been like navigating that change. We were in the midst of that, Do you have advice for others that are navigating that change? >>Don't be afraid of it, you know, a lot of people want to, you know, I call it, we're moving from where we're uh naming, we still have cats and dogs, they have a name, the VMS either whether or not their physical boxes or their VMS to where it's more like it's a cattle, you know, it's like we don't own the Os and not to be afraid afraid of that because change is really good. You know, the ability for me to not have to worry about patching and operating system is huge, you know, where I can rely on someone like the chaos and and the version and allow them to, if CV comes out, they let me know I go and I use their tools to be able to upgrade. So I don't have to literally worry about owning that Os and continues the same thing. You know, you, you, you know, it's all about being fault tolerant, right? And being able to be changed where you can actually brought a new version of a container, a base image with a lot of these without having to go and catch a bunch of servers, I mean patch night was held, I'm sorry if I could say that, but it was a nightmare, you know, but this whole world has just been a game changer >>with that. So Van cut from your perspective, you were coming at it, going into a startup, looking at the landscape in the future and seeing opportunity, um what what what's that been like for you? I guess the question for you is more something lisa and I talk about this concept of peak kubernetes, where are we in the wave, is this just is this just the beginning, are we in the thick of it? >>Yeah, I think I would say we're kind of transitioning from earlier doctors too early majority face in the whole, you know, um crossing the chasm analogy. Right, so uh I would say we're still the early stages of this big wave that's going to transform how infrastructure is built, apps are, apps are built and managed and run in production. Um I think some of the uh pieces, the key pieces are falling in place and maturing, uh there are some other pieces like observe ability and security, uh you know, kind of edge use cases need to be, you know, they're kind of going to get a lot more mature and you'll see that the cloud as we know today and the apps as we know today, they're going to be radically different and you know, if you're not building your apps and your business on this modern platform, on this modern infrastructure, you're gonna be left behind. Um, you know, I, my wife's birthday was a couple of days ago. I was telling this story a couple of friends is that I r I used another flowers delivery website. Uh they missed delivering the flowers on the same day, right? So when they told me all kinds of excuses, then I just went and looked up, you know, like door dash, which delivers uh, you know, and then, you know, like your food, but there's also flower delivery, indoor dash and I don't do it, I door dash flowers to her and I can track the flower does all the way she did not eat them, okay, You need them. But my kids love the chocolates though. So, you know, the case in point is that you cannot be, you know, building a modern business without leveraging the moral toolchain and modern toolchain and how the business is going to be delivered. That that thing is going to be changing dramatically. And those kind of customer experience, if you don't deliver, uh, you're not gonna be successful in business and communities is the fundamental technology that enables these containers. It's a fundamental piece of technology that enables building new businesses, you know, modernizing existing businesses and the five G is gonna be, there's gonna be new innovations that's going to get unleashed. And uh, again, communities and containers enable us to leverage those. And so we're still scratching the surface on this, it's big now, it's going to be much, much bigger as we go to the next couple of years. >>Speaking of scratching the surface, Michael, take us out in the last 30 seconds or so with where CHG healthcare is on its digital transformation. How is port works facilitating that? >>So we're right in the thick of it. I mean we are we still have what we call the legacy, we're working on getting those. But I mean we're really moving forward um to provide that rich experience, especially with inventing driven platforms like Kafka and Kubernetes and partnering with port works is one of the key things for us with that and a W s along with that. But we're, and I remember I heard a talk and I can't, I can't remember me but he he talked about how, how kubernetes just sort of like 56 K. Modem, You're hearing it, see, but it's got to get to the point where it's just there, it's just the high speed internet and Kelsey Hightower, That's who Great. Yeah, and I really like that because that's true, you know, and that's where we're on that transition, where we're still early, it's still that 50. So you still want to hear a note, you still want to do cube Cto, you want to learn it the hard way and do all that fun stuff, but eventually it's gonna be where it's just, it's just there and it's running everything like five G. I mean stripped down doing Micro K. It's things like that, you know, we're gonna see it in a lot of other areas and just proliferate and really accelerate uh the industry and compute and memory and, and storage and >>yeah, a lot of acceleration guys, thank you. This has been a really interesting session. I always love digging into customer use cases how C H. G is really driving its evolution with port works Venkat. Thanks for sharing with us. What's going on with port works a year after the acquisition. It sounds like all good stuff. >>Thank you. Thanks for having us. It's been fun, our >>pleasure. Alright for Dave Nicholson. I'm lisa martin. You're watching the cube live from Los Angeles. This is our coverage of Yukon cloud native Con 21 mhm

>>Welcome back to HPD discovered 2021. The virtual edition. My name is Dave Volonte and you're watching the cubes continuous coverage of H. P. S. Big customer event. Patrick Moorehead is here of moor insights and strategy is the number one analyst in the research analyst. Business. Patrick. Always a pleasure. Great to see you, >>David. Great to see you too. And I know you're you're up there fighting for that number one spot to. It's great to see you and it's great to see you in the meetings that were in. But it's even more fun to be here on the cube. I love to be on the cube and every once in a while you'll even call me a friend of the cube, >>unquestionably my friend and so and I can't wait second half. I mean you're traveling right now. We're headed to Barcelona to mobile World Congress later on this month. So so we're gonna we're gonna see each other face to face this year. 100%. So looking forward to that. So you know, let's get into it. Um you know, before we get into H. P. E. Let's talk a little bit about what you're seeing in the market. We've got, you know, we we finally, it feels like the on prem guys are finally getting their cloud act together. Um it's maybe taken a while, but we're seeing as a service models emerge. I think it's resonating with customers. The clearly not everything is moving to the cloud. There's this hybrid model emerging. Multi cloud is real despite what, you know, >>some some >>cloud players want to say. And then there's this edges like jump ball, what are you seeing in the marketplace? >>Yeah. Davis, as exciting as ever in. Just to put in perspective, I mean the public cloud has been around for about 10 years and still only 20% around 20% of the data in 20% of the applications are there now will be a very important ones and I'm certainly not a public cloud denier, I never have been, but there are some missing pieces that need to come together. And you know, even five years ago we were debating dave the hybrid cloud. And I feel like when amazon brought out outposts, the conversation was over right now, what you have is cloud native folks building out hybrid and on prem capabilities, you have a classic on, on prem folks building out hybrid and as a service capabilities. And I really think it boils down 22 things. I mean it's, it's wanting to have more flexibility and you know, I hate to use it because it sounds like a marketing word, but agility, the ability to spin up things and spin down things in a very, a quick way. And uh you know what they've learned, The veterans also know, hey, let's do this in a way that doesn't lock us in too much into a certain vendor. And I've been around for a long time. David and I'm a realist too. Well, you have to lock yourself into something. Uh it just depends on what do you want to lock yourself into, but super exciting and what H. P. E. You know, when they further acts in the sea with Green Lake, I think it was four years ago, uh I think really started to stir the pot. >>You know, you mentioned the term cloud denial, but you know, and I feel like the narrative from, I like to determine as I think you should use the term veteran. You know, it's very, they're ours is the only industry patrick where legacy is a pejorative, but so, but the point I want to make is I feel like there's been a lot of sort of fear from the veteran players, but, but I look at it differently, I wonder what your take is. I, I think, I think I calculated that the Capex spending by the big four public clouds including Alibaba last year was $100 billion. That's like a gift to the world. Here we're gonna spend $100 billion like the internet. Here you go build. And so I, and I feel like companies like HP are finally saying, yeah, we're gonna build, we're gonna build a layer and we're gonna hide the complexity and we're gonna add value on top. What do you think about that? >>Yeah. So I think it's now, I wish, I wish the on prem folks like HP, you would have done it 10 years ago, but I don't think anybody expected the cloud to be as big as it's become over the last 10 years. I think we saw companies like salesforce with sas taking off, but I think it is the right direction because there are advantages to having workloads on prem and if you add an as a service capability on top of the top of that, and let's say even do a Coehlo or a managed service, it's pretty close to being similar to the public cloud with the exception, that you can't necessarily swipe a credit card for a bespoke workload if you're a developer and it is a little harder to scale out. But that is the next step in the equation day, which is having, having these folks make capital expenditures, make them in a Polo facility and then put a layer to swipe a credit card and you literally have the public cloud. >>Yeah. So that's, that's a great point. And that's where it's headed, isn't it? Um, so let's, let's talk about the horses on the track. Hp as you mentioned, I didn't realize it was four years ago. I thought it was, wow, That's amazing. So everybody's followed suit. You see, Dallas announced, Cisco has announced, uh, Lenovo was announced, I think IBM as well. So we, so everybody's sort of following suit there. The reality is, is it's taken some time to get this stuff standardized. What are you seeing from, from HP? They've made some additional announcements, discover what's your take on all this. >>Yeah. So HPD was definitely the rabbit here and they were first in the market. It was good to see. First off some of their, Um, announcements on, on how it's going and they talked about $428 billion 1200 customers over 900 partners and 95% retention. And I think that's important. Anybody who's in the lead and remember what aws I used to do with the slide with the amount of customers would just get bigger and bigger and bigger and that's a good way to show momentum. I like the retention part two which is 95%. And I think that that says a lot uh probably the more important announcements that they made is they talked about the G. A. Of some of their solutions on Green Lake and whether it is A. S. A. P. Hana. Ml apps HPC with Francis, VD. I was Citrus and video but they also brought more of what I would call a vertical layer and I'm sure you've seen the vertical ization of all of these cloud and as a service workloads. But what they're doing with Epic, with EMR and looseness, with financial payments and Splunk and intel with data and risk analysis and finally, a full stack for telco five G. One of the biggest secrets and I covered this about five years ago is HPV actually has a full stack that Western european carriers use and they're now extending that to five G. And um, so more horizontal, uh, and, and more vertical. That was the one of the big swipes, uh, that I saw that there was a second though, but maybe we can talk about these. >>Yeah. Okay. Okay. So, so the other piece of that of course is standardization right there there because there was a, there was a, there was a lot of customization leading up to this and everybody sort of, everybody always had some kind of financial game they can play and say, hey, there's an adversary as a service model, but this is definitely more of a standardized scalable move that H P E. Is making with what they call Lighthouse. Right? >>Yeah, that's exactly right. And I've talked to some Green Lake customers and they obviously gave it kudos or they wouldn't have HP wouldn't have served them up and they wouldn't have been buying it. But they did say, um, it took, it took a while, took some paperwork to get it going. It's not 100% of push button, but that's partially because hp allows you to customize the hardware. You want a one off network adapter. Hp says yes, right. You want to integrate a different type of storage? They said yes. But with Green Lake Lighthouse, it's more of a, what you see is what you get, which by the way, is very much like the public cloud or you go to a public cloud product sheet or order sheet. You're picking from a list and you really don't know everything that's underneath the covers, aside from, let's say, the speed of the network, the type of the storage and the amount of the storage you get. You do get to pick between, let's say, an intel processor, Graviton two or an M. D processor. You get to pick your own GPU. But that's pretty much it. And HP Lighthouse, sorry, Green Lake Lighthouse uh is bringing, I think a simplification to Green Lake that it needs to truly scale beyond, let's say the White House customers that HP Yeah, >>Well done. So, you know, and I hear your point about we're 10 years in plus. And to me this is like a mandate. I mean, this is okay, good, good job guys about time. But if I had a, you know, sort of look at the big player, it's like we have an oligopoly here in this, in this business. It's HP, Cisco, you got Dell Lenovo, you've got, you know, IBM, they're all doing this and they all have a different little difference, you know, waste of skin of catch. And your point about simplicity, it seems like HP HP is all in antony's like, okay, here's what we're going to announce that, you know, a while ago. So, and they seem to have done a good job with Wall Street and they got a simple model, you know, Dell is obviously bigger portfolio, much more complicated. IBM is even more complicated than that. I don't know so much about Lenovo and in Cisco of course, has acquired a ton of SAAS companies and sort of they've got a lot of bespoke products that they're trying to put together. So they've got, but they do have SAS models. So each of them is coming at it from a different perspective. How do you think? And so and the other point we got lighthouse, which is sort of Phase one, get product market fit. Phase two now is scale, codify standardized and then phase three is the moat build your unique advantage that protects your business. What do you see as HP ES sort of unique value proposition and moat that they can build longer term. >>That's a great, great question. And let me rattle off kind of what I'm seeing that some of these players here, So Cisco, ironically has sells the most software of any of those players that you mentioned, uh with the exception of IBM um and yeah, C I >>CSDB two. Yeah, >>yeah, they're the they're the number two security player, uh Microsoft, number one, So and I think the evaluation on the street uh indicate that shows that I feel like Dell tech is a very broad play because not only do they have servers, storage, networking insecurity, but they also have Pcs and devices. So it's a it's a scale and end play with a focus on VM ware solutions, not exclusively of course. Uh And um then you've got Lenovo who is just getting into the as a service game and are gosh, they're doing great in hyper scale, they've got scale there vertically integrated. I don't know if if too many people talk about that, but Lenovo does a lot of their own manufacturing and they actually manufacture Netapp storage solutions as well. So yeah, each of these folks brings a different game to the table. I think with h P e, what you're bringing the table is nimble. When HP and HP split, the number one thing that I said was that ah, h P E is going to have to be so much faster than it offsets the scale that Dell technology has and the HBs credit, although there, I don't think we're getting credit for this in the stock market yet. Um and I know you and I are both industry folks, not financial folks, but I think their biggest thing is speed and the ability to move faster. And that is what I've seen as it relates to the moat, which is a unique uh competitive advantage. Quite frankly, I'm still looking for that day uh in in in what that is. And I think in this industry it's nearly impossible. And I would posit that that any, even the cloud folks, if you say, is there something that AWS can do that as your can't if it put it put its mind to it or G C P. I don't think so. I think it's more of a kind of land and expand and I think for H P E. When it comes to high performance computing and I'm not just talking about government installations, I'm talking about product development, drug development. I think that is a landing place where H P. E already does pretty well can come in and expand its footprint. >>You know, that's really interesting um, observations. So, and I would agree with you. It's kind of like, this is a copycat industry. It's like the west coast offense like the NFL, >>so, >>so the moat comes from, you know, brand execution and your other point about when HP and HP split, that was a game changer because all of a sudden you saw companies like them, you always had a long term relationship with H P E, but or HP, but then they came out of the woodworks and started to explode. And so it really opened up opportunities. So it really is a execution, isn't it? But go ahead please. >>Dave if I had to pick something that I think HP HPV needs to always be ahead in as a service and listen you and I both know announcements don't mean delivery, but there is correlation between if you start four years ahead of somebody that other company is going to have to put just, I mean they're going to have to turn that ship and many of its competitors really big ships to be able to get there. So I think what Antonio needs to do is run like hell, right? Because it, it I think it is in the lead and as a service holistically doesn't mean they're going to be there forever, but they have to stay ahead. They have to add more horizontal solutions. They have to add more vertical solutions. And I believe that at some point it does need to invest in some Capex at somebody like Anna Quinn X play credit card swiper on top of that. And Dave, you have the public, you have the public cloud, you don't have all the availability zones, but you have a public cloud. >>Yeah, that's going to happen. I think you're right on. So we see this notion of cloud expanding. It's no longer just remote set of services. Somewhere out in the cloud. It's like you said, outpost was the sort of signal. Okay, We're coming on prem. Clearly the on prem uh, guys are connecting to the cloud. Multi cloud exists, we know this and then there's the edge but but but that brings me to that sort of vision and everybody's laying out of this this this seamless integration hiding the complexity log into my cloud and then life will be good. But the edge is different. Right? It's not just, you know, retail store or a race track. I mean there's the far edge, there's the Tesla car, there's gonna be compute everywhere and that sort of ties into the data. The data flows, you know the real time influencing at the edge ai new semiconductor models. You you came out of the semiconductor industry, you know it inside and out arm is exploding, dominating in the edge with apple and amazon Alexa and things like that. That's really where the action is. So this is a really interesting cocktail and soup that we have going on. How do >>you say? Well, you know, Dave if the data most data, I think one thing most everybody agrees on is that most of the data will be created on the edge, whether that's a moving edge a car, a smartphone or what I call an edge data center without tile flooring. Like that server that's bolted to the wall of Mcdonald's. When you drive through, you can see it versus the walmart. Every walmart has a raised tile floor. It's the edge to economically and performance wise, it doesn't make any sense to send all that data to the mother ships. Okay. And whether that's unproven data center or the giant public cloud, more efficient way is to do the compute at the closest way possible. But what it does, it does bring up challenges. The first challenge is security. If I wanted to, I could walk in and I could take that server off the Mcdonald's or the Shell gas station wall. So I can't do that in a big data center. Okay, so security, physical security is a challenge. The second is you don't have the people to go in there and fix stuff that are qualified. If you have a networking problem that goes wrong in Mcdonald's, there's nobody there that can help uh they can they can help you fix that. So this notion of autonomy and management and not keeping hyper critical data sitting out there and it becomes it becomes a security issue becomes a management issue. Let me talk about the benefits though. The benefits are lower latency. You want you want answers more quickly when that car is driving down the road And it has a 5GV 2 x communication cameras can't see around corners. But that car communicating ahead, that ran into the stop sign can, through Vita X talked to the car behind it and say, hey, something is going on there, you can't go to, you can't go to the big data center in the sky, let's make that happen, that is to be in near real time and that computer has to happen on the edge. So I think this is a tremendous opportunity and ironically the classic on prem guys, they own this, they own this space aside from smartphones of course, but if you look at compute on a light pole, companies like Intel have built complete architecture is to do that, putting compute into five G base stations, heck, I just, there was an announcement this week of google cloud and its gaming solution putting compute in a carrier edge to give lower latency to deliver a better experience. >>Yeah, so there, of course there is no one edge, it's highly fragmented, but I'm interested in your thoughts on kinda whose stack actually can play at the edge. And I've been sort of poking uh H P E about this. And the one thing that comes back consistently is Aruba, we we could take a room but not only to the, to the near edge, but to the far edge. And and that, do you see that as a competitive advantage? >>Oh gosh, yes. I mean, I would say the best acquisition That hp has made in 10 years has been aruba, it's fantastic and they also managed it in the right way. I mean it was part of HB but it was, it was managed a lot more loosely then, you know, a company that might get sucked into the board and I think that paid off tremendously. They're giving Cisco on the edge a absolute run for their money, their first with new technologies, but it's about the solution. What I love about what a ruble looks at is it's looking at entertainment solutions inside of a stadium, a information solution inside of an airport as opposed to just pushing the technology forward. And then when you integrate compute with with with Aruba, I think that's where the real magic happens. Most of the data on a permanent basis is actually video data. And a lot of it's for security, uh for surveillance. And quite frankly, people taking videos off, they're off their smartphones and downloaded video. I I just interviewed the chief network officer of T mobile and their number one bit of data is video, video uploaded, video download. But that's where the magic happens when you put that connectivity and the compute together and you can manage it in a, in an orderly and secure fashion. >>Well, I have you we have a ton of time here, but I I don't pick your brain about intel the future of intel. I know you've been following it quite closely, you always have Intel's fighting a forefront war, you got there battling a. M. D. There, battling your arm slash and video. They're they're taking on TSMC now and in foundry and, and I'll add china for the looming threat there. So what's your prognosis for for intel? >>Yeah, I liked bob the previous Ceo and I think he was doing a lot of of the right things, but I really think that customers and investors and even their ecosystem wanted somebody leading the company with a high degree of technical aptitude and Pat coming, I mean, Pat had a great job at VM or, I mean he had a great run there and I think it is a very positive move. I've never seen the energy at Intel. Probably in the last 10 years that I've seen today. I actually got a chance to talk with Pat. I visited Pat uhh last month and and talk to him about pretty much everything and where he wanted to take the company the way you looked at technology, what was important, what's not important. But I think first off in the world of semiconductors, there are no quick fixes. Okay. Intel has a another two years Before we see what the results are. And I think 2023 for them is gonna be a huge year. But even with all this competition though, Dave they still have close to 85% market share in servers and revenue share for client computing around 90%. Okay. So and they built out there networking business, they build out a storage business um with obtain they have the leading Aid as provider with Mobileye. And and listen I was I was one of Intel's biggest, I was into one of Intel's biggest, I was Intel's biggest customer when I was a compact. I was their biggest competitor at A. M. B. So um I'm not obviously not overly pushing or there's just got to wait and see. They're doing the right things. They have the right strategy. They need to execute. One of the most important things That Intel did is extend their alliance with TSMC. So in 2023 we're going to see Intel compute units these tiles they integrate into the larger chips called S. O. C. S. B. Manufactured by TSMC. Not exclusively, but we could see that. So literally we could have AMG three nanometer on TSMC CPU blocks, competing with intel chips with TSMC three nanometer CPU blocks and it's on with regard to video. I mean in video is one of these companies that just keeps going charging, charging hard and I'm actually meeting with Jensen wang this week and Arm Ceo Simon Segers to talk about this opportunity and that's a company that keeps on moving interestingly enough in video. If the Arm deal does go through will be the largest chip license, see CPU licensee and have the largest CPU footprint on on the planet. So here we have A and D. Who's CPU and Gpu and buying an F. P. G. A company called Xilinx, you have Intel, Cpus, Gpus machine learning accelerators and F. P. G. S and then you've got arms slashing video bit with everything as well. We have three massive ecosystems. They're gonna be colliding here and I think it's gonna be great for competition date. Competition is great. You know, when there's not competition in Cpus and Gpus, we know what happens, right. Uh, the B just does not go on and we start to stagnate. And I did, I do feel like the industry on CPU started to stagnate when intel had no competition. So bring it on. This is gonna be great for for enterprises then customers to, and then, oh, by the way, the custom Chip providers, WS has created no less than 15 custom semiconductors started with networking uh, and, and nitro and building out an edge that surrounded the general compute and then it moved to Inferential to for inference trainee um, is about to come out for training Graviton and gravitas to for general purpose CPU and then you've got Apple. So innovation is huge and you know, I love to always make fun of the software is eating the world. I always say yeah but has to run on something. And so I think the combination of semiconductors, software and cloud is just really a magical combination. >>Real quick handicap the video arm acquisition. What what are the odds that that they will be successful? They say it's on track. You've got to 2 to 13 to 1 10 to 1. >>I say 75%. Yes 25%. No China is always the has been the odd odd man out for the last three years. They scuttled the qualcomm NXP deal. You just don't know what china is going to do. I think the Eu with some conditions is gonna let this fly. I think the U. S. Is absolutely going to let this fly. And even though the I. P. Will still stay over in the UK, I think the U. S. Wants to see, wants to see this happen. Japan and Korea. I think we'll allow this china is the odd man out. >>In a word, the future of H. P. E. Is blank >>as a service >>patrick Moorehead. Always a pleasure my friend. Great to see you. Thanks so much for coming back in the cube. >>Yeah, Thanks for having me on. I appreciate that. >>Everybody stay tuned for more great coverage from HP discover 21 this is day Volonte for the cube. The leader and enterprise tech coverage. We'll be right back. >>Mm.

>>Welcome back to HPD discovered 2021. My name is Dave Volonte and you're watching the cubes virtual coverage of discovering we're super excited to have Jason Newton back in the cube. He's part of the HPV mastermind alliance behind its messaging and marketing and he's been instrumental and up leveling the conversation over the last several years from ports and lungs and gigahertz, two topics that resonate with business technology executives, which is basically every executive on the planet. Jason. Great to see you welcome back to the program. >>Hey, I'm thrilled to be here. >>Okay, We're gonna talk about the future of enterprise tech and the evolution of cloud hybrid cloud, its expansion to the edge where we are today, where we're headed and how we're going to get there. And I'm excited to start this off. We're living in an era where value and competition. We talk about this all the time is defined by data and the insights that organizations can extract from that data, the products and services that >>they can build, >>that our data centric, What do you think this means to HP and what does it mean for your customers? >>Well, I think we're at the right moment at the right time and I think for the customer it just what's happening now, what's possible to create value from data, it's just a tremendous opportunity to accelerate the transformation they were already driving for their business. Um, we're seeing our customers do amazing things with data, not just monetizing data, but like world changing types of things around uh healthcare and finance, transforming experiences for their customers and all of this is being driven by data. >>Well, I'm, I'm excited to see how you guys approach that. I mean you're talking about this, you know, the cloud to edge strategy and I've been having discussions with various execs at discover obviously remotely about how far hp egos and certainly you're gonna have compute everywhere. And Aruba seems to me to be a really interesting part of that platform. You're gonna go to the deep edge, so you got a lot of assets in the arsenal. How are you thinking about that? >>Well, it really needs to come together into one experience and you mentioned Aruba, I mean that's where it all starts with secure connectivity. The more that we connect things up in a secure way, the more data that we're going to be able to create, analyze and act upon. So it really plays a critical world. But if you look at h p e, we really have an embarrassment of riches of assets and expertise and partnerships at global scale and there's not a part of our business that isn't focused on some part of the data challenges that customers have, from edge computing to supercomputing to storage. What we're doing with the Admiral software, it's all focused on helping customers take in that data and then create insights from it, create new innovations from it. >>Talk a little bit more about the customer challenges that you're specifically solving at H. P. E. What what do you see there? How are you thinking about that? >>And I think one of the biggest ones where the conversation always starts with is you know I have a lot of data but it's all in silos. Um even within my organization or in some cases I know there's data out there but it's in another silo. How do I get access to it? How do I hear that word a lot When we talk to customers, you need to get access for my teams to that data. So first step is just how do I bring it all together? How do I Federated all of that data in one place? That's one area that we're helping customers solve. Um The second is in order to bring those those pieces together, the different data owners have to have a trust right to share the data because often there's not an incentive for them to do that. Like I own the data, I don't want to share it. So we have to establish different parameters or capabilities in order to enable that type of of trust and sharing. And there has to be some mutual benefit right as part of that. And we see that with inside of companies and we see it with multiple different organizations. Once you can overcome those, those are really hard challenges. Once you overcome those things, everything becomes astronomically more easy to deal with and everything starts to go faster. And that's kind of where we're trying to get people on that modern day to maturity curve up to that point where they do have federation. They do have curation, they are able to share. They know what they're going to benefit from it. And then we can get on to the task of enabling the teams to do analytics. It's at speed and scale. >>You talk you talk about federation. So there's an interesting challenge that you're describing and you and I have had some good conversations about this because you want to kind of you to obtain that data if you will and put it in a place that you can actually get to it, share it, make it discoverable. And of course at the same time it's all over the place. So you've kind of got these these pods that are that can talk to each other uh and facilitate that, that kind of data sharing and then what I call, you know, building data products, building data services and technology is at the point now, it's evolving to enable us to do that. It's a look back at the last 10 years, it's just far too complex. >>Yeah, we heard Antonio earlier today talk about, you know, building not private clouds, but private data spaces. And it's really that idea of how do I, how do I bring an experience to the data? Right. That is agile and fast and cloud, like or cloud. And in the case of what we're actually doing now building a cloud platform um if that's exactly where customers are trying to get to um and we look at these data spaces as the advantage by going bringing that to the data. Obviously there's the, you know, the physics of it, the performance and that kind of thing. But you know, we can pay more attention to like data sovereignty laws, um, you know, we can dress things like data ownership within these spaces so that teams can come together and freely collaborate and and act on that data together. >>You know, I've been watching you guys for now several years and you've you've taken this messaging and marketing thing pretty seriously. Even a lot of times, you know, we see it all a lot of times is this gimmicks and I don't mean that necessarily a bad way. There's actually some really good gimmicky marketing that gets a lot of attention, but your approach is different. Um it's very thoughtful. Uh it's cultural, I'll say you're trying to cultural sort of what you say with what you do. And so I want to ask you how you're going about, you know, changing the way in which you provide solutions. I sort of alluded that uh, to that at the top versus how you've done it in the past and how you're helping customers redefine their business for success. >>Well, the way that we're thinking about that is um and I think you heard it very clearly and consistently from Antonio earlier today, we're transforming into an edge to cloud company. Okay, We are building an edge to cloud platform. That is Green Lake. That platform is the way that will deliver cloud services to our customers for their workloads to their datasets wherever that needs to be. We're committed to a truly hybrid model, right edge on prem cloud together. So those elements, it starts to crystallize. I think a lot more about who this company is. The type of challenges that we need to solve. Talking about the things is not, is not interesting to customers. They want to know what problems can you help me solve? How fast can you do it right? What outcome can you help me achieve? And that's the way that you know, we, we talked about this a lot dave that we continue to transform and have those, those more meaningful conversations and like I said, every time we get to the data challenges, they know the opportunities there. They have a dream and a vision of what they want to go do. They just need a partner like HP to help them get there. >>So we talk a lot about Green Lake and as a service, you guys were threw the gauntlet down first. I gotta give you props because you're kind of all in on it. You're not a halfway house. I'll give you that much. But now we've seen at least I can count at least four other large competitors follow suit. How should we think about your strategy and specifically your advantage relative to the competitors? Let's let's talk first in terms of as a service in Green Lake and then maybe >>overall. Yeah, I mean, I think you see a lot of people following Green Lakes lead, we've been out in front for a while. We were the first to say the world will be hybrid and it is, we were the first to make the big bet at the edge. We were the first to see that not all the data is going to go into one unified location, it's going to continue to be distributed and therefore a cloud experience has to travel to that data. We created the Green Lake brand years before anybody else did. And now, while they're just now trying to figure out how do I do hardware is a service or a better way to sell my products. We're moving on, we're focused on the workloads and the workflows and the data sets. Um, Green Lake is much, much more mature and now that we have everybody on board across the company, we're moving much faster as well. Right? And that's more of a statement for the traditional competitors. Right? The traditional spaces, you know, they're still just stuck on like hardware, service infrastructure as a service were at the workload level and much higher. And I think what you're seeing from the public cloud players is, wow, data center an on prem and edges hard. Um, a lot harder than, than I think they really anticipated. And uh, you know, they're, they're reassessing. So I feel like we're in the place where the world is moving to, right? And we're really writing, you know, the first chapter of the new hp? Um Not the last >>has it, has it changed the way this as a service mentality, has it changed the way or how has it changed the way in which your product groups >>are behaving? Um quite a bit um you know, it is a mindset shift and you know it's and uh I think we have the culture that will successfully enabled because we've always been so customer centric, I think as you move two and as a service it becomes much more about how do I ensure customer success? Right? How do I, how do I put an environment in place and then use that as an opportunity to solve more problems across our customers environments? So I think that aspect is what you know really is driving our thinking now is what new services can I can I land on the green Lake edge to cloud platform to solve different data centric challenges? >>Yeah. You talked about, you know, lead and where you are in the majority model. What do you what do you what was the hardest part about making that change? Was it the, was it the leadership was that the sales compensation, was it to get the product guys out of the widgets? What was the hardest thing? >>Yeah, I think, I think go to market is as big a challenge as anything. Um You know, I I think in marketing it's our job to show the art of the possible in the future um even if it's uncomfortable for the organization. Um and I think that helps articulate Antonio's vision and give him a true north and he's a fabulous leader in a culture that you know, they believe and trust in him and so they're following. Um, but, you know, the challenges are, um, not so much, you know, the technology, uh, in many cases it is the people and the skills and uh, you know, building those new relationships within accounts and uh, those aspects, those intangible things. Um, so, you know, we're doing a lot around um enablement, sales, enablement. And of course with our uh, and most importantly with our our partners who are out there selling for us. It is a it is a new approach, but it's a good approach because it's so customer centric, it's not product centric. >>So what are the, so how are the customers and partners reacting? Of course you're gonna say great, but how do you know, like, what what kind of metrics do you look at, what kind of things that are important to you to track, that gives you confidence that you're you're on the right track. >>They're buying more stuff. >>Okay, rhetoric. >>Yeah. No, I mean um like I think there was some skepticism, you know, at first because we have been doing some of that infrastructure as a service type of thing for a while before we ever had a Green Lake brand. And they're like, well, is this just the same thing? Like No, we're truly cloud defying this platform. We're building a cloud native platform. You saw it in the announcements today, right? With cloud native security, just like you get in the public cloud that you can deploy and run these these workloads um in your choice of location and the more that we can show evidence of our messaging in the experience that we actually deliver. That's when customers start to lean. And so we look at a ton of metrics. I mean, you know, it's not one data point. We listen to Gardner. Um you know, we have our own internal research that we do, we're constantly getting feedback from our field. In fact, last week was two weeks ago, we had a board of advisors meeting brought in, you know, some of our top top customers just to hear from them, you know, um you know, what are we doing? Good, What we're not doing good. So it's it's a lot of different pieces that go into, how are we doing with the customer and how are they into this? But this is we're only doing what they told us they wanted. Bring me bring the cloud to me and my data. I can't move at all. But I don't want different operating models. I want a consistent experience. I want to be able to focus and innovate. I don't want to deal with, you know, the underlying pieces of the infrastructure. >>Right? And >>so yeah, we're doing what they ask. >>So they okay, but that sounds good. But then it's hard to do that. I mean, you got to put real is, that's a lot of elbow grease, a lot of investment, a lot of innovation. Uh, like you say, you got to line the organizations. That's, that's not a trivial task. I mean, I tell you, Jason, I've been, I've been hearing this, you know, early days, even 10 years ago, I think we're finally at the point now where the industry is responding to what those customers really want. And of course, you know, it's like Steve jobs with the iPhone, ask them what they want, they're not going to tell you an iPhone, right? They maybe they didn't know 10 years ago, but I think it really came into focus in the last several years and investment is a key there. >>Yeah. I mean I think the last decade was the digital transformation was all about, you know, how do I bring speed to code and take advantage of public cloud and and I think that took us further. It took us, but now, okay, the next chapter is a very data century. How do I bring speed agility to data and data analytics and especially at the edge and where things are, you know, need to live. How do I make a consistent experience that's gonna be our focus for the next 10 years. And like I said, I feel like we're at the right moment in history as a company with the right assets, expertise partnerships to go and help customers take advantage of that. >>Well it's interesting the last decade we talked about big data. We don't use that term much anymore, but like many things like the internet for example, it's over something or maybe it's overhyped at the beginning, but it's always under hyped when you actually see the force that can be. I I feel like we actually are now entering the true data era. So, so you're excited about a lot of things obviously as a service, but I gotta, I got a sense there's more that you're not sharing with us. So what are you most excited about for HP in the future? >>Well, like I said, becoming that edge to cloud company watching Green Lake blossom as it is. I mean tremendous innovations that we announced today and yes, there's things I can't share that I know are coming later this year. I have seen the roadmaps. It's it's it's really compelling, very compelling and impressive the things that we're doing with asthma role combined that together with with Green Lake and that experience the types of data analytic platform environments that we can build to unify those data silos to accelerate the machine learning and analytics teams. Um it's really all coming together and those are the things that I'm excited about. Um you know, changing that perception of H. P. E. Is infrastructure as a service and hardware is a service and that kind of thing. It's not about as a service is the experience, right? The value is in the data and watching us be able to help customers solve those data challenges and seize those those data opportunities is what I'm most excited about. >>Well the other thing too is the world has some big challenges, population and energy. You know, we could just make the huge list and and I feel like tech companies not only are in a position to help but I think they have a they have a responsibility and I gotta say I think most tech companies big large tech companies are stepping up and have great leadership around that. And what are your thoughts on that? >>Well yeah we talked about value from data. It's all about the insights is where the value comes from but values not always about profit and monetization data truly does have the opportunity to solve some of the world's biggest challenges. Um I was just reading this morning about C. G. A. I. R. And the things that they're doing in agriculture with these, they've got a big data set platform that um I think could be literally the thing that ends up helping solve world hunger. The thing that everyone sort of jokes about. I'm like no seriously now with the data that could be possible. >>Yeah, I think you're right, I think we are going to solve world hunger, world nutrition maybe a different story, but we'll tackle that next. Um last question, you know, what else should we be focused on at discover how can folks learn more >>well? You know, this is a three day event, so today was really about the news and excitement and clarifying our position as an edge to cloud company and the Green Lake is our edge to cloud platform. The way that we deliver the cloud to you. Um Tomorrow is really about how all of that vision strategy manifests itself into the experience and the products and solutions that you can consume. Um There'll also be a lot of sharing of uh the keynote is when I'm looking forward to with Dr England Go, he's ahead of ai and he's gonna be sharing all the lessons and learnings from hundreds of engagements that he's been driving with customers, showing exactly how to overcome the data silo problem, the trust problem, how to bring agility to analytics and then thursday is kind of the geek out day, right? We get to talk to Hewlett Packard labs, we get to go and touch the technology, meet the technologists, interact with them. Um and and understand what are those technologies that are gonna be crucial You know, for the next 10 years of data driven transformation. >>Some really exciting stuff there. Jason, thank you so much for spending some time on the cube again. Really great to see you. >>I appreciate the invite every time is a pleasure. Thank you. >>Thanks for being with us for our ongoing coverage of HPD discovered 21 this is Dave Volonte, you're watching the cube. The leader in digital check coverage will be right back. >>Mhm. Mhm.

>>Welcome back to HPD discovered 2021. The virtual edition. My name is Dave Volonte and you're watching the cubes continuous coverage of H. P. S. Big customer event. Patrick Moorehead is here of moor insights and strategy is the number one analyst in the research analyst. Business. Patrick. Always a pleasure. Great to see you, >>David. Great to see you too. And I know you're you're up there fighting for that number one spot to. It's great to see you and it's great to see you in the meetings that were in. But it's even more fun to be here on the cube. I love to be on the cube and every once in a while you'll even call me a friend of the cube, >>unquestionably my friend and so and I can't wait second half. I mean you're traveling right now. We're headed to Barcelona to mobile World Congress later on this month. So so we're gonna we're gonna see each other face to face this year. 100%. So looking forward to that. So, you know, let's get into it. Um you know, before we get into H. P. E. Let's talk a little bit about what you're seeing in the market. We've got, you know, we we we finally, it feels like the on prem guys are finally getting their cloud act together. Um, it's maybe taken a while, but we're seeing as a service models emerge. I think it's resonating with customers. The clearly not everything is moving to the cloud. There's this hybrid model emerging. Multi cloud is real despite what, you know, >>some some >>cloud players want to say. And then there's this edges like jump ball, what are you seeing in the marketplace? >>Yeah. Davis, as exciting as ever in. Just to put in perspective, I mean, the public cloud has been around for about 10 years and still only 20%. Around 20% of the data in 20% of the applications are there now, albeit very important ones. And I'm certainly not a public cloud denier, I never have been, but there are some missing pieces that need to come together. And you know, even five years ago we were debating dave the hybrid cloud and I feel like when Amazon brought out outposts, the conversation was over right now, what you have is cloud native folks building out hybrid and on prem capabilities, you have the classic on prem folks building out hybrid and as a service capabilities. And I really think it boils down 22 things. I mean it's wanting to have more flexibility and you know, I hate to use it because it sounds like a marketing word, but agility, the ability to spin up things and spin down things in a very quick way. And uh, you know what they've learned. The veterans also know, hey, let's do this in a way that doesn't lock us in too much into a certain vendor. And I've been around for a long time. David and I'm a realist too. Well, you have to lock yourself into something. It just depends on what do you want to lock yourself into, but super exciting. And what H. P. E. When they threw the acts in the sea with Green Lake, I think it was four years ago, I think really started to stir the pot. >>You know, you mentioned the term cloud denial, but you know, and I feel like the narrative from, I like to determine is I think you should use the term veteran. You know, it's very, they're ours is the only industry patrick where legacy is a pejorative, but but but so but the point I want to make is I feel like there's been a lot of sort of fear from the veteran players, but I look at it differently. I wonder what you're taking. I think, I think, I think I calculated that the Capex spending by the big four public clouds including Alibaba last year was $100 billion. That's like a gift to the world. Here, we're going to spend $100 billion like the internet here you go build. And and so I, and I feel like companies like HP are finally saying, yeah, we're gonna build, we're gonna build a layer and we're gonna hide the complexity and we're gonna add value on top. What do you think about that? >>Yeah. So I think it's now, I wish, I wish the on prem folks like HP, you would have done it 10 years ago, but I don't think anybody expected the cloud to be as big as it's become over the last 10 years. I think we saw companies like salesforce with sas taking off, but I think it is the right direction because there are advantages to having workloads on prem and if you add an as a service capability on top of the top of that, and let's say even do a Coehlo or a managed service, it's pretty close to being similar to the public cloud with the exception, that you can't necessarily swipe a credit card for a bespoke workload if you're a developer and it is a little harder to scale out. But that is the next step in the equation day, which is having, having these folks make capital expenditures, make them in a polo facility and then put a layer to swipe a credit card and you literally have the public cloud. >>Yeah. So that's, that's a great point and that's where it's headed, isn't it? Um, so let's, let's talk about the horses on the track. Hp. As you mentioned, I didn't realize it was four years ago. I thought it was, wow, That's amazing. So everybody's followed suit. You see, Dallas announced, Cisco has announced, uh, Lenovo was announced, I think IBM as well. So we, so everybody started following suit there. The reality is, is it's taken some time to get this stuff standardized. What are you seeing from, from HP? They've made some additional announcements, discover what's your take on all this. >>Yeah. So HPD was definitely the rabbit here and they were first in the market. It was good to see, first off some of their, Um, announcements on, on how it's going. And they talked about 4, $28 billion 1200 customers over 900 partners and 95% retention. And I think that's important anybody who's in the lead and remember what Aws used to do with the slide with the amount of customers would just get bigger and bigger and bigger and that's a good way to show momentum. I like the retention part two which is 95%. And I think that that says a lot uh probably the more important announcements that they made is they talked about the G. A. Of some of their solutions on Green Lake and whether it was S. A. P. Hana Ml apps HPC with Francis V. I was Citrus in video but they also brought more of what I would call a vertical layer and I'm sure you've seen the vertical ization of all of these cloud and as a service workloads. But what they're doing with Epic with EMR and looseness, with financial payments and Splunk and intel with data and risk analysis and finally, a full stack for telco five G. One of the biggest secrets and I covered this about five years ago is HPV actually has a full stack that western european carriers use and they're now extending that to five G. And um, so more horizontal uh and and more vertical. That was the one of the big swipes uh that I saw that there was a second though, but maybe we can talk about these. >>Yeah. Okay, Okay. So, so the other piece of that of course is standardization right there there because there was a, there was, there was a lot of customization leading up to this and everybody sort of, everybody always had some kind of financial game they can play and say, hey, there's an adversary as a service model, but this is definitely more of a standardized scalable move that H P E. Is making with what they call Lighthouse, Right? >>Yeah, that's exactly right. And I've talked to some Green Lake customers and they obviously gave it kudos or they wouldn't have HP wouldn't have served them up and they wouldn't have been buying it. But they did say, um, it took, it took a while, took some paperwork to get it going. It's not 100% of push button, but that's partially because hp allows you to customize the hardware. You want a one off network adapter. Hp says yes, right. You want to integrate a different type of storage? They said yes. But with Green Lake Lighthouse, it's more of a, what you see is what you get, which by the way is very much like the public cloud or you go to a public cloud product sheet or order sheet. You're picking from a list and you really don't know everything that's underneath the covers, aside from, let's say the speed of the network, the type of the storage and the amount of the storage you get. You do get to pick between, let's say, an intel processor, Graviton two or an M. D processor. You get to pick your own GPU. But that's pretty much it. And HP Lighthouse, sorry, Green Lake Lighthouse uh, is bringing, I think a simplification to Green Lake that it needs to truly scale beyond, let's say, the white house customers at HP. Yeah, >>Well done. So, you know, and I hear your point about 10 years in, you know, plus and to me this is like a mandate. I mean, this is okay. Good, good job guys about time. But if I had a, you know, sort of look at the big players, like, can we have an oligopoly here in this, in this business? It's HP, Cisco, you got Dell Lenovo, you've got, you know, IBM, they're all doing this and they all have a different little difference, you know, waste of skin of catch. And your point about simplicity, it seems like HP HP is all in Antonio's like, okay, here's what we're going to announce that, you know, while ago, so, and they seem to have done a good job with Wall Street and they get a simple model, you know, Dell's obviously bigger portfolio, much more complicated. IBM is even more complicated than that. I don't know so much about Lenovo and in Cisco of course, has acquired a ton of SAAS companies and sort of they've got a lot of bespoke products that they're trying to put together, so they've got, but they do have SAS models. So each of them is coming at it from a different perspective. How do you think? And so and the other point we got lighthouse, which is sort of Phase one, get product market fit. Phase two now is scale codify standardized and then phase three is the moat build your unique advantage that protects your business. What do you see as HP? Es sort of unique value proposition and moat that they can build longer term. >>That's a great, great question. And let me rattle off kind of what I'm seeing that some of these these players here. So Cisco, ironically, has sells the most software of any of those players that you mentioned, uh with the exception of IBM. Um, and yeah, C >>ICSDB two. Yeah, >>yeah, they're the they're the number two security player, uh, Microsoft, number one. So and I think the evaluation on the street uh indicate that shows that I feel like uh Deltek is a is a very broad play because not only do they have servers, storage, networking and security, but they also have Pcs and devices, so it's a it's a scale and end play with a focus on VM ware solutions, not exclusively, of course. Uh And um then you've got Lenovo who is just getting into the as a service game and are gosh, they're doing great in hyper scale, they've got scale there vertically integrated. I don't know if if too many people talk about that, but Lenovo does a lot of their own manufacturing and they actually manufacture Netapp storage solutions as well. So yeah, each of these folks brings a different game to the table, I think with h P E, what your bring to the table is nimble. When HP and HP split, the number one thing that I said was that uh huh H P E is going to have to be so much faster than it offsets the scale that Dell technology has and the HBs credit, although there, I don't think we're getting credit for this in the stock market yet. Um, and I know you and I are both industry folks, not financial folks, but I think their biggest thing is speed and the ability to move faster and that is what I've seen as it relates to the moat, which is a unique uh, competitive advantage. Quite frankly, I'm still looking for that day in, in, in what that is and I think in this industry it's nearly impossible and I would posit that that any, even the cloud folks, if you say, is there something that AWS can do that Azure can't, if it put it put its mind to it or G C P. I don't think so. I think it's more of a kind of land and expand and I think for H P E, when it comes to high performance computing and I'm not just talking about government installations, I'm talking about product development, drug development, I think that is a landing place where H P E already does pretty well can come in and expand its footprint, >>you know, that's really interesting um, observations. So, and I would agree with you, it's kind of like, this is a copycat industry, it's like the west coast offense, like the NFL >>and >>so, so the moat comes from, you know, brand execution and your other point about when HP and HP split, that was a game changer, because all of a sudden you saw companies like them, you always had a long term relationship with H P E but or HP, but then they came out of the woodworks and started to explode. And so it really opened up opportunities. So it really >>is an execution, >>isn't it? But go ahead, please >>Dave if I had to pick something that I think HP HPV needs to always be ahead and as a service and listen, you know, I both know announcements don't mean delivery, but there is correlation between if you start four years ahead of somebody that other company is going to have to put just, I mean they're gonna have to turn that ship and many of its competitors really big ships to be able to get there. So I think what Antonio needs to do is run like hell, right, Because it, it, I think it is in the lead and as a service holistically doesn't mean they're going to be there forever, but they have to stay ahead. They have to add more horizontal solutions. They have to add more vertical solutions. And I believe that at some point it does need to invest in some Capex at somebody like ANna Quinn x play credit card swiper on top of that. And Dave, you have the public, you have the public cloud, you don't have all the availability zones, but you have a public cloud. >>Yeah, that's going to happen. I think you're right on. So we see this notion of cloud expanding. It's no longer just remote set of services. Somewhere out in the cloud. It's as you said, outpost was the sort of signal. Okay, We're coming on prem clearly the on prem, uh, guys are connecting to the cloud. Multi cloud exists, we know this and then there's the edge but but but that brings me to that sort of vision and everybody's laying out of this this this seamless integration hiding the complexity log into my cloud and then life will be good. But the edge is different. Right? It's not just, you know, retail store or a race track. I mean there's the far edge, there's the Tesla car, there's gonna be compute everywhere. And that sort of ties into the data. The data flows, you know the real time influencing at the edge ai new semiconductor models. You you came out of the semiconductor industry, you know it inside and out arm is exploding is dominating in the edge with with with apple and amazon Alexa and things like that. That's really where the action is. So this is a really interesting cocktail and soup that we have going on. How do you >>say? Well, you know, Dave if the data most data, I think one thing most everybody agrees on is that most of the data will be created on the edge. Whether that's a moving edge a car, a smartphone or what I call an edge data center without tile flooring. Like that server that's bolted to the wall of Mcdonald's. When you drive through, you can see it versus the walmart. Every walmart has a raised tile floor. It's the edge to economically and performance wise, it doesn't make any sense to send all that data to the mother ships. Okay. And whether that's unproven data center or the giant public cloud, more efficient way is to do the compute at the closest way possible. But what it does, it does bring up challenges. The first challenge is security. If I wanted to, I could walk in and I could take that server off the Mcdonald's or the Shell gas station wall. So I can't do that in a big data center. Okay, so security, Physical security is a challenge. The second is you don't have the people to go in there and fix stuff that are qualified. If you have a networking problem that goes wrong and Mcdonald's, there's nobody there that can help uh, they can they can help you fix that. So this notion of autonomy and management and not keeping hyper critical data sitting out there and it becomes it becomes a security issue becomes a management issue. Let me talk about the benefits though. The benefits are lower latency. You want you want answers more quickly when that car is driving down the road and it has a five G V two X communication cameras can't see around corners, but that car communicating ahead, that ran into the stop sign, can I through vi to X. Talk to the car behind it and say, hey, something is going on there, you can't go to, you can't go to the big data center in the sky to make that happen, that is to be in near real time and that computer has to happen on the edge. So I think this is a tremendous opportunity and ironically the classic on prem guys, they own this, they own this space aside from smartphones of course, but if you look at compute on a light pole, companies like Intel have built Complete architectures to do that, putting compute into 5G base stations. Heck, I just, there was an announcement this week of google cloud in its gaming solution putting compute in a carrier edge to give lower latency to deliver a better experience. >>Yeah, so there, of course there is no one edge, it's highly fragmented, but I'm interested in your thoughts on kind of who's stack actually can play at the edge. And I've been sort of poking uh H P E about this. And the one thing that comes back consistently is Aruba, we we can take a room but not only to the, to the near edge, but to the far edge. And and that, do you see that as a competitive advantage? >>Oh gosh, yes. I mean, I would say the best acquisition That hp has made in 10 years has been aruba it's fantastic. And they also managed it in the right way. I mean, it was part of HB but it was it was managed a lot more loosely then, you know, a company that might get sucked into the board. And I think that paid off tremendously. They're giving Cisco on the edge a absolute run for their money, their first with new technologies. But it's about the solution. What I love about what a ruble looks at is it's looking at entertainment solutions inside of a stadium, um a information solution inside of an airport as opposed to just pushing the technology forward. And then when you integrate compute with with with Aruba, I think that's where the real magic happens. Most of the data on a permanent basis is actually video data. And a lot of it's for security uh for surveillance. And quite frankly, people taking videos off, they're off their smartphones and downloading video. I I just interviewed the chief network officer of T mobile and their number one bit of data is video, video uploaded, video download. But that's where the magic happens when you put that connectivity and the compute together and you can manage it in a, in an orderly and secure fashion >>while I have you, we have a ton of time here, but I I don't pick your brain about intel, the future of intel. I know you've been following it quite closely, you always have Intel's fighting a forefront war. You got there, battling A. M. D. There, battling your arm slash and video. They're they're taking on TSMC now and in foundry and, and I'll add china for the looming threat there. So what's your prognosis for for intel? >>Yeah, I liked bob the previous Ceo and I think he was doing a lot of of the right things, but I really think that customers and investors and even their ecosystem wanted somebody leading the company with a high degree of technical aptitude and Pat coming, I mean, Pat had a great job at VM or, I mean, he had a great run there and I think it is a very positive move. I've never seen the energy At Intel probably in the last 10 years that I've seen today. I actually got a chance to talk with pat. I visited pat uhh last month and and talk to him about pretty much everything and where he wanted to take the company the way you looked at technology, what was important, what's not important. But I think first off in the world of semiconductors, there are no quick fixes. Okay. Intel has a another two years Before we see what the results are. And I think 2023 for them is gonna be a huge year. But even with all this competition though, Dave they still have close to 85% market share in servers and revenue share for client computing around 90%. Okay. So and they've built out there networking business, they build out a storage business um with with obtain they have the leading Aid as provider with Mobileye. And and listen I was I was one of Intel's biggest, I was into one of Intel's biggest, I was Intel's biggest customer when I was a compact. I was their biggest competitor at AMG. So um I'm not obviously not overly pushing or there's just got to wait and see. They're doing the right things. They have the right strategy. They need to execute. One of the most important things That Intel did is extend their alliance with TSMC. So in 2023 we're going to see Intel compute units these tiles, they integrate into the larger chips called S. O. C S B. Manufactured by TSMC. Not exclusively, but we could see that. So literally we could have AMG three nanometer on TSMC CPU blocks, competing with intel chips with TSMC three nanometer CPU blocks and it's on with regard to video. I mean in video is one of these companies that just keeps going charging, charging hard and I'm actually meeting with Jensen wang this week and Arms Ceo Simon Segers to talk about this opportunity and that's a company that keeps on moving interestingly enough in video. If the arm deal does go through will be the largest chip license, see CPU licensee and have the largest CPU footprint on the planet. So here we have AMG who's CPU and Gpu and buying an F. P. G. A company called Xilinx, you have Intel, Cpus, Gpus machine learning accelerators and F. P. G. S. And then you've got arms slashing video bit with everything as well. We have three massive ecosystems. They're gonna be colliding here and I think it's gonna be great for competition. Date. Competition is great. You know, when there's not competition in CPUs and Gpus, we know what happens right. Uh, the beach just does not go on and we start to stagnate. And I did, I do feel like the industry on CPU started to stagnate when intel had no competition. So bring it on. This is gonna be great for for enterprises then customers to and then, oh, by the way, you have the custom Chip providers. WS has created no less than 15 custom semiconductors started with networking and nitro and building out an edge that surrounded the general computer. And then it moved to Inferential for inference trainee um, is about to come out for training Graviton and Gravitas to for general purpose CPU and then you've got apple. So innovation is huge and I love to always make fun of the software is eating the world. I always say yeah but has to run on something. And so I think the combination of semiconductors software and cloud is just really a magical combination. >>Real quick handicap the video arm acquisition. What what are the odds that that they will be successful? They say it's on track. You got a 2 to 13 to 1 10 to 1. >>I say 75%. Yes 25%. No China is always the has been the odd odd man out for the last three years. They scuttled the Qualcomm NXp deal. You just don't know what china is going to do. I think the EU with some conditions is going to let this fly. I think the U. S. Is absolutely going to let this fly. And even though the I. P. Will still stay over in the UK, I think the U. S. Wants to see wants to see this happen, Japan and Korea I think we'll allow this china is the odd man out. >>In a word, the future of h p. E is blank >>as a service >>patrick Moorehead. Always a pleasure. My friend. Great to see you. Thanks so much for coming back in the cube. >>Yeah, Thanks for having me on. I appreciate that. >>Everybody stay tuned for more great coverage from HP discover 21 this is day Volonte for the cube. The leader and enterprise tech coverage. We'll be right back.

>>Mhm >>Yes, welcome to this cube conversation. I'm lisa martin excited about this conversation. It's combining my background in life sciences with technology. Please welcome Mike Tarsa Lee, the chief scientific officer at Tetra Science. Mike I'm so excited to talk to you today. >>Thank you lisa and thank you very much to the cube for hosting us. >>Absolutely. So we talk about cloud and data all the time. This is going to be a very interesting conversation especially because we've seen events of the last what are we on 14 months and counting have really accelerated the need for drug discovery and really everyone's kind of focused on that. But I want you to talk with our audience about Tetra science, Who you guys are, what you do and you were founded in 2014. You just raised 80 million in series B but give us an idea of who you are and what you do. >>Got it. Tetro Science, what are we? We are digital plumbers and that may seem funny but really we are taking the world of data and we are trying to resolve it in such a way that people can actually pipe it from the data sources they have in a vendor agnostic way to the data targets in which they need to consume that data. So bringing that metaphor a little bit more to life sciences, let's say that you're a chemist and you have a mass spec and an NMR and some other piece of technology and you need all of those to speak the same language. Right? Generally speaking, all of these are going to be made by different vendors. They're all going to have different control software and they're all going to have slightly different ways of sending their data in. Petro Science takes those all in. We bring them up to the cloud or cloud native solution. We harmonize them, we extract the data first and then we actually put it into what we call our special sauce are intermediate data schema to harmonize it. So you have sort of like a picture and a diagram of what the prototypical mass spec or H P. L. C. Or cell counting data should look like. And then we build pipelines to export that data over to where you need it. So if you need it to live in an L. N. Or a limb system or in a visualization tool like spot fire tableau. We got you covered. So again we're trying to pipe things from left to right from sources to targets and we're trying to do it with scientific context. >>That was an outstanding description. Data plumbers who have secret sauce and never would have thought I would have heard that when I woke up this morning. But I'm going to unpack this more because one of the things that I read in the press release that just went out just a few weeks ago announcing the series B funding, it said that that picture science is pioneering a $300 billion dollar Greenfield data market and operating this is what got my attention without a direct cloud native and open platform competitor. Why is that? >>That's right. If you look at the way pharma data is handled today, even those that long tend to be either on prem solutions with a sort of license model or a distribution into a company and therefore maintenance costs, professional services, etcetera. Or you're looking at somebody who is maybe cloud but their cloud second, you know, they started with their on prem journey and they said we should go and build out some puppies, we should go to the cloud migrate. However, we're cloud first cloud native. So that's one first strong point. And the second is that in terms of data harmonization and in terms of looking at data in a vendor agnostic way, um many companies claim to do it. But the real hard test of this, the metal, what will say is when you can look at this with the Scientific contextual ization we offer. So yes, you can collect the data and put it on a cloud. Okay great. Yes. You may be able to do an extract, transform and load and move it to somewhere else. Okay. But can you actually do that from front to back while retaining all the context of the data while keeping all of the metadata in the right place? With veracity, with G XP readiness, with data fidelity and when it gets over to the other side can somebody say oh yeah that's all the data from all the H. P. L. C. S we control. I got it. I see where it is. I see where to go get it, I see who created it. I see the full data train and validation landscape and I can rebuild that back and I can look back to the old raw source files if I need to. Um I challenge someone to find another direct company that's doing that today. >>You talk about that context and the thing that sort of surprises me is with how incredibly important scientific discovery is and has been for since the beginning of time. Why is why has nobody come out in the last seven years and tried to facilitate this for life sciences organizations. >>Right. I would say that people have tried and I would say that there are definitely strides being made in the open source community, in the data science community and inside pharma and biotech themselves on these sort of build motif, right. If you are inside of a company and you understand your own ontology and processes while you can probably design an application or a workflow using several different tools in order to get that data there. But will it be generally useful to the bioscience community? One thing we pride ourselves on is when we product eyes a connector we call or an integration, we actually do it with a many different companies, generic cases in mind. So we say, OK, you have an h p l C problem over at this top pharma, you have an HPC problem with this biotech and you have another one of the C R. O. Okay. What are the common points between all of those? Can we actually distill that down to a workflow? Everyone's going to need, for example a compliance workflow. So everybody needs compliance. Right. So we can actually look into an empower or a unicorn operation and we can say, okay, did you sign off on that? Did it come through the right way? Was the data corrupted etcetera? That's going to be generically useful to everybody? And that's just one example of something we can do right now for anybody in bio pharma. >>Let's talk about the events of the last 14 months or so mentioned 10 X revenue growth in 2020. Covid really really highlighted the need to accelerate drug discovery and we've seen that. But talk to me about some of the things that Tetra science has seen and done to facilitate that. >>Yeah, this past 14 months. I mean um I will say that the global pandemic has been a challenge for everyone involved ourselves as well. We've basically gone to a full remote workforce. Um We have tried our very best to stay on top of it with remote collaboration tools with vera, with GIT hub with everything. However, I'll say that it's actually been some of the most successful time in our company's history because of that sort of lack of any kind of friction from the physical world. Right? We've really been able to dig down and dig deep on our integrations are connections, our business strategy. And because of that, we've actually been able to deliver a lot of value to customers because, let's be honest, we don't actually have to be on prem from what we're doing since we're not an on prem solution and we're not an original equipment manufacturer, we don't have to say, okay, we're going to go plug the thing in to the H. P. L. C. We don't have to be there to tune the specific wireless protocols or you're a W. S. Protocols, it can all be done remotely. So it's about building good relationships, building trust with our colleagues and clients and making sure we're delivering and over delivering every time. And then people say great um when I elect a Tetra solution, I know what's going right to the cloud, I know I can pick my hosting options, I know you're going to keep delivering more value to me every month. Um Thanks, >>I like that you make it sound simple and that actually you bring up a great point though that the one of the many things that was accelerated this last year Plus is the need to be remote that need to be able to still communicate, collaborate but also the need to establish and really foster those relationships that you have with existing customers and partners as everybody was navigating very, very different challenges. I want to talk now about how you're helping customers unlock the problem that is in every industry data silos and point to point integration where things can talk to each other, Talk to me about how you're helping customers like where do they start with? Touch? Where do you start that? Um kind of journey to unlock data value? >>Sure. Journey to unlock data value. Great question. So first I'll say that customers tend to come to us, it's the oddest thing and we're very lucky and very grateful for this, but they tend to have heard about what we've done with other companies and they come to us they say listen, we've heard about a deployment you've done with novo Nordisk, I can say that for example because you know, it's publicly known. Um so they'll say, you know, we hear about what you've done, we understand that you have deep expertise in chromatography or in bio process. And they'll say here's my really sticky problem. What can you do here? And invariably they're going to lay out a long list of instruments and software for us. Um we've seen lists that go up past 2000 instruments. Um and they'll say, yeah, they'll say here's all the things we need connected, here's four or five different use cases. Um we'll bring you start to finish, we'll give you 20 scientists in the room to talk through them and then we to get somewhere between two and four weeks to think about that problem and come back and say here's how we might solve that. Invariably, all of these problems are going to have a data silos somewhere, there's going to be in Oregon where the preclinical doesn't see the biology or the biology doesn't see the screening etcetera. So we say, all right, give us one scientist from each of those, hence establishing trust, establishing input from everybody. And collaboratively we'll work with, you will set up an architecture diagram, will set up a first version of a prototype connector, will set up all this stuff they need in order to get moving, we'll deliver value upfront before we've ever signed a contract and will say, is this a good way to go for you? And they'll say either no, no, thank you or they'll say yes, let's go forward, let's do a pilot a proof of concept or let's do a full production rollout. And invariably this data silos problem can usually be resolved by again, these generic size connectors are intermediate data schema, which talks and moves things into a common format. Right? And then also by organizationally, since we're already connecting all these groups in this problem statement, they tend to continue working together even when we're no longer front and center, right? They say, oh we set up that thing together. Let's keep thinking about how to make our data more available to one another. >>Interesting. So culturally, within the organization it sounds like Tetra is having significant influences their, you know, the collaboration but also data ownership. Sometimes that becomes a sticky situation where there are owners and they want to read retain that control. Right? You're laughing? You've been through this before. I'd like to understand a little bit more though about the conversation because typically we're talking about tech but we're also talking about science. Are you having these technical conversations with scientists as well as I. T. What is that actual team from the customer perspective look >>like? Oh sure. So the technical conversation and science conversation are going on sometimes in parallel and sometimes in the same threat entirely. Oftentimes the folks who reach out to us first tend to be the scientists. They say I've got a problem, you know and and my research and and I. T. Will probably hear about this later. But let's go. And then we will invariably say well let's bring in your R. And D. I. T. Counterparts because we need them to help solve it right? But yes we are usually having those conversations in parallel at first and then we unite them into one large discussion. And we have varied team members here on the Tetris side we have me from science along with multiple different other PhD holders and pharma lifers in our business who actually can look at the scientific use cases and recommend best practices for that and visualizations. We also have a lot of solutions architects and delivery engineers who can look at it from the how should the platform assemble the solution and how can we carry it through? Um And those two groups are three groups really unite together to provide a unified front and to help the customer through and the customer ends up providing the same thing as we do. So they'll give us on the one call, right? Um a technical expert, a data and QA person and a scientist all in one group and they'll say you guys work together to make sure that our orders best represented here. Um And I think that that's actually a really productive way to do this because we end up finding out things and going deeper into the connector than we would have otherwise. >>It's very collaborative, which is I bet those are such interesting conversations to be a part of it. So it's part of the conversation there helping them understand how to establish a common vision for data across their organization. >>Yes, that that tends to be a sort of further reaching conversation. I'll say in the initial sort of short term conversation, we don't usually say you three scientists or engineers are going to change the fate of the entire orig. That's maybe a little outside of our scope for now. But yes, that first group tends to describe a limited solution. We help to solve that and then go one step past and then they'll nudge somebody else in the Oregon. Say, do you see what Petra did over here? Maybe you could use it over here in your process. And so in that way we sort of get this cultural buy in and then increased collaboration inside a single company. >>Talk to me about some customers that you've worked with it. Especially love to know some of the ones that you've helped in the last year where things have been so incredibly dynamic in the market. But give us an insight into maybe some specific customers that work with you guys. >>Sure. I'd love to I'll speak to the ones that are already on our case studies. You can go anytime detector science dot com and read all of these. But we've worked with Prelude therapeutics for example. We looked at a high throughput screening cascade with them and we were able to take an instrument that was basically unloved in a corner at T. Can liquid handler, hook it up into their Ln. And their screening application and bring in and incorporate data from an external party and do all of that together and merge it so they could actually see out the other side a screening cascade and see their data in minutes as opposed to hours or days. We've also worked as you've seen the press release with novo Nordisk, we worked on automating much of their background for their chromatography fleet. Um and finally we've also worked with several smaller biotechs in looking at sort of in stan shih ation, they say well we've just started we don't have an L. N. We don't have a limbs were about to buy these 50 instruments. Um what can you do with us and we'll actually help them to scope what their initial data storage and harmonization strategy should even be. Um so so we're really man, we're at everywhere from the enterprise where its fleets of thousands of instruments and we're really giving data to a large amount of scientists worldwide, all the way down to the small biotech with 50 people who were helping add value there. >>So big range there in terms of the data conversation, I'm curious has have you seen it change in the last year plus with respect to elevating to the C suite level or the board saying we've got to be able to figure this out because as we saw, you know, the race for the Covid 19 vaccine for example. Time to value and and to discovery is so critical. Is that C suite or board involved in having conversations with you guys? >>It's funny because they are but they are a little later. Um we tend to be a scientist and user driven um solution. So at the beginning we get a power user, an engineer or a R and D I. T. Person in who really has a problem to solve. And as they are going through and developing with us, eventually they're going to need either approval for the time, the resources or the budget and then they'll go up to their VP or their CIA or someone else at the executive level and say, let's start having more of this conversation. Um, as a tandem effort, we are starting to become involved in some thought leadership exercises with some larger firms. And we are looking at the strategic aspect through conferences, through white papers etcetera to speak more directly to that C suite and to say, hey, you know, we could fit your industry for dato motif. And then one other thing you said, time to value. So I'll say that the Tetro science executive team actually looks at that as a tract metric. So we're actually looking at driving that down every single week. >>That's outstanding. That's a hard one to measure, especially in a market that is so dynamic. But that time to value for your customers is critical. Again, covid sort of surfaced a number of things and some silver linings. But that being able to get hands on the day to make sure that you can actually pull insights from it accelerate facilitate drug discovery. That time to value there is absolutely critical. >>Yeah. I'll say if you look at the companies that really, you know, went first and foremost, let's look at Moderna right? Not our customer by the way, but we'll look at Madonna quickly as an example as an example are um, everything they do is automated, right? Everything they do is cloud first. Everything they do is global collaboration networks, you know, with harmonized data etcetera. That is the model we believe Everyone's going to go to in the next 3-5 years. If you look at the fact that Madonna went from sequence to initial vaccine in what, 50, 60 days, that kind of delivery is what the market will become accustomed to. And so we're going to see many more farmers and biotechs move to that cloud first. Distributed model. All data has to go in somewhere centrally. Everyone has to be able to benefit from it. And we are happy to help them get >>Well that's that, you know, setting setting a new record for pace is key there, but it's also one of those silver linings that has come out of this to show that not only was that critical to do, but it can be done. We have the technology, we have the brain power to be able to put those all user would harmonize those together to drive this. So give me a last question. Give me an insight into some of the things that are ahead for Tetra science the rest of this year. >>Oh gosh, so many things. One of the nice parts about having funding in the bank and having a dedicated team is the ability to do more. So first of course our our enterprise pharma and BioPharma clients, there are plenty more use cases, workflows, instruments. We've just about scratch the surface but we're going to keep growing and growing our our integrations and connectors. First of all right we want to be like a netflix for connectors. You know we just want you to come and say look do they have the connector? No well don't worry. They're going to have it in a month or two. Um so that we can be basically the almost the swiss army knife for every single connector you can imagine. Then we're going to be developing a lot more data apps so things that you can use to derive value from your data out. And then again, we're going to be looking at helping to educate everybody. So how is cloud useful? Why go to the system with harmonization? How does this influence your compliance? How can you do bi directional communication? There's lots of ways you can use. Once you have harmonized centralized data, you can do things with it to influence your order and drive times down again from days and weeks, two minutes and seconds. So let's get there. And I think we're going to try doing that over the next year. >>That's awesome. Never a dull moment. And I, you should partner with your marketing folks because we talked about, you talked about data plumbing the secret sauce and becoming the netflix of connectors. These are three gems that you dropped on this this morning mike. This has been awesome. Thank you for sharing with us what teacher science is doing, how you're really helping to fast track a lot of the incredibly important research that we're all really um dependent on and helping to heal the world through data. It's been a pleasure talking with you. >>Haley says I'm a real quickly. It's a team effort. The entire Tetro science team deserves credit for this. I'm just lucky enough to be able to speak to you. So thank you very much for the opportunity. >>And she about cheers to the whole touch of science team. Keep up the great work guys. Uh for mike Roselli, I'm lisa martin. You're watching this cube conversation. >>Mhm.

>>mhm >>Yes, >>everyone welcome back to the cubes coverage of Red Hat summit 2021. I'm john for your host of the cube, we've got a great segment here on how Red Hat is working with telcos and the disruption in the telco cloud. We've got a great guest cube alumni Darrell Jordan smith, senior vice president of industries and global accounts at Red Hat, uh Darryl, great to see you. Thanks for coming back on the cube. >>It's great to be here and I'm really excited about having the opportunity to talk to you >>today. Yeah, we're not in person in real life is coming back soon, although I hear mobile world congress might be in person this year looking like it's good a lot of people gonna be virtual activating. I know a lot to talk about this is probably one of the most important topics in the industry because when you talk about telco industry, you're really talking about um the edge, talking about five G talking about industrial benefits for business because it's not just Edge for connectivity access. We're talking about internet of things from self driving cars to business benefits. It's not just consumer, it's really bringing that together, you guys are really leading with the cloud native platform from rail, open shift men and services. Everything about the cloud native underpinnings you guys have been successful as a company but now in your area, telco is being disrupted. Absolutely. Give us your take on this is super exciting. >>Well, it's actually one of the most exciting times I've been in the industry for 30 years are probably aging myself now. But in the telecommunications industry, this, for me is the most exciting. It's where technology is actually going to visibly change the way that everyone interacts with the network and with the applications that are being developed out there on our platform and as you mentioned IOT and a number of the other ai and Ml innovations that are occurring in the market place. We're going to see a new wave of applications and innovation. >>What's the key delivery workloads you're seeing with Five G environment? Um, obviously it's not just, you know, five G in the sense of thinking about mobile phones or mobile computers as they are now. Um, it's not just that consumer, hey, surf the web and check your email and get an app and download and communicate. It's bigger than that. Now, can you tell us Where you see the workloads coming in on the 5G environment? >>You hit the nail on the head, The the the, the killer application isn't the user or the consumer and the way that we traditionally have known it, because you might be able to download a video in that take 20 seconds less, but you're not going to pay an awful lot more money for that. The real opportunity around five years, the industrial applications, things that I connected car, automotive, driving, um factory floor automation, how you actually interface digitally with your bank, how we're doing all sorts of things more intelligently at the edge of the network using artificial intelligence and machine learning. So all of those things are going to deliver a new experience for everyone that interacts with the network and the telcos are at the heart of it. >>You know, I want to get into the real kind of underpinnings of what's going on with the innovations happening. You just kind of laid out kind of the implications of the use cases and the target application workloads. But there's kind of two big things going on with the edge in five G one is under the hood, networking, you know, what's going on with the moving the packets around the workload, throughput, bandwidth etcetera, and all that goes on under the hood. And then there's the domain expertise in the data where AI and machine learning have to kind of weaving. So let's take the first part first. Um open shift is out there. Red hat's got a lot of products, but you have to nail the networking requirements and cloud Native with container ization because at large scales, not just packaged, it's all kinds of things going on security, managing a compute at the edge. There's a lot of things under the hood, if you will from a networking perspective, could you share what red hats doing in that area? >>So when we last spoke with the cube, we talked a lot about GMOs and actually people living Darryl, >>can I Cause you really quickly? I'm really sorry. Keep your answer in mind. We're gonna >>go right from that question. >>We're just kidding. Um, are you, is anything that you're >>using or touching running into the desk? We're just getting >>a little bit of shakiness on your camera >>and I don't want to. >>So anyway, >>that is my, my elbows. No worries. So no >>worries. Okay, so take your answer. I'll give you like a little >>321 from behind the scenes >>and and we'll go right as if >>john just ask >>the questions, we're gonna stay running. >>So I think, uh, >>can you ask the question just to get out of my mind? Perfect. Well let's, let's do >>from that. So we'll stay on your shot. So you'll hear john, but it'll be as if >>he just asked the question. So jOHn >>team up. Here we go. I'm just gonna just jimmy and just keep my other question on the okay, here we go. So Darryl, open shift is optimized for networking requirements for cloud native. It's complex into the hood. What is red hat doing under the hood to help in the edge in large complex networks for large scale. >>Yeah. So, so that's a very good question in that we've been building on our experience with open stack and the last time I was on the cube, I talked about, you know, people virtualizing network applications and network services. We're taking a lot of that knowledge that we've learned from open stack and we're bringing that into the container based world. So we're looking at how we accelerate packets. We're looking at how we build cloud native applications on bare metal in order to drive that level of performance. We're looking at actually how we do the certification around these applications and services because they may be sitting in different app lets across the cloud, but in some instances running on multiple clouds at the same time. So we're building on our experience from open stack, we're bringing all of that into open shipping, container based environment with all of the tallinn necessary to make that effective. >>It's interesting with all the automation going on. Certainly with the edge developing nicely the way you're describing it, certainly disrupting the Telco cloud, you have an operator mindset of cloud Native operator thinking, kind of, it's distributed computing, we know that, but it's hybrid. So it's essentially cloud operations. So there's an operator mindset here that's just different. Could you just share quickly before we move on to the next segment? What's different about this operating model for the, these new kinds of operators? As you guys been saying, the C I O is the new cloud operator, That's the skill set they have to be thinking and certainly to anyone else provisioning and managing infrastructure has to think like an operator, what's your >>view? They certainly do need anything like an operator. They need to look at how they automate a lot of these functions because they're actually deployed in many different places will at the same time they have to live independently of each other. That's what cloud native actually really is. So the whole, the whole notion of five nines and vertically orientated stacks of five nines availability that's kind of going out the window. We're looking at application availability across a hybrid cloud environment and making sure the application can live and sustain itself. So operators as part of open shift is one element of that operations in terms of management and orchestration and all the tooling that we actually also providers red hat but also in conjunction with a big partner ecosystem, such as companies like net cracker, for example, or IBM as another example or Erickson bringing their automation tool sets and their orchestration tool sets of that whole equation to address exactly that problem >>you bring up the ecosystem. And this is really an interesting point. I want to just hit on that real quick because reminds me of the days when we had this massive innovation wave in the nineties during that era. The client server movement really was about multi vendor, right. And that you're starting to see that now and where this ties into here I think is when we get your reaction to this is that, you know, moving to the cloud was all about 2 2015. Move to the cloud moved to the cloud cloud native. Now it's all about not only being agile and better performance, but you're gonna have smaller footprints with more security requires more enterprise requirements. This is now it's more complicated. So you have to kind of make the complications go away and now you have more people in the ecosystem filling in these white spaces. So you have to be performance and purpose built if you will. I hate to use that word, but or or at least performing an agile, smaller footprint grade security enabling other people to participate. That's a requirement. Can you share your reaction to that? >>Well, that's the core of what we do. A red hat. I mean we take open source community software into a hardened distribution fit for the telecommunications marketplace. So we're very adapt to working with communities and third parties. That ecosystem is really important to us. We're investing hundreds of engineers, literally hundreds of engineers working with our ecosystem partners to make sure that their applications services certified, running on our platform, but but also importantly is certified to be running in conjunction with other cloud native applications that sit over the same cloud. So that that is not trivial to achieve in any stretch of the imagination. And a lot of 80 technology skills come to bear. And as you mentioned earlier, a lot of networking skills, things that we've learned and we've built with a lot of these traditional vendors, we bring that to the marketplace. >>You know, I've been saying on the cube, I think five years ago I started talking about this, it was kind of a loose formulation, I want to get your reaction because you brought up ecosystem, you know, saying, you know, you're gonna see the big clouds develop out. The amazon Microsoft came in after and now google and others and I said there's gonna be a huge wave of of what I call secondary clouds and you see companies like snowflake building on on top of amazon and so you start to see the power law of new cloud service providers emerging that can either sit and work with across multiple clouds. Either one cloud or others that's now multi cloud and hybrid. But this rise of the new more C. S. P. S, more cloud service providers, this is a huge part of your area right now because some call that telco telco cloud edge hits that. What is red hat doing in this cloud service provider market specifically? How do you help them if I'm a cloud service provider, what do I get in working with Red Hat? How do I be successful because it's very easy to be a cloud service provider now more than ever. What do I do? How do you help? How do you help me? >>Well, we we we offer a platform called open shift which is a containerized based platform, but it's not just a container. It involves huge amounts of tooling associated with operating it, developing and around it. So the concept that we have is that you can bring those applications, developed them once on 11 single platform and run it on premise. You can run it natively as a service in Microsoft environment. You can actually run it natively as a service in amazon's environment. You can running natively on IBM's Environment. You can build an application once and run it in all of them depending on what you want to achieve, who actually provide you the best, owning the best terms and conditions the best, the best tooling in terms of other services such as Ai associated with that. So it's all about developing it once, certifying it once but deploying it in many, many different locations, leveraging the largest possible developing ecosystem to drive innovation through applications on that common platform. >>So assumption there is that's going to drive down costs. Can you why that benefits the economics are there? We talk about the economics. >>Yeah. So it does drive down costs a massive important aspect but more importantly it drives up agility. So time to market advantages actually attainable for you so many of the tell coast but they deploy a network service traditionally would take them literally maybe a year to roll it all out. They have to do it in days, they have to do updates in real time in data operations in literally minutes. So we were building the fabric necessary in order to enable those applications and services to occur. And as you move into the edge of the network and you look at things like private five G networks, service providers or telcos in this instance will be able to deliver services all the way out to the edge into that private five G environment and operate that in conjunction with those enterprise clients. >>So open shit allows me if I get this right on the CSP to run, have a horizontally scalable organization. Okay. From a unification platform standpoint. Okay, well it's 5G and other functions, is that correct? That's correct. Ok. So you've got that now, now I want to come in and bring in the top of the stack or the other element. That's been a big conversation here at Redhead Summit and in the industry that is A I and the use of data. One of the things that's emerging is the ability to have both the horizontal scale as well as the special is um of the data and have that domain expertise. Uh you're in the industries for red hat. This is important because you're gonna have one industry is going to have different jargon, different language, different data, different KPI S. So you've got to have that domain expertise to enable the ability to write the apps and also enable a I can, you know how that works and what were you doing there? >>So we're developing open shift and a number of other of our technologies to be fit for the edge of the network where a lot of these Ai applications will reside because you want them closer to the client or the the application itself where it needs to reside. We're creating that edge fabric, if you like. The next generation of hybrid cloud is really going to be, in my view at the edge we're enabling a lot of the service providers to go after that but we're also igniting by industry, You mentioned different industries. So if I look at, for example, manufacturing with mind sphere, we recently announced with Seaman's how they do at the edge of the network factory automation, collecting telemetry, doing real time data and analytics, looking at materials going through the factory floor in order to get a better quality results with lower, lower levels of imperfections as they run through that system and just one industry and they have their own private and favorite Ai platforms and data sets. They want to work with with their own data. Scientists who understand that that that ecosystem inherently you can move that to health care and you can imagine how you actually interface with your health care professionals here in north America, but also around the world, How those applications and services and what the Ai needs to do in terms of understanding x rays and looking at common errors associated with different x rays to. A practitioner can make a more specific diagnosis faster saving money and potentially lives as well. So different different vertical markets in this space have different AI and Ml requirements and needs different data science is different data models. And what we're seeing is an ecosystem of companies that are starting up there in that space that we have, what service part of IBM. But you have processed the labs of H T H 20 and a number of other very, very important AI based companies in that ecosystem. >>Yeah. And you get the horizontal scalability of the control plane and in the platform if you will, that gives you cross organizational leverage uh and enable that than vertical expertise. >>Exactly. And you want to build an Ai application that might run on a factory floor for for certain reasons to its location and what they're actually physically building. You might want to run their on premise, you might actually want to put it into IBM cloud or in Zur or into AWS, You develop, it wants to open shift, you can deploy it in all of those as a service sitting natively in those environments. >>Darrell, great chat. I got a lot going on telco cloud, There's a lot of cloud, native disruption going on. It's a challenge and an opportunity and some people have to be on the right side of history on this one if they're going to get it right. Well, no, and the scoreboard will be very clear because this is a shift, it's a shift. So again, you hit all the key points that I wanted to get out. But I want to ask you to more areas that are hot here at red hat summit 21 as well again and as well in the industry and get your reaction and thoughts on uh, and they are def sec ops and automation. Okay. Two areas. Everyone's talking about DEV ops which we know is infrastructure as code programming ability under the hood. Modern application development. All good. Yeah, the second their security to have sex shops. That's critical automation is continuing to be the benefits of cloud native. So Deb see cops and automation. What you're taking has that impact the telco world in your world. >>You can't you can't operate a network without having security in place. You're talking about very sensitive data. You're talking about applications that could be real time chris pickling mrs actually even life saving or life threatening if you don't get them right. So the acquisition that red hat recently made around stack rocks, really helps us make that next level of transition into that space. And we're looking about how we go about securing containers in a cloud native environment. As you can imagine, there will be many, many thousands tens of thousands of containers running if one is actually misbehaving for what one of a better term that creates a security risk in a security loophole. Were assuring that up that's important for the deployment, open shift in the Tokyo domain and other domains in terms of automation. If you can't do it at scale and if you look at five G and you look at the radios at the edge of the network and how you're gonna provision of those services. You're talking about hundreds of thousands of nodes, hundreds of thousands. You have to automate a lot of those processes, otherwise you can't scale to meet the opportunity, you can't physically deploy, >>you know, Darryl, this is a great conversation, you know, as a student of history and um development and I always kind of joke about that and you you've been around the industry for a long time. Telcos have been balancing this um evolution of digital business for many, many decades. Um and now with Cloud Native, it's finally a time where you're starting to see that it's just the same game now, new infrastructure, you know, video, voice, text data all now happening all transformed and going digital all the way, all aspects of it in your opinion. How should telcos be thinking about as they put their plans in place for next generation because you know, the world is now cloud Native. There's a huge surface here of opportunities, different ecosystem relationships, the power dynamics are shifting. It's it's really a time where there will be winners and there will be losers. What's your, what's your view on on how the telco industry needs to clarify and how they be positioned for success. >>So, so one of the things I truly believe very deeply that the telcos need to create a platform, horizontal platform that attracts developer and ecosystems to their platform because innovation is gonna sit elsewhere, then there might be a killer application that one telco might create. But in reality most of those innovations that most of those disruptors are going to occur from outside of that telco company. So you want to create an environment where you're easy to engage and you've got maximum sets of tools and versatility and agility in order to attract that innovation. If you attract the innovation, you're going to ignite the business opportunity that 5G and 60 and beyond is going to actually provide you or enable your business to drive. And you've really got to unlock that innovation and you can only unlock in our view, red hat innovation. If you're open, you follow open standards, you're using open systems and open source is a method or a tool that you guys, if you're a telco, I would ask you guys need to leverage and harness >>and there's a lot, there's a lot of upside there if you get that right, there's plenty of upside, a lot of leverage, a lot of assets to advantage the whole offline online. Coming back together, we are living in a hybrid world, certainly with the pandemic, we've seen what that means. It's put a spotlight on critical infrastructure and the critical shifts. If you had to kind of get pinned down Darryl, how would you describe that learnings from the pandemic as folks start to come out of the pandemic? There's a light at the end of the tunnel as we come out of this pandemic, companies want a growth strategy, wanna be positioned for success what you're learning coming out of the pandemic. >>So from my perspective, which really kind of 11 respect was was very admirable. But another respect is actually deeply uh a lot of gratitude is the fact that the telecommunications companies because of their carrier, great capabilities and their operational prowess were able to keep their networks up and running and they had to move significant capacity from major cities to rural areas because everyone was working from home and in many different countries around the world, they did that extremely and with extremely well. Um and their networks held up I don't know and maybe someone will correct me and email me but I don't know one telco had a huge network outage through this pandemic and that kept us connected. It kept us working. And it also what I also learned is that in certain countries, particularly at a time where they have a very large prepaid market, they were worried that the prepaid market in the pandemic would go down because they felt that people would have enough money to spend and therefore they wouldn't top up their phones as much. The opposite effect occurred. They saw prepaid grow and that really taught me that that connectivity is critical in times of stress that we're also everyone's going through. So I think there are some key learnings that >>yeah, I think you're right on the money there. It's like they pulled the curtain back of all the fun and said necessity is the mother of invention and when you look at what happened and what had to happen to survive in the pandemic and be functional. Your, you nailed it, the network stability, the resilience, but also the new capabilities that were needed had to be delivered in an agile way. And I think, you know, it's pretty much the forcing function for all the projects that are on the table to know which ones to double down on. So I think you pretty much nailed it. Darrell Jordan smith, senior vice president of industries and global accounts for red hat kibble, unnatural. Thanks for that insight. Thanks for sharing great conversation around telcos and telco clouds and all the edge opportunities. Thanks for coming on. >>Thank you john >>Okay. It's the cubes coverage of Red Hat summit 21. I'm John for your host. Thanks for watching. Mhm mhm

>>C G technology is focused on data where we have long believed that data is in our DNA. We help maximize humanity's potential by delivering world class, precision engineered data solutions developed through sustainable and profitable partnerships. Included in our offerings are hard disk drives. As I'm sure many of you know, ah, hard drive consists of a slider also known as a drive head or transducer attached to a head gimbal assembly. I had stack assembly made up of multiple head gimbal assemblies and a drive enclosure with one or more platters, or just that the head stacked assembles into. And while the concept hasn't changed, hard drive technology has progressed well beyond the initial five megabytes, 500 quarter inch drives that Seagate first produced. And, I think 1983. We have just announced in 18 terabytes 3.5 inch drive with nine flatters on a single head stack assembly with dual head stack assemblies this calendar year, the complexity of these drives further than need to incorporate Edge analytics at operation sites, so G Edward stemming established the concept of continual improvement and everything that we do, especially in product development and operations and at the end of World War Two, he embarked on a mission with support from the US government to help Japan recover from its four time losses. He established the concept of continual improvement and statistical process control to the leaders of prominent organizations within Japan. And because of this, he was honored by the Japanese emperor with the second order of the sacred treasure for his teachings, the only non Japanese to receive this honor in hundreds of years. Japan's quality control is now world famous, as many of you may know, and based on my own experience and product development, it is clear that they made a major impact on Japan's recovery after the war at Sea Gate. The work that we've been doing and adopting new technologies has been our mantra at continual improvement. As part of this effort, we embarked on the adoption of new technologies in our global operations, which includes establishing machine learning and artificial intelligence at the edge and in doing so, continue to adopt our technical capabilities within data science and data engineering. >>So I'm a principal engineer and member of the Operations and Technology Advanced Analytics Group. We are a service organization for those organizations who need to make sense of the data that they have and in doing so, perhaps introduce a different way to create an analyzed new data. Making sense of the data that organizations have is a key aspect of the work that data scientist and engineers do. So I'm a project manager for an initiative adopting artificial intelligence methodologies for C Gate manufacturing, which is the reason why I'm talking to you today. I thought I'd start by first talking about what we do at Sea Gate and follow that with a brief on artificial intelligence and its role in manufacturing. And I'd like them to discuss how AI and machine Learning is being used at Sea Gate in developing Edge analytics, where Dr Enterprise and Cooper Netease automates deployment, scaling and management of container raised applications. So finally, I like to discuss where we are headed with this initiative and where Mirant is has a major role in case some of you are not conversant in machine learning, artificial intelligence and difference outside some definitions. To cite one source, machine learning is the scientific study of algorithms and statistical bottles without computer systems use to effectively perform a specific task without using explicit instructions, relying on patterns and inference Instead, thus, being seen as a subset of narrow artificial intelligence were analytics and decision making take place. The intent of machine learning is to use basic algorithms to perform different functions, such as classify images to type classified emails into spam and not spam, and predict weather. The idea and this is where the concept of narrow artificial intelligence comes in, is to make decisions of a preset type basically let a machine learn from itself. These types of machine learning includes supervised learning, unsupervised learning and reinforcement learning and in supervised learning. The system learns from previous examples that are provided, such as images of dogs that are labeled by type in unsupervised learning. The algorithms are left to themselves to find answers. For example, a Siris of images of dogs can be used to group them into categories by association that's color, length of coat, length of snout and so on. So in the last slide, I mentioned narrow a I a few times, and to explain it is common to describe in terms of two categories general and narrow or weak. So Many of us were first exposed to General Ai in popular science fiction movies like 2000 and One, A Space Odyssey and Terminator General Ai is a I that can successfully perform any intellectual task that a human can. And if you ask you Lawn Musk or Stephen Hawking, this is how they view the future with General Ai. If we're not careful on how it is implemented, so most of us hope that is more like this is friendly and helpful. Um, like Wally. The reality is that machines today are not only capable of weak or narrow, a I AI that is focused on a narrow, specific task like understanding, speech or finding objects and images. Alexa and Google Home are becoming very popular, and they can be found in many homes. Their narrow task is to recognize human speech and answer limited questions or perform simple tasks like raising the temperature in your home or ordering a pizza as long as you have already defined the order. Narrow. AI is also very useful for recognizing objects in images and even counting people as they go in and out of stores. As you can see in this example, so artificial intelligence supplies, machine learning analytics inference and other techniques which can be used to solve actual problems. The two examples here particle detection, an image anomaly detection have the potential to adopt edge analytics during the manufacturing process. Ah, common problem in clean rooms is spikes in particle count from particle detectors. With this application, we can provide context to particle events by monitoring the area around the machine and detecting when foreign objects like gloves enter areas where they should not. Image Anomaly detection historically has been accomplished at sea gate by operators in clean rooms, viewing each image one at a time for anomalies, creating models of various anomalies through machine learning. Methodologies can be used to run comparative analyses in a production environment where outliers can be detected through influence in an automated real Time analytics scenario. So anomaly detection is also frequently used in machine learning to find patterns or unusual events in our data. How do you know what you don't know? It's really what you ask, and the first step in anomaly detection is to use an algorithm to find patterns or relationships in your data. In this case, we're looking at hundreds of variables and finding relationships between them. We can then look at a subset of variables and determine how they are behaving in relation to each other. We use this baseline to define normal behavior and generate a model of it. In this case, we're building a model with three variables. We can then run this model against new data. Observations that do not fit in the model are defined as anomalies, and anomalies can be good or bad. It takes a subject matter expert to determine how to classify the anomalies on classify classification could be scrapped or okay to use. For example, the subject matter expert is assisting the machine to learn the rules. We then update the model with the classifications anomalies and start running again, and we can see that there are few that generate these models. Now. Secret factories generate hundreds of thousands of images every day. Many of these require human toe, look at them and make a decision. This is dull and steak prone work that is ideal for artificial intelligence. The initiative that I am project managing is intended to offer a solution that matches the continual increased complexity of the products we manufacture and that minimizes the need for manual inspection. The Edge Rx Smart manufacturing reference architecture er, is the initiative both how meat and I are working on and sorry to say that Hamid isn't here today. But as I said, you may have guessed. Our goal is to introduce early defect detection in every stage of our manufacturing process through a machine learning and real time analytics through inference. And in doing so, we will improve overall product quality, enjoy higher yields with lesser defects and produce higher Ma Jin's. Because this was entirely new. We established partnerships with H B within video and with Docker and Amaranthus two years ago to develop the capability that we now have as we deploy edge Rx to our operation sites in four continents from a hardware. Since H P. E. And in video has been an able partner in helping us develop an architecture that we have standardized on and on the software stack side doctor has been instrumental in helping us manage a very complex project with a steep learning curve for all concerned. To further clarify efforts to enable more a i N M l in factories. Theobald active was to determine an economical edge Compute that would access the latest AI NML technology using a standardized platform across all factories. This objective included providing an upgrade path that scales while minimizing disruption to existing factory systems and burden on factory information systems. Resource is the two parts to the compute solution are shown in the diagram, and the gateway device connects to see gates, existing factory information systems, architecture ER and does inference calculations. The second part is a training device for creating and updating models. All factories will need the Gateway device and the Compute Cluster on site, and to this day it remains to be seen if the training devices needed in other locations. But we do know that one devices capable of supporting multiple factories simultaneously there are also options for training on cloud based Resource is the stream storing appliance consists of a kubernetes cluster with GPU and CPU worker notes, as well as master notes and docker trusted registries. The GPU nodes are hardware based using H B E l 4000 edge lines, the balance our virtual machines and for machine learning. We've standardized on both the H B E. Apollo 6500 and the NVIDIA G X one, each with eight in video V 100 GP use. And, incidentally, the same technology enables augmented and virtual reality. Hardware is only one part of the equation. Our software stack consists of Docker Enterprise and Cooper Netease. As I mentioned previously, we've deployed these clusters at all of our operations sites with specific use. Case is planned for each site. Moran Tous has had a major impact on our ability to develop this capability by offering a stable platform in universal control plane that provides us, with the necessary metrics to determine the health of the Kubernetes cluster and the use of Dr Trusted Registry to maintain a secure repository for containers. And they have been an exceptional partner in our efforts to deploy clusters at multiple sites. At this point in our deployment efforts, we are on prem, but we are exploring cloud service options that include Miranda's next generation Docker enterprise offering that includes stack light in conjunction with multi cluster management. And to me, the concept of federation of multi cluster management is a requirement in our case because of the global nature of our business where our operation sites are on four continents. So Stack Light provides the hook of each cluster that banks multi cluster management and effective solution. Open source has been a major part of Project Athena, and there has been a debate about using Dr CE versus Dr Enterprise. And that decision was actually easy, given the advantages that Dr Enterprise would offer, especially during a nearly phase of development. Cooper Netease was a natural addition to the software stack and has been widely accepted. But we have also been a work to adopt such open source as rabbit and to messaging tensorflow and tensor rt, to name three good lab for developments and a number of others. As you see here, is well, and most of our programming programming has been in python. The results of our efforts so far have been excellent. We are seeing a six month return on investment from just one of seven clusters where the hardware and software cost approached close to $1 million. The performance on this cluster is now over three million images processed per day for their adoption has been growing, but the biggest challenge we've seen has been handling a steep learning curve. Installing and maintaining complex Cooper needs clusters in data centers that are not used to managing the unique aspect of clusters like this. And because of this, we have been considering adopting a control plane in the cloud with Kubernetes as the service supported by Miranda's. Even without considering, Kubernetes is a service. The concept of federation or multi cluster management has to be on her road map, especially considering the global nature of our company. Thank you.

>>lie from Copenhagen, Denmark. >>It's the >>Q covering Nutanix dot Next 2019. Brought to you by >>Nutanix. Welcome back, everyone to the cubes. Live coverage of Nutanix. Stop! Next here in Copenhagen, Denmark. I'm your host, Rebecca Knight, coasting along side of stew minimum. Of course. We're joined by Regime Mirani. He is the CTO clad platforms at Nutanix. Thank you so much for coming on the Cubans. You need >>to be here as usual. >>So you were up on the main stage talking about your guiding force. Your mission to make enterprise computing so reliable, so ubiquitous that it's invisible. >>You don't think about >>it. You don't even get a little No, I mean, look, >>if you look at any successful technology, consumer technology doesn't need to be aware of the details around it, right? I mean, take cars, even because the first introduced you probably had to understand Rick operate. There was how it all works. Remember for water in the radiator. But most people don't know how to do that today. I wouldn't know how to do that today, even though my Utah actually had to do some of those things. Um, that isn't the point. of the cars or self driving. Now the same thing should happen to computing. And we spend way too much time today just doing things that keep the light. Don't nights on. Just imagine infrastructure patching things up, grading them. I really should be something that not what idea is doing i d should be focusing on the business, delivering applications that their customers need and not so much on managing infrastructure. >>Rajiv, that one click Simplicity is so important, yet we know things are becoming even more complicated. Bring us inside a little bit that you know, you've got 14,000 customers. Guess and there's been a major, basically rewrite of a less to be able to be ready for all of the new ash cloud Native envy me obtained, you know, you name it all of these things. How do you balance getting all of this new stuff up with making sure that you keep that simplicity and don't make things for all of your customers while all the jet engines, uh, you know, >>it takes constant effort. It takes a conscious effort to make sure that things are in drifting away from our goal of being simple and to be frank. At times it has and you know, we periodically to audits off all our work floors. Make sure that as simple as you think they are and haven't drifted over time. And occasionally we do find some rail clunkers and have to go back and fix those things. What >>makes it >>different is that we start with a fairly opinionated view on how things should be done. The idea is to make it simple for 99% of the people, while still offering the all that washed options of one person power users would need them and making sure that we understand what 90% 99% of people need. And focusing on that is very important to a lot of customer focus study sort of design reviews, but also this constant going back and you're taking work feel like we m creation like provisioning of'em. When he started, it was pretty simple right then, as we started adding more and more options eyes, this thing going to use a PC I passed through isn't going to use this option. That option suddenly realized that now they're 30 things that people are feeling into provisional we have, most of which nobody cares I care about. So you go back, read I tte keep doing that again and again and again. >>So rich Eve It's one thing when you talk about living on different servers, whether it be super micro underneath or Delhi Emcee Lenovo H p e. It's >>gonna be a >>little bit different if you're talking about where you're going with H p E Green Lake with, you know, the X in AWS that you talk about when I talk to people, you know, it's like, Oh, I'm trying to use terror form and you know, But I have to write it. One way to work with Amazon. I have to write it another way. If it's, you know, azure G C P S o. You know, will Nutanix be able to keep that simplicity and bring, you know, homogeneity to thes dispersed invite? >>Absolutely. So the point is, watch a layer of abstraction right the way we are going to public cloud away we go every server winter out the way of doing things and sigh all if it starts with the hyper wiser and the story of stock and networking with three layers of abstraction. And if you have the same three components everywhere, everything we built on top of that remains exactly the same. Prison was the same on a P S. On the same. Everything looks the same. So higher level constructs like calm and so on don't have to be aware of what the actual substrate is creating a calm blueprint, whether it works on ZAY on AWS or whether Trump's on SX or whether runs on Nutanix H way. The blue blueprint remains exactly the same. Now, if you want to consume more, service is if you want to consume. So this is an Amazon, which are not available on premises. You want to use things like auto scaling groups in Ec2. Sure, you could then create blueprints that our customers we're putting in the substrate. >>So, in terms of this, you said, you start with a very opinionated place of where the customer is well, First of all, it's based on customer feedback and customer surveys. And so where were are you right now in terms of where the customer is? Are you meeting the customer now, or is the customer ahead or what? Where would you describe that? I think it >>depends on what you're looking at. If you're looking at the core products, absolutely, the customers are with us. They were ready to consume. They actually drive a lot of the innovation that we're doing. We're feeding, feeding back changes that we could be doing to make things even simpler on the private cloud side that's getting there. I think we get a lot off feedback on files on on present pro on com on on Flow because those have started getting a lot of adoption in the market, and we do get a lot of feedback on them on. So our newer products that you started a war being more recently, it's a more collaborative process. There were actually working with customers directly understanding their problems on dhe, moving a roadmap forward based on that. So while it's early in terms off adoption in production, the whole process is very collaborative in those situations. So we really are very close to the customers there. >>What are some of the biggest customer problems right now that they're facing what's what's keeping them up at night and therefore keeping you up at night? >>Security is always a big one. Complexity, people skills. All those things are big problems. In fact, one of the biggest things like that was just training enough people to handle all the complexity in a data set. Is the Morrigan removed from that? The more they don't have to focus on that, the easier you make their lives. The other thing is just a lot of time to spend on routine activities which, which acquired disruption to service is right. This is something we've talked about before. Why does it Why does it require a legacy three tier system to have maintenance windows and downtime to do an upgrade? Google our has downtime. Google is never down for maintenance. Doesn't mean they're not already there waiting all the time. So how do we bring that same kind of capabilities on premises that's gonna focus our long power? >>So, Rajiv, when I'm talking to users out there, when they talk about all of the items that are out there that they need to deal with and the routine task automation is something keeps, you know, coming up. So tell us where automation fits into some of the new things that you were talking about today in this week with your customer? >>Yeah, automation >>for us. Waking automation in three steps anything that's automatic better be safe. First of all, safety is paramount. Started security. It has to be simple, and we talked about how calm provides for that. And then you can start adding in this new wave off technologies around artificial intelligence and machine learning. And it's not so much about automation right now. It's all gone to me. It's it's autonomous operations, not just scripts. That due to a task on dhe, that's >>an area >>we invested in very heavily early on with our prison pro product way, build our own patented or thumbs for machine learning applied them to operational metrics like capacity planning. And what if modeling and dynamic alerts and what we've been doing with that is extending that more into the application layer so that not only can you apply these algorithms to CP when memory, we can actually get insights into Hey, the Leighton see on this particular application looks somewhat unusual, or the amount of cash available on a sequel server is unusually low and act on those, and the other part is acting on on alert. Something happens. There's a human being need to get in wall to solve for that. And if it does, then well, it's not really automatic. Right? So that's the other part that we introduce, which is a cross for a product which lets you define these action chains that automatically, uh, what about to be triggered when Annie went on alert takes place, they can go ahead and fix the problem. But also, you know, simple things like send your slack notification or an email locked. They went, maybe create a snapshot of your wee am so that you could go back and be back problems later. All that sort of thing made really, really simple. >>Yes, it goes back to the simplicity and the invisibility to this. >>Yes, yes. Uh, autonomous data centers, by definition, have to be invisible, right? If if if If you're to get involved in marriage and autonomous Data center, then what's the plane? It's a point. Exactly. So the whole idea is that, uh, human involvement in day to day operations against solo that everybody's focused on applications on line of business use cases. >>Rajiv, when it when it comes to those applications. You know, you talked about some of the new enhancements like envy me on and obtain, You know, Where are your customers today? You know, Are there any interesting applications that you're seeing them deploying today? Ah, Pattern. I've talked about the last couple of years of the Nutanix show, is modernized the platform and then modernized the absolute top of it. Things like container ization. I'm sure to bell curve in a journey where all the customers But you know, what are some of the patterns that air starting emergen where they finding success? >>Yeah, This >>whole wave off new applications around data pipelines with Kafka spark things like that Apache stack effectively which are putting more more off load on storage in particular. So that's that's one area. We see customers looking for more performance. But >>even, >>you know, some of the traditional ah traditional uh, applications like ASAP Hana and epic and meditate expanse. They also have patterns which can benefit greatly with some of that wants wants that we have been making and gets a technical issue. No, The size of the working said with it all fits and car and on sst was spitting on magnetic drives. But something like we've been doing is moving the overheads. If you do have a miss and you go to slow a media, you still get good performance. And that's really how we're getting good to the new. >>Well, yeah, maybe without getting, you know, we don't need to go drill down into the core of the intel chip everything. But you know, Nutanix doesn't just take off the shelf stuff and, you know, put a box together. It's software, and there's work that happens with your partners in the ecosystem. Give us a little flavor as toe. You know where you're making the investments and where some of those partnerships and integrations or a key? >>Yeah, So on the platform side, Ah, a lot of the investments happen in validation of the platforms, making sure that we're ahead of the curve in adopting technologies but also feeding back from our side things we would like to see in the platform. Right? So how do you adapt things like R d m A. To handle not just the traditional work with the happy converge workload? How do you essentially look for things in this new class? of memories that would benefit from data locality for us. So that's one class off partnership that we have the hardware vendors with GHB, with Intel, with the IBM, a whole bunch of people. But >>then >>we also have partnerships up the stock these days with companies like service. Now, with we for backup for for our mind product. I think you saw a little bit of that today. It's a whole bunch of things happening across all areas. >>One of the things that it really comes across at this conference is just how strong Nutanix culture is. The company culture, the humble, honest, hungry and another word that's creeping in now is resilient. I'm wondering if you could talk a little bit about your division of the company and describe how the company's resilience, the employees and the company itself has really displayed itself. >>So, you know, as it any company you know, Any time you go through the kind of growth we have, there's the forward momentum that everybody sees. They also a lot of setbacks that people don't really see, and they've been a whole bunch of us off these in our history. They've been areas where literally. The product has has a floor which is so fundamental we call it internally a near death experience. What's really great until again, from an engineering point of yours, how the teams come together at that point instead of these war rooms, even working weekends, Everybody's there. Everybody's on it and nobody talks about. Hey, look, where's my work? Life? Balance of things like that, especially when they're the customer in world. If there's if there's a problem that's causing customers outages, our engineers will give up everything. They'll give up everything and not just at work with their lives to make sure that gets fixed. And that has helped us get Basti setbacks get back in stride. Happens last Now. It used to happen a lot earlier, but spill this real culture resilience from the big *** in the early engineers. >>All right, Rajiv, what's exciting? You going forward? You know you don't have to touch on this one. But you know, when I saw at the end, the site clusters and hibernate feature was something that was like, Oh, yeah. I don't think I've seen that as to how I could make sure I save my data be ableto, you know, Shut things down. Maybe start there. But give us You know what a little bit. Look forward as to where the team's playing. >>Now, that's kind of, >>you know, thinking that detail thing that you have to do. What, you want to launch a new product, right? Okay, look, the whole point of doing doings, I clusters on Amazon. One of the biggest use cases. This cloud bursting cloud busting is not just about increasing your workload size, scaling it up at some point, you want to scale it down? How do you do that for state for work? Stateless. It's easy. All I'm registering Web servers over that sort of my way, they're gone. But our database that I scaled out over there well, that data can't go away. So we had to find ways to essentially solve for those from. So that's how the hibernate feature came around in general, The bigger question that you asked about, You know what I'm most excited about? I >>think this >>whole convergence of private and public cloud with same stack on both sides is a new new tank. It really hasn't existed before. Um, the father applications can now move back and forth seamlessly between public cloud and private cloud without rewriting without re factoring without a big lift and shift is very, very interesting. But by itself, it's not enough. Um, the flip that's missing is what about data movement? What about if you have your data and Amazon and I want to move it on premises? That there really are no good solutions of the Amazon doesn't give you a P eyes on dhe the tools to do that. So I think data movement's gonna be a big thing. And then Billy, a common service's tack on board because it's not just networking, storage in and compute anymore, right? If you're an Amazon, you're probably using all kinds off. Networking service is security groups. Ah, Route 53. How do you take those kind of service is and also make them available on premises. >>So, Rajiv, is there anything you've learned as a team when you look at AWS outposts or Oracle clouded customer, we've had a few years of talking about, but not a lot of deployments yet, so, you know, not saying you're late to the market, but you know what would have been able to sit back and learn from what has been done so far. >>So the >>reason we >>a little bit late to the market is that we think of solving a problem which the other windows are not, Which is kind of what I alluded to before that is that how do you support both the legacy applications on the cloud Net Cloud applications? How do you provide for migration both ways? Applications of a born in the cloud and now you want to move them on premises or applications of a born on premises and you want to move them to the Cloud Outpost is great. I think it's a good good product of technologies that AWS are thinks that hybrid is the right strategy, but it's also one problem. It's also the problem off cloud applications running on premises it does not solve for the problem of legacy applications running and cloud right, that is just a cz difficult as ever. That's that's not become any easier without force. Similarly, if you look at what we are very swing with AWS, it's also legacy applications going going to AWS. But in doing so, they don't have access to all the different networking services that AWS offers because you're not running and a sex, and you're kind of running a different networking start tonight. So with well, thought long and hard about this problem. And I said, Hey, look, we're not going to take the easy answer over here. You can take Take our stock, which is known to run both legacy and cloud native applications. If probe in that on Internet natively into Amazon so that you can use Amazon service is you can use our service is you can a legacy. Applications can run more than applications without giving up. Anything on that, I think is why signal this longer? But I think it's a more powerful solution for the long term. >>Thank you so much for coming on the Cube. It's always a pleasure having you on my back and see us again. Thanks. I'm Rebecca Knight for stew. Minutemen stay more of the cubes. Live coverage of dot Next Nutanix here in Copenhagen,

>> from our studios in the heart of Silicon Valley, Palo Alto, California It is >> a cute conversation. Hey, welcome back. Get ready. Geoffrey here with the Cube. We're gonna rip out the studios for acute conversation. It's the middle of the summer, the conference season to slow down a little bit. So we get a chance to do more cute conversation, which is always great. Excited of our next guest. He's Ridge, IP, Ops Statik. He's a VP and GM from key. Cite, Reject. Great to see you. >> Thank you for hosting us. >> Yeah. So we've had Marie on a couple of times. We had Bethany on a long time ago before the for the acquisition. But for people that aren't familiar with key site, give us kind of a quick overview. >> Sure, sure. So I'm within the excess solutions group Exhale really started was founded back in 97. It I peered around 2000 really started as a test and measurement company quickly after the I poet became the number one vendor in the space, quickly grew around 2012 and 2013 and acquired two companies Net optics and an ooey and net optics and I knew we were in the visibility or monitoring space selling taps, bypass witches and network packet brokers. So that formed the Visibility Group with a nice Xia. And then around 2017 key cite acquired Xia and we became I S G or extra Solutions group. Now, key site is also a very large test and measurement company. It is the actual original HB startup that started in Palo Alto many years ago. An HB, of course, grew, um it also started as a test and measurement company. Then later on it, it became a get a gun to printers and servers. HB spun off as agile in't, agile in't became the test and measurement. And then around 2014 I would say, or 15 agile in't spun off the test and measurement portion that became key site agile in't continued as a life and life sciences organization. And so key sites really got the name around 2014 after spinning off and they acquired Xia in 2017. So more joy of the business is testing measurement. But we do have that visibility and monitoring organization to >> Okay, so you do the test of measurement really on devices and kind of pre production and master these things up to speed. And then you're actually did in doing the monitoring in life production? Yes, systems. >> Mostly. The only thing that I would add is that now we are getting into live network testing to we see that mostly in the service provider space. Before you turn on the service, you need to make sure that all the devices and all the service has come up correctly. But also we're seeing it in enterprises to, particularly with security assessments. So reach assessment attacks. Security is your eye to organization really protecting the network? So we're seeing that become more and more important than they're pulling in test, particularly for security in that area to so as you. As you say, it's mostly device testing. But then that's going to network infrastructure and security networks, >> Right? So you've been in the industry for a while, you're it. Until you've been through a couple acquisitions, you've seen a lot of trends, so there's a lot of big macro things happening right now in the industry. It's exciting times and one of the ones. Actually, you just talked about it at Cisco alive a couple weeks ago is EJ Computer. There's a lot of talk about edges. Ej the new cloud. You know how much compute can move to the edge? What do you do in a crazy oilfield? With hot temperatures and no powers? I wonder if you can share some of the observations about EJ. You're kind of point of view as to where we're heading. And what should people be thinking about when they're considering? Yeah, what does EJ mean to my business? >> Absolutely, absolutely. So when I say it's computing, I typically include Io TI agent. It works is along with remote and branch offices, and obviously we can see the impact of Io TI security cameras, thermal starts, smart homes, automation, factory automation, hospital animation. Even planes have sensors on their engines right now for monitoring purposes and diagnostics. So that's one group. But then we know in our everyday lives, enterprises are growing very quickly, and they have remote and branch offices. More people are working from remotely. More people were working from home, so that means that more data is being generated at the edge. What it's with coyote sensors, each computing we see with oil and gas companies, and so it doesn't really make sense to generate all that data. Then you know, just imagine a self driving car. You need to capture a lot of data and you need to process. It just got really just send it to the cloud. Expect a decision to mate and then come back and so that you turn left or right, you need to actually process all that data, right? We're at the edge where the source of the data is, and that means pushing more of that computer infrastructure closer to the source. That also means running business critical applications closer to the source. And that means, you know, um, it's it's more of, ah, madness, massively distributed computer architecture. Um, what happens is that you have to then reliably connect all these devices so connectivity becomes important. But as you distribute, compute as well as applications, your attack surface increases right. Because all of these devices are very vulnerable. We're probably adding about 5,000,000 I ot devices every day to our network, So that's a lot of I O T. Devices or age devices that we connect many of these devices. You know, we don't really properly test. You probably know from your own home when you can just buy something and could easily connect it to your wife. I Similarly, people buy something, go to their work and connect to their WiFi. Not that device is connected to your entire network. So vulnerabilities in any of these devices exposes the entire network to that same vulnerability. So our attack surfaces increasing, so connection reliability as well as security for all these devices is a challenge. So we enjoy each computing coyote branch on road officers. But it does pose those challenges. And that's what we're here to do with our tech partners. Toe sold these issues >> right? It's just instinct to me on the edge because you still have kind of the three big um, the three big, you know, computer things. You got the networking right, which is just gonna be addressed by five g and a lot better band with and connectivity. But you still have store and you still have compute. You got to get those things Power s o a cz. You're thinking about the distribution of that computer and store at the edge versus in the cloud and you've got the Leighton see issue. It seems like a pretty delicate balancing act that people are gonna have to tune these systems to figure out how much to allocate where, and you will have physical limitations at this. You know the G power plant with the sure by now the middle of nowhere. >> It's It's a great point, and you typically get agility at the edge. Obviously, don't have power because these devices are small. Even if you take a room order branch office with 52 2 100 employees, there's only so much compute that you have. But you mean you need to be able to make decisions quickly. They're so agility is there. But obviously the vast amounts of computer and storage is more in your centralized data center, whether it's in your private cloud or your public cloud. So how do you do the compromise? When do you run applications at the edge when you were in applications in the cloud or private or public? Is that in fact, a compromise and year You might have to balance it, and it might change all the time, just as you know, if you look at our traditional history off compute. He had the mainframes which were centralized, and then it became distributed, centralized, distributed. So this changes all the time and you have toe make decisions, which which brings up the issue off. I would say hybrid, I t. You know, they have the same issue. A lot of enterprises have more of a, um, hybrid I t strategy or multi cloud. Where do you run the applications? Even if you forget about the age even on, do you run an on Prem? Do you run in the public cloud? Do you move it between class service providers? Even that is a small optimization problem. It's now even Matt bigger with H computer. >> Right? So the other thing that we've seen time and time again a huge trend, right? It's software to find, um, we've seen it in the networking space to compete based. It's offered to find us such a big write such a big deal now and you've seen that. So when you look at it from a test a measurement and when people are building out these devices, you know, obviously aton of great functional capability is suddenly available to people, but in terms of challenges and in terms of what you're thinking about in software defined from from you guys, because you're testing and measuring all this stuff, what's the goodness with the badness house for people, you really think about the challenges of software defined to take advantage of the tremendous opportunity. >> That's a really good point. I would say that with so far defined it working What we're really seeing is this aggregation typically had these monolithic devices that you would purchase from one vendor. That wonder vendor would guarantee that everything just works perfectly. What software defined it working, allows or has created is this desegregated model. Now you have. You can take that monolithic application and whether it's a server or a hardware infrastructure, then maybe you have a hyper visor or so software layer hardware, abstraction, layers and many, many layers. Well, if you're trying to get that toe work reliably, this means that now, in a way, the responsibility is on you to make sure that you test every all of these. Make sure that everything just works together because now we have choice. Which software packages should I install from which Bender This is always a slight differences. Which net Nick Bender should I use? If PJ smart Nick Regular Nick, you go up to the layer of what kind of ax elation should I use? D. P. D K. There's so many options you are responsible so that with S T N, you do get the advantage of opportunity off choice, just like on our servers and our PCs. But this means that you do have to test everything, make sure that everything works. So this means more testing at the device level, more testing at the service being up. So that's the predeployment stage and wants to deploy the service. Now you have to continually monitor it to make sure that it's working as you expected. So you get more choice, more diversity. And, of course, with segregation, you can take advantage of improvements on the hardware layer of the software layer. So there's that the segregation advantage. But it means more work on test as well as monitoring. So you know there's there's always a compromise >> trade off. Yeah, so different topic is security. Um, weird Arcee. This year we're in the four scout booth at a great chat with Michael the Caesars Yo there. And he talked about, you know, you talk a little bit about increasing surface area for attack, and then, you know, we all know the statistics of how long it takes people to know that they've been reach its center center. But Mike is funny. He you know, they have very simple sales pitch. They basically put their sniffer on your network and tell you that you got eight times more devices on the network than you thought. Because people are connecting all right, all types of things. So when you look at, you know, kind of monitoring test, especially with these increased surface area of all these, Iet devices, especially with bring your own devices. And it's funny, the H v A c seemed to be a really great place for bad guys to get in. And I heard the other day a casino at a casino, uh, connected thermometer in a fish tank in the lobby was the access point. How is just kind of changing your guys world, you know, how do you think about security? Because it seems like in the end, everyone seems to be getting he breached at some point in time. So it's almost Maur. How fast can you catch it? How do you minimize the damage? How do you take care of it versus this assumption that you can stop the reaches? You >> know, that was a really good point that you mentioned at the end, which is it's just better to assume that you will be breached at some point. And how quickly can you detect that? Because, on average, I think, according to research, it takes enterprise about six months. Of course, they're enterprise that are takes about a couple of years before they realize. And, you know, we hear this on the news about millions of records exposed billions of dollars of market cap loss. Four. Scout. It's a very close take partner, and we typically use deploy solutions together with these technology partners, whether it's a PM in P. M. But very importantly, security, and if you think about it, there's terabytes of data in the network. Typically, many of these tools look at the packet data, but you can't really just take those terabytes of data and just through it at all the tools, it just becomes a financially impossible toe provide security and deploy such tools in a very large network. So where this is where we come in and we were the taps, we access the data where the package workers was essentially groom it, filtering down to maybe tens or hundreds of gigs that that's really, really important. And then we feed it, feed it to our take partners such as Four Scout and many of the others. That way they can. They can focus on providing security by looking at the packets that really matter. For example, you know some some solutions only. Look, I need to look at the package header. You don't really need to see the send the payload. So if somebody is streaming Netflix or YouTube, maybe you just need to send the first mega byte of data not the whole hundreds of gigs over that to our video, so that allows them to. It allows us or helps us increase the efficiency of that tool. So the end customer can actually get a good R Y on that on that investment, and it allows for Scott to really look at or any of the tech partners to look at what's really important let me do a better job of investigating. Hey, have I been hacked? And of course, it has to be state full, meaning that it's not just looking at flow on one data flow on one side, looking at the whole communication. So you can understand What is this? A malicious application that is now done downloading other malicious applications and infiltrating my system? Is that a DDOS attack? Is it a hack? It's, Ah, there's a hole, equal system off attacks. And that's where we have so many companies in this in this space, many startups. >> It's interesting We had Tom Siebel on a little while ago actually had a W s event and his his explanation of what big data means is that there's no sampling air. And we often hear that, you know, we used to kind of prior to big day, two days we would take a sample of data after the fact and then tried to to do someone understanding where now the more popular is now we have a real time streaming engines. So now we're getting all the data basically instantaneously in making decisions. But what you just bring out is you don't necessarily want all the data all the time because it could. It can overwhelm its stress to Syria. That needs to be a much better management approach to that. And as I look at some of the notes, you know, you guys were now deploying 400 gigabit. That's right, which is bananas, because it seems like only yesterday that 100 gigabyte Ethan, that was a big deal a little bit about, you know, kind of the just hard core technology changes that are impacting data centers and deployments. And as this band with goes through the ceiling, what people are physically having to do, do it. >> Sure, sure, it's amazing how it took some time to go from 1 to 10 gig and then turning into 40 gig, but that that time frame is getting shorter and shorter from 48 2 108 100 to 400. I don't even know how we're going to get to the next phase because the demand is there and the demand is coming from a number of Trans really wants five G or the preparation for five G. A lot of service providers are started to do trials and they're up to upgrading that infrastructure because five G is gonna make it easier to access state of age quickly invest amounts of data. Whenever you make something easy for the consumer, they will consume it more. So that's one aspect of it. The preparation for five GS increasing the need for band with an infrastructure overhaul. The other piece is that we're with the neutralization. We're generating more Eastern West traffic, but because we're distributed with its computing, that East West traffic can still traverse data centers and geography. So this means that it's not just contained within a server or within Iraq. It actually just go to different locations. That also means your data center into interconnect has to support 400 gig. So a lot of network of hitmen manufacturers were typically call them. Names are are releasing are about to release 400 devices. So on the test side, they use our solutions to test these devices, obviously, because they want to release it based the standards to make sure that it works on. So that's the pre deployment phase. But once these foreign jiggy devices are deployed and typically service providers, but we're start slowly starting to see large enterprises deploy it as a mention because because of visualization and computing, then the question is, how do you make sure that your 400 gig infrastructure is operating at the capacity that you want in P. M. A. P M. As well as you're providing security? So there's a pre deployment phase that we help on the test side and then post deployment monitoring face. But five G is a big one, even though we're not. Actually we haven't turned on five year service is there's tremendous investment going on. In fact, key site. The larger organization is helping with a lot of these device testing, too. So it's not just Xia but key site. It's consume a lot of all of our time just because we're having a lot of engagements on the cellphone side. Uh, you know, decide endpoint side. It's a very interesting time that we're living in because the changes are becoming more and more frequent and it's very hot, so adapt and make sure that you're leading that leading that wave. >> In preparing for this, I saw you in another video camera. Which one it was, but your quote was you know, they didn't create electricity by improving candles. Every line I'm gonna steal it. I'll give you credit. But as you look back, I mean, I don't think most people really grown to the step function. Five g, you know, and they talk about five senior fun. It's not about your phone. It says this is the first kind of network built four machines. That's right. Machine data, the speed machine data and the quantity of Mr Sheen data. As you sit back, What kind of reflectively Again? You've been in this business for a while and you look at five G. You're sitting around talking to your to your friends at a party. So maybe some family members aren't in the business. How do you How do you tell them what this means? I mean, what are people not really seeing when they're just thinking it's just gonna be a handset upgrade there, completely missing the boat? >> Yeah, I think for the for the regular consumer, they just think it's another handset. You know, I went from three G's to 40 year. I got I saw bump in speed, and, you know, uh, some handset manufacturers are actually advertising five G capable handsets. So I'm just going to be out by another cell phone behind the curtain under the hurt. There's this massive infrastructure overhaul that a lot of service providers are going through. And it's scary because I would say that a lot of them are not necessarily prepared. The investment that's pouring in is staggering. The help that they need is one area that we're trying to accommodate because the end cell towers are being replaced. The end devices are being replaced. The data centers are being upgraded. Small South sites, you know, Um, there's there's, uh how do you provide coverage? What is the killer use case? Most likely is probably gonna be manufacturing just because it's, as you said mission to make mission machine learning Well, that's your machine to mission communication. That's where the connected hospitals connected. Manufacturing will come into play, and it's just all this machine machine communication, um, generating vast amounts of data and that goes ties back to that each computing where the edge is generating the data. But you then send some of that data not all of it, but some of that data to a centralized cloud and you develop essentially machine learning algorithms, which you then push back to the edge. The edge becomes a more intelligent and we get better productivity. But it's all machine to machine communication that, you know, I would say that more of the most of the five communication is gonna be much information communication. Some small portion will be the consumers just face timing or messaging and streaming. But that's gonna be there exactly. Exactly. That's going to change. I'm of course, we'll see other changes in our day to day lives. You know, a couple of companies attempted live gaming on the cloud in the >> past. It didn't really work out just because the network latency was not there. But we'll see that, too, and was seeing some of the products coming out from the lecture of Google into the company's where they're trying to push gaming to be in the cloud. It's something that we were not really successful in the past, so those are things that I think consumers will see Maur in their day to day lives. But the bigger impact is gonna be for the for the enterprise >> or jet. Thanks for ah, for taking some time and sharing your insight. You know, you guys get to see a lot of stuff. You've been in the industry for a while. You get to test all the new equipment that they're building. So you guys have a really interesting captaincy toe watches developments. Really exciting times. >> Thank you for inviting us. Great to be here. >> All right, Easier. Jeff. Jeff, you're watching the Cube. Where? Cube studios and fellow out there. Thanks for watching. We'll see you next time.