>> From theCUBE Studios in Palo Alto and Boston, bringing you data-driven insights from theCUBE and ETR. This is Breaking Analysis with Dave Vellante. >> Spark became a top level Apache project in 2014, and then shortly thereafter, burst onto the big data scene. Spark, along with the cloud, transformed and in many ways, disrupted the big data market. Databricks optimized its tech stack for Spark and took advantage of the cloud to really cleverly deliver a managed service that has become a leading AI and data platform among data scientists and data engineers. However, emerging customer data requirements are shifting into a direction that will cause modern data platform players generally and Databricks, specifically, we think, to make some key directional decisions and perhaps even reinvent themselves. Hello and welcome to this week's wikibon theCUBE Insights, powered by ETR. In this Breaking Analysis, we're going to do a deep dive into Databricks. We'll explore its current impressive market momentum. We're going to use some ETR survey data to show that, and then we'll lay out how customer data requirements are changing and what the ideal data platform will look like in the midterm future. We'll then evaluate core elements of the Databricks portfolio against that vision, and then we'll close with some strategic decisions that we think the company faces. And to do so, we welcome in our good friend, George Gilbert, former equities analyst, market analyst, and current Principal at TechAlpha Partners. George, good to see you. Thanks for coming on. >> Good to see you, Dave. >> All right, let me set this up. We're going to start by taking a look at where Databricks sits in the market in terms of how customers perceive the company and what it's momentum looks like. And this chart that we're showing here is data from ETS, the emerging technology survey of private companies. The N is 1,421. What we did is we cut the data on three sectors, analytics, database-data warehouse, and AI/ML. The vertical axis is a measure of customer sentiment, which evaluates an IT decision maker's awareness of the firm and the likelihood of engaging and/or purchase intent. The horizontal axis shows mindshare in the dataset, and we've highlighted Databricks, which has been a consistent high performer in this survey over the last several quarters. And as we, by the way, just as aside as we previously reported, OpenAI, which burst onto the scene this past quarter, leads all names, but Databricks is still prominent. You can see that the ETR shows some open source tools for reference, but as far as firms go, Databricks is very impressively positioned. Now, let's see how they stack up to some mainstream cohorts in the data space, against some bigger companies and sometimes public companies. This chart shows net score on the vertical axis, which is a measure of spending momentum and pervasiveness in the data set is on the horizontal axis. You can see that chart insert in the upper right, that informs how the dots are plotted, and net score against shared N. And that red dotted line at 40% indicates a highly elevated net score, anything above that we think is really, really impressive. And here we're just comparing Databricks with Snowflake, Cloudera, and Oracle. And that squiggly line leading to Databricks shows their path since 2021 by quarter. And you can see it's performing extremely well, maintaining an elevated net score and net range. Now it's comparable in the vertical axis to Snowflake, and it consistently is moving to the right and gaining share. Now, why did we choose to show Cloudera and Oracle? The reason is that Cloudera got the whole big data era started and was disrupted by Spark. And of course the cloud, Spark and Databricks and Oracle in many ways, was the target of early big data players like Cloudera. Take a listen to Cloudera CEO at the time, Mike Olson. This is back in 2010, first year of theCUBE, play the clip. >> Look, back in the day, if you had a data problem, if you needed to run business analytics, you wrote the biggest check you could to Sun Microsystems, and you bought a great big, single box, central server, and any money that was left over, you handed to Oracle for a database licenses and you installed that database on that box, and that was where you went for data. That was your temple of information. >> Okay? So Mike Olson implied that monolithic model was too expensive and inflexible, and Cloudera set out to fix that. But the best laid plans, as they say, George, what do you make of the data that we just shared? >> So where Databricks has really come up out of sort of Cloudera's tailpipe was they took big data processing, made it coherent, made it a managed service so it could run in the cloud. So it relieved customers of the operational burden. Where they're really strong and where their traditional meat and potatoes or bread and butter is the predictive and prescriptive analytics that building and training and serving machine learning models. They've tried to move into traditional business intelligence, the more traditional descriptive and diagnostic analytics, but they're less mature there. So what that means is, the reason you see Databricks and Snowflake kind of side by side is there are many, many accounts that have both Snowflake for business intelligence, Databricks for AI machine learning, where Snowflake, I'm sorry, where Databricks also did really well was in core data engineering, refining the data, the old ETL process, which kind of turned into ELT, where you loaded into the analytic repository in raw form and refine it. And so people have really used both, and each is trying to get into the other. >> Yeah, absolutely. We've reported on this quite a bit. Snowflake, kind of moving into the domain of Databricks and vice versa. And the last bit of ETR evidence that we want to share in terms of the company's momentum comes from ETR's Round Tables. They're run by Erik Bradley, and now former Gartner analyst and George, your colleague back at Gartner, Daren Brabham. And what we're going to show here is some direct quotes of IT pros in those Round Tables. There's a data science head and a CIO as well. Just make a few call outs here, we won't spend too much time on it, but starting at the top, like all of us, we can't talk about Databricks without mentioning Snowflake. Those two get us excited. Second comment zeros in on the flexibility and the robustness of Databricks from a data warehouse perspective. And then the last point is, despite competition from cloud players, Databricks has reinvented itself a couple of times over the year. And George, we're going to lay out today a scenario that perhaps calls for Databricks to do that once again. >> Their big opportunity and their big challenge for every tech company, it's managing a technology transition. The transition that we're talking about is something that's been bubbling up, but it's really epical. First time in 60 years, we're moving from an application-centric view of the world to a data-centric view, because decisions are becoming more important than automating processes. So let me let you sort of develop. >> Yeah, so let's talk about that here. We going to put up some bullets on precisely that point and the changing sort of customer environment. So you got IT stacks are shifting is George just said, from application centric silos to data centric stacks where the priority is shifting from automating processes to automating decision. You know how look at RPA and there's still a lot of automation going on, but from the focus of that application centricity and the data locked into those apps, that's changing. Data has historically been on the outskirts in silos, but organizations, you think of Amazon, think Uber, Airbnb, they're putting data at the core, and logic is increasingly being embedded in the data instead of the reverse. In other words, today, the data's locked inside the app, which is why you need to extract that data is sticking it to a data warehouse. The point, George, is we're putting forth this new vision for how data is going to be used. And you've used this Uber example to underscore the future state. Please explain? >> Okay, so this is hopefully an example everyone can relate to. The idea is first, you're automating things that are happening in the real world and decisions that make those things happen autonomously without humans in the loop all the time. So to use the Uber example on your phone, you call a car, you call a driver. Automatically, the Uber app then looks at what drivers are in the vicinity, what drivers are free, matches one, calculates an ETA to you, calculates a price, calculates an ETA to your destination, and then directs the driver once they're there. The point of this is that that cannot happen in an application-centric world very easily because all these little apps, the drivers, the riders, the routes, the fares, those call on data locked up in many different apps, but they have to sit on a layer that makes it all coherent. >> But George, so if Uber's doing this, doesn't this tech already exist? Isn't there a tech platform that does this already? >> Yes, and the mission of the entire tech industry is to build services that make it possible to compose and operate similar platforms and tools, but with the skills of mainstream developers in mainstream corporations, not the rocket scientists at Uber and Amazon. >> Okay, so we're talking about horizontally scaling across the industry, and actually giving a lot more organizations access to this technology. So by way of review, let's summarize the trend that's going on today in terms of the modern data stack that is propelling the likes of Databricks and Snowflake, which we just showed you in the ETR data and is really is a tailwind form. So the trend is toward this common repository for analytic data, that could be multiple virtual data warehouses inside of Snowflake, but you're in that Snowflake environment or Lakehouses from Databricks or multiple data lakes. And we've talked about what JP Morgan Chase is doing with the data mesh and gluing data lakes together, you've got various public clouds playing in this game, and then the data is annotated to have a common meaning. In other words, there's a semantic layer that enables applications to talk to the data elements and know that they have common and coherent meaning. So George, the good news is this approach is more effective than the legacy monolithic models that Mike Olson was talking about, so what's the problem with this in your view? >> So today's data platforms added immense value 'cause they connected the data that was previously locked up in these monolithic apps or on all these different microservices, and that supported traditional BI and AI/ML use cases. But now if we want to build apps like Uber or Amazon.com, where they've got essentially an autonomously running supply chain and e-commerce app where humans only care and feed it. But the thing is figuring out what to buy, when to buy, where to deploy it, when to ship it. We needed a semantic layer on top of the data. So that, as you were saying, the data that's coming from all those apps, the different apps that's integrated, not just connected, but it means the same. And the issue is whenever you add a new layer to a stack to support new applications, there are implications for the already existing layers, like can they support the new layer and its use cases? So for instance, if you add a semantic layer that embeds app logic with the data rather than vice versa, which we been talking about and that's been the case for 60 years, then the new data layer faces challenges that the way you manage that data, the way you analyze that data, is not supported by today's tools. >> Okay, so actually Alex, bring me up that last slide if you would, I mean, you're basically saying at the bottom here, today's repositories don't really do joins at scale. The future is you're talking about hundreds or thousands or millions of data connections, and today's systems, we're talking about, I don't know, 6, 8, 10 joins and that is the fundamental problem you're saying, is a new data error coming and existing systems won't be able to handle it? >> Yeah, one way of thinking about it is that even though we call them relational databases, when we actually want to do lots of joins or when we want to analyze data from lots of different tables, we created a whole new industry for analytic databases where you sort of mung the data together into fewer tables. So you didn't have to do as many joins because the joins are difficult and slow. And when you're going to arbitrarily join thousands, hundreds of thousands or across millions of elements, you need a new type of database. We have them, they're called graph databases, but to query them, you go back to the prerelational era in terms of their usability. >> Okay, so we're going to come back to that and talk about how you get around that problem. But let's first lay out what the ideal data platform of the future we think looks like. And again, we're going to come back to use this Uber example. In this graphic that George put together, awesome. We got three layers. The application layer is where the data products reside. The example here is drivers, rides, maps, routes, ETA, et cetera. The digital version of what we were talking about in the previous slide, people, places and things. The next layer is the data layer, that breaks down the silos and connects the data elements through semantics and everything is coherent. And then the bottom layers, the legacy operational systems feed that data layer. George, explain what's different here, the graph database element, you talk about the relational query capabilities, and why can't I just throw memory at solving this problem? >> Some of the graph databases do throw memory at the problem and maybe without naming names, some of them live entirely in memory. And what you're dealing with is a prerelational in-memory database system where you navigate between elements, and the issue with that is we've had SQL for 50 years, so we don't have to navigate, we can say what we want without how to get it. That's the core of the problem. >> Okay. So if I may, I just want to drill into this a little bit. So you're talking about the expressiveness of a graph. Alex, if you'd bring that back out, the fourth bullet, expressiveness of a graph database with the relational ease of query. Can you explain what you mean by that? >> Yeah, so graphs are great because when you can describe anything with a graph, that's why they're becoming so popular. Expressive means you can represent anything easily. They're conducive to, you might say, in a world where we now want like the metaverse, like with a 3D world, and I don't mean the Facebook metaverse, I mean like the business metaverse when we want to capture data about everything, but we want it in context, we want to build a set of digital twins that represent everything going on in the world. And Uber is a tiny example of that. Uber built a graph to represent all the drivers and riders and maps and routes. But what you need out of a database isn't just a way to store stuff and update stuff. You need to be able to ask questions of it, you need to be able to query it. And if you go back to prerelational days, you had to know how to find your way to the data. It's sort of like when you give directions to someone and they didn't have a GPS system and a mapping system, you had to give them turn by turn directions. Whereas when you have a GPS and a mapping system, which is like the relational thing, you just say where you want to go, and it spits out the turn by turn directions, which let's say, the car might follow or whoever you're directing would follow. But the point is, it's much easier in a relational database to say, "I just want to get these results. You figure out how to get it." The graph database, they have not taken over the world because in some ways, it's taking a 50 year leap backwards. >> Alright, got it. Okay. Let's take a look at how the current Databricks offerings map to that ideal state that we just laid out. So to do that, we put together this chart that looks at the key elements of the Databricks portfolio, the core capability, the weakness, and the threat that may loom. Start with the Delta Lake, that's the storage layer, which is great for files and tables. It's got true separation of compute and storage, I want you to double click on that George, as independent elements, but it's weaker for the type of low latency ingest that we see coming in the future. And some of the threats highlighted here. AWS could add transactional tables to S3, Iceberg adoption is picking up and could accelerate, that could disrupt Databricks. George, add some color here please? >> Okay, so this is the sort of a classic competitive forces where you want to look at, so what are customers demanding? What's competitive pressure? What are substitutes? Even what your suppliers might be pushing. Here, Delta Lake is at its core, a set of transactional tables that sit on an object store. So think of it in a database system, this is the storage engine. So since S3 has been getting stronger for 15 years, you could see a scenario where they add transactional tables. We have an open source alternative in Iceberg, which Snowflake and others support. But at the same time, Databricks has built an ecosystem out of tools, their own and others, that read and write to Delta tables, that's what makes the Delta Lake and ecosystem. So they have a catalog, the whole machine learning tool chain talks directly to the data here. That was their great advantage because in the past with Snowflake, you had to pull all the data out of the database before the machine learning tools could work with it, that was a major shortcoming. They fixed that. But the point here is that even before we get to the semantic layer, the core foundation is under threat. >> Yep. Got it. Okay. We got a lot of ground to cover. So we're going to take a look at the Spark Execution Engine next. Think of that as the refinery that runs really efficient batch processing. That's kind of what disrupted the DOOp in a large way, but it's not Python friendly and that's an issue because the data science and the data engineering crowd are moving in that direction, and/or they're using DBT. George, we had Tristan Handy on at Supercloud, really interesting discussion that you and I did. Explain why this is an issue for Databricks? >> So once the data lake was in place, what people did was they refined their data batch, and Spark has always had streaming support and it's gotten better. The underlying storage as we've talked about is an issue. But basically they took raw data, then they refined it into tables that were like customers and products and partners. And then they refined that again into what was like gold artifacts, which might be business intelligence metrics or dashboards, which were collections of metrics. But they were running it on the Spark Execution Engine, which it's a Java-based engine or it's running on a Java-based virtual machine, which means all the data scientists and the data engineers who want to work with Python are really working in sort of oil and water. Like if you get an error in Python, you can't tell whether the problems in Python or where it's in Spark. There's just an impedance mismatch between the two. And then at the same time, the whole world is now gravitating towards DBT because it's a very nice and simple way to compose these data processing pipelines, and people are using either SQL in DBT or Python in DBT, and that kind of is a substitute for doing it all in Spark. So it's under threat even before we get to that semantic layer, it so happens that DBT itself is becoming the authoring environment for the semantic layer with business intelligent metrics. But that's again, this is the second element that's under direct substitution and competitive threat. >> Okay, let's now move down to the third element, which is the Photon. Photon is Databricks' BI Lakehouse, which has integration with the Databricks tooling, which is very rich, it's newer. And it's also not well suited for high concurrency and low latency use cases, which we think are going to increasingly become the norm over time. George, the call out threat here is customers want to connect everything to a semantic layer. Explain your thinking here and why this is a potential threat to Databricks? >> Okay, so two issues here. What you were touching on, which is the high concurrency, low latency, when people are running like thousands of dashboards and data is streaming in, that's a problem because SQL data warehouse, the query engine, something like that matures over five to 10 years. It's one of these things, the joke that Andy Jassy makes just in general, he's really talking about Azure, but there's no compression algorithm for experience. The Snowflake guy started more than five years earlier, and for a bunch of reasons, that lead is not something that Databricks can shrink. They'll always be behind. So that's why Snowflake has transactional tables now and we can get into that in another show. But the key point is, so near term, it's struggling to keep up with the use cases that are core to business intelligence, which is highly concurrent, lots of users doing interactive query. But then when you get to a semantic layer, that's when you need to be able to query data that might have thousands or tens of thousands or hundreds of thousands of joins. And that's a SQL query engine, traditional SQL query engine is just not built for that. That's the core problem of traditional relational databases. >> Now this is a quick aside. We always talk about Snowflake and Databricks in sort of the same context. We're not necessarily saying that Snowflake is in a position to tackle all these problems. We'll deal with that separately. So we don't mean to imply that, but we're just sort of laying out some of the things that Snowflake or rather Databricks customers we think, need to be thinking about and having conversations with Databricks about and we hope to have them as well. We'll come back to that in terms of sort of strategic options. But finally, when come back to the table, we have Databricks' AI/ML Tool Chain, which has been an awesome capability for the data science crowd. It's comprehensive, it's a one-stop shop solution, but the kicker here is that it's optimized for supervised model building. And the concern is that foundational models like GPT could cannibalize the current Databricks tooling, but George, can't Databricks, like other software companies, integrate foundation model capabilities into its platform? >> Okay, so the sound bite answer to that is sure, IBM 3270 terminals could call out to a graphical user interface when they're running on the XT terminal, but they're not exactly good citizens in that world. The core issue is Databricks has this wonderful end-to-end tool chain for training, deploying, monitoring, running inference on supervised models. But the paradigm there is the customer builds and trains and deploys each model for each feature or application. In a world of foundation models which are pre-trained and unsupervised, the entire tool chain is different. So it's not like Databricks can junk everything they've done and start over with all their engineers. They have to keep maintaining what they've done in the old world, but they have to build something new that's optimized for the new world. It's a classic technology transition and their mentality appears to be, "Oh, we'll support the new stuff from our old stuff." Which is suboptimal, and as we'll talk about, their biggest patron and the company that put them on the map, Microsoft, really stopped working on their old stuff three years ago so that they could build a new tool chain optimized for this new world. >> Yeah, and so let's sort of close with what we think the options are and decisions that Databricks has for its future architecture. They're smart people. I mean we've had Ali Ghodsi on many times, super impressive. I think they've got to be keenly aware of the limitations, what's going on with foundation models. But at any rate, here in this chart, we lay out sort of three scenarios. One is re-architect the platform by incrementally adopting new technologies. And example might be to layer a graph query engine on top of its stack. They could license key technologies like graph database, they could get aggressive on M&A and buy-in, relational knowledge graphs, semantic technologies, vector database technologies. George, as David Floyer always says, "A lot of ways to skin a cat." We've seen companies like, even think about EMC maintained its relevance through M&A for many, many years. George, give us your thought on each of these strategic options? >> Okay, I find this question the most challenging 'cause remember, I used to be an equity research analyst. I worked for Frank Quattrone, we were one of the top tech shops in the banking industry, although this is 20 years ago. But the M&A team was the top team in the industry and everyone wanted them on their side. And I remember going to meetings with these CEOs, where Frank and the bankers would say, "You want us for your M&A work because we can do better." And they really could do better. But in software, it's not like with EMC in hardware because with hardware, it's easier to connect different boxes. With software, the whole point of a software company is to integrate and architect the components so they fit together and reinforce each other, and that makes M&A harder. You can do it, but it takes a long time to fit the pieces together. Let me give you examples. If they put a graph query engine, let's say something like TinkerPop, on top of, I don't even know if it's possible, but let's say they put it on top of Delta Lake, then you have this graph query engine talking to their storage layer, Delta Lake. But if you want to do analysis, you got to put the data in Photon, which is not really ideal for highly connected data. If you license a graph database, then most of your data is in the Delta Lake and how do you sync it with the graph database? If you do sync it, you've got data in two places, which kind of defeats the purpose of having a unified repository. I find this semantic layer option in number three actually more promising, because that's something that you can layer on top of the storage layer that you have already. You just have to figure out then how to have your query engines talk to that. What I'm trying to highlight is, it's easy as an analyst to say, "You can buy this company or license that technology." But the really hard work is making it all work together and that is where the challenge is. >> Yeah, and well look, I thank you for laying that out. We've seen it, certainly Microsoft and Oracle. I guess you might argue that well, Microsoft had a monopoly in its desktop software and was able to throw off cash for a decade plus while it's stock was going sideways. Oracle had won the database wars and had amazing margins and cash flow to be able to do that. Databricks isn't even gone public yet, but I want to close with some of the players to watch. Alex, if you'd bring that back up, number four here. AWS, we talked about some of their options with S3 and it's not just AWS, it's blob storage, object storage. Microsoft, as you sort of alluded to, was an early go-to market channel for Databricks. We didn't address that really. So maybe in the closing comments we can. Google obviously, Snowflake of course, we're going to dissect their options in future Breaking Analysis. Dbt labs, where do they fit? Bob Muglia's company, Relational.ai, why are these players to watch George, in your opinion? >> So everyone is trying to assemble and integrate the pieces that would make building data applications, data products easy. And the critical part isn't just assembling a bunch of pieces, which is traditionally what AWS did. It's a Unix ethos, which is we give you the tools, you put 'em together, 'cause you then have the maximum choice and maximum power. So what the hyperscalers are doing is they're taking their key value stores, in the case of ASW it's DynamoDB, in the case of Azure it's Cosmos DB, and each are putting a graph query engine on top of those. So they have a unified storage and graph database engine, like all the data would be collected in the key value store. Then you have a graph database, that's how they're going to be presenting a foundation for building these data apps. Dbt labs is putting a semantic layer on top of data lakes and data warehouses and as we'll talk about, I'm sure in the future, that makes it easier to swap out the underlying data platform or swap in new ones for specialized use cases. Snowflake, what they're doing, they're so strong in data management and with their transactional tables, what they're trying to do is take in the operational data that used to be in the province of many state stores like MongoDB and say, "If you manage that data with us, it'll be connected to your analytic data without having to send it through a pipeline." And that's hugely valuable. Relational.ai is the wildcard, 'cause what they're trying to do, it's almost like a holy grail where you're trying to take the expressiveness of connecting all your data in a graph but making it as easy to query as you've always had it in a SQL database or I should say, in a relational database. And if they do that, it's sort of like, it'll be as easy to program these data apps as a spreadsheet was compared to procedural languages, like BASIC or Pascal. That's the implications of Relational.ai. >> Yeah, and again, we talked before, why can't you just throw this all in memory? We're talking in that example of really getting down to differences in how you lay the data out on disk in really, new database architecture, correct? >> Yes. And that's why it's not clear that you could take a data lake or even a Snowflake and why you can't put a relational knowledge graph on those. You could potentially put a graph database, but it'll be compromised because to really do what Relational.ai has done, which is the ease of Relational on top of the power of graph, you actually need to change how you're storing your data on disk or even in memory. So you can't, in other words, it's not like, oh we can add graph support to Snowflake, 'cause if you did that, you'd have to change, or in your data lake, you'd have to change how the data is physically laid out. And then that would break all the tools that talk to that currently. >> What in your estimation, is the timeframe where this becomes critical for a Databricks and potentially Snowflake and others? I mentioned earlier midterm, are we talking three to five years here? Are we talking end of decade? What's your radar say? >> I think something surprising is going on that's going to sort of come up the tailpipe and take everyone by storm. All the hype around business intelligence metrics, which is what we used to put in our dashboards where bookings, billings, revenue, customer, those things, those were the key artifacts that used to live in definitions in your BI tools, and DBT has basically created a standard for defining those so they live in your data pipeline or they're defined in their data pipeline and executed in the data warehouse or data lake in a shared way, so that all tools can use them. This sounds like a digression, it's not. All this stuff about data mesh, data fabric, all that's going on is we need a semantic layer and the business intelligence metrics are defining common semantics for your data. And I think we're going to find by the end of this year, that metrics are how we annotate all our analytic data to start adding common semantics to it. And we're going to find this semantic layer, it's not three to five years off, it's going to be staring us in the face by the end of this year. >> Interesting. And of course SVB today was shut down. We're seeing serious tech headwinds, and oftentimes in these sort of downturns or flat turns, which feels like this could be going on for a while, we emerge with a lot of new players and a lot of new technology. George, we got to leave it there. Thank you to George Gilbert for excellent insights and input for today's episode. I want to thank Alex Myerson who's on production and manages the podcast, of course Ken Schiffman as well. Kristin Martin and Cheryl Knight help get the word out on social media and in our newsletters. And Rob Hof is our EIC over at Siliconangle.com, he does some great editing. Remember all these episodes, they're available as podcasts. Wherever you listen, all you got to do is search Breaking Analysis Podcast, we publish each week on wikibon.com and siliconangle.com, or you can email me at David.Vellante@siliconangle.com, or DM me @DVellante. Comment on our LinkedIn post, and please do check out ETR.ai, great survey data, enterprise tech focus, phenomenal. This is Dave Vellante for theCUBE Insights powered by ETR. Thanks for watching, and we'll see you next time on Breaking Analysis.

(light, upbeat music) >> The last decade of cloud computing introduced and popularized an operating model that emphasized, simplified IT infrastructure provisioning and management. As well, it ushered in an era of consumption-based pricing and much more facile IT management, generally. Now these principles, they've bled into traditional data centers, which have increasingly become software led, programmable and DevOps centric. Now as we enter the post isolation era, it's ironic that not only are IT executives pursuing hybrid strategies, but everyone is talking about hybrid. Hybrid work, hybrid teams, hybrid events, hybrid meetings. The world has gone hybrid and the cloud is no exception. The cloud is expanding. Public cloud models are pushing to the data center and the edge on premises infrastructure is connecting to public clouds and managing data workflows and infrastructure across clouds and out to the edge. Now most leading technology executives that I speak with, they're essentially architecting their own clouds. And what I mean by that is they're envisioning and building an abstraction layer that hides the complexity of the underlying infrastructure and manages workloads intelligently. The end customer doesn't know or care where the data is, as long as it's secure, properly governed, and could be accessed quickly, all irrespective of physical location. Now for the most part, this vision, it can't be bought off the shelf. It needs to be built by placing bets on key technology partners and leveraging the so-called API economy. In other words, picking technology vendors that I trust in programmatically codifying and automating where possible my organizational edicts and business requirements into my own cloud to uniquely support my application portfolio in my modern business processes, which by the way, are rapidly evolving. Now, a key to enabling this vision is optionality. Meaning, not getting locked into one single technology platform, but rather having the confidence that as technology evolves, which it always does, I can focus my energies on adding value to my business through process innovation and human capital growth. Hello, everyone and welcome to this cube conversation and video exclusive on a major new industry development and partnership that's designed to maximize customer infrastructure options and move the new era of hybrid cloud computing forward. We have two industry leaders joining us today. Monica Kumar is the senior vice president of marketing and cloud go-to-market from Nutanix, and David Farrell is the senior vice president and general manager for global strategic alliances at Red Hat. Folks, welcome to theCUBE. Thanks for coming on. >> Good to be here today. >> Thank you so much. >> All right, so Red Hat is the poster child for open source success and it's executing on a strategy based on Red Hat Enterprise Linux, RHEL and OpenShift, the industry's leading container platform, to drive cloud-like experiences. Nutanix is a pioneering company and was the first to truly envision and successfully bring to market a cloud operating model to data center infrastructure. So you two, are getting together and forming a deeper, more substantive relationship. So Monica, tell us about the hard news. What's the scoop? >> Yeah, of course. So, first of all, I'm so excited to be here with David Farrell from Red Hat and for those of you who may not know this, I have a very deep personal connection with Red Hat from my previous role as well. I've been working with Red Hat since the early 2000s. So it gives me great pleasure to be here on behalf of Nutanix and with David from Red Hat, to be announcing a formal strategic partnership to deliver open hybrid multi-cloud solutions. Now let me explain to you what I mean by that. This partnership that we're announcing today is going to enable best-in-class solutions for building, scaling and managing containerized and virtualized cloud native applications in of course, hyper-converged infrastructure environments. So the collaboration is going to bring together these industry-leading technologies. Enabling and integrating Red Hat OpenShift and Red Hat Enterprise Linux, onto the Nutanix cloud platform, which includes, you know, our well-known Nutanix AOS and AHV hypervisor technologies. Now the question is, why are we doing all this? It's because of, as you said, Dave, the rapid evolution of hybrid cloud strategies and adoption of containers and Kubernetes in our customer base to develop, deploy and manage apps. And what we're hearing from our customers is that they want this integration between Red Hat Technologies and Nutanix Solutions. >> Okay. Thank you, Monica. So big news David, from Red Hat's perspective. Okay. So Red Hat, Nutanix, both leaders in their respective fields. David, what spurred the decision to partner from your standpoint? >> Yeah. And listen, let me echo Monica's comments as well. So we're really excited about the partnership with Nutanix. And we're excited because Nutanix is the leader in hybrid cloud infrastructure, but we're even more excited because this is what customers have been asking us to do. And that's really at the core of the decision. I think both teams, both companies have been listening to customers and we've got a groundswell of enterprise customers around the world that are asking us to come together. Bring our technologies together from a certification perspective, which Monica spoke about, right, is number one. So RHEL and OpenShift being certified on top of AHV, right. To provide the best-in-class service for enterprise grade applications, but there's more to it than just the certification. Like customers are looking for a world-class integrated support experience as well as they go into, into production. So we also have integrated support, right. So customers can contact Nutanix, they can contact Red Hat and having that seamless, that seamless experience is really, really critical and something that our customers have been asking us for. And then we'll continue to work from a roadmap perspective as well, from an engineering perspective, to make sure that our roadmaps are aligned and the customers have assurance over time and continuity over time so that they can make investments that they know are going to pay off and be safe investments and scalable investments over the long arc of their technology horizon, so. So those are, those are kind of our view of why this is good for customers and back to your points, David, it's about choice and optionality, right? And choice and consistency, and I think the verdict is in now, in the industry, that hybrid is the future, right? Everybody kind of agrees on that, right? In certain applications and certain workloads are going to run on-prem, others are going to run on the public cloud, and customers need choice to be able to decide what's the right destination for those workloads. And that's what Red Hat's all about, that's what RHEL's all about, what OpenShift is all about, is that it runs on any cloud infrastructure. Now it runs on Nutanix HCI. >> So I liked that two, one virtual throat to choke, or maybe better put, maybe one virtual hand to shake. So David staying with you, maybe you could talk about some of the other key terms of the partnership. Maybe focus on joint solutions that the customers can expect and I'm particularly interested in the engineering collaboration. I know there's a go-to-market component, but the engineering collaboration and technology innovation that we can expect. >> Yeah. So there's a few components to it, David. One is, obviously as I talked about roadmap, right. And that's, you know, our technology teams coming together, looking at the existing roadmaps for RHEL and OpenShift, but also adjacent capabilities that are coming from the Red Hat portfolio and capabilities that are coming from our ISV ecosystems and our respective ecosystems. This is a big win for our partners, as well, that have been asking us to work together. So we'll continue to keep the radar up about what some of those functionalities and capabilities ought to be. Whether we make them or somebody else makes them to pull into the, pull into the strategy, if you will. The second big principle around joint engineering is going to be around customer experience, right. So for example, we're starting off with the agnostic installer and by the way, this is coming Thursday, right? I think we're live on Thursday, the 29th, right? So this is in market, it is GA, it's available today, the 29th, right. And then we will move to the, to the UPI- so sorry, to the IPI installer in the second half of this year, right. To provide a more automated experience and then I think on the Nutanix side, Monica can, can talk to this, that Nutanix is building APIs to also automate installation, right? So first and foremost, we're all about getting the solution and getting the jointly engineered technologies working together and providing a superior customer experience for our customers that are deploying Red Hat on top of Nutanix. And that's going to be the guiding, the guiding driver, if you will, for how we work together. >> Yeah. And let me add to that. Like you said, we are, the engineering is already bearing fruit for our customers, right. As of today, when we announcing, we already have certified versions of Red Hat Linux with AHV, number one. Number two, as you said, the agnostic installer is available. We will make the automated installer available so any customer can deploy OpenShift using the Nutanix cloud platform in the very near future, right. Those are the two sort of the beginnings of the engineering and this is going to, this is a longterm partnership, so we will continue to evolve the different configurations that we, you know, that we test and that we validate as well as we go on. So I'm really excited about the fact that we are going to be offering customers fully tested, validated configurations to deploy. (cross talk) >> Go ahead >> David if I may just in there as well, I mean, so that's on the engineering side, right. But there'll also be an important thing, customers expect us to cooperate in to engage proactively as we face them, right. So that both the Red Hat, part of the agreement is that both the Red Hat and the Nutanix field teams, right the customer teams, will also be enabled, right. We'll do technical enablement for our teams, stand up proof of technologies, right. So that we're burning in some of the technology, if you will, and working out the kinks before the customer has to, right. And this is also a key value proposition is we're doing this work upstream, both in the engineering teams and in the field engagement teams so that customers can get time to market, if you will, and speed of solution deployment. >> Got it. So we'd love to talk about the sweet spot, the ideal customer profile at ICP. So is there a particular type of customer Monica, that stands to benefit most from the partnership and the certifications that you're committing to? >> Yeah. I mean, if you look at, you know, cloud native app development, that's happening across all types of segments, but particularly, you know, enterprise customers running, in all industries practically, running tier one applications or building custom applications in the cloud would be a great focus for this. Our customers who are mature in their cloud native journeys and want to build and run cloud native workloads at scale would be another type of audience. I mean, when you really think about the gamut of customers we serve jointly together, it's all the way from, you know, mid-sized customers who are, who may want a complete solution that's built for them, to enterprise customers and even globals accounts that are actually doing a lot of custom application development and then deploying things at scale. So really, I mean, anybody who's developing applications, anybody who's running workloads, you know, database workloads, applications that they're building, analytics workloads, I think for all of them. This is a very beneficial solution and I would say specifically from a Nutanix customer perspective, we've had a demand for, you know, the certification with AHV and RHEL for a long time. So that's something our customers are very much looking forward to. We have a large number of customers who already are deploying that configuration and now they know it's fully tested, fully supported, and there's an ongoing roadmap from both companies to support it. And then as far as OpenShift goes, we are super excited about the possibilities of providing that optionality to customers and really meeting them at every level of their journey to the cloud. >> So you got the product level certifications, that to me is all about trust and it's kind of table stakes, but if I have that, now I can, I can lean in. What other kind of value dimensions should we be thinking about with regard to this, this partnership? I mean, obviously, you know, cost savings, you know, speed, things like that, but maybe you could sort of add more color to that. >> Yeah. Well, absolutely, look. I mean, anytime there's joint there's integration, there is complexity that's taken out of deployment from the customer's hands and the vendors do the work upfront, that results in a lot of different benefits. Including productivity benefits, speed to market benefits, total cost of ownership benefits, as you said. So we expect that the fact that the two companies are now going to do all this work upfront for our customers, they'll be able to deploy and do things that we're doing, you know, much faster than before, right? So that's, you know, definitely we believe, and then also joined support. I think David mentioned that, the fact that we are offering joint support as well to our customers we'll be problem solving together. So the seamless support experience will provide faster resolution for our joint customers. >> Great. David, I wonder if you could kind of share your view of you know, thinking about the Nutanix cloud platform, what makes it well suited for supporting OpenShift and cloud native workloads? >> Well, I think the, look first off, they're the leader, right. They bring the most trusted and tried HCI environment in the industry to bear for customers, right. And they deliver on the promises that Monica just went through, right, around simplicity, around ease of use, around scalability, around optionality, right. And they take that complexity away and that's what customers I think are telling both Red Hat and Nutanix, and really everybody for that matter, right. Is that they want to focus on the business outcomes, on the business value, on the applications, that differentiate them. And Nutanix really takes away a lot of that complexity for the customer at the infrastructure level, right. And then RHEL, and OpenShift and Red Hat do that as well, both at the infrastructure level and at the application level, right. So when it comes to simplicity, and when it comes to choice, but consistency, both Nutanix and Red Hat have that at the core of how we build and how we engineer products that we take to market to remove that complexity so the customers can move quickly, more cost-effectively, and have that optionality that they're after. >> Yeah and David, if I may add to that, and thank you again for saying the things you said, that's exactly why our customers choose us. One of the key factors is our distributed architecture as well, because of the way it's architected, the Nutanix cloud platform delivers an environment that's highly scalable and resilient, and it's well suited for enterprise deployments of Red Hat, OpenShift at scale. The platform also includes, you know, fully integrated unified storage, which addresses many of the challenging problems faced by operators routinely in configuring and managing storage for stateful containers, for example. So there's a lot of goodness there and the combination of Red Hat, both you know, RHEL and OpenShift, any 10x platform, I believe, offers really unparalleled value to our customers in terms of the technology we bring and the integration we bring to our customers. >> Okay, great. Last question, David, maybe you first, and then Monica, you can bring us home. Where do you guys want to see this partnership going? >> We want to see it going where, customers are getting the most value of course, right. And we would like to see obviously adoption, right. So, anytime two leaders like ourselves come together, it's all about delivering for the customer. We've got a long list of customers that have been asking us, as Monica said to do this, and it's overwhelming, right. So we're responding to that. We've got a pipeline of, of customers that we're already beginning to engage on. And so we'll measure our progress based upon adoption, right, and how customers adopt the solution, the shared solution as we go forward. How they're feeding back to us, the value that they're getting, and also encouraging them to engage with us around the roadmap and where we take the solution, right. So I think those are ways that, you know, we'll be focused on adoption and satisfaction around it across the marketplace and the degree of interaction and input we get from customers with respect to the roadmap. And Monica, how do you feel about it? >> Yeah. What's success look like Monica? >> Yeah, look, we all know that technology is a means to an end, right? And the end is solving customer problems, as David said. For us, success will be when we have many, many, many, joined happy customers that are getting benefit from our platform. To me, this is just the beginning of our relationship to help customers. The best is yet to come. I'm super excited, as I said, for many reasons, but specifically, because we know there's a huge demand out there for this integrated solution between Red Hat and Nutanix and we'll start delivering it to our customers. So we've been, we'll be working very closely with our customers to see how that option goes, and we want to delight them with this, with our joint solution. That's our goal. >> Thank you. Well, David, you kind of alluded to it. Customers have been looking forward to this for quiet some time, and number of us have been thinking about this happening and to me, the key, is you're actually putting some real muscle behind it as seen in the engineering resources. And you got to have that type of commitment before you really go forward, otherwise, it's just kind of a yeah a nice press release, nice party deal, this isn't. So congratulations on figuring this out. Good luck. And we'll be really excited to watch your progress. Appreciate you guys coming to theCUBE. Okay. And thank you for watching everybody. This is Dave Vellante for theCube. We'll see you next time. (light, upbeat music)

>> From theCUBE Studios in Palo Alto in Boston, bringing you data-driven insights from theCUBE and ETR, this is Braking Analysis with Dave Vellante. >> Intel's big announcement this week underscores the threat that the United States faces from China. The US needs to lead in semiconductor design and manufacturing. And that lead is slipping because Intel has been fumbling the ball over the past several years, a mere two months into the job, new CEO Pat Gelsinger wasted no time in setting a new course for perhaps, the most strategically important American technology company. We believe that Gelsinger has only shown us part of his plan. This is the beginning of a long and highly complex journey. Despite Gelsinger's clear vision, his deep understanding of technology and execution ethos, in order to regain its number one position, Intel we believe we'll need to have help from partners, competitors and very importantly, the US government. Hello everyone and welcome to this week's Wikibon CUBE insights powered by ETR. In this breaking analysis we'll peel the onion Intel's announcement of this week and explain why we're perhaps not as sanguine as was Wall Street on Intel's prospects. And we'll lay out what we think needs to take place for Intel to once again, become top gun and for us to gain more confidence. By the way this is the first time we're broadcasting live with Braking Analysis. We're broadcasting on the CUBE handles on Twitch, Periscope and YouTube and going forward we'll do this regularly as a live program and we'll bring in the community perspective into the conversation through chat. Now you may recall that in January, we kind of dismissed analysis that said Intel didn't have to make any major strategic changes to its business when they brought on Pat Gelsinger. Rather we said the exact opposite. Our view at time was that the root of Intel's problems could be traced to the fact that it wasn't no longer the volume leader. Because mobile volumes dwarf those of x86. As such we said that Intel couldn't go up the learning curve for next gen technologies as fast as its competitors and it needed to shed its dogma of being highly vertically integrated. We said Intel needed to more heavily leverage outsourced foundries. But more specifically, we suggested that in order for Intel to regain its volume lead, it needed to, we said at the time, spin out its manufacturing, create a joint venture sure with a volume leader, leveraging Intel's US manufacturing presence. This, we still believe with some slight refreshes to our thinking based on what Gelsinger has announced. And we'll talk about that today. Now specifically there were three main pieces and a lot of details to Intel's announcement. Gelsinger made it clear that Intel is not giving up its IDM or integrated device manufacturing ethos. He called this IDM 2.0, which comprises Intel's internal manufacturing, leveraging external Foundries and creating a new business unit called Intel Foundry Services. It's okay. Gelsinger said, "We are not giving up on integrated manufacturing." However, we think this is somewhat nuanced. Clearly Intel can't, won't and shouldn't give up on IDM. However, we believe Intel is entering a new era where it's giving designers more choice. This was not explicitly stated. However we feel like Intel's internal manufacturing arm will have increased pressure to serve its designers in a more competitive manner. We've already seen this with Intel finally embracing EUV or extreme ultraviolet lithography. Gelsinger basically said that Intel didn't lean into EUV early on and that it created more complexity in its 10 nanometer process, which dominoed into seven nanometer and as you know the rest of the story and Intel's delays. But since mid last year, it's embraced the technology. Now as a point of reference, Samsung started applying EUV for its seven nanometer technology in 2018. And it began shipping in early 2020. So as you can see, it takes years to get this technology into volume production. The point is that Intel realizes it needs to be more competitive. And we suspect, it will give more freedom to designers to leverage outsource manufacturing. But Gelsinger clearly signaled that IDM is not going away. But the really big news is that Intel is setting up a new division with a separate PNL that's going to report directly to Pat. Essentially it's hanging out a shingle and saying, we're open for business to make your chips. Intel is building two new Fabs in Arizona and investing $20 billion as part of this initiative. Now well Intel has tried this before earlier last decade. Gelsinger says that this time we're serious and we're going to do it right. We'll come back to that. This organizational move while not a spin out or a joint venture, it's part of the recipe that we saw as necessary for Intel to be more competitive. Let's talk about why Intel is doing this. Look at lots has changed in the world of semiconductors. When you think about it back when Pat was at Intel in the '90s, Intel was the volume leader. It crushed the competition with x86. And the competition at the time was coming from risk chips. And when Apple changed the game with iPod and iPhone and iPad, the volume equation flipped to mobile. And that led to big changes in the industry. Specifically, the world started to separate design from manufacturing. We now see firms going from design to tape out in 12 months versus taking three years. A good example is Tesla and his deal with ARM and Samsung. And what's happened is Intel has gone from number one in Foundry in terms of clock speed, wafer density, volume, lowest cost, highest margin to falling behind. TSMC, Samsung and alternative processor competitors like NVIDIA. Volume is still the maker of kings in this business. That hasn't changed and it confers advantage in terms of cost, speed and efficiency. But ARM wafer volumes, we estimate are 10x those of x86. That's a big change since Pat left Intel more than a decade ago. There's also a major chip shortage today. But you know this time, it feels a little different than the typical semiconductor boom and bust cycles. Semiconductor consumption is entering a new era and new use cases emerging from automobiles to factories, to every imaginable device piece of equipment, infrastructure, silicon is everywhere. But the biggest threat of all is China. China wants to be self-sufficient in semiconductors by 2025. It's putting approximately $60 billion into new chip Fabs, and there's more to come. China wants to be the new economic leader of the world and semiconductors are critical to that goal. Now there are those poopoo the China threat. This recent article from Scott Foster lays out some really good information. But the one thing that caught our attention is a statement that China's semiconductor industry is nowhere near being a major competitor in the global market. Let alone an existential threat to the international order and the American way of life. I think Scotty is stuck in the engine room and can't see the forest of the trees, wake up. Sure. You can say China is way behind. Let's take an example. NAND. Today China is at about 64 3D layers whereas Micron they're at 172. By 2022 China's going to be at 128. Micron, it's going to be well over 200. So what's the big deal? We say talk to us in 2025 because we think China will be at parody. That's just one example. Now the type of thinking that says don't worry about China and semi's reminds me of the epic lecture series that Clay Christiansen gave as a visiting professor at Oxford University on the history of, and the economics of the steel industry. Now if you haven't watched this series, you should. Basically Christiansen took the audience through the dynamics of steel production. And he asked the question, "Who told the steel manufacturers that gross margin was the number one measure of profitability? Was it God?" he joked. His point was, when new entrance came into the market in the '70s, they were bottom feeders going after the low margin, low quality, easiest to make rebar sector. And the incumbents nearly pulled back and their mix shifted to higher margin products and their gross margins went up and life was good. Until they lost the next layer. And then the next, and then the next, until it was game over. Now, one of the things that got lost in Pat's big announcement on the 23rd of March was that Intel guided the street below consensus on revenue and earnings. But the stock went up the next day. Now when asked about gross margin in the Q&A segment of the announcement, yes, gross margin is a if not the key metric in semi's in terms of measuring profitability. When asked Intel CFO George Davis explained that with the uptick in PCs last year there was a product shift to the lower margin PC sector and that put pressure on gross margins. It was a product mix thing. And revenue because PC chips are less expensive than server chips was affected as were margins. Now we shared this chart in our last Intel update showing, spending momentum over time for Dell's laptop business from ETR. And you can see in the inset, the unit growth and the market data from IDC, yes, Dell's laptop business is growing, everybody's laptop business is growing. Thank you COVID. But you see the numbers from IDC, Gartner, et cetera. Now, as we pointed out last time, PC volumes had peaked in 2011 and that's when the long arm of rights law began to eat into Intel's dominance. Today ARM wafer production as we said is far greater than Intel's and well, you know the story. Here's the irony, the very bucket that conferred volume adventures to Intel PCs, yes, it had a slight uptick last year, which was great news for Dell. But according to Intel it pulled down its margins. The point is Intel is loving the high end of the market because it's higher margin and more profitable. I wonder what Clay Christensen would say to that. Now there's more to this story. Intel's CFO blame the supply constraints on Intel's revenue and profit pressures yet AMD's revenue and profits are booming. So RTSMCs. Only Intel can't seem to thrive when there's this massive chip shortage. Now let's get back to Pat's announcement. Intel is for sure, going forward investing $20 billion in two new US-based fabrication facilities. This chart shows Intel's investments in US R&D, US CapEx and the job growth that's created as a result, as well as R&D and CapEx investments in Ireland and Israel. Now we added the bar on the right hand side from a Wall Street journal article that compares TSMC CapEx in the dark green to that of Intel and the light green. You can see TSMC surpass the CapEx investment of Intel in 2015, and then Intel took the lead back again. And in 2017 was, hey it on in 2018. But last year TSMC took the lead, again. And appears to be widening that lead quite substantially. Leading us to our conclusion that this will not be enough. These moves by Intel will not be enough. They need to do more. And a big part of this announcement was partnerships and packaging. Okay. So here's where it gets interesting. Intel, as you may know was late to the party with SOC system on a chip. And it's going to use its packaging prowess to try and leap frog the competition. SOC bundles things like GPU, NPU, DSUs, accelerators caches on a single chip. So better use the real estate if you will. Now Intel wants to build system on package which will dis-aggregate memory from compute. Now remember today, memory is very poorly utilized. What Intel is going to do is to create a package with literally thousands of nodes comprising small processors, big processors, alternative processors, ARM processors, custom Silicon all sharing a pool of memory. This is a huge innovation and we'll come back to this in a moment. Now as part of the announcement, Intel trotted out some big name customers, prospects and even competitors that it wants to turn into prospects and customers. Amazon, Google, Satya Nadella gave a quick talk from Microsoft to Cisco. All those guys are designing their own chips as does Ericsson and look even Qualcomm is on the list, a competitor. Intel wants to earn the right to make chips for these firms. Now many on the list like Microsoft and Google they'd be happy to do so because they want more competition. And Qualcomm, well look if Intel can do a good job and be a strong second sourced, why not? Well, one reason is they compete aggressively with Intel but we don't like Intel so much but it's very possible. But the two most important partners on this slide are one IBM and two, the US government. Now many people were going to gloss over IBM in this announcement, but we think it's one of the most important pieces of the puzzle. Yes. IBM and semiconductors. IBM actually has some of the best semiconductor technology in the world. It's got great architecture and is two to three years ahead of Intel with POWER10. Yes, POWER. IBM is the world's leader in terms of dis-aggregating compute from memory with the ability to scale to thousands of nodes, sound familiar? IBM leads in power density, efficiency and it can put more stuff closer together. And it's looking now at a 20x increase in AI inference performance. We think Pat has been thinking about this for a while and he said, how can I leave leap frog system on chip. And we think he thought and said, I'll use our outstanding process manufacturing and I'll tap IBM as a partner for R&D and architectural chips to build the next generation of systems that are more flexible and performant than anything that's out there. Now look, this is super high end stuff. And guess who needs really high end massive supercomputing capabilities? Well, the US military. Pat said straight up, "We've talked to the government and we're honored to be competing for the government/military chips boundary." I mean, look Intel in my view was going to have to fall down into face not win this business. And by making the commitment to Foundry Services we think they will get a huge contract from the government, as large, perhaps as $10 billion or more to build a secure government Foundry and serve the military for decades to come. Now Pat was specifically asked in the Q&A section is this Foundry strategy that you're embarking on viable without the help of the US government? Kind of implying that it was a handout or a bailout. And Pat of course said all the right things. He said, "This is the right thing for Intel. Independent of the government, we haven't received any commitment or subsidies or anything like that from the US government." Okay, cool. But they have had conversations and I have no doubt, and Pat confirmed this, that those conversations were very, very positive that Intel should head in this direction. Well, we know what's happening here. The US government wants Intel to win. It needs Intel to win and its participation greatly increases the probability of success. But unfortunately, we still don't think it's enough for Intel to regain its number one position. Let's look at that in a little bit more detail. The headwinds for Intel are many. Look it can't just flick a switch and catch up on manufacturing leadership. It's going to take four years. And lots can change in that time. It tells market momentum as well as we pointed out earlier is headed in the wrong direction from a financial perspective. Moreover, where is the volume going to come from? It's going to take years for Intel to catch up for ARMS if it never can. And it's going to have to fight to win that business from its current competitors. Now I have no doubt. It will fight hard under Pat's excellent leadership. But the Foundry business is different. Consider this, Intel's annual CapEx expenditures, if you divide that by their yearly revenue it comes out to about 20% of revenue. TSMC spends 50% of its revenue each year on CapEx. This is a different animal, very service oriented. So look, we're not pounding the table saying Intel's worst days are over. We don't think they are. Now, there are some positives, I'm showing those in the right-hand side. Pat Gelsinger was born for this job. He proved that the other day, even though we already knew it. I have never seen him more excited and more clearheaded. And we agreed that the chip demand dynamic is going to have legs in this decade and beyond with Digital, Edge, AI and new use cases that are going to power that demand. And Intel is too strategic to fail. And the US government has huge incentives to make sure that it succeeds. But it's still not enough in our opinion because like the steel manufacturers Intel's real advantage today is increasingly in the high end high margin business. And without volume, China is going to win this battle. So we continue to believe that a new joint venture is going to emerge. Here's our prediction. We see a triumvirate emerging in a new joint venture that is led by Intel. It brings x86, that volume associated with that. It brings cash, manufacturing prowess, R&D. It brings global resources, so much more than we show in this chart. IBM as we laid out brings architecture, it's R&D, it's longstanding relationships. It's deal flow, it can funnel its business to the joint venture as can of course, parts of Intel. We see IBM getting a nice licensed deal from Intel and or the JV. And it has to get paid for its contribution and we think it'll also get a sweet deal and the manufacturing fees from this Intel Foundry. But it's still not enough to beat China. Intel needs volume. And that's where Samsung comes in. It has the volume with ARM, has the experience and a complete offering across products. We also think that South Korea is a more geographically appealing spot in the globe than Taiwan with its proximity to China. Not to mention that TSMC, it doesn't need Intel. It's already number one. Intel can get a better deal from number two, Samsung. And together these three we think, in this unique structure could give it a chance to become number one by the end of the decade or early in the 2030s. We think what's happening is our take, is that Intel is going to fight hard to win that government business, put itself in a stronger negotiating position and then cut a deal with some supplier. We think Samsung makes more sense than anybody else. Now finally, we want to leave you with some comments and some thoughts from the community. First, I want to thank David Foyer. His decade plus of work and knowledge of this industry along with this collaboration made this work possible. His fingerprints are all over this research in case you didn't notice. And next I want to share comments from two of my colleagues. The first is Serbjeet Johal. He sent this to me last night. He said, "We are not in our grandfather's compute era anymore. Compute is getting spread into every aspect of our economy and lives. The use of processors is getting more and more specialized and will intensify with the rise in edge computing, AI inference and new workloads." Yes, I totally agree with Sarbjeet. And that's the dynamic which Pat is betting and betting big. But the bottom line is summed up by my friend and former IDC mentor, Dave Moschella. He says, "This is all about China. History suggests that there are very few second acts, you know other than Microsoft and Apple. History also will say that the antitrust pressures that enabled AMD to thrive are the ones, the very ones that starved Intel's cash. Microsoft made the shift it's PC software cash cows proved impervious to competition. The irony is the same government that attacked Intel's monopoly now wants to be Intel's protector because of China. Perhaps it's a cautionary tale to those who want to break up big tech." Wow. What more can I add to that? Okay. That's it for now. Remember I publish each week on wikibon.com and siliconangle.com. These episodes are all available as podcasts. All you got to do is search for Braking Analysis podcasts and you can always connect with me on Twitter @dvellante or email me at david.vellante, siliconangle.com As always I appreciate the comments on LinkedIn and in clubhouse please follow me so that you're notified when we start a room and start riffing on these topics. And don't forget to check out etr.plus for all the survey data. This is Dave Vellante for theCUBE insights powered by ETR, be well, and we'll see you next time. (upbeat music)

>>Yeah. Okay. Now we're going to dig deeper into HP es moral and try to better understand how it's going to impact customers. And with me to do that are Robert Christensen is the vice president strategy in the office of the C, T. O. And Kumar Srikanth is the chief technology officer and head of software both, of course, with Hewlett Packard Enterprise. Gentlemen, welcome to the program. Thanks for coming on. >>Good seeing you. Thanks for having us. >>Always. Great. Great to see you guys. So, Esmeralda, kind of a interesting name. Catchy name. But tomorrow, what exactly is H P E s bureau? >>Yeah. It's indeed a catchy name. Our branding team done a fantastic job. I believe it's actually a derivation from Esmeralda. The Spanish for Emerald Berlin. Supposed to have some very mystical powers. Um, and they derived as moral from there, and we all actually, initially that we heard it was interesting. Um, so as well was our effort to take all the software, the platform tools that HB has and provide these modern operating platform to the customers and put it under one brand. It has a modern container platform. It has a persistent stories distribute the date of February. It has been foresight, as many of our customers similar, So it's the think of it as a container platform offering for modernization of the civilization of the customers. >>Yeah, it's an interesting to talk about platform, so it's not a lot of times people think product, but you're positioning it as a platform, so it has a broader implications. >>That's very true. So as the customers are thinking of this civilization, modernization containers and microservices, as you know there has become, has become the stable whole. So it's actually a container orchestration platform. It offers open source proven. It is as well as the persistence always bolted to >>so by the way, s moral, I think emerald in Spain, I think in the culture it also has immunity powers as well. So immunity >>from >>lock in and all those other terrible diseases. Maybe it helps us with covid to rob Robert. When you talk to customers, what problems do you probe for that that is immoral. Can can do a good job solving. >>Yeah, they That's a really great question because a lot of times they don't even know what it is that they're trying to solve for, other than just a very narrow use case. But the idea here is to give them a platform by which they can bridge both the public and private environment for what to do an application development specifically in the data side. So when they're looking to bring Container Ization, which originally got started on the public cloud and has moved its way, I should say, become popular in the public cloud and has moved its way on premises. Now Esmeralda really opens the door to three fundamental things. But how do I maintain an open architecture like you're referring to some low or oh, no lock in of my applications And there were two. How do I gain a data fabric or data consistency of accessing the data so I don't have to rewrite those applications when I do move them around and then, lastly, where everybody is heading down, the real value is in the AI ML initiatives that companies are are really bringing that value of their data and locking the data at where the data is being generated and stored. And so the is moral platform is those multiple pieces that I was talking about stacked together to deliver those solutions for the client. >>So come on, what's the How does it work? What's the sort of I p or the secret sauce behind it all? What makes HP different? >>Continuing our team of medical force around, uh, it's a moral platform for optimizing the data Indians who were close. I think I would say there are three unique characteristics of this platform. Number one is actually provides you both an ability to run stable and stateless were close under the same platform, and number two is as we were thinking about. Unlike analogues, covenant is open source. It actually produce you all open source government as well as an orchestration behind you. So you can actually you can provide this hybrid, um, thing that drivers was talking about. And then actually we built the work flows into it. For example, we're actually announced along with Esmeralda MLS, but on their customers can actually do the work flow management. Our own specifically did the work force. So the magic is if you want to see the secrets of is all the efforts that have been gone into some of the I p acquisitions that HBs the more years we should be. Blue Data bar in the nimble emphasize, all these pieces are coming together and providing a modern digitalization platform for the customers. >>So these pieces, they all have a little bit of a machine intelligence in them. Yeah, People used to think of a I as the sort of separate thing, having the same thing with containers, right? But now it's getting embedded in into the stack. What? What is the role of machine intelligence or machine learning in Edinburgh? >>I would take a step back and say, You know this very well. They're the customer's data amount of data that is being generated, and 95% or 98% of data is machine generated, and it has a serious amount of gravity, and it is sitting at the edge, and we were the only the only one that edge to the cloud data fabric that's built. So the number one is that we are bringing computer or a cloud to the data. They're taking the data to the cloud like if you go, it's a cloud like experience that provides the customer. Yeah, is not much value to us if we don't harness the data. So I said this in one of the blood. Of course, we have gone from collecting the data era to the finding insights into the data so that people have used all sorts of analysis that we are to find data is the new oil to the air and the data. And then now you're applications have to be modernized. And nobody wants to write an obligation in a non microservices fashion because you want to build the modernization. So if you bring these three things, I want to have a data. Gravity have lots of data. I had to build an area applications and I want to have an idea those three things I think we bring together to the customs. >>So, Robert, let's stay on customers from it. I mean, you know, I want to understand the business impact, the business case. I mean, why should all the you know, the cloud developers have all the fun? You mentioned that you're bridging the cloud and on Prem, uh, they talk about when you talk to customers and what they are seeing is the business impact. What's the real drivers for them. >>That's a great question because at the end of the day I think the reason survey that was that cost and performance is still the number one requirement for the real close. Second is agility, the speed of which they want to move. And so those two are the top of mind every time. But the thing we find in as moral, which is so impactful, is that nobody brings together the silicon, the hardware, the platform and all that stacked together work and combined, like as moral does with the platforms that we have and specifically, you know, when we start getting 90 92 93% utilization out of ai ml workloads on very expensive hardware, it really, really is a competitive advantage over a public cloud offering which does not offer those kind of services. And the cost models are so significantly different. So we do that by collapsing the stack. We take out as much intellectual property, give me, um, as much software pieces that are necessary. So we are closest to the silicon closest to the applications bring into the hardware itself, meaning that we can inter leave the applications, meaning that you can get to true multi tendency on a particular platform that allows you to deliver a cost optimized solution. So when you talk about the money side, absolutely. There's just nothing out there and then on the second side, which is agility. Um, one of the things that we know is today is that applications need to be built in pipelines. Right? This is something that has been established now for quite some time now. That's really making its way on premises. And what Kumar was talking about was, how do we modernize? How do we do that? Well, there's going to be something that you want to break into Microservices and containers. There's something you don't now the ones that they're going to do that they're gonna get that speed and motion etcetera out of the gate. And they can put that on premises, which is relatively new these days to the on premises world. So we think both will be the advantage. >>Okay, I want to unpack that a little bit. So the cost is clearly really 90 plus percent utilization. I mean, come on. You know, even even a pre virtualization. We know what it was like even with virtualization, you never really got that high. I mean, people would talk about it, but are you really able to sustain that in real world workloads? >>Yeah, I think when you I think when you when you make your exchangeable currency into small pieces, you can insert them into many areas. And we have one customer was running 18 containers on a single server and each of those containers, as you know, early days of data. You actually modernized what we consider we won containers of micro B. Um, so if you actually build these microservices and you have all anti affinity rules and you have rationing formulas all correctly, you can pack being part of these things extremely violent. We have seen this again. It's not a guarantee. It all depends on your application and your I mean, as an engineer, we want to always understand how this can be that sport. But it is a very modern utilization of the platform with the data and once you know where the data is, and then it becomes very easy to match those >>now. The other piece of the value proposition that I heard Robert is it's basically an integrated stack, so I don't have to cobble together a bunch of open source components. It's there. There's legal implications. There's obviously performance implications that I would imagine that resonates is particularly with the enterprise buyer, because they have the time to do all this integration. >>That's a very good point. So there is an interesting, uh, interesting question that enterprise they want to have an open source, so there is no lock in. But they also need help to implement and deploy and manage it because they don't have expertise. And we all know that Katie has actually brought that AP the past layer standardization. So what we have done is we've given the open source and you write to the covenant is happy, but at the same time orchestration, persistent stories, the data fabric, the ai algorithms, all of them are bolted into it. And on the top of that, it's available both as a licensed software and run on Prem. And the same software runs on the Green Lake so you can actually pay as you go and you don't we run it for them in in a collar or or in their own data center. >>Oh, good. I was one of my latter questions, so I can get this as a service paid by the drink. Essentially, I don't have to install a bunch of stuff on Prem and pay >>a perpetual license container at the service and the service in the last Discover. And now it's gone production. So both MLRS is available. You can run it on friends on the top of Admiral Container platform or you can run inside of the Green Bay. >>Robert, are there any specific use case patterns that you see emerging amongst customers? >>Yeah, absolutely. So there's a couple of them. So we have a really nice relationship that we see with any of the Splunk operators that were out there today. Right? So Splunk containerized their operator. That operator is the number one operator, for example, for Splunk, um, in the i t operation side or notifications as well as on the security operation side. So we found that that runs highly effective on top of his moral on top of our platforms that we just talked about what, uh, Kumar just talked about, but I want to also give a little bit of backgrounds to that same operator platform. The way that the Admiral platform has done is that we've been able to make highly active, active with a check availability at 95 nines for that same spark operator on premises on the kubernetes open source, which is, as far as I'm concerned. Very, very high end computer science work. You understand how difficult that is? Uh, that's number one. Number two, you'll see spark just a spark. Workloads as a whole. All right. Nobody handles spark workloads like we do. So we put a container around them, and we put them inside the pipeline of moving people through that basic, uh uh, ml ai pipeline of getting a model through its system through its train and then actually deployed to our MLS pipeline. This is a key fundamental for delivering value in the data space as well. And then, lastly, this is This is really important. When you think about the data fabric that we offer, um, the data fabric itself, it doesn't necessarily have to be bolted with the container platform to container at the actual data. Fabric itself can be deployed underneath a number of our for competitive platforms who don't handle data. Well, we know that we know that they don't handle it very well at all. And we get lots and lots of calls for people say, Hey, can you take your as Merrill data for every and solve my large scale, highly challenging data problems, we say yes. And then when you're ready for a real world full time but enterprise already, container platform would be happy to privilege. >>So you're saying if I'm inferring correctly, you're one of the values? Is your simplifying that whole data pipeline and the whole data science science project? Unintended, I guess. >>Okay, >>that's so so >>absolutely So where does the customer start? I mean, what what are the engagements like? Um, what's the starting point? >>It's being is probably one of the most trusted enterprise supplier for many, many years, and we have a phenomenal workforce of the both. The PowerPoint next is one of the leading world leading support organization. There are many places to start with. The right one is Obviously all these services are available on the green leg as we just start apart and they can start on a pay as you go basis. We have many customers that. Actually, some of the grandfather from the early days of pleaded and map are and they're already running, and they actually improvised on when, as they move into their next generation modernization, um, you can start with simple as metal container platform with persist with the story compared to this operation and can implement as as little as $10 and to start working. Um, and finally, there is a a big company like HP E. As an enterprise company defined next services. It's very easy for the customers to be able to get that support on the day to operation. >>Thank you for watching everybody's day volonte for the Cube. Keep it right there for more great content from Esmeralda. >>A mhm, okay.

from the cube studios in Palo Alto in Boston connecting with thought leaders all around the world this is a cube conversation on June 23rd the Wall Street Journal reported that Dell is exploring strategic options for its approximately 81% share in VMware both Dell and VMware stocks popped on the news we believe that Dell is floating this trial balloon to really gauge investor customer and partner sentiment and perhaps send a signal to the short sellers that you know what Michael Dell has other arrows in his quiver to unlock in case you want to squeeze me I'm gonna squeeze you back who knows hello everyone and welcome to this week's wiki Bond cube insights powered by ETR in this breaking analysis we'll unpack some of the complicated angles in the ongoing VMware saga and assess five scenarios that we think are possible as it pertains to this story as always we're going to bring in some ETR customer data to analyze what's happening with the spending picture let's take a look at what happened and just do a quick recap The Wall Street Journal story said that Dell was considering spinning off VMware or buying the remaining 19 percent of VMware stock that it doesn't own the Journal article cited unnamed sources and said that a spinoff would not likely happen until 7 September 2021 for tax reasons that would mark of course the 5 year anniversary of Dell acquiring EMC and would allow for a tax free transaction always a good thing what's going on here and what options does Dell really have what does it mean for Dell VMware customers and partners we're gonna try to answer those questions today so first of all why would Dell make such a move well I think there's tweet from your own name Marc he's a portfolio manager at one main capital it kind of sums it up he laid out this chart which shows Dells market cap prior to the stock pop you know it's closer to 38 billion today and the value of its VMware owner which is over 50 billion since the stock pop but let me cut to the chase investors value the core assets of Dell which accounts for around 80 billion dollars in revenue when you exclude vmware somewhere south of negative 10 billion dollars why it's because Dell is carrying more than 30 billion dollars of core debt when you exclude Dell Financial Services and it looks like a conglomerate owning the vast majority of VMware shares Michael Dell has something like a 97 percent voting control Cordell is a low margin low growth business and as some have complained that Michael uses VMware as his piggy bank and many investors just won't touch the stock so the stock generally Dell stock has underperformed I've often said even going back to the EMC days that owning the stock of VMware's owner is actually a cheap way to buy vmware but that's assuming that the value somehow gets unlocked at some point so Dell is perhaps signaling that it has some options and other levers to pull as I said you may be trying to give pause to the shorts now let's have a look at some of the ETR spending data and value and evaluate the respective positions of Dell and VMware in the market place this chart here uses the core ETR methodology that we like to talk about all the time for those not familiar we use the concept of net score net score is a simple metric it's like Net Promoter Score sort of the chart shows element the elements of Dells net score so each quarter ETR goes out and ask customers do you plan to adopt the vendor new that's the lime green at 4% spend more relative to last year more meaning more than 6% that's the forest green and you can see that's at 32% flat spend is the grey meaning plus or minus 5% and then decrease spending by 6 percent or greater that's the pink and that's just 11% for Dell or are you replacing the platform to see that that's the bright red there at 7% so net score is a measure of momentum and it's derived by adding the greens and subtracting the Reds and he can see Dell in the last ETR survey which was taken at the height of the pandemic has a net score of 18% now we we colored that soft red it's not terrible but it's not great either now of course this is across Dells entire portfolio and it excludes vmware so what about vmware so this next graphic that we're showing you it applies the exact same methodology to vmware and as you can see vmware has a much higher net score at 35% which of course shouldn't surprise anybody it's a higher growth company but 46% of vmware customers plan to spend more this year relative to last year and only 11% planned to spend less that's pretty strong now what if we combined dell and vmware and looked at them as a single entity hmm wouldn't that be interesting okay here you go so there were nine hundred and seventy five respondents in the last ETR survey when we matched the two companies together and you can see the combined net score is 27% with 42 percent of respondents planning to spend more this year than they did last year so you may be asking well is this any good how does this compare to dell and vmware competitors well I'm glad you asked so here we show that in this chart the net score comparisons so we take the combined dell and vmware at 27% Cisco as we often reported consistently shows pretty strong relative to the enterprise data center players and you can see HPE is a kind of a tepid 17 percent so it's got some work to do to live up to the promises of the HP HPE split we also we also show IBM red hat at 14% so there's some room for improvement there also and you can see IBM in the danger zone as we break that down and red hat much stronger but you know what it softened somewhat in the EGR survey since last year so we'd like to see better momentum from IBM and RedHat it's kind of unfortunate that kovat hit when it did his IBM was just kind of ramping up its RedHat go to market now just for comparison purposes for kicks we include Nutanix nifty annex is a much smaller company but it's one that's fairly mature and you can see at 52% its net scores much higher than the big whales now we've been reporting for months on high fliers like automation anywhere CrowdStrike octa rubric snowflake uipath these emerging companies have net scores you know north of 60% and even in the 70% range but of course they're growing from a much smaller base so you would expect that now let's put this into context with a two-dimensional view that we'd like to show now as you know in addition to net score that metric we like to use so-called market share market share is a measure of pervasiveness in the data set or essentially market share in the survey and it's a proxy for a real market share so what this chart here does it plots several companies with their net scores on the y-axis and market share on the x-axis and you can see that we combine Dell and VMware together and we plotted them in that red highlighted box just for comparison purposes so what does this tell you about the competitive landscape well first everyone would love to be AWS Microsoft - we didn't plot Microsoft because they're so bloody dominant they skew the chart somewhat but they would be way way out to the right on the x-axis because they have such a huge number of products and mentions in the data set so we left them out now you can see vmware and cisco are kind of right on top of each other which is sort of ironic as they're you know kind of increasingly overlapping with their offerings in the marketplace particularly nsx and you can see the other companies and for context we've added a few more competitors like theme and CommVault and you know they're in a pretty strong position as well as the combination of Dell and VMware so let's start there Steve Phil analyst Brad Reebok was quoted in the market watch publication is saying the following we have long believed Dell would ultimately buy in the approximately 19% our 12 and a half billion of VMware that it does not own in order to gain full control over VMware's substantial free cash flow which is about four billion dollars annually and we still expect this to be the ultimate outcome huh you know I don't know I'm not sure about this on the one hand you can see from the previous chart this would be a better outcome for Dell from a competitive standpoint what it did is it pulls Dell up and to the right yeah but perhaps not so much for VMware as it went down and to the left adèle would have to raise a bunch more cash to do this transaction and what take on even more debt you know maybe it could get Silverlake to finance the deal you know then essentially Dell would become the Oracle of infrastructure you know it certainly would make Dell even more strategic to CIOs would that be good for customers well on the one hand I guess it would bring better integration between Dell and VMware yeah but I wonder if that's the critical issue for customers yeah and nearly and I think it would stifle VMware's innovation engine and a little bit further and I wonder how Pat Yeltsin here would react I mean my guess is he would call it a day and what about Sanjay Putin who was the obvious next in line for the CEO job at VMware what he becomes the president of Dells software division and what about the rest of the team at VMware yes they're a Silicon Valley stalwart and that would slowly morph into austin-based Dell with the debt burden growing you know it's gonna mean more of VMware's cash would go to paying down the debt meaning less for R&D or even stock buybacks what you know I'm not a huge fan of and I'm not a huge fan of this scenario for sure the the technology park partner ecosystem would be ice cold on such a deal although you know you could argue there are already less than lukewarm but here I want to explore some other options so the next on the list is Dell could sell VMware to a private equity firm mmm or a strategic it could basically wipe out its debt and have some cash left over to sail into the sunset that would be a big pill for someone to swallow even though Michael Dell has 97 percent voting power I think there's fine print that says he has a responsibility to protect the interest of the minority shareholders so to get approval it would have to sell at a premium you know that could be as high as you know almost seventy billion dollars Microsoft has the cash but they don't need VMware and Amazon I guess could pull it off but that certainly is not likely even if Google who has the cash we're interested in buying VMware Google be the most likely candidate you know it would give Google Cloud instant access to the coveted enterprise but it's really hard to conceive I mean same for a PE company 65 to 70 billion you know they get their money out in 15 to 20 years so I I just I just don't see that as viable all right what's next how about this scenario of spinning off VMware that the Journal reported so in this transaction Dell shareholders would get a bunch of vmware stock now there may be some financial wizardry that tom sweet dell CFCF owned his band of financial geniuses could swing I can't even begin to speculate what that would be but but I've heard there's some magic that they could pull off to maybe pull some cash out of such a transaction and this would unlock the value of both Dell and VMware by removing the conglomerate and liquidity hangover for Dell and it were to definitely attract more sideline investors into VMware stock and Michael Dell would still own a boatload of VMware stock personally so there's an incentive there so this is interesting and certainly possible you know I think in a way it would be good for VMware customers VMware we get full autonomy and control over its destiny without Delvaux guarding its cash so it could freely innovate Dell would become probably less strategic for customers so I don't think that for Dell EMC buyers you know the technology ecosystem partners like HPE IBM Napa cetera would would would they would like it more but they were already kind of down the path of looking to optimize VMware alternatives so you know think about Cisco but you know I think for VMware customers okay I think for for daily MC customers not so much now what about the do-nothing scenario you know I think this is as possible as any outcome Dell keep chipping away at its debt using VMware as a strategic linchpin with customers sure they continue to pay the liquidity overhang tax and they'll frustrate some shareholders who we're going to remain on the sidelines but you know that's been the pattern anyway now what about delivering some of the VMware ownership so the more I think about it the more I like this scenario what if del sold 20% of its VMware stake and let's say raised ten twelve billion dollars in cash that it could use to really eat into its debt burden a move like this combined with its historical debt pay down could cut its death debt in half by say 2021 and get the company back to investment grade rating something that Tom sweet has aspired towards this one dropped hundreds of millions if not a billion dollars to the bottom line and it would allow Dell to continue to control VMware what I don't know I don't know if there are nuances to this scenario in other words does this dropping ownership from roughly eighty percent to about sixty percent trigger some loss of control or some reporting issue I'm sure it's buried somewhere in the public filings or acquisition Docs but this option to me makes some sense it doesn't really radically alter their relationships with customers or partners so it's kind of stable with VMware maintains its existing autonomy and even somewhat lessens Dale's perceived control over VMware in an attacks Dells debt burden yeah it's still a bit of a halfway house but I think it's a more attractive and as I said stable option in my view okay let's talk about what to look for next you know it looks like the stock market is coming to the reality that we are actually in a recession although it appears that Nasdaq is trying to ignore this or maybe the the markets a little bit off because they're afraid Joe Biden is gonna win the election he's not gonna be good for the for the economy we'll see we'll see what the economic shutdown means for tech companies in this earnings season etrs next survey is in the field and they're gonna have fresh data on the impact of kovat going into the dog days of summer here's what I think let me give you my preview and you'll see in a few weeks you know how accurate is I believe that tech spending is going to be soft broadly I think it's gonna especially be the case for legacy on-prem providers and expect their traditional businesses to to deteriorate somewhat I think there's gonna be bright spots in text protect for sure the ones we've reported on cloud yes absolutely automation you know I'm really looking closely at the battle between the two top our PA vendors automation anywhere in uipath I think there's a really interesting story brewing there and the names that we've been pounding like snowflake the security guys like CrowdStrike and octa and Z scalar I think they're gonna continue to do very well with this work from home pivot we also expect Microsoft to continue to show staying power but because of their size you know they're exposed to soft demand pockets but I think that continue to be very very strong and threatening to a lot of segments in the market now for Dell I think the data center businesses continue to be a tough one despite some of the new product cycles especially in storage but I think dal is gonna continue to benefit from the work from home pivot as I believe there's still some unmet demand and laptops we're gonna see that I believe show up in Dells income statement in the form of their their client revenue I'd love to know what you think you could tweet me at Devante or you can always email me at david dot Volante at Silicon angle com please comment on my LinkedIn post always appreciate I post weekly on silicon angle calm and on wiki bond calm so check out those properties and of course go to e TR dot plus for all the survey action as I say e TR is in the field with the current survey they got fresh Cova data so we're excited the report on that in the coming weeks remember these episodes are all available as podcast wherever you listen this is Dave Volante for the cube insights powered by ETR thanks for watching everyone we'll see you next time [Music]

>> Narrator: Live, from Washington DC, it's the CUBE, covering .NEXT Conference. Brought to you by Nutanix. >> Welcome back to Nutanix NEXTConf everybody. #NEXTConf, this is theCUBE, the leader in live tech coverage. We go out to the events, we extract the signal from the noise. My name is Dave Vellante, and I'm here with Stu Miniman. Stephen Hadley is here. He's the former US National Security Advisor, and currently with RHG, who is an advisor to Nutanix. He's an expert on national security and foreign policy, and public policy. Stephen, thanks very much for coming on theCUBE. >> Nice to be here. >> So very important topic. One that you just can't talk about enough. So lets start. We're here at this sort of infrastructure show. We're up-leveling it now to this very important topic of security. There's so many things that are going on. We interviewed Pat Gelsinger on theCUBE five or six years ago and asked him, is security a do-over? He had a one word answer. Yes. So, where are we at? What's the state of cyber today? >> Well, let's talk in a couple respects. You know, one of the things that's been interesting to follow your industry, and I'm not a technical person. But, interesting following your industry, a lot of what was done, social media and all the rest, started to be fun. It was almost a toy. And what has happened, is you now have become, this industry and the services it provide are a international, global, and national resource. And is at the center of how we do business today. And it's been interesting to watch the industry deal with that challenge. It started out, what do you do about child pornography that gets onto the various sites and the like? Then it got to be, what do you do about terrorism? Now it's, what do you do about false news? And it's been interesting to see the industry, and I think very effectively, start to respond to what are the responsibilities they have to their users, in these various troublesome areas. And what are the solutions, technologically and process-wise. And I think the industry is taking the lead, and I would encourage them to do so, because I think the industry needs to define the solutions. If you wait to Washington to define the solutions, we'll get it wrong, as we usually do in Washington. >> Well, so let's come back and talk about that. But, I like to think of three categories of cyber threats. You've got the hackers. Like you said, maybe it's child porn or something else like that. You've got criminals, organized crime. And then you've got state-sponsored. Where do you feel the industry, that you've just sort of said, the industry really has to lead. Where do you think the industry should put its focus? Should they think about the attackers? Should they think more about the defense? Is that a right way to look at it? Those sort of three categories of threats? >> I think those are three categories. They are different kinds of threats. I think the industry is going to have to deal with all of them. I think the principal focus is going to be on defense. There has been a discussion in the literature, should companies have the ability to go on offense? And to respond to cyber attacks, by trying to reach out and hurt the attacker. That's a tricky question. And I guess, as a national security type, my instinct is, the industry needs to lead on defense. The government needs to think about offensive responses. I think particularly since one of the problems you've got in this business is the attribution problem. Someone marches into your country, you know who's doing it. If you get a cyber attack, it's not clear who the enemy is. And who the attack is coming from. And it makes the issue of response very difficult. Secondly, the problem of collateral damage. As we saw, beginning with Stuxnet, and in these latest attacks. You try to hit somebody over here offensively with cyber, and turns out your hitting users in 150 countries. So I think the industry's responsibility is to defend and to try to prevent their systems being used by various nefarious characters. The issue of how to respond to cyber attacks, I think is much more a state function. A law enforcement function, in terms of ordinary criminals and the like. A national security function, in terms of nation states. >> Well Robert Gates in theCUBE last April said that even governments have to be very careful about using cyber as an offensive weapon. You mention Stuxnet, and we saw what happened. But there are no standards with cyber war. With conventional warfare there's the Geneva Convention, there's standards that we can apply. With cyber it's the Wild West. So, what is industry's role in terms of creating those standards of cyber attacks? >> I think industry can inform it. I think it's going to be difficult for industry to take the lead. And I think one of the, my response would be, one of the problems is, cyber attacks, the attackers pay no penalty with cyber attacks. It's hard to find. It's hard to prove. And there's no responses. And, there's a whole question of what is the right response? So for example, some years ago, over eight 10 years ago, Russia pretty clearly took down the Estonian government, which was a real E government. Now NATO is, Estonia is in NATO. NATO, one of the pillars of NATO is an attack on one, is an attack on all. Was that an attack? Huge debate within NATO. Was it an attack, was not an attack? Nobody died. Traditional measure of where you've been attacked. On the other hand, a government was almost paralyzed. What's the right response? Do you have to respond only in cyberspace? Would you think of responding conventionally, through conventional military power to a cyber attack? None of that has been worked out. And, as a consequence, nobody pays any price for cyber attacks. My own view particularly with respect to state-sponsored cyber attacks, is until the country pays a disproportionate attack in cyberspace, for a cyber attack, you won't get them to stop. But as you just talked about rightly, it's very hard to respond in cyberspace, because of the unintended consequences and the cyber collateral damage, if you will. My hope, the way out of this, is, as you've seen in these last attacks over the last week or so, which were targeted, I think the most recent one was targeted on Ukraine, and ended up affecting 150 countries. I would hope that some of these at some point are going to bring the international community to it's senses. And people are going to basically say look, we're all vulnerable. We're all at risk. The United States is more dependent probably than other countries, but China isn't too far behind. And for the United States and China to start leading an international conversation about developing the rules of the road. I think that would be good. I think though there needs to be a panel from industry, that supports that effort. Or my worry is the governments will get it wrong, and will impair the growth of the industry, which is bringing so much benefit to the global community. >> Really interesting point. A couple of years ago, we interviewed the President of ICANN. The organization that >> Stephen: Yeah, I know him. >> oversees the entire internet >> Stephen: Good guy. >> Stu: Fadi, and he was really concerned that companies like China, and Germany were going to say, we're going to have our own internet. We're just going to wall things off. Kind of goes against what you're saying, is we need to work together. We see, dissonance between private corporations, and governments now. How do we get globally working on technology, working together? Rather than fragmenting more. >> And you make a very good point. It's working together on the basis of our principals. Look, our view is that a global internet, free access for everyone is a powerful political statement, and can be empowering of individuals. So it is a small d, democratic institution. And it is an enormous economic power. It would be a tragedy if individual countries start to Balkanize the internet. And start to make them national systems. Because you know the countries that will do it, are countries that are authoritarian, and will convert a device that actually empowers individuals to be a device by which the state controls individuals. Secondly, it will risk cutting them off from the global community. Which will have economic consequences, much less social consequences. So, I think it is important for us to try to take the lead and start that conversation, and to do it while we're still talking about a global internet, and really haven't lost that. So this conversation needs to start sooner rather than later. >> You're the Chairman of the United States Institute of Peace. I have to believe that there is some parallels between the work you're doing there, and what we were just discussing. Trying to get cooperation across communities. >> There is, in this sense. One of the things that USIP has found is, and when I was in government I always used to think about what governments can do to resolve conflicts, end wars and preserve peace. And that's sort of top-down government policy. What US Institute of Peace is doing, is bottom-up. Facilitating groups, civil society, and peace-builders and peace makers, in war-torn communities to begin to resolve the ethnic conflicts, the tribal conflicts, the religious conflicts that are really the kindling, and the fuel for conflict. And through an affiliated organization of the USIP called Peace Tech Lab, technology people are coming together with civil society people and saying, what are the tools you need that we can put on an app, and use on an internet platform that will allow you to do your bottom-up peace building work? And it's very powerful. So for example, election violence. Always a big problem. There are civil society groups using technology that we're able to monitor through social media the first signs of electoral violence, and bombard them with text messages and the like, to try to bring down the temperature. So, what we're seeing at USIP is, there is a bottom-up component of peace building that can be technologically enabled, to allow people to try to maintain peace in their communities. It is the new frontier in some sense, for the work of the US Institute of Peace. >> So, with Stuxnet we saw that malware had the potential to kill people. Maybe in and of itself, that malware didn't kill people, although people died in that whole dynamic, with two nuclear engineers in Iran. My question is, and Stuxnet is 15 year old technology. >> Yeah, I don't think it's Stuxnet was responsible for any of technicians. >> Dave: No, right, so let's clarify that. >> There was a separate. >> And it was associated with that whole initiative, and. >> There was an effort to set back the Iran nuclear program. >> Yes, right, but it wasn't the malware itself. But the malware was demonstrated to do damage, and it could theoretically, and probably in practice, kill people. And it's, as I say, 15 year old technology, and just scratching the surface. So, god knows where we are today. You may know, I don't. But you've sort of put forth this notion that countries, states need to come together, and sort of address this problem. My question is that, I'm inferring that the US has a lead. And as the leader, with the best weapon, what's the motivation for the United States and other countries, who are the "haves", to work with the "have-nots", and actually create these standards? Is it because we have more to lose? I wonder if you could comment. >> I think it's vulnerability. I mean look, we're more dependent on the internet. We're more dependent on cyber systems. Look, to your point, if you bring down and get into the control systems that allow you to shut off the water filtration plants, and bring down the electric grid, a lot of people are going to die. They're going to start in hospitals, and it's going to get worse. So, what is the task? The first task is, and we've known about this problem, of the vulnerability for critical interest structure since the 1990s, that the first studies were written. Government has been slow. Quite frankly, industry has been slow. And it's, I think that train is finally moving. Some sectors are farther ahead. The financial sector is much better and further along at hardening their infrastructure against cyber penetration. But we still are very vulnerable through control systems, in our water system, electric grid, all the rest. And of course, the internet of things, has only multiplied the portals through which people can get into these systems. So there's a huge task of defense. And hardening that needs to go on. And that's a responsibility of industry, and government working together. It can only be done if industry and government work together. That's the process we need within the country. Secondly then, can the US lead in a process to try to develop rules of the road that provide another layer of protection? But it's got to start with hardening our infrastructure here at home. >> I got to ask you about fake news. Fake news in Russia. Is Russia an adversary? Should they be perceived, from a diplomacy standpoint, should we be antagonistic? Or should we try to be more friendly? As it relates to what's been going on with fake news. I wonder if you could tie those together and give us your thoughts. >> Well look, one of the things that's different about Russia today, is what we've seen in the election. This effort through hacking, through disclosing emails, through probing our electoral infrastructure, through a variety of things the Russians are doing. They intervened in our election process, in a bigger way than we've ever seen before, and they're doing the same thing in Europe. That is a new problem. We need to get to the bottom of it, to know what happened. People do it from the standpoint of retaliating against Russia. I think the bigger problem is we need to harden our electoral infrastructure. Our electoral infrastructure turns out to be critical infrastructure that we have to harden, just like our electric grid, and our water supply systems. And you know, fool me once, shame on you. Fool me twice, shame on me. If we don't harden our electoral infrastructure so this cannot happen again, next time it happens, it's our fault. >> So kind of a cyber Star Wars. Is it, we don't know if it's technically feasible. That's not your area of expertise, that's industry's problem to figure out. >> Stephen: Yes sir. >> Stephen, you are a fantastic guest. Thanks so much for coming on theCUBE, really appreciate your insights. >> Stephen: Delighted to be here, thanks very much. >> Alright, keep it right there everybody. We'll be back with our next guest, right after this short break. This is theCUBE, we're live from Nutanix .NEXT, NEXTConf Be right back.

>> Announcer: Live from Las Vegas, it's theCUBE covering HPE Discover 2017, brought to you by Hewlett Packard Enterprise. >> Okay, welcome back everyone. We're live here in Las Vegas for SiliconANGLE's CUBE coverage of HPE Discover 2017. This is our seventh year of covering HPE Discover Now. HPE Discover in its second year. I'm John Furrier, my co-host Dave Vellante. We've got two great guests, two doctors, PhD's in the house here. So Eng Lim Goh, VP and SGI CTO, PhD, and Tuomas Sandholm, Professor at Carnegie Mellon University of Computer Science and also runs the marketplace lab over there, welcome to theCube guys, doctors. >> Thank you. >> Thank you. >> So the patient is on the table, it's called machine learning, AI, cloud computing. We're living in a really amazing place. I call it open bar and open source. There's so many new things being contributed to open source, so much new hardware coming on with HPE that there's a lot of innovation happening. So want to get your thoughts first on how you guys are looking at this big trend where all this new software is coming in and these new capabilities, what's the vibe, how do you look at this. You must be, Carnegie Mellon, oh this is an amazing time, thoughts. >> Yeah, it is an amazing time and I'm seeing it both on the academic side and the startup side that you know, you don't have to invest into your own custom hardware. We are using HPE with the Pittsburgh Supercomputing Center in academia, using cloud in the startups. So it really makes entry both for academic research and startups easier, and also the high end on the academic research, you don't have to worry about maintaining and staying up to speed with all of the latest hardware and networking and all that. You know it kind of. >> Focus on your research. >> Focus on the research, focus on the algorithms, focus on the AI, and the rest is taken care of. >> John: Eng talk about the supercomputer world that's now there, if you look at the abundant computer intelligent edge we're seeing genome sequencing done in minutes, the prices are dropping. I mean high performance computing used to be this magical, special thing, that you had to get a lot of money to pay for or access to. Democratization is pretty amazing can I just hear your thoughts on what you see happening. >> Yes, Yes democratization in the traditional HPC approach the goal is to prediction and forecasts. Whether the engine will stay productive, or financial forecasts, whether you should buy or sell or hold, let's use the weather as an example. In traditional HPC for the last 30 years what we do to predict tomorrows weather, what we do first is to write all the equations that models the weather. Measure today's weather and feed that in and then we apply supercomputing power in the hopes that it will predict tomorrows weather faster than tomorrow is coming. So that has been the traditional approach, but things have changed. Two big things changed in the last few years. We got these scientists that think perhaps there is a new way of doing it. Instead of calculating your prediction can you not use data intensive method to do an educated guess at your prediction and this is what you do. Instead of feeding today's weather information into the machine learning system they feed 30 years everyday, 10 thousand days. Everyday they feed the data in, the machine learning system guess at whether it will rain tomorrow. If it gets it wrong, it's okay, it just goes back to the weights that control the inputs and adjust them. Then you take the next day and feed it in again after 10 thousand tries, what started out as a wild guess becomes an educated guess, and this is how the new way of doing data intensive computing is starting to emerge using machine learning. >> Democratization is a theme I threw that out because I think it truly is happening. But let's get specific now, I mean a lot of science has been, well is climate change real, I mean this is something that is in the news. We see that in today's news cycle around climate change things of that as you mentioned weather. So there's other things, there's other financial models there's other in healthcare, in disease and there's new ways to get at things that were kind of hocus pocus maybe some science, some modeling, forecasting. What are you seeing that's right low hanging fruit right now that's going to impact lives? What key things will HPC impact besides weather? Is healthcare there, where is everyone getting excited? >> I think health and safety immediately right. Health and safety, you mentioned gene sequencing, drug designs, and you also mentioned in gene sequencing and drug design there is also safety in designing of automobiles and aircrafts. These methods have been traditionally using simulation, but more and more now they are thinking while these engines for example, are flying can you collect more data so you can predict when this engine will fail. And also predict say, when will the aircraft lands what sort of maintenance you should be applying on the engine without having to spend some time on the ground, which is unproductive time, that time on the ground diagnosing the problems. You start to see application of data intensive methods increased in order to improve safety and health. >> I think that's good and I agree with that. You could also kind of look at some of the technology perspective as to what kind of AI is going to be next and if you look back over the last five to seven years, deep learning has become a very hot part of machine learning and machine learning is part of AI. So that's really lifted that up. But what's next there is not just classification or prediction, but decision making on top of that. So we'll see AI move up the chain to actual decision making on top of just the basic machine learning. So optimization, things like that. Another category is what we call strategic reasoning. Traditionally in games like chess, or checkers and now Go, people have fallen to AI and now we did this in January in poker as well, after 14 years of research. So now we can actually take real strategic reasoning under imperfect information settings and apply it to various settings like business strategy optimization, automated negotiation, certain areas of finance, cyber security, and so forth. >> Go ahead. >> I'd like to interject, so we are very on it and impressed right. If we look back years ago IBM beat the worlds top chess player right. And that was an expert system and more recently Google Alpha Go beat even a more complex game, Go, and beat humans in that. But what the Professor has done recently is develop an even more complex game in a sense that it is incomplete information, it is poker. You don't know the other party's cards, unlike in the board game you would know right. This is very much real life in business negotiation in auctions, you don't quite know what the other party' thinking. So I believe now you are looking at ways I hope right, that poker playing AI software that can handle incomplete information, not knowing the other parties but still able to play expertly and apply that in business. >> I want to double down on that, I know Dave's got a question but I want to just follow this thread through. So the AI, in this case augmented intelligence, not so much artificial, because you're augmenting without the perfect information. It's interesting because one of the debates in the big data world has been, well the streaming of all this data is so high-velocity and so high-volume that we don't know what we're missing. Everyone's been trying to get at the perfect information in the streaming of the data. And this is where the machine learning if I get your point here, can do this meta reasoning or this reasoning on top of it to try to use that and say, hey let's not try to solve the worlds problems and boil the ocean over and understand it all, let's use that as a variable for AI. Did I get that right? >> Kind of, kind of I would say, in that it's not just a technical barrier to getting the big data, it's also kind of a strategic barrier. Companies, even if I could tell you all of my strategic information, I wouldn't want to. So you have to worry not just about not having all the information but are there other guys explicitly hiding information, misrepresenting and vice versa, you doing strategic action as well. Unlike in games like Go or chess, where it's perfect information, you need totally different kinds of algorithms to deal with these imperfect information games, like negotiation or strategic pricing where you have to think about the opponents responses. >> It's your hairy window. >> In advance. >> John: Knowing what you don't know. >> To your point about huge amounts of data we are talking about looking for a needle in a haystack. But when the data gets so big and the needles get so many you end up with a haystack of needles. So you need some augmentation to help you to deal with it. Because the humans would be inundated with the needles themselves. >> So is HPE sort of enabling AI or is AI driving HPC. >> I think it's both. >> Both, yeah. >> Eng: Yeah, that's right, both together. In fact AI is driving HPC because it is a new way of using that supercomputing power. Not just doing computer intensive calculation, but also doing it data intensive AI, machine learning. Then we are also driving AI because our customers are now asking the same questions, how do I transition from a computer intensive approach to a data intensive one also. This is where we come in. >> What are your thoughts on how this affects society, individuals, particularly students coming in. You mentioned Gary Kasparov losing to the IBM supercomputer. But he didn't stop there, he said I'm going to beat the supercomputer, and he got supercomputers and humans together and now holds a contest every year. So everybody talks about the impact of machines replacing humans and that's always happened. But what do you guys see, where's the future of work, of creativity for young people and the future of the economy. What does this all mean? >> You want to go first or second? >> You go ahead first. (Eng and Tuomas laughing) >> They love the fighting. >> This is a fun topic, yeah. There's a lot of worry about AI of course. But I think of AI as a tool, much like a hammer or a saw So It's going to make human lives better and it's already making human lives better. A lot of people don't even understand all the things that already have AI that are helping them out. There's this worry that there's going to be a super species that's AI that's going to take over humans. I don't think so, I don't think there's any demand for a super species of AI. Like a hammer and a saw, a hammer and a saw is better than a hammersaw, so I actually think of AI as better being separate tools for separate applications and that is very important for mankind and also nations and the world in the future. One example is our work on kidney exchange. We run the nationwide kidney exchange for the United Network for Organ Sharing, which saves hundreds of lives. This is an example not only that saves lives and makes better decisions than humans can. >> In terms of kidney candidates, timing, is all of that. >> That's a long story, but basically, when you have willing but incompatible live donors, incompatible with the patient they can swap their donors. Pair A gives to pair B gives to pair C gives to pair A for example. And we also co-invented this idea of chains where an altruist donor creates a while chain through our network and then the question of which combination of cycles and chains is the best solution. >> John: And no manual involvement, your machines take over the heavy lifting? >> It's hard because when the number of possible solutions is bigger than the number of atoms in the universe. So you have to have optimization AI actually make the decisions. So now our AI makes twice a week, these decisions for the country or 66% of the transplant centers in the country, twice a week. >> Dr. Goh would you would you add anything to the societal impact of AI? >> Yes, absolutely on the cross point on the saw and hammer. That's why these AI systems today are very specific. That's why some call them artificial specific intelligence, not general intelligence. Now whether a hundred years from now you take a hundred of these specific intelligence and combine them, whether you get an emergent property of general intelligence, that's something else. But for now, what they do is to help the analyst, the human, the decision maker and more and more you will see that as you train these models it's hard to make a lot of correct decisions. But ultimately there's a difference between a correct decision and, I believe, a right decision. Therefore, there always needs to be a human supervisor there to ultimately make the right decision. Of course, he will listen to the machine learning algorithm suggesting the correct answer, but ultimately the human values have to be applied to decide whether society accepts this decision. >> All models are wrong, some are useful. >> So on this thing there's a two benefits of AI. One is a this saves time, saves effort, which is a labor savings, automation. The other is better decision making. We're seeing the better decision making now become more of an important part instead of just labor savings or what have you. We're seeing that in the kidney exchange and now with strategic reasoning, now for the first time we can do better strategic reasoning than the best humans in imperfect information settings. Now it becomes almost a competitive need. You have to have, what I call, strategic augmentation as a business to be competitive. >> I want to get your final thoughts before we end the segment, this is more of a sharing component. A lot of young folks are coming in to computer science and or related sciences and they don't need to be a computer science major per se, but they have all the benefits of this goodness we're talking about here. Your advice, if both of you could share you opinion and thoughts in reaction to the trend where, the question we get all the time is what should young people be thinking about if they're going to be modeling and simulating a lot of new data scientists are coming in some are more practitioner oriented, some are more hard core. As this evolution of simulations and modeling that we're talking about have scale here changes, what should they know, what should be the best practice be for learning, applying, thoughts. >> For me you know the key thing is be comfortable about using tools. And for that I think the young chaps of the world as they come out of school they are very comfortable with that. So I think I'm actually less worried. It will be a new set of tools these intelligent tools, leverage them. If you look at the entire world as a single system what we need to do is to move our leveraging of tools up to a level where we become an even more productive society rather than worrying, of course we must be worried and then adapt to it, about jobs going to AI. Rather we should move ourselves up to leverage AI to be an even more productive world and then hopefully they will distribute that wealth to the entire human race, becomes more comfortable given the AI. >> Tuomas your thoughts? >> I think that people should be ready to actually for the unknown so you've got to be flexible in your education get the basics right because those basics don't change. You know, math, science, get that stuff solid and then be ready to, instead of thinking about I'm going to be this in my career, you should think about I'm going to be this first and then maybe something else I don't know even. >> John: Don't memorize the test you don't know you're going to take yet, be more adaptive. >> Yes, creativity is very important and adaptability and people should start thinking about that at a young age. >> Doctor thank you so much for sharing your input. What a great world we live in right now. A lot of opportunities a lot of challenges that are opportunities to solve with high performance computing, AI and whatnot. Thanks so much for sharing. This is theCUBE bringing you all the best coverage from HPE Discover. I'm John Furrier with Dave Vellante, we'll be back with more live coverage after this short break. Three days of wall to wall live coverage. We'll be right back. >> Thanks for having us.

>>Hi everyone, welcome to this conversation. Lisa Martin here with Kim King, the SVP of Strategic Partners and Alliances at Hitachi. Kim, it's great to have you on the program. Thank you so much for joining me today. >>Thanks Lisa. It's great to be here. >>Let's talk about, so as we know, we talk about cloud all the time, the landscape, the cloud infrastructure landscape increasingly getting more and more complex. What are some of the biggest challenges and pain points that you're hearing from customers today? >>Yeah, so lot. There are lots, but I would say the, the few that we hear consistently, our cost, the complexity, right? Really the complexity of where do they go, how do they do it, and then availability. They have a lot of available options, but again, going back to complexity and cost, where do they think that they should move and how, how do they make that a successful move to the cloud? >>So talk to me, Hitachi vent has a great partner ecosystem. Where do partners play a role in helping customers to address some of the challenges with respect to the cloud landscape? >>Yeah, so part, our partners are really leading the way in the area of cloud in terms of helping customers understand the complexity is of the cloud. As we talked about, they're truly the trusted advisor. So when they look at a customer's complete infrastructure, what are the workloads, what are the CRI critical applications that they work with? What's the unique architecture that they have to drive with that customer for successful outcome and help them architect that? And so partners are truly leading the way across the board, understanding the complexities of each individual customer and then helping them make the right decisions with and for them. And then bringing us along as part of that, >>Talk to me a little bit about the partner landscape, the partner ecosystem at Hitachi. How does this fit into the overall sheet for the company? >>So we really look at our ecosystem as an extension of our sales organization and and really extension across the board, I would say our goal is to marry the right customer with the right partner and help them achieve their goals, ensure that they keep costs in check, that they ensure they don't have any security concerns, and that they have availability for the solutions and applications that they're trying to move to the cloud, which is most important. So we really, we really look at our ecosystem as a specialty ecosystem that adds high value for the right customers. >>So Kim, talk to me about how partners fit into Hitachi van's overall strategy. >>So I think our biggest differentiators with partners is that they're not just another number. Our partner organization is that valued extension of our overall sales pre-sales services organization. And we treat them like an extension of our organization. It's funny because I was just on a call with an analyst earlier this week and they said that AWS has increased their number of partners to 150,000 partners from, it was just under a hundred thousand. And I'm really not sure how you provide quality engagement to partners, right? And is how is that really a sustainable strategy? So for us, we look at trusted engagement across the ecosystem as a def differentiation. Really our goal is to make their life simple and profitable and really become their primary trusted partner when we go to market with them. And we see that paying dividends with our partners as they engage with us and as they expand and grow across the segments and then grow globally with us as well. >>And that's key, right? That synergistic approach when you're in customer conversations, what do you articulate as the key competitive differentiators where it relates to your partners? >>So really the, that they're the trusted advisor for that partner, right? That they understand our solutions better than any solution out there. And because we are not trying to be all things to our customers and our partners, that we being bring best breaths of breed, best of breed solutions to our customers through our partner community, they can truly provide that end user experience and the successful outcome that's needed without, you know, sort of all kinds of, you know, crazy cha challenges, right? When you look at it, they really wanna make sure that they're driving that co-developed solution and the successful outcome for that customer. >>So then how do you feel that Hitachi Ventura helps partners really to grow and expand their own business? >>Wow, so that's, there's tons of ways, but we've, we've created a very simplified, what we call digital selling platform. And in that digital selling platform, we've allowed our partners to choose their own price and pre-approve their pricing and their promotions. They've actually, we've expanded the way we go to market with our partners from a sort of a technical capabilities. We give them online what we call Hitachi online labs that allow them to really leverage all of the solutions and demo systems out there today. And they have complete access to any one of our resources, product management. And so we really have, like I said, we actually provide our partners with better tools and resources sometimes than we do our own sales and pre-sales organization. So we, we look at them as, because they have so many other solutions out there that we have to be one step ahead of everybody else to give them that solution capability and the expertise that they need for their customers. >>So if you dig in, where is it that hit Tashi van is helping partners succeed with your portfolio? >>Wow. So I think just across the board, I think we're really driving that profitable, trusted, and simplified engagement with our partner community because it's a value based and ease of doing business. I say that we allow them to scale and drive that sort of double digit growth through all of the solutions and and offerings that we have today. And because we've taken the approach of a very complex technical sort of infrastructure from a high end perspective and scaled it all the way through to our midsize enterprise, that allows them to really enter any customer at any vertical and provide them a really quality solution with that 100% data availability guarantee that we provide all of our customers. >>So then if we look at the overall sales cycle and the engagements, where is it that you're helping cus your partners rather succeed with the portfolio? >>Say that again? Sorry, my brain broke. No, >>No worries. So if we look at the overall sales cycle, where is it specifically where you're helping customers to succeed with the portfolio? >>So from the sales cycle, I think because we have the, a solution that is simple, easy, and really scaled for the type of customer that we have out there, it allows them to basically right size their infrastructure based on the application, the workload, the quality or the need that application may have and ensure that we provide them with that best solution. >>So then from a partner's perspective, how is it that Hitachi Valar is helping them to actually close deals faster? >>So lots of great ways I think between our pre-sales organization that's on call and available a hundred percent of the time. I think that we've seen, again, the trusted engagement with them from a pricing and packaging perspective. You know, we, you know, two years ago it would take them two to three weeks to get a pre-approved quote where today they pre-approved their own quotes in less than an hour and can have that in the hands of a customer. So we've seen that the ability for our partners to create and close orders in very short periods of time and actually get to the customers needs very quickly, >>So dramatically faster. Yes. Talk about overall, so the partner relationship's quite strong, very synergistic that that Hitachi Van Tara has with its customers. Let's kind of step back out and look at the cloud infrastructure. How do you see it evolving the market evolving overall in say the next six months, 12 months? >>Yeah, so we see it significantly, we've been doing a lot of studies around this specifically. So we have a couple of different teams. We have our sort of our standard partner team that's out there and now we have a specialty cloud service provider team that really focuses on partners that are building and their own infrastructure or leveraging the infrastructure of a large hyperscaler or another GSI and selling that out. And then what we found is when we dig down deeper into our standard sort of partner reseller or value added reseller market, what we're seeing is that they are want to have the capability to resell the solution, but they don't necessarily wanna have to own and manage the infrastructure themselves. So we're helping both of them through that transition. We see that it's gonna, so it's funny cuz you're seeing a combination of many customers move to really the hyperscale or public cloud and many of them want to repatriate their infrastructure back because they see costs and they see challenges around all of that. And so our partners are helping them understand, again, what is the best solution for them as opposed to let's just throw everything in the public cloud and hope that it works. We're we're really helping them make the right choices and decisions and we're putting the right partners together to make that happen. >>And how is that feedback, that data helping you to really grow and expand the partner program as a whole? >>Yeah, so it's been fantastic. We have a whole methodology that we, we created, which is called PDM plan, develop monetize with partners. And so we went specifically to market with cloud service providers that'll, and we really tested this out with them. We didn't just take a solution and say, here, go sell it, good luck and have, you know, have a nice day. Many vendors are doing that to their partners and the partners are struggling to monetize those solutions. So we spend a lot of time up front planning with them. What is not only the storage infrastructure but your potentially your data resiliency and, and everything else that you're looking at, your security solutions. How do we package those all together? How do we help you monetize them? And then who do you target from a customer perspective so that they've built up a pipeline of opportunities that they can go and work with us on and we really sit side by side with them in a co-development environment. >>In terms of that side by side relationship, how does the partner ecosystem play a role in Hitachi Ventura's as a service business? >>So our primary go to market with our, as a service business is with and through partners. So our goal is to drive all, almost all of our as a service. Unless it's super highly complex and something that a partner cannot support, we will make sure that they really, we leverage that with them, with all of our partners. >>So strong partner relationships, very strong partner ecosystem. What would you say, Kim, are the priorities for the partner ecosystem going forward? The next say year? >>Yeah, so we have tons of priorities, right? I think really it's double digit growth for them and for us. And understanding how a simpler approach that's customized for the specific vertical or customer base or go to market that they have that helps them quickly navigate to be successful. Our goal is always to facilitate trusted engagements with our partners, right? And then really, as I said, directionally our goal is to be 95 to a hundred percent of all of our business through partners, which helps customers and then really use that trusted advisor status they have to provide that value base to the customer. And then going back on our core tenants, which are, you know, really a trusted, simplified, profitable engagement with our partner community that allows them to really drive successful outcomes and go to market with us. And the end users. >>Trust is such an important word, we can't underutilize it in these conversations. Last question. From a channel business perspective, what are some of the priorities coming down the pike? >>Oh, again, my biggest priority, right, is always to increase the number of partner success stories that we have and increase the value to our partners. So we really dig in, we, we right now sit about number one or number two in, in our space with our partners in ease of doing business and value to our channel community. We wanna be number one across the board, right? Our goal is to make sure that our partner community is successful and that they really have those profitable engagements and that we're globally working with them to drive that engagement and, and help them build more profitable businesses. And so we just take tons of feedback from our partners regularly to help them understand, but we, we act on it very quickly so that we can make sure we incorporate that into our new program and our go to markets as we roll out every year. >>It sounds like a great flywheel of communications from the partners. Kim, thank you so much for joining me today, talking about what Hitachi van is doing with its partner ecosystem, the value in it for customers. We appreciate your insights. >>Thank you very much. >>You're watching the Cube, the leader in live tech coverage.

>>Partnerships in the technology business, they take many forms. For example, technology engineering partnerships, they drive value in terms of things like integration and simplification for customers. There are product partnerships. They fill gaps to create more comprehensive portfolios and more fluid relationships. Partner ecosystems offer high touch services. They offer managed services, specialty services, and other types of value based off of strong customer knowledge and years of built up trust partner. Ecosystems have evolved quite dramatically over the last decade with the explosion of data and the popularity of cloud models. Public, private, hybrid cross clouds. You know, yes it's true. Partnerships are about selling solutions, but they're also about building long term sustainable trust, where a seller learns the ins and outs of a customer's organization and can anticipate needs that are gonna drive bottom line profits for both sides of the equation, the buyer and the seller. >>Hello and welcome to our program. My name is Dave Ante and along with Lisa Martin, we're going to explore how Hitachi Van Tara drives customer success with its partners. First up, Lisa speaks with Kim King. She's the senior vice president of Strategic Partners and Alliances at Hitachi Van. And they'll set the table for us with an overview of how Hitachi is working with partners and where their priorities are focused. Then Russell Kingsley, he's the CTO and global VP of Technical sales at Hitachi Van Tara. He joins Lisa for a discussion of the tech and they're gonna get into cloud generally and hybrid cloud specifically in the role that partners play in the growing as a service movement. Now, after that I'll talk with Tom Christensen, he's the global technology advisor and executive analyst at Hitachi Vitara. And we're gonna talk about a really important topic, sustainability. We're gonna discuss where it came from, why it matters, and how it can drive bottom line profitability for both customers and partners. Let's get right to it. >>Where for the data driven, for those who understand clarity is currency. Believe progress requires precision and no neutral is not an option. We're for the data driven. The ones who can't tolerate failure, who won't put up with downtime or allow access to just anyone. We're for the data driven who act on insight instead of instinct. Bank on privacy instead of probabilities and rely on resilience instead of reaction. We see ourselves in the obsessive, the incessant, progressive, and the meticulously engineered. We enable the incredible identify with the analytical and are synonymous with the mission critical. We know what it means to be data driven because data is in our dna. We were born industrial and and we breathe digital. We speak predictive analytics so you can keep supply chains moving. We bleed in store and online insights so you can accurately predict customer preferences. We sweat security and digital privacy so you can turn complex regulations into competitive advantage. We break down barriers and eliminate silos. So you can go from data rich to data driven because it's clear the future belongs to the data driven. >>Hey everyone, welcome to this conversation. Lisa Martin here with Kim King, the SVP of Strategic Partners and Alliances at Hitachi Ventera. Kim, it's great to have you on the program. Thank you so much for joining me today. >>Thanks Lisa. It's great to be here. >>Let's talk about, so as we know, we talk about cloud all the time, the landscape, the cloud infrastructure landscape increasingly getting more and more complex. What are some of the biggest challenges and pain points that you're hearing from customers today? >>Yeah, so lot. There are lots, but I would say the, the few that we hear consistently are cost the complexity, right? Really the complexity of where do they go, how do they do it, and then availability. They have a lot of available options, but again, going back to complexity and cost, where do they think that they should move and how, how do they make that a successful move to the cloud? >>So talk to me, Hitachi Ventura has a great partner ecosystem. Where do partners play a role in helping customers to address some of the challenges with respect to the cloud landscape? >>Yeah, so part, our partners are really leading the way in the area of cloud in terms of helping customers understand the complexities of the cloud. As we talked about, they're truly the trusted advisor. So when they look at a customer's complete infrastructure, what are the workloads, what are the CRI critical applications that they work with? What's the unique architecture that they have to drive with that customer for a successful outcome and help them architect that? And so partners are truly leading the way across the board, understanding the complexities of each individual customer and then helping them make the right decisions with and for them. And then bringing us along as part of that, >>Talk to me a little bit about the partner landscape, the partner ecosystem at Hitachi Ventura. How does this fit into the overall strategy for the company? >>So we really look at our ecosystem as an extension of our sales organization and and really extension across the board, I would say our goal is to marry the right customer with the right partner and help them achieve their goals, ensure that they keep costs in check, that they ensure they don't have any security concerns, and that they have availability for the solutions and applications that they're trying to move to the cloud, which is most important. So we really, we really look at our ecosystem as a specialty ecosystem that adds high value for the right customers. >>So Kim, talk to me about how partners fit into Hitachi van's overall strategy. >>So I think our biggest differentiators with partners is that they're not just another number. Our partner organization is that valued extension of our overall sales pre-sales services organization. And we treat them like an extension of our organization. It's funny because I was just on a call with an analyst earlier this week and they said that AWS has increased their number of partners to 150,000 partners from, it was just under a hundred thousand. And I'm really not sure how you provide quality engagement to partners, right? And is how is that really a sustainable strategy? So for us, we look at trusted engagement across the ecosystem as a def differentiation. Really our goal is to make their life simple and profitable and really become their primary trusted partner when we go to market with them. And we see that paying dividends with our partners as they engage with us and as they expand and grow across the segments and then grow globally with us as well. >>And that's key, right? That synergistic approach when you're in customer conversations, what do you articulate as the key competitive differentiators where it relates to your partners? >>So really the, that they're the trusted advisor for that partner, right? That they understand our solutions better than any solution out there. And because we're not trying to be all things to our customers and our partners that we being bring best breaths of breed, best of breed solutions to our customers through our partner community, they can truly provide that end user experience and the successful outcome that's needed without, you know, sort of all kinds of, you know, crazy cha challenges, right? When you look at it, they really wanna make sure that they're driving that co-developed solution and the successful outcome for that customer. >>So then how do you feel that Hitachi Ventura helps partners really to grow and expand their own business? >>Wow, so that's, there's tons of ways, but we've, we've created a very simplified, what we call digital selling platform. And in that digital selling platform, we have allowed our partners to choose their own price and pre-approve their pricing and their promotions. They've actually, we've expanded the way we go to market with our partners from a sort of a technical capabilities. We give them online what we call Hitachi online labs that allow them to really leverage all of the solutions and demo systems out there today. And they have complete access to any one of our resources, product management. And so we really have, like I said, we actually provide our partners with better tools and resources sometimes than we do our own sales and pre-sales organization. So we, we look at them as, because they have so many other solutions out there that we have to be one step ahead of everybody else to give them that solution capability and the expertise that they need for their customers. >>So if you dig in, where is it that Hiti is helping partners succeed with your portfolio? >>Wow. So I think just across the board, I think we're really driving that profitable, trusted, and simplified engagement with our partner community because it's a value base and ease of doing business. I say that we allow them to scale and drive that sort of double digit growth through all of the solutions and and offerings that we have today. And because we've taken the approach of a very complex technical sort of infrastructure from a high end perspective and scale it all the way through to our mid-size enterprise, that allows them to really enter any customer at any vertical and provide them a really quality solution with that 100% data availability guarantee that we provide all of our customers. >>So then if we look at the overall sales cycle and the engagement, where is it that you're helping cus your partners rather succeed with the portfolio? >>Say that again? Sorry, my brain broke. No, >>No worries. So if we look at the overall sales cycle, where is it specifically where you're helping customers to succeed with the portfolio? >>So from the sales cycle, I think because we have the, a solution that is simple, easy, and really scaled for the type of customer that we have out there, it allows them to basically right size their infrastructure based on the application, the workload, the quality or the need that application may have and ensure that we provide them with that best solution. >>So then from a partner's perspective, how is it that Hitachi van is helping them to actually close deals faster? >>Yeah, so lots of great ways I think between our pre-sales organization that's on call and available a hundred percent of the time, I think that we've seen, again, the trusted engagement with them from a pricing and packaging perspective. You know, we, you know, two years ago it would take them two to three weeks to get a pre-approved quote where today they preapproved their own quotes in less than an hour and can have that in the hands of a customer. So we've seen that the ability for our partners to create and close orders in very short periods of time and actually get to the customer's needs very quickly, >>So dramatically faster. Yes. Talk about overall, so the partner relationship's quite strong, very synergistic that, that Hitachi Ventura has with its customers. Let's kind of step back out and look at the cloud infrastructure. How do you see it evolving the market evolving overall in say the next six months, 12 months? >>Yeah, so we see it significantly, we've been doing a lot of studies around this specifically. So we have a couple of different teams. We have our sort of our standard partner team that's out there and now we have a specialty cloud service provider team that really focuses on partners that are building and their own infrastructure or leveraging the infrastructure of a large hyperscaler or another GSI and selling that out. And then what we found is when we dig down deeper into our standard sort of partner reseller or value added reseller market, what we're seeing is that they are want to have the capability to resell the solution, but they don't necessarily wanna have to own and manage the infrastructure themselves. So we're helping both of them through that transition. We see that it's gonna, so it's funny cuz you're seeing a combination of many customers move to really the hyperscale or public cloud and many of them want to repatriate their infrastructure back because they see costs and they see challenges around all of that. And so our partners are helping them understand, again, what is the best solution for them as opposed to let's just throw everything in the public cloud and hope that it works. We're we're really helping them make the right choices and decisions and we're putting the right partners together to make that happen. >>And how was that feedback, that data helping you to really grow and expand the partner program as a whole? >>Yeah, so it's been fantastic. We have a whole methodology that we, we created, which is called PDM plan, develop monetize with partners. And so we went specifically to market with cloud service providers that'll, and we really tested this out with them. We didn't just take a solution and say, here, go sell it, good luck and have, you know, have a nice day. Many vendors are doing that to their partners and the partners are struggling to monetize those solutions. So we spend a lot of time upfront planning with them what is not only the storage infrastructure but your potentially your data resiliency and, and everything else that you're looking at your security solutions. How do we package those all together? How do we help you monetize them? And then who do you target from a customer perspective so that they've built up a pipeline of opportunities that they can go and work with us on and we really sit side by side with them in a co-development environment. >>In terms of that side by side relationship, how does the partner ecosystem play a role in Hitachi Venturas as a service business? >>So our primary go to market with our, as a service business is with and through partners. So our goal is to drive all, almost all of of our as a service. Unless it's super highly complex and something that a partner cannot support, we will make sure that they really, we leverage that with them with all of our partners. >>So strong partner relationships, very strong partner ecosystem. What would you say, Kim, are the priorities for the partner ecosystem going forward? The next say year? >>Yeah, so we have tons of priorities, right? I think really it's double digit growth for them and for us and understanding how a simpler approach that's customized for the specific vertical or customer base or go to market that they have that helps them quickly navigate to be successful. Our goal is always to facilitate trusted engagements with our partners, right? And then really, as I said, directionally our goal is to be 95 to a hundred percent of all of our business through partners, which helps customers and then really use that trusted advisor status they have to provide that value base to the customer. And then going back on our core tenants, which are, you know, really a trusted, simplified, profitable engagement with our partner community that allows them to really drive successful outcomes and go to market with us. And the end users >>Trust is such an important word, we can't underutilize it in these conversations. Last question. Sure. From a channel business perspective, what are some of the priorities coming down the pi? >>Oh, again, my biggest priority right, is always to increase the number of partner success stories that we have and increase the value to our partners. So we really dig in, we, we right now sit about number one or number two in, in our space with our partners in ease of doing business and value to our channel community. We wanna be number one across the board, right? Our goal is to make sure that our partner community is successful and that they really have those profitable engagements and that we're globally working with them to drive that engagement and, and help them build more profitable businesses. And so we just take tons of feedback from our partners regularly to help them understand, but we, we act on it very quickly so that we can make sure we incorporate that into our new program and our go to markets as we roll out every year. >>It sounds like a great flywheel of communications from the partners. Kim, thank you so much for joining me today talking about what Hitachi Vanta is doing with its partner ecosystem, the value in IT for customers. We appreciate your insights. >>Thank you very much. >>Up next, Russell Kingsley joins me, TTO and global VP of technical sales at Hitachi van you watch in the cube, the leader in live tech coverage. Hey everyone, welcome back to our conversation with Hitachi van Tara, Lisa Martin here with Russell Skillings Lee, the CTO and global VP of technical sales at Hitachi Van Russell. Welcome to the program. >>Hi Lisa, nice to be here. >>Yeah, great to have you. So here we are, the end of calendar year 2022. What are some of the things that you're hearing out in the field in terms of customers priorities for 2023? >>Yeah, good one. Just to, to set the scene here, we tend to deal with enterprises that have mission critical IT environments and this has been been our heritage and continues to be our major strength. So just to set the scene here, that's the type of customers predominantly I'd be hearing from. And so that's what you're gonna hear about here. Now, in terms of 20 23, 1 of the, the macro concerns that's hitting almost all of our customers right now, as you can probably appreciate is power consumption. And closely related to that is the whole area of ESG and decarbonization and all of that sort of thing. And I'm not gonna spend a lot of time on that one because that would be a whole session in itself really, but sufficient to say it is a priority for us and we, we are very active in, in that area. >>So aside from from that one that that big one, there's also a couple that are pretty much in common for most of our customers and, and we're in areas that we can help. One of those is in an exponential growth of the amount of data. It's, it's predicted that the world's data is going to triple by 2025 as opposed to where it was in 2020. And I think everyone's contributing to that, including a lot of our customers. So just the, the act of managing that amount of data is, is a challenge in itself. And I think closely related to that, a desire to use that data better to be able to gain more business insights and potentially create new business outcomes and business ideas are, is another one of those big challenges in, in that sense, I think a lot of our customers are in what I would kind of call, I affectionately call the, the post Facebook awakening era. >>And that, and what I mean by that is our traditional businesses, you know, when Facebook came along, they kind of illustrated, hey, I can actually make some use out of what is seemingly an enormous amount of useless data, which is exactly what Facebook did. They took a whole lot of people's Yeah. The minutia of people's lives and turned it into, you know, advertising revenue by gaining insights from, from those, you know, sort of seemingly useless bits of data and, you know, right. And I think this actually gave rise to a lot of digital business at that time. You know, the, this whole idea of what all you really need to be successful and disrupt the business is, you know, a great idea, you know, an app and a whole bunch of data to, to power it. And I think that a lot of our traditional customers are looking at this and wondering how do they get into the act? Because they've been collecting data for decades, an enormous amount of data, right? >>Yes. I mean, every company these days has to be a data company, but to your point, they've gotta be able to extract those insights, monetize it, and create real value new opportunities for the business at record speed. >>Yes, that's exactly right. And so being able to, to wield that data somehow turn it, it kind of turns out our customer's attentions to the type of infrastructure they've got as well. I mean, if you think about those, those companies that have been really successful in leveraging that data, a lot of them have, especially in the early days, leverage the cloud to be able to build out their capabilities. And, and the reason why the cloud became such a pivotal part of that is because it offered self-service. IT and, you know, easy development platforms to those people that had these great ideas. All they needed was access to, to, you know, the provider's website and a credit card. And now all of a sudden they could start to build a business from that. And I think a lot of our traditional IT customers are looking at this and thinking, now how do I build a similar sort of infrastructure? How do I, how do I provide that kind of self-service capability to the owners of business inside my company rather than the IT company sort of being a gatekeeper to a selected set of software packages. How now do I provide this development platform for those internal users? And I think this, this is why really hybrid cloud has become the defacto IT sort of architectural standard, even even for quite traditional, you know, IT companies. >>So when it comes to hybrid cloud, what are some of the challenges the customers are facing? And then I know Hitachi has a great partner ecosystem. How are partners helping Hitachi Ventura and its customers to eliminate or solve some of those hybrid cloud challenges? >>Yeah, it's, it, it's a great question and you know, it's, it's not 1975 anymore. It's not, it's not like you're going to get all of your IT needs from, from one, from one vendor hybrid by sort of, it's, you know, by definition is going to involve multiple pieces. And so there basically is no hybrid at all without a partner ecosystem. You really can't get everything at, at a one stop shop like you used to. But even if you think about the biggest public cloud provider on the planet, aws even, it has a marketplace for partner solutions. So, so even they see, even for customers that might consider themselves to be all in on public cloud, they are still going to need other pieces, which is where their marketplace come comes in. Now for, for us, you know, we are, we're a company that, we've been in the IT business for over 60 years, one of one of the few that could claim that sort of heritage. >>And you know, we've seen a lot of this type of change ourselves, this change of attitude from being able to provide everything yourself to being someone who contributes to an overall ecosystem. So partners are absolutely essential. And so now we kind of have a, a partner first philosophy when it comes to our routes to market on, you know, not just our own products in terms of, you know, a resale channel or whatever, but also making sure that we are working with some of the biggest players in hybrid infrastructure and determining where we can add value to that in our, in our own solutions. And so, you know, when it comes to those, those partner ecosystems, we're always looking for the spaces where we can best add our own capability to those prevailing IT architectures that are successful in the marketplace. And, you know, I think that it's probably fair to say, you know, for us, first and foremost, we, we have a reputation for having the biggest, most reliable storage infrastructure available on the planet. >>And, and we make no apologies for the fact that we tout our speeds and feeds and uptime supremacy. You know, a lot of our, a lot of our competitors would suggest that, hey, speeds and feeds don't matter. But you know, that's kind of what you say when, when you're not the fastest or not the most reliable, you know, of course they matter. And for us, what we, the way that we look at this is we say, let's look at who's providing the best possible hybrid solutions and let's partner with them to make those solutions even better. That's the way we look at it. >>Can you peel the, the onion a little bit on the technology underpinning the solutions, give a glimpse into that and then maybe add some color in terms of how partners are enhancing that? >>Yeah, let me, let me do that with a few examples here, and maybe what I can do is I can sort of share some insight about the way we think with partnering with, with particular people and why it's a good blend or why we see that technologically it's a good blend. So for example, the work we do with VMware, which we consider to be one of our most important hybrid cloud partners and in, and in fact it's, it's my belief, they have one of the strongest hybrid cloud stories in the industry. It resonates really strongly with, with our customers as well. But you know, we think it's made so much better with the robust underpinnings that we provide. We're one of the, one of the few storage vendors that provides a 100% data availability guarantee. So we, we take that sort of level of reliability and we add other aspects like life cycle management of the underpinning infrastructure. >>We combine that with what VMware's doing, and then when you look at our converged or hyper-converged solutions with them, it's a better together story where you now have what is one of the best hybrid cloud stories in the industry with VMware. But now for the on premise part, especially, you've now added a hundred percent data, data availability guarantee, and you've made managing the underlying infrastructure so much easier through the tools that we provide that go down to that level A level underneath where VMware are. And so that's, that's VMware. I've got a couple, couple more examples just to sort of fill, fill that out a bit. Sure. Cisco is another part, very strong partner of ours, a key partner. And I mean, you look at Cisco, they're a 50 billion IT provider and they don't have a dedicated storage infrastructure of their own. So they're going to partner with someone. >>From our perspective, we look at Cisco's, Cisco's customers and we look at them and think they're very similar to our own in terms of they're known to appreciate performance and reliability and a bit of premium in quality, and we think we match them them quite well. They're already buying what we believe are the best converge platforms in the industry from Cisco. So it makes sense that those customers would want to compliment that investment with the best array, best storage array they can get. And so we think we are helping Cisco's customers make the most of their decision to be ucs customers. Final one for, for you, Lisa, by way of example, we have a relationship with, with Equinix and you know, Equinix is the world's sort of leading colo provider. And the way I think they like to think of themselves, and I too tend to agree with them, is their, they're one of the most compelling high-speed interconnect networks in the world. >>They're connected to all of the, the, the significant cloud providers in most of the locations around the world. We have a, a relationship with them where we find we have customers in common who really love the idea of compute from the cloud. Compute from the cloud is great because compute is something that you are doing for a set period of time and then it's over you. Like you have a task, you do some compute, it's done. Cloud is beautiful for that. Storage on the other hand is very long lived storage doesn't tend to operate in that same sort of way. It sort of just becomes a bigger and bigger blob over time. And so the cost model around public cloud and storage is not as compelling as it is for compute. And so our, with our relationship with Equinix, we help our customers to be able to create, let's call it a, a data anchor point where they put our arrays into, into an Equinix location, and then they utilize Equinix as high speeding interconnects to the, to the cloud providers, okay. To take the compute from them. So they take the compute from the cloud providers and they own their own storage, and in this way they feel like we've now got the best of all worlds. Right. What I hope that illustrates Lisa is with those three examples is we are always looking for ways to find our key advantages with any given, you know, alliance partners advantages, >>Right? What are, when you're in customer conversations, and our final few minutes here, I wanna get, what are some of the key differentiators that you talk about when you're in customer conversations, and then how does the partner ecosystem fit into Hitachi vans as a service business? We'll start with differentiators and then let's move into the as service business so we can round out with that. >>Okay. Let's start with the differentiators. Yeah. Firstly and I, and hopefully I've kind of, I've hit this point hard, hard enough. We do believe that we have the fastest and most reliable storage infrastructure on the planet. This is kind of what we are known for, and customers that are working with us already sort of have an appreciation for that. And so they're looking for, okay, you've got that now, how can you make my hybrid cloud aspirations better? So we do have that as a fundamental, right? So, but secondly I'd say, I think it's also because we go beyond just storage management and, and into the areas of data management. You know, we've got, we've got solutions that are not just about storing the bits. We do think that we do that very well, but we also have solutions that move into the areas of enrichment, of the data, cataloging of the data, classification of the data, and most importantly, analytics. >>So, you know, we, we think it's, some of our competitors just stop at storing stuff and some of our competitors are in the analytics space, but we feel that we can bridge that. And we think that that's a, that's a competitive advantage for us. One of the other areas that I think is key for us as well is, as I said, we're one of the few vendors who've been in the marketplace for 60 years and we think this, this, this gives us a more nuanced perspective about things. There are many things in the industry, trends that have happened over time where we feel we've seen this kind of thing before and I think we will see it again. But you only really get that perspective if you are, if you are long lived in the industry. And so we believe that our conversations with our customers bear a little bit more sophistication. It's not just, it's not just about what's the latest and greatest trends. >>Right. We've got about one minute left. Can you, can you round us out with how the partner ecosystem is playing a role in the as service business? >>They're absolutely pivotal in that, you know, we, we ourselves don't own data centers, right? So we don't provide our own cloud services out. So we are 100% partner focused when it comes to that aspect. Our formula is to help partners build their cloud services with our solutions and then onsell them to their customers as as as a service. You know, and by what quick way of example, VMware for example, they've got nearly 5,000 partners selling VMware cloud services. 5,000 blows me away. And many of them are our partners too. So we kind of see this as a virtuous cycle. We've got product, we've got an an alliance with VMware and we work together with partners in common for the delivery of an as a service business. >>Got it. So the, as you said, the partner ecosystem is absolutely pivotal. Russell, it's been a pleasure having you on the program talking about all things hybrid cloud challenges, how Hitachi van is working with its partner ecosystems to really help customers across industries solve those big problems. We really appreciate your insights and your time. >>Thank you very much, Lisa. It's been great. >>Yeah, yeah. For Russell Stingley, I'm Lisa Martin. In a moment we're gonna continue our conversation with Tom Christensen. Stay tuned. >>Sulfur Royal has always embraced digital technology. We were amongst the first hospitals in the UK to install a full electronic patient record system. Unfortunately, as a result of being a pioneer, we often find that there's gaps in the digital solutions. My involvement has been from the very start of this program, a group of us got together to discuss what the problems actually were in the hospital and how we could solve this. >>The digital control center is an innovation that's been designed in partnership between ourselves, anti touch, and it's designed to bring all of the information that is really critical for delivering effective and high quality patient care. Together the DCC is designed not only to improve the lives of patients, but also of our staff giving us information that our demand is going to increase in the number of patients needing support. The technology that we're building can be replicated across sulfur, the NCA, and the wider nhs, including social care and community services. Because it brings all of that information that is essential for delivering high quality efficient care. >>The DCC will save time for both staff and more importantly our patients. It will leave clinicians to care for patients rather than administrate systems and it will allow the system that I work with within the patient flow team to effectively and safely place patients in clinically appropriate environments. >>But we chose to partner with Hitachi to deliver the DCC here at Sulfur. They were willing to work with us to co-produce and design a product that really would work within the environment that we find ourselves in a hospital, in a community setting, in a social care setting. >>My hopes for the DCC is that ultimately we will provide more efficient and reliable care for our patients. >>I do believe the digital control center will improve the lives of staff and also the patients so that we can then start to deliver the real change that's needed for patient care. >>Okay, we're back with Tom Christensen, who's the global technology advisor and executive analyst at Hitachi Van Tara. And we're exploring how Hitachi Van Tower drives customer success specifically with partners. You know Tom, it's funny, back in the early part of the last decade, there was this big push around, remember it was called green it and then the oh 7 0 8 financial crisis sort of put that on the back burner. But sustainability is back and it seems to be emerging as a mega trend in in it is, are you seeing this, is it same wine new label? How real is this trend and where's the pressure coming from? >>Well, we clearly see that sustainability is a mega trend in the IT sector. And when we talk to CIOs or senior IT leaders or simply just invite them in for a round table on this topic, they all tell us that they get the pressure from three different angles. The first one is really end consumers and end consumers. Nowaday are beginning to ask questions about the green profile and what are the company doing for the environment. And this one here is both private and public companies as well. The second pressure that we see is coming from the government. The government thinks that companies are not moving fast enough so they want to put laws in that are forcing companies to move faster. And we see that in Germany as an example, where they are giving a law into enterprise companies to following human rights and sustainability tree levels back in the supply chain. >>But we also see that in EU they are talking about a new law that they want to put into action and that one will replicate to 27 countries in Europe. But this one is not only Europe, it's the rest of the world where governments are talking about forcing companies to move faster than we have done in the past. So we see two types of pressure coming in and at the same time, this one here starts off at the CEO at a company because they want to have the competitive edge and be able to be relevant in the market. And for that reason they're beginning to put KPIs on themself as the ceo, but they're also hiring sustainability officers with sustainability KPIs. And when that happens it replicates down in the organization and we can now see that some CIOs, they have a kpi, others are indirectly measured. >>So we see direct and indirect. The same with CFOs and other C levels. They all get measured on it. And for that reason it replicates down to IT people. And that's what they tell us on these round table. I get that pressure every day, every week, every quarter. But where is the pressure coming from? Well the pressure is coming from in consumers and new laws that are put into action that force companies to think differently and have focus on their green profile and doing something good for the environment. So those are the tree pressures that we see. But when we talk to CFOs as an example, we are beginning to see that they have a new store system where they put out request for proposal and this one is in about 58% of all request for proposal that we receive that they are asking for our sustainability take, what are you doing as a vendor? >>And in their score system cost has the highest priority and number two is sustainability. It waits about 15, 20 to 25% when they look at your proposal that you submit to a cfo. But in some cases the CFO say, I don't even know where the pressure is coming from. I'm asked to do it. Or they're asked to do it because end consumers laws and so on are forcing them to do it. But I would answer, yeah, sustainability has become a make trend this year and it's even growing faster and faster every month we move forward. >>Yeah, Tom, it feels like it's here to stay this time. And your point about public policy is right on, we saw the EU leading with privacy and GDPR and it looks like it's gonna lead again here. You know, just shifting gears, I've been to a number of Hitachi facilities in my day. OWA is my favorite because on a clear day you can see Mount Fuji, but other plants I've been to as well. What does Hitachi do in the production facility to reduce CO2 emissions? >>Yeah, I think you're hitting a good point here. So what we have, we have a, a facility in Japan and we have one in Europe and we have one in America as well to keep our production close to our customers and reduced transportation for the factory out to our customers. But you know, in the, in the, in the May region back in 2020 13, we created a new factory. And when we did that we were asked to do it in an energy, energy neutral way, which means that we are moving from being powered by black energy to green energy in that factory. And we build a factory with concrete walls that were extremely thick to make it cold in the summertime and hot in the winter time with minimum energy consumption. But we also put 17,000 square meters of solar panel on the roof to power that factory. >>We were collecting rain waters to flush it in the toilet. We were removing light bulbs with L E D and when we sent out our equipment to our customers, we put it in a, instead of sending out 25 packages to a customer, we want to reduce the waste as much as possible. And you know, this one was pretty new back in 2013. It was actually the biggest project in EA at that time. I will say if you want to build a factory today, that's the way you are going to do it. But it has a huge impact for us when electricity is going up and price and oil and gas prices are coming up. We are running with energy neutral in our facility, which is a big benefit for us going forward. But it is also a competitive advantage to be able to explain what we have been doing the last eight, nine years in that factory. We are actually walking to talk and we make that decision even though it was a really hard decision to do back in 2013, when you do decisions like this one here, the return of investment is not coming the first couple of years. It's something that comes far out in the future. But right now we are beginning to see the benefit of the decision we made back in 2013. >>I wanna come back to the economics, but before I do, I wanna pick up on something you just said because you know, you hear the slogan sustainability by design. A lot of people might think okay, that's just a marketing slogan, slogan to vector in into this mega trend, but it sounds like it's something that you've been working on for quite some time. Based on your last comments, can you add some color to that? >>Yeah, so you know, the factory is just one example of what you need to do to reduce the CO2 emission and that part of the life of a a product. The other one is really innovating new technology to drive down the CO2 emission. And here we are laser focused on what we call decarbonization by design. And this one is something that we have done the last eight years, so this is far from you for us. So between each generation of products that we have put out over the last eight years, we've been able to reduce the CO2 emission by up to 30 to 60% between each generation of products that we have put into the market. So we are laser focused on driving that one down, but we are far from done, we still got eight years before we hit our first target net zero in 2030. So we got a roadmap where we want to achieve even more with new technology. At its core, it is a technology innovator and our answers to reduce the CO2 emission and the decarbonization of a data center is going to be through innovating new technology because it has the speed, the scale, and the impact to make it possible to reach your sustainability objectives going forward. >>How about recycling? You know, where does that fit? I mean, the other day it was, you know, a lot of times at a hotel, you know, you used to get bottled water, now you get, you know, plant based, you know, waters in a box and, and so we are seeing it all around us. But for a manufacturer of your size, recycling and circular economy, how does that fit into your plans? >>Yeah, let me try to explain what we are doing here. Cause one thing is how you produce it. Another thing is how you innovate all that new technology, but you also need to combine that with service and software, otherwise you won't get the full benefit. So what we are doing here, when it comes to exploring circular economics, it's kind of where we have an eternity mindset. We want to see if it is possible to get nothing out to the landfill. This is the aim that we are looking at. So when you buy a product today, you get an option to keep it in your data center for up to 10 years. But what we wanna do when you keep it for 10 years is to upgrade only parts of the system. So let's say that you need more CBU power, use your switch the controller to next generation controller and you get more CPU power in your storage system to keep it those 10 years. >>But you can also expand with new this media flash media, even media that doesn't exist today will be supported over those 10 years. You can change your protocol in the, in the front end of your system to have new protocols and connect to your server environment with the latest and greatest technology. See, the benefit here is that you don't have to put your system into a truck and a recycle process after three years, four years, five years, you can actually postpone that one for 10 years. And this one is reducing the emission again. But once we take it back, you put it on the truck and we take it into our recycling facility. And here we take our own equipment like compute network and switches, but we also take competitor equipment in and we recycle as much as we can. In many cases, it's only 1% that goes to the landfill or 2% that goes to the landfill. >>The remaining material will go into new products either in our cycle or in other parts of the electronic industry. So it will be reused for other products. So when we look at what we've been doing for many years, that has been linear economics where you buy material, you make your product, you put it into production, and it goes into land feed afterwards. The recycling economics, it's really, you buy material, you make your product, you put it into production, and you recycle as much as possible. The remaining part will go into the landfill. But where we are right now is exploring circle economics where you actually buy material, make it, put it into production, and you reuse as much as you can. And only one 2% is going into the landfill right now. So we have come along and we honestly believe that the circular economics is the new economics going forward for many industries in the world. >>Yeah. And that addresses some of the things that we were talking about earlier about sustainability by design, you have to design that so that you can take advantage of that circular economy. I, I do wanna come back to the economics because, you know, in the early days of so-called green, it, there was a lot of talk about, well, I, I, I'll never be able to lower the power bill. And the facilities people don't talk to the IT people. And that's changed. So explain why sustainability is good business, not just an expense item, but can really drive bottom line profitability. I, I understand it's gonna take some time, but, but help us understand your experience there, Tom. >>Yeah, let me try to explain that one. You know, you often get the question about sustainability. Isn't that a cost? I mean, how much does it cost to get that green profile? But you know, in reality when you do a deep dive into the data center, you realize that sustainability is a cost saving activity. And this one is quite interesting. And we have now done more than 1,200 data center assessment around the world where we have looked at data centers. And let me give you just an average number from a global bank that we work with. And this one is, it is not different from all the other cases that we are doing. So when we look at the storage area, what we can do on the electricity by moving an old legacy data center into a new modernized infrastructure is to reduce the electricity by 96%. >>This is a very high number and a lot of money that you save, but the CO2 mission is reduced by 96% as well. The floor space can go up to 35% reduction as well. When we move down to the compute part, we are talking about 61% reduction in electricity on the compute part just by moving from legacy to new modern infrastructure and 61% on the CO2 emission as well. And see this one here is quite interesting because you save electricity and you and you do something really good for the environment. At the same time, in this case I'm talking about here, the customer was paying 2.5 million US dollar annually and by just modernizing that infrastructure, we could bring it down to 1.1 million. This is 1.4 million savings straight into your pocket and you can start the next activity here looking at moving from virtual machine to containers. Containers only use 10% of the CPU resources compared to a virtual machine. Move up to the application layer. If you have that kind of capability in your organization, modernizing your application with sustainability by design and you can reduce the C, the CO2 emission by up to 50%. There's so much we can do in that data center, but we often start at the infrastructure first and then we move up in the chain and we give customers benefit in all these different layers. >>Yeah, A big theme of this program today is what you guys are doing with partners do, are partners aware of this in your view? Are they in tune with it? Are they demanding it? What message would you like to give the channel partners, resellers and, and distributors who may be watching? >>So the way to look at it is that we offer a platform with product, service and software and that platform can elevate the conversation much higher up in the organization. And partners get the opportunity here to go up and talk to sustainability officers about what we are doing. They can even take it up to the CEO and talk about how can you reach your sustainability KPI in the data center. What we've seen this round table when we have sustainability officers in the room is that they're very focused on the green profile and what is going out of the company. They rarely have a deep understanding of what is going on at the data center. Why? Because it's really technical and they don't have that background. So just by elevating the conversation to these sustainability officers, you can tell them what they should measure and how they should measure that. And you can be sure that that will replicate down to the CIO and the CFO and that immediately your request for proposal going forward. So this one here is really a golden opportunity to take that story, go out and talk to different people in the organization to be relevant and have an impact and make it more easy for you to win that proposal when it gets out. >>Well really solid story on a super important topic. Thanks Tom. Really appreciate your time and taking us through your perspectives. >>Thank you Dave, for the invitation. >>Yeah, you bet. Okay, in a moment we'll be back. To summarize our final thoughts, keep it right there. >>Click by click. The world is changing. We make sense of our world by making sense of data. You can draw more meaning from more data than was ever possible before, so that every thought and every action can build your path to intelligent innovation to change the way the world works. Hitachi Van Tara. >>Okay, thanks for watching the program. We hope you gained a better understanding of how Hitachi Ventura drives customer success with its partners. If you wanna learn more about how you can partner for profit, check out the partner togetherPage@hitachiventera.com and there's a link on the webpage here that will take you right to that page. Okay, that's a wrap for Lisa Martin. This is Dave Valante with the Cube. You a leader in enterprise and emerging tech coverage.

>> We're back at the ARIA Las Vegas. We're covering CrowdStrike's Fal.Con 22. First one since 2019. Dave Vellante and Dave Nicholson on theCUBE. Adam Meyers is here, he is the Senior Vice President of Intelligence at CrowdStrike. Adam, thanks for coming to theCUBE. >> Thanks for having me. >> Interesting times, isn't it? You're very welcome. Senior Vice President of Intelligence, tell us what your role is. >> So I run all of our intelligence offerings. All of our analysts, we have a couple hundred analysts that work at CrowdStrike tracking threat actors. There's 185 threat actors that we track today. We're constantly adding more of them and it requires us to really have that visibility and understand how they operate so that we can inform our other products: our XDR, our Cloud Workload Protections and really integrate all of this around the threat actor. >> So it's that threat hunting capability that CrowdStrike has. That's what you're sort of... >> Well, so think of it this way. When we launched the company 11 years ago yesterday, what we wanted to do was to tell customers, to tell people that, well, you don't have a malware problem, you have an adversary problem. There are humans that are out there conducting these attacks, and if you know who they are what they're up to, how they operate then you're better positioned to defend against them. And so that's really at the core, what CrowdStrike started with and all of our products are powered by intelligence. All of our services are our OverWatch and our Falcon complete, all powered by intelligence because we want to know who the threat actors are and what they're doing so we can stop them. >> So for instance like you can stop known malware. A lot of companies can stop known malware, but you also can stop unknown malware. And I infer that the intelligence is part of that equation, is that right? >> Absolutely. That that's the outcome. That's the output of the intelligence but I could also tell you who these threat actors are, where they're operating out of, show you pictures of some of them, that's the threat intel. We are tracking down to the individual persona in many cases, these various threats whether they be Chinese nation state, Russian threat actors, Iran, North Korea, we track as I said, quite a few of these threats. And over time, we develop a really robust deep knowledge about who they are and how they operate. >> Okay. And we're going to get into some of that, the big four and cyber. But before we do, I want to ask you about the eCrime index stats, the ECX you guys call it a little side joke for all your nerds out there. Maybe you could explain that Adam >> Assembly humor. >> Yeah right, right. So, but, what is that index? You guys, how often do you publish it? What are you learning from that? >> Yeah, so it was modeled off of the Dow Jones industrial average. So if you look at the Dow Jones it's a composite index that was started in the late 1800s. And they took a couple of different companies that were the industrial component of the economy back then, right. Textiles and railroads and coal and steel and things like that. And they use that to approximate the overall health of the economy. So if you take these different stocks together, swizzle 'em together, and figure out some sort of number you could say, look, it's up. The economy's doing good. It's down, not doing so good. So after World War II, everybody was exuberant and positive about the end of the war. The DGI goes up, the oil crisis in the seventies goes down, COVID hits goes up, sorry, goes down. And then everybody realizes that they can use Amazon still and they can still get the things they need goes back up with the eCrime index. We took that approach to say what is the health of the underground economy? When you read about any of these ransomware attacks or data extortion attacks there are criminal groups that are working together in order to get things spammed out or to buy credentials and things like that. And so what the eCrime index does is it takes 24 different observables, right? The price of a ransom, the number of ransom attacks, the fluctuation in cryptocurrency, how much stolen material is being sold for on the underground. And we're constantly computing this number to understand is the eCrime ecosystem healthy? Is it thriving or is it under pressure? And that lets us understand what's going on in the world and kind of contextualize it. Give an example, Microsoft on patch Tuesday releases 56 vulnerabilities. 11 of them are critical. Well guess what? After hack Tuesday. So after patch Tuesday is hack Wednesday. And so all of those 11 vulnerabilities are exploitable. And now you have threat actors that have a whole new array of weapons that they can deploy and bring to bear against their victims after that patch Tuesday. So that's hack Wednesday. Conversely we'll get something like the colonial pipeline. Colonial pipeline attack May of 21, I think it was, comes out and all of the various underground forums where these ransomware operators are doing their business. They freak out because they don't want law enforcement. President Biden is talking about them and he's putting pressure on them. They don't want this ransomware component of what they're doing to bring law enforcement, bring heat on them. So they deplatform them. They kick 'em off. And when they do that, the ransomware stops being as much of a factor at that point in time. And the eCrime index goes down. So we can look at holidays, and right around Thanksgiving, which is coming up pretty soon, it's going to go up because there's so much online commerce with cyber Monday and such, right? You're going to see this increase in online activity; eCrime actors want to take advantage of that. When Christmas comes, they take vacation too; they're going to spend time with their families, so it goes back down and it stays down till around the end of the Russian Orthodox Christmas, which you can probably extrapolate why that is. And then it goes back up. So as it's fluctuating, it gives us the ability to really just start tracking what that economy looks like. >> Realtime indicator of that crypto. >> I mean, you talked about, talked about hack Wednesday, and before that you mentioned, you know, the big four, and I think you said 185 threat actors that you're tracking, is 180, is number 185 on that list? Somebody living in their basement in their mom's basement or are the resources necessary to get on that list? Such that it's like, no, no, no, no. this is very, very organized, large groups of people. Hollywood would have you believe that it's guy with a laptop, hack Wednesday, (Dave Nicholson mimics keyboard clacking noises) and everything done. >> Right. >> Are there individuals who are doing things like that or are these typically very well organized? >> That's a great question. And I think it's an important one to ask and it's both it tends to be more, the bigger groups. There are some one-off ones where it's one or two people. Sometimes they get big. Sometimes they get small. One of the big challenges. Have you heard of ransomware as a service? >> Of course. Oh my God. Any knucklehead can be a ransomwarist. >> Exactly. So we don't track those knuckleheads as much unless they get onto our radar somehow, they're conducting a lot of operations against our customers or something like that. But what we do track is that ransomware as a service platform because the affiliates, the people that are using it they come, they go and, you know, it could be they're only there for a period of time. Sometimes they move between different ransomware services, right? They'll use the one that's most useful for them that that week or that month, they're getting the best rate because it's rev sharing. They get a percentage that platform gets percentage of the ransom. So, you know, they negotiate a better deal. They might move to a different ransomware platform. So that's really hard to track. And it's also, you know, I think more important for us to understand the platform and the technology that is being used than the individual that's doing it. >> Yeah. Makes sense. Alright, let's talk about the big four. China, Iran, North Korea, and Russia. Tell us about, you know, how you monitor these folks. Are there different signatures for each? Can you actually tell, you know based on the hack who's behind it? >> So yeah, it starts off, you know motivation is a huge factor. China conducts espionage, they do it for diplomatic purposes. They do it for military and political purposes. And they do it for economic espionage. All of these things map to known policies that they put out, the Five Year Plan, the Made in China 2025, the Belt and Road Initiative, it's all part of their efforts to become a regional and ultimately a global hegemon. >> They're not stealing nickels and dimes. >> No they're stealing intellectual property. They're stealing trade secrets. They're stealing negotiation points. When there's, you know a high speed rail or something like that. And they use a set of tools and they have a set of behaviors and they have a set of infrastructure and a set of targets that as we look at all of these things together we can derive who they are by motivation and the longer we observe them, the more data we get, the more we can get that attribution. I could tell you that there's X number of Chinese threat groups that we track under Panda, right? And they're associated with the Ministry of State Security. There's a whole other set. That's too associated with the People's Liberation Army Strategic Support Force. So, I mean, these are big operations. They're intelligence agencies that are operating out of China. Iran has a different set of targets. They have a different set of motives. They go after North American and Israeli businesses right now that's kind of their main operation. And they're doing something called hack and lock and leak. With a lock and leak, what they're doing is they're deploying ransomware. They don't care about getting a ransom payment. They're just doing it to disrupt the target. And then they're leaking information that they steal during that operation that brings embarrassment. It brings compliance, regulatory, legal impact for that particular entity. So it's disruptive >> The chaos creators that's.. >> Well, you know I think they're trying to create a they're trying to really impact the legitimacy of some of these targets and the trust that their customers and their partners and people have in them. And that is psychological warfare in a certain way. And it, you know is really part of their broader initiative. Look at some of the other things that they've done they've hacked into like the missile defense system in Israel, and they've turned on the sirens, right? Those are all things that they're doing for a specific purpose, and that's not China, right? Like as you start to look at this stuff, you can start to really understand what they're up to. Russia very much been busy targeting NATO and NATO countries and Ukraine. Obviously the conflict that started in February has been a huge focus for these threat actors. And then as we look at North Korea, totally different. They're doing, there was a major crypto attack today. They're going after these crypto platforms, they're going after DeFi platforms. They're going after all of this stuff that most people don't even understand and they're stealing the crypto currency and they're using it for revenue generation. These nuclear weapons don't pay for themselves, their research and development don't pay for themselves. And so they're using that cyber operation to either steal money or steal intelligence. >> They need the cash. Yeah. >> Yeah. And they also do economic targeting because Kim Jong Un had said back in 2016 that they need to improve the lives of North Koreans. They have this national economic development strategy. And that means that they need, you know, I think only 30% of North Korea has access to reliable power. So having access to clean energy sources and renewable energy sources, that's important to keep the people happy and stop them from rising up against the regime. So that's the type of economic espionage that they're conducting. >> Well, those are the big four. If there were big five or six, I would presume US and some Western European countries would be on there. Do you track, I mean, where United States obviously has you know, people that are capable of this we're out doing our thing, and- >> So I think- >> That defense or offense, where do we sit in this matrix? >> Well, I think the big five would probably include eCrime. We also track India, Pakistan. We track actors out of Columbia, out of Turkey, out of Syria. So there's a whole, you know this problem is getting worse over time. It's proliferating. And I think COVID was also, you know a driver there because so many of these countries couldn't move human assets around because everything was getting locked down. As machine learning and artificial intelligence and all of this makes its way into the cameras at border and transfer points, it's hard to get a human asset through there. And so cyber is a very attractive, cheap and deniable form of espionage and gives them operational capabilities, not, you know and to your question about US and other kind of five I friendly type countries we have not seen them targeting our customers. So we focus on the threats that target our customers. >> Right. >> And so, you know, if we were to find them at a customer environment sure. But you know, when you look at some of the public reporting that's out there, the malware that's associated with them is focused on, you know, real bad people, and it's, it's physically like crypted to their hard drive. So unless you have sensor on, you know, an Iranian or some other laptop that might be target or something like that. >> Well, like Stuxnet did. >> Yeah. >> Right so. >> You won't see it. Right. See, so yeah. >> Well Symantec saw it but way back when right? Back in the day. >> Well, I mean, if you want to go down that route I think it actually came from a company in the region that was doing the IR and they were working with Symantec. >> Oh, okay. So, okay. So it was a local >> Yeah. I think Crisis, I think was the company that first identified it. And then they worked with Symantec. >> It Was, they found it, I guess, a logic controller. I forget what it was. >> It was a long time ago, so I might not have that completely right. >> But it was a seminal moment in the industry. >> Oh. And it was a seminal moment for Iran because you know, that I think caused them to get into cyber operations. Right. When they realized that something like that could happen that bolstered, you know there was a lot of underground hacking forums in Iran. And, you know, after Stuxnet, we started seeing that those hackers were dropping their hacker names and they were starting businesses. They were starting to try to go after government contracts. And they were starting to build training offensive programs, things like that because, you know they realized that this is an opportunity there. >> Yeah. We were talking earlier about this with Shawn and, you know, in the nuclear war, you know the Cold War days, you had the mutually assured destruction. It's not as black and white in the cyber world. Right. Cause as, as Robert Gates told me, you know a few years ago, we have a lot more to lose. So we have to be somewhat, as the United States, careful as to how much of an offensive posture we take. >> Well here's a secret. So I have a background on political science. So mutually assured destruction, I think is a deterrent strategy where you have two kind of two, two entities that like they will destroy each other if they so they're disinclined to go down that route. >> Right. >> With cyber I really don't like that mutually assured destruction >> That doesn't fit right. >> I think it's deterrents by denial. Right? So raising the cost, if they were to conduct a cyber operation, raising that cost that they don't want to do it, they don't want to incur the impact of that. Right. And think about this in terms of a lot of people are asking about would China invade Taiwan. And so as you look at the cost that that would have on the Chinese military, the POA, the POA Navy et cetera, you know, that's that deterrents by denial, trying to, trying to make the costs so high that they don't want to do it. And I think that's a better fit for cyber to try to figure out how can we raise the cost to the adversary if they operate against our customers against our enterprises and that they'll go someplace else and do something else. >> Well, that's a retaliatory strike, isn't it? I mean, is that what you're saying? >> No, definitely not. >> It's more of reducing their return on investment essentially. >> Yeah. >> And incenting them- disincening them to do X and sending them off somewhere else. >> Right. And threat actors, whether they be criminals or nation states, you know, Bruce Lee had this great quote that was "be like water", right? Like take the path of least resistance, like water will. Threat actors do that too. So, I mean, unless you're super high value target that they absolutely have to get into by any means necessary, then if you become too hard of a target, they're going to move on to somebody that's a little easier. >> Makes sense. Awesome. Really appreciate your, I could, we'd love to have you back. >> Anytime. >> Go deeper. Adam Myers. We're here at Fal.Con 22, Dave Vellante, Dave Nicholson. We'll be right back right after this short break. (bouncy music plays)

(upbeat music) >> Hey everyone! Welcome to the AWS Partner Showcase. This is season one, episode three with a focus on women in tech. I'm your host, Lisa Martin. I've got two guests here with me, Sue Persichetti, the EVP of Global AWS Strategic Alliances at Jefferson Frank. A Tenth Revolution Group company. And Danielle Greshock, one of our own CUBE alumni, joins us, ISV PSA director. Ladies, it's great to have you on the program talking about a topic that is near and dear to my heart, women in tech. >> Thank you, Lisa! >> Great to be here! >> So let's go ahead and start with you. Give the audience an understanding of Jefferson Frank, what does the company do, and about the partnership with AWS. >> Sure, so let's just start, Jefferson Frank is a Tenth Revolution Group company. And if you look at it, it's really talent as a service. So Jefferson Frank provides talent solutions all over the world for AWS clients, partners, and users, et cetera. And we have a sister company called Revolent, which is a talent creation company within the AWS ecosystem. So we create talent and put it out in the ecosystem. Usually underrepresented groups, over half of them are women. And then we also have a company called Rebura, which is a delivery model around AWS technology. So all three companies fall under the Tenth Revolution Group organization. >> Got it, Danielle, talk to me a little bit about from AWS' perspective and the focus on hiring more women in technology and about the partnership. >> Yes, this has definitely been a focus ever since I joined eight years ago, but also just especially in the last few years of we've grown exponentially and our customer base has changed. We want to have an organization interacting with them that reflects our customers, right? And we know that we need to keep pace with that even with our growth. And so we've very much focused on early career talent, bringing more women and underrepresented minorities into the organization, sponsoring those folks, promoting them, giving them paths to grow inside of the organization. I'm an example of that, of course, I've benefited from it. But also, I try to bring that into my organization as well and it's super important. >> Tell me a little bit about how you benefited from that, Danielle. >> I just think that I've been able to get, a seat at the table. I think that. I feel as though I have folks supporting me very deeply and want to see me succeed. And also they put me forth as a representative to bring more women into the organization as well. They give me a platform in order to do that, like this, but also many other spots as well. And I'm happy to do it because I feel that... you always want to feel that you're making a difference in your job. And that is definitely a place where I get that time and space in order to be that representative. To bring more women into benefiting from having careers in technology, which there's a lot of value there. >> Lot of value. Absolutely. So back over to you, what are some of the trends that you are seeing from a gendered diversity perspective in tech? We know the numbers of women in technical positions. >> Right. There's so much data out there that shows when girls start dropping out, but what are some of the trends that you're seeing? >> So that's a really interesting question. And Lisa, I had a whole bunch of data points that I wanted to share with you but just two weeks ago, I was in San Francisco with AWS at The Summit. And we were talking about this, we were talking about how we can collectively together attract more women, not only to AWS, not only to technology, but to the AWS ecosystem in particular. And it was fascinating because I was talking about the challenges that women have, and how hard to believe but about 5% of women who were in the ecosystem have left in the past few years. Which was really, really something that shocked everyone when we were talking about it, because all of the things that we've been asking for, for instance working from home, better pay, more flexibility, better maternity leave. Seems like those things are happening. So we're getting what we want, but people are leaving. And it seemed like the feedback that we got was that a lot of women still felt very underrepresented. The number one thing was that they couldn't be... you can't be what you can't see. So because they... we feel, collectively women, people who identify as women, just don't see enough women in leadership, they don't see enough mentors. I think I've had great mentors, but just not enough. I'm lucky enough to have the president of our company, Zoe Morris is a woman and she does lead by example. So I'm very lucky for that. And Jefferson Frank really quickly we put out a hiring, a salary, and hiring guide. Career and hiring guide every year. And the data points, and that's about 65 pages long, no one else does it. It gives an abundance of information around everything about the AWS ecosystem that a hiring manager might need to know. What I thought was really unbelievable was that only 7% of the people that responded to it were women. So my goal, being that we have such a very big global platform, is to get more women to respond to that survey. So we can get as much information and take action. So... >> Absolutely only 7%. So a long way to go there. Danielle, talk to me about AWS' focus on women in tech. I was watching, Sue, I saw that you shared on LinkedIn the TED Talk that the CEO and founder of Girls Who Code did. And one of the things that she said was that there was a survey that HP did some years back that showed that 60%... that men will apply for jobs if they only meet 60% of the list of requirements. Whereas with females, it's far, far less. We've all been in that imposter syndrome conundrum before. But Danielle, talk to us about AWS' specific focus here to get these numbers up. >> Well, I think it speaks to what Susan was talking about how I think we're approaching it top and bottom, right? We're looking out at who are the women who are currently in technical positions and how can we make AWS an attractive place for them to work? And that's a lot of the changes that we've had around maternity leave and those types of things. But then also, a more flexible working arrangements. But then also early... how can we actually impact early career women and actually women who are still in school. And our training and certification team is doing amazing things to get more girls exposed to AWS, to technology, and make it a less intimidating place. And have them look at employees from AWS and say like, "Oh, I can see myself in those people". And kind of actually growing the viable pool of candidates. I think we're limited with the viable pool of candidates when you're talking about mid-to-late career. But how can we help retrain women who are coming back into the workplace after having a child, and how can we help with military women who want to... or underrepresented minorities who want to move into AWS? We have a great military program but then also just that early high school career getting them in that trajectory. >> Sue, is that something that Jefferson Frank is also able to help with is getting those younger girls before they start to feel... >> Right. "There's something wrong with me, I don't get this." >> Right. >> Talk to us about how Jefferson Frank can help really drive up that in those younger girls. >> Let me tell you one other thing to refer back to that Summit that we did we had breakout sessions and that was one of the topics. Cause that's the goal, right? To make sure that there are ways to attract them. That's the goal. So some of the things that we talked about was mentoring programs from a very young age, some people said high school. But then we said, even earlier, goes back to you can't be what you can't see. So getting mentoring programs established. We also talked about some of the great ideas was being careful of how we speak to women using the right language to attract them. And so there was a teachable moment for me there actually. It was really wonderful because an African American woman said to me, "Sue". And I was talking about how you can't be what you can't see. And what she said was, "Sue, it's really different for me as an African American woman" Or she identified as non-binary but she was relating to African American women. She said, "You're a white woman. Your journey was very different than my journey". And I thought, "This is how we're going to learn". I wasn't offended by her calling me out at all. It was a teachable moment. And I thought I understood that but those are the things that we need to educate people on. Those moments where we think we're saying and doing the right thing, but we really need to get that bias out there. So here at Jefferson Frank we're trying really hard to get that careers and hiring guide out there. It's on our website to get more women to talk to it, but to make suggestions in partnership with AWS around how we can do this. Mentoring. We have a mentor me program. We go around the country and do things like this. We try to get the education out there in partnership with AWS. We have a women's group, a women's leadership group. So much that we do and we try to do it in partnership with AWS. >> Danielle, can you comment on the impact that AWS has made so far regarding some of the trends and and gender diversity that Sue was talking about? What's the impact that's been made so far with this partnership? >> Well, I think just being able to get more of the data and have awareness of leaders on how... it used to be a couple years back, I would feel like sometimes the solving to bring more women into the organization was kind of something that folks thought, "Oh, this is... Danielle is going to solve this." And I think a lot of folks now realize, "Oh, this is something that we all need to solve for." And a lot of my colleagues, who maybe a couple years ago didn't have any awareness or didn't even have the tools to do what they needed to do in order to improve the statistics on their or in their organizations, now actually have those tools and are able to kind of work with companies like Susan's work with Jefferson Frank in order to actually get the data, and actually make good decisions, and feel as though they often... these are not lived experiences for these folks. So they don't know what they don't know. And by providing data, and providing awareness, and providing tooling, and then setting goals, I think all of those things have really turned things around in a very positive way. >> And so you bring up a great point about from a diversity perspective. What is Jefferson Frank doing to get those data points up to get more women of all, well, really underrepresented minorities to be able to provide that feedback so that you can have the data and gleamy insights from it to help companies like AWS on their strategic objectives? >> Right, so when I go back to that careers and hiring guide, that is my focus today really, because the more data that we have and the data takes... we need people to participate in order to accurately get ahold of that data. So that's why we're asking. We're taking the initiative to really expand our focus. We are a global organization with a very, very massive database all over the world. But if people don't take action then we can't get the right... the data will not be as accurate as we'd like it to be, therefore take better action. So what we're doing is we're asking people all over the world to participate on our website jeffersonfrank.com In the survey so we can learn as much as we can. 7% is such a... Danielle and I we've got to partner on this just to sort of get that message out there, get more data so we can execute. Some of the other things that we're doing, we're partnering, as I mentioned, more of these events. We're doing around the Summits, we're going to be having more EDNI events, and collecting more information from women. Like I said, internally, we do practice what we preach and we have our own programs that are out there, that are within our own company where the women who are talking to candidates and clients every single day are trying to get that message out there. So if I'm speaking to a client or one of our internal people are speaking to a client or a candidate, they're telling them, "Listen, we really are trying to get these numbers up. We want to attract as many people as we can. Would you mind going to this hiring guide and offering your own information?" So we've got to get that 7% up. We've got to keep talking. We've got to keep getting programs out there. One other thing I wanted to Danielle's point, she mentioned women in leadership, the number that we gathered was only 9% of women in leadership within the AWS ecosystem. We've got to get that number up as well, because I know for me, when I see people like Danielle or her peers it inspires me. And I feel like I just want to give back. Make sure I send the elevator back to the first floor and bring more women in to this amazing ecosystem. >> Absolutely, we need- >> Love that metaphor. >> I do too! But to your point to get those numbers up not just at AWS, but everywhere else we need It's a help me help you situation. >> Exactly. >> So ladies, underrepresented minorities, if you're watching go to the Jefferson Frank website, take the survey. Help provide the data so that the women here that are doing this amazing work, have it to help make decisions and have more of females in leadership roles or underrepresented minorities. So we can be what we can see. >> Exactly. >> Ladies, thank you so much for joining me today and sharing what you guys are doing together to partner on this important cause. >> Thank you for having me, Lisa! >> Thank you! Thank you! >> My pleasure! For my guests, I'm Lisa Martin. You're watching theCUBES coverage of the AWS partner showcase. Thanks for your time. (gentle xylophone music)

(inspiring music) >> Announcer: theCUBE presents HPE Discover 2022. Brought to you by HPE. >> Welcome back to theCUBE's coverage of HPE Discover 2022, from the Venetian in Las Vegas, the first Discover since 2019. I really think this is my 14th Discover, when you include HP, when you include Europe. And I got to say this Discover, I think has more energy than any one that I've ever seen, about 8,000 people here. Really excited to have one of HPE's longstanding partners, Veeam CTO, Danny Allen is here, joined by David Harvey, Vice President of Strategic Alliances at Veeam. Guys, good to see you again. It was just earlier, let's see, last month, we were together out here. >> Yeah, just a few weeks ago. It's fantastic to be back and what it's telling us, technology industry is coming back. >> And the events business, of course, is coming back, which we love. I think the expectations were cautious. You saw it at VeeamON, a little more than you expected, a lot of great energy. A lot of people, 'cause it was last month, it was their first time out, >> Yes. >> in two years. Here, I think people have started to go out more, but still, an energy that's palpable. >> You can definitely feel it. Last night, I think I went to four consecutive events and everyone's out having those discussions and having conversations, it's good to be back. >> You guys hosted the Storage party last night, which is epic. I left at midnight, I took a picture, it was still packed. I said, okay, time to go, nothing good happens after midnight kids. David, talk about the alliance with HPE, how it's evolved, and where you see it going? >> I appreciate it, and certainly this, as you said, has been a big alliance for us. Over 10 years or so, fantastic integrations across the board. And you touched on 2019 Discover. We launched with GreenLake at that event, we were one of the launch partners, and we've seen fantastic growth. Overall, what we're excited about, is that continuation of the movement of the customer's buying patterns in line with HPE's portfolio and in line with Veeam. We continue to be with all their primary, secondary storage, we continue to be a spearhead position with GreenLake, which we're really excited about. And we're also really excited to hear from HPE, unfortunately under NDA, some of their future stuff they're investing in, which is a really nice invigoration for what they're doing for their portfolio. And we see that being a big deal for us over the next 24 months. >> Your relationship with HPE predates the HP, HPE split. >> Mmm. >> Yes. >> But it was weird, because they had Data Protector, and that was a quasi-competitor, or really not, but it was a competitor, a legacy competitor, of what you guys have, kind of modern data protection I think is the tagline, if I got it right. Post the split, that was an S-curve moment, wasn't it, in terms of the partnership? >> It really was. If you go back 10 years, we did our first integration sending data to StoreOnce and we had some blueprints around that. But now, if you look what we have, we have integrations on the primary side, so, 3PAR, Primera, Nimble, all their top-tier storage, we can manage the snapshots. We have integration on the target side. We integrate with Catalyst in the movement of data and the management of data. And, as David alluded to, we integrate with GreenLake. So, customers who want to take this as a consumption model, we integrate with that. And so it's been, like you said, the strongest relationship that we have on the technology alliance side. >> So, V12, you announced at VeeamON. What does that mean for HPE customers, the relationship? Maybe you guys could both talk about that. >> Technology side, to touch on a few things that we're doing with them, ransomware has been a huge issue. Security's been a big theme, obviously, at the conference, >> Dave: Yeah, you bet. and one of the things we're doing in V12 is adding immutability for both StoreOnce and StoreEver. So, we take the features that our partners have, immutability being big in the security space, and we integrate that fully into the product. So a customer checks a box and says, hey, I want to make sure that the data is secure. >> Yeah, and also, it's another signification about the relationship. Every single release we've done has had HPE at the heart of it, and the same thing is being said with V12. And it shows to our customers, the continual commitment. Relationships come and go. They're hard, and the great news is, 10 years has proven that we get through good times and tricky situations, and we both continue to invest, et cetera. And I think there's a lot of peace of mind and the revenue figures prove that, which is what we're really excited about. >> Yeah I want to come back to that, but just to follow up, Danny, on that immutability, that's a feature that you check? It's service within GreenLake, or within Veeam? How does that all work? >> We have immutability now depending on the target. We introduced the ability to send data, for example, into S3 two years ago, and make it immutable when you send it to an S3 or S3 compatible environment. We added, in Version 11, the ability to take a Linux repository and make it, and harden it, essentially make it immutable. But what we're doing now is taking our partner systems like StoreOnce, like StoreEver, and when we send data there, we take advantage of an API flag or whatever it happens to be, that it makes the data, when it's written to that system, can't be deleted, can't be encrypted. Now, what does that mean for a customer? Well, we do all the hard work in the back end, it's just a check box. They say, I want to make it immutable, and we manage how long it's immutable. Because if you made everything immutable forever, that's hugely expensive, right? So, it's all about, how long is that immutable before you age it out and make sure the new data coming in is immutable. >> Dave: It's like an insurance policy, you have that overlap. >> Yes. >> Right, okay. And then David, you mentioned the revenue, Lou bears that out. I got the IDC guys comin' on later on today. I'll ask 'em about that, if that's their swim lane. But you guys are basically a statistical tie, with Dell for number one? Am I getting that right? And you're growing at a faster rate, I believe, it's hard to tell 'cause I don't think Dell reports on the pace of its growth within data protection. You guys obviously do, but is that right? It's a statistical tie, is it? >> Yeah, hundred percent. >> Yeah, statistical tie for first place, which we're super excited about. When I joined Veeam, I think we were in fifth place, but we've been in the leader's quadrant of the Gartner Magic- >> Cause and effect there or? (panelists laughing) >> No, I don't think so. >> Dave: Ha, I think maybe. >> We've been on a great trajectory. But statistical tie for first place, greatest growth sequentially, and year-over-year, of all of the data protection vendors. And that's a testament not just to the technology that we're doing, but partnerships with HPE, because you never do this, the value of a technology is not that technology alone, it's the value of that technology within the ecosystem. And so that's why we're here at HPE Discover. It's our joint technology solutions that we're delivering. >> What are your thoughts or what are you seeing in the field on As-a-service? Because of course, the messaging is all about As-a-service, you'd think, oh, a hundred percent of everything is going to be As-a-service. A lot of customers, they don't mind CapEx, they got good, balance sheet, and they're like, hey, we'll take care of this, and, we're going to build our own little internal cloud. But, what are you seeing in the market in terms of As-a-service, versus, just traditional licensing models? >> Certainly, there's a mix between the two. What I'd say, is that sources that are already As-a-service, think Microsoft 365, think AWS, Azure, GCP, the cloud providers. There's a natural tendency for the customer to want the data protection As-a-service, as well for those. But if you talk about what's on premises, customers who have big data centers deployed, they're not yet, the pendulum has not shifted for that to be data protection As-a-service. But we were early to this game ourselves. We have 10,000, what we call, Veeam Cloud Service Providers, that are offering data protection As-a-service, whether it be on premises, so they're remotely managing it, or cloud hosted, doing data protection for that. >> So, you don't care. You're providing the technology, and then your customers are actually choosing the delivery model. Is that correct? >> A hundred percent, and if you think about what GreenLake is doing for example, that started off as being a financial model, but now they're getting into that services delivery. And what we want to do is enable them to deliver it, As-a-service, not just the financial model, but the outcome for the customer. And so our technology, it's not just do backup, it's do backup for a multi-tenant, multi-customer environment that does all of the multi-tenancy and billing and charge back as part of that service. >> Okay, so you guys don't report on this, but I'm going to ask the question anyway. You're number one now, let's call you, let's declare number one, 'cause we're well past that last reporting and you're growin' faster. So go another quarter, you're now number one, so you're the largest. Do you spend more on R&D in data protection than any other company? >> Yes, I'm quite certain that we do. Now, we have an unfair advantage because we have 450,000 customers. I don't think there's any other data protection company out there, the size and scope and scale, that we have. But we've been expanding, our largest R&D operation center's in Prague, it's in Czech Republic, but we've been expanding that. Last year it grew 40% year on year in R&D, so big investment in that space. You can see this just through our product space. Five years ago, we did data protection of VMware only, and now we do all the virtual environments, all the physical environments, all the major cloud environments, Kubernetes, Microsoft 365, we're launching Salesforce. We announced that at VeeamON last month and it will be coming out in Q3. All of that is coming from our R&D investments. >> A lot of people expect that when a company like Insight, a PE company, purchases a company like Veeam, that one of the things they'll dial down is R&D. That did not happen in this case. >> No, they very much treat us as a growth company. We had 22% year-over-year growth in 2020, and 25% year-over-year last year. The growth has been tremendous, they continue to give us the freedom. Now, I expect they'll want returns like that continuously, but we have been delivering, they have been investing. >> One of my favorite conversations of the year was our supercloud conversation, which was awesome, thank you for doing that with me. But that's clearly an area of focus, what we call supercloud, and you don't use that term, I know, you do sometimes, but it's not your marketing, I get that. But that is an R&D intensive effort, is it not? To create that common experience. And you see HPE, attempting to do that as well, across all these different estates. >> A hundred percent. We focus on three things, I always say, our differentiators, simplicity, flexibility, and reliability. Making it simple for the customers is not an easy thing to do. Making that checkbox for immutability? We have to do a lot behind the scenes to make it simple. Same thing on flexibility. We don't care if they're using 3PAR, Primera, Nimble, whatever you want to choose as the primary storage, we will take that out of your hands and make it really easy. You mentioned supercloud. We don't care what the cloud infrastructure, it can be on GreenLake, it can be on AWS, can be on Azure, it can be on GCP, it can be on IBM cloud. It is a lot of effort on our part to abstract the cloud infrastructure, but we do that on behalf of our customers to take away that complexity, it's part of our platform. >> Quick follow-up, and then I want to ask a question of David. I like talking to you guys because you don't care where it is, right? You're truly agnostic to it all. I'm trying to figure out this repatriation thing, cause I hear a lot of hey, Dave, you should look into repatriation that's happened all over the place, and I see pockets of it. What are you seeing in terms of repatriation? Have customers over-rotated to the cloud and now they're pullin' back a little bit? Or is it, as I'm claiming, in pockets? What's your visibility on that? >> Three things I see happening. There's the customers who lifted up their data center, moved it into the cloud and they get the first bill. >> (chuckling) Okay. >> And they will repatriate, there's no question. If I talk to those customers who simply lifted up and moved it over because the CIO told them to, they're moving it back on premises. But a second thing that we see is people moving it over, with tweaks. So they'll take their SQL server database and they'll move it into RDS, they'll change some things. And then you have people who are building cloud-native, they're never coming back on premises, they are building it for the cloud environment. So, we see all three of those. We only really see repatriation on that first scenario, when they get that first bill. >> And when you look at the numbers, I think it gets lost, 'cause you see the cloud is growing so fast. So David, what are the conversations like? You had several events last night, The Veeam party, slash Storage party, from HPE. What are you hearing from your alliance partners and the customers at the event. >> I think Danny touched on that point, it's about philosophy of evolution. And I think at the end of the day, whether we're seeing it with our GSI alliances we've got out there, or with the big enterprise conversations we're having with HPE, it's about understanding which workloads they want to move. In our mind, the customers are getting much smarter in making that decision, rather than experimenting. They're really taking a really solid look. And the work we're doing with the GSIs on workplace modernization, data center transformation, they're really having that investment work up front on the workloads, to be able to say, this works for me, for my personality and my company. And so, to the point about movement, it's more about decisive decision at the start, and not feeling like the remit is, I have to do one thing or another, it's about looking at that workflow position. And that's what we've seen with the revenue part as well. We've seen our movement to GreenLake tremendously grow in the last 18 months to two years. And from our GSI work as well, we're seeing the types of conversations really focus on that workload, compared to, hey, I just need a backup solution, and that's really exciting. >> Are you having specific conversations about security, or is it a data protection conversation still, (David chuckles) that's an adjacency to security? >> That's a great question. And I think it's a complex one, because if you come to a company like Veeam, we are there, and you touched on it before, we provide a solution when something has happened with security. We're not doing intrusion detection, we're not doing that barrier position at the end of it, but it's part of an end-to-end assumption. And I don't think that at this particular point, I started in security with RSA and Check Point, it was about layers of protection. Now it's layers of protection, and the inevitability that at some point something will happen, so about the recovery. So the exciting conversations we're having, especially with the big enterprises, is not about the fear factor, it's about, at some point something's going to occur. Speed of recovery is the conversation. And so for us, and your question is, are they talking to us about security, or more, the continuity position? And that's where the synergy's getting a lot simpler, rather than a hard demark between security and backup. >> Yeah, when you look at the stock market, everything's been hit, but security, with the exception of Okta, 'cause it got that weird benign hack, but security, generally, is an area that CIOs have said, hey, we can't really dial that back. We can maybe, some other discretionary stuff, we'll steal and prioritize. But security seems to be, and I think data protection is now part of that discussion. You're not a security company. We've seen some of your competitors actually pivot to become security companies. You're not doing that, but it's very clearly an adjacency, don't you think? >> It's an adjacency, and it's a new conversation that we're having with the Chief Information Security Officer. I had a meeting an hour ago with a customer who was hit by ransomware, and they got the call at 2:00 AM in the morning, after the ransomware they recovered their entire portfolio within 36 hours, from backups. Didn't even contact Veeam, I found out during this meeting. But that is clearly something that the Chief Information Security Officer wants to know about. It's part of his purview, is the recovery of that data. >> And they didn't pay the ransom? >> And they did not pay the ransom, not a penny. >> Ahh, we love those stories. Guys, thanks so much for coming on theCUBE. Congratulations on all the success. Love when you guys come on, and it was such a fun event at VeeamON. Great event here, and your presence is, was seen. The Veeam green is everywhere, so appreciate your time. >> Thank you. >> Thanks, Dave. >> Okay, and thank you for watching. This is Dave Vellante for John Furrier and Lisa Martin. We'll be back right after this short break. You're watching theCUBE's coverage of HPE Discover 2022, from Las Vegas. (inspiring music)

>>We're seeing green here at Vemo in 2022, you're watching the cube, Dave ante and David Nicholson wrapping up our second day of coverage. Dave, good show. Good to be, you know, again, good to be back. This is our third show in a row. We're a Cuban as well. So the cube is, is out there, but same every, every show we go to so far has been most of the people here haven't been out in two plus years. Yeah. Right. And, and, and they're like, Hey, let's go. Let's hug. Let's shake. I got my red band on cuz we've been on a lot of shows or just being careful <laugh> um, you know, Hey, but it's great to see people back, uh, >>Absolutely >>Such a different vibe than virtual virtual sucks. Everybody hates it now, but now it's going hybrid. People are trying to figure that out. Yeah. Uh, but it's, it's in your view, what's different. What's the same >>In terms of, uh, in person versus hybrid kind of what's happened since what's >>Different being here now versus say 2019, not that you were here in 2019, but a show in 2019. >>I, I think there's right now, there's a certain sense of, uh, of appreciation for the ability to come and do this. Mm-hmm <affirmative> um, >>As opposed to on we or oh, another show, right? >>Yeah. Yeah, exactly. And, and, uh, a personal opinion is that, um, I think that the hybrid model moving forward is going to end up being additive. I don't know that I don't, you know, people say we'll never go back to having in person the way we did before. Um, I'm holding out hope that that's not the case because I, I think so there's so much value to the kinds of conversations that we have, not only here on the set with folks in person, but just the hallway conversations, uh, the dinner conversations, um, those are so critical, uh, not only with between vendors and customers, but between different business units. Um, you know, I, I, I came into this thinking, you know, I know Veeam very well. I've known them since the beginning. Um, but you think I'm going to a conference to talk about backup software and it wasn't like that at all. I mean, this is, this is an overarching, very, very interesting subject to cover. So how is it different? I think people are appreciative. I wouldn't say we're backed full throttle a hundred percent, um, uh, back in the game yet. But, uh, but we we're getting there. Some >>Of the highlights Veeam now, number one, statistical tie for first place in revenue. There aren't a lot of segments, especially in storage where Dell is not number one, I guess technically Dell is like, I don't know, half a percentage point ahead, but Veeam's gonna blow by that. Unless Dell gets its data, >>Protect me as the luxury of focus, they can focus >>Like a laser on it focus. Right? That, that we, we saw this in the P PC where focused, we saw Dell's ascendancy cuz they were focused on PCs, right? Yeah. We saw Seagate on dis drives Intel and microprocesors Oracle on databases and, and, and Veeam applied that model to what they call modern data protection. Um, and, and the, so the reason why we think they're gonna go past is they growing at 20 plus percent each year. And, and I can almost guarantee Dell's data protection business isn't although it's been in a, I, I sense a downward slope lately, they don't divulge that data. Um, but if they were growing nicely, they would be talking about it. So I think they've been kind of hiding that ball, but Dell, you know, you can't count those guys out they're baby. >>No, you can't. And there's always >>A, they don't like to lose. They get that EMC DNA still in >>There. Yeah. You take, you can, you might take your eye off the ball for a little while to focus on other things. But uh, I think it'll be healthy for the industry at large, as Veeam continues to take market share. There's definitely gonna be pushback from, from others in the field, but >>The pure software play. Um, and you know that no hardware agenda thing and all that I think is, is clearly in Veeam's favor. Uh, but we'll see. I mean, Dell's got other, other strengths as do others. I mean, this is, this is, let's not forget this, this, this market is crowded and getting kind. I mean, you got, you got other players, new, new entrants, like cohesive in Rubrik Rubic, by the way is the one I was kind of referring to. That seems to be, you go to their LinkedIn, they seem to be pivoting to security. I was shocked when I saw that. I'm like, wow, is that just like a desperation move? Is that a way to get your valuation up? Is that, is there something I'm missing? I, I don't know. I haven't talked to those guys in a little bit, need to get, get there, but cause he and Rubrik couldn't get to IPO prior to, uh, you know, the, the, the, the, the tech sell off the tech lash. >>If you will Veeam, didn't need toves. We have 30% EBITDA and, and has had it for a while. So they've been, they caught lightning in a bottle years ago, and then now they got the inside capital behind them. Um, you got new entrance, like, like Kuo, you got com. Vault is out there. You still got, you know, Veritas is still out there competing and you know, a number of other, you get you got is wherever HP software landed in, in the MicroStrategy, uh, micro strategy. <laugh> um, no not micro strategy anyway, in that portfolio of companies that HP sold its software business to, you know, they're still out there. So, you know, a lot of ways to, to buy backup and recovery software, but these guys being the leader is no surprise. >>Yeah. You know, it's, I, I, I have to say it to me. It's a classic story of discipline >>Microfocus, sorry, >>Microfocus. Yeah, that's right. That's right. You know, it's funny. I, I, I could see that logo on a, I know I've got a notebook at home. Um, but, but theme is a classic example of well disciplined growth where you're not playing the latest buzzword game and trying to create adjacent businesses that are really, that might sound sexy, but have nothing to do with your core. They've been very, very disciplined about their approach, starting with, you know, looking at VMFS and saying, this is what we're gonna do, and then branching out from there in a logical way. So, so they're not out ahead of the tips of their skis in a way that some others have have gotten. And those, you know, sometimes swinging for the fence is great, but you can strike out that way also. And they've been hitting, you know, you could say they've been hitting singles and doubles just over and over and over again for years now. Well, that's been a great strategy. >>You've seen this a lot. I mean, I, I think you watched this at EMC when you were there as you, it was acquisitions to try to keep the growth up. It was, it was great marketing. I mean, unbelievable marketing cloud meets big data. Oh yeah. And you'd hear on CNBC. AMC is the cloud company. You're like, eh, fucking have a cloud. So, so you, you you've seen companies do that to your point about getting ahead of your skis. VMs never done that EMS like, eh, this is the product that works great. Yeah. Customers love it. They buy it, you know, we got the distribution channel set up and so that's always been, been, been part of their DNA. Um, and I think the other piece is putting meat on the bone of the tagline of modern data protection. When I first heard that I'm like, mm, okay. >>But then when you peel the onion on that, the core is back up in recovery, a lot of focus on recovery. And then the way they, I remember it was there in the audience when they announced, you know, support for bare metal, people went crazy. I'm like, wow, okay. They cuz they used to say, oh, never virtualization forever. Okay. So they beat that drum and you never say never in this business, do you, and then moving on to cloud and hybrid and containers and we're hearing about super cloud now, and maybe there'll be an edge use case there it's still unclear what that pattern is. You've talked about that with Zs, but it's not clear to me where you put your muscle yet in, um, in edge, but really being able to manage all that data that is people talk about data management that starts to be data management. And they've got a footprint that enables 'em to do that. >>Yeah. And, and I'd like to see that same discipline approach. That's gotten them here to continue no need to get on board a hype cycle. Um, what I really love from a business execution perspective from Veeam is the fact that they know their place in terms of the, their strategic advisory role for end user customers and their places largely in partnership with folks in the channel partners, large and small, um, in a couple of the conversations we had over the last few days, we talked about this idea that there are fewer and fewer seats at the table. Uh, working with customers, customers can't have 25 strategic vendor partners and a lot of smaller niche players that focus on something even as important as backup will pretend that they are, that they hold the same sort of strategic weight as a hyperscale cloud provider. Does they pretend that they're gonna be there in the CX O meetings? Um, when they're not Veeam knows exactly how to best leverage what they do with customers and that's through partners in the channel. >>The other thing is, um, new CEO, a non Eron, uh, the fifth CEO, I think I'm correct. Is that right at, at VE yes. Um, so two founders, uh, and then when Peter McKay came on, he was co CEO. Um, and then, um, yep. And let's see, I think yep. You the fifth. Okay. So each of the CEOs kind of had their own mark. Right. Um, and we asked an on in the analyst thing, what do you want your legacy to be? And I, I loved his answer. He's like, this is a fragmented business with a lot of adjacencies and we are the leader in revenue, but we only have 12% revenue share. I want to take that to 25%, 40%. That's like EMC at 30 plus percent of the storage market, Cisco of 60% of the networking market. Wow. If anybody could ever get there, but so 25 to 30% of a market that's that's big. Yeah. I liked his demeanor thought he had a really good style philosophy. Well-spoken well spoken. So new leadership, obviously insight brought him in to take them to the next level. Um, and, and really drive. I gotta believe get ready for IPO. We kind of admitted that. >>Yeah. And I, and IPO for them, one thing he mentioned is that, um, in this case, this is not an IPO let's high five and go to Vegas and get table service because now we finally have money. Uh, they're not doing, you know, obviously an injection in capital from an IPO is always a good thing or should be a good thing if handled properly, but that's not their primary driver. So it'll be very interesting to see if they can hit the timing. Right. Um, how that, how that works out >>Well and, and bill large is his was predecessor. Uh, he, he, he took over, uh, once the company, excuse me, went private. Um, >>Yeah, that phone backed up. >>I still good in the mic once the company went private, uh, well, no, they were always private. Once they got acquired for five plus billion dollars from inside capital, um, they, they put bill in charge, perfect choice for the transition. And it was like, okay, bill. It's like, when you, my brother's a sailor. He says, Hey, take, take the wheel, see that lighthouse or see that tree go for it, keep it on track. And that's what bill did. Perfect. And he knew the company knew where all the skeletons were buried and, and was perfect. Perfect transition for that. Now they're bringing in somebody who they feel can take it to the next level. They're at a billion. He said he could see 5 billion and, and beyond. So that's kind of cool. Um, the other thing was ecosystem as companies got a really robust ecosystem, all the storage array vendors came on. >>The, the, the backup appliance companies, you know, came on to the cube and had a presence here. Why? Because this is where all the customers are. This is the leader in backup in recovery. Yeah. They all want to partner with that leader. Now they're at out the other shows as well, uh, for the Veeam competitors, but frankly, Veeam, Veeam competitors. They don't have, like you said, they're pure play. Many of them don't have a show like this, or it's a smaller event. Um, and so they gotta be here. Uh, and I think the, the, the other thing was the ransomware study. What I really liked about Veeam is they not only just talked about it, they not only talked about their solution. They sh they did deep dive surveys and shared a ton of data with guys that knew data. Um, Dave Russell and Jason Buffington, both former analysts, Russell was a Gartner very well respected top Gartner analyst for years. Jason buff, Buffington at ESG who those guys did always did some really good, still do deep research. So you had them representing that data, but sharing it with the community, of course, it's, it's gonna be somewhat self-serving, but it wasn't as blatant. It that wasn't nearly as blatant as I often see with these surveys, gender surveys, I'll look at 'em. I can tell within like, seconds, whether it's just a bunch of marketing, you know, what, or there's real substance. Yeah. And this one had real substance to >>It. Yeah. And it's okay. When substance supports your business model. >>Yeah. Cool. >>It's great. Good >>Marketing. But yeah, as an best marketing, I'm not gonna use it. The whole industry can use this and build on it. Yeah. I think there were a lot of unanswered questions. I, what I love about Vema is they're going back and they, they did it in February. They, they updated it just recently. Now they're going back and doing more cuz they want to get it by country. So they're making investments. And then they're sharing that with the industry. I love that. >>It'll be interesting to see if they continue it over time, how things change if things change. Um, one of the things that we really didn't talk a lot about is, uh, and you know, it's, I know it's talked about behind closed doors, um, this idea of, uh, stockpiling day zero exploits, and the fact that a lot of these, these >>Things, >>A lot of these problems arguably could have been headed off, had our taxpayer funded organizations, shared information with private industry in a more timely fashion. Um, um, we had, um, uh, uh, was it, uh, Gina from AWS who gave the example of, uh, the not Petia, uh, experience in the hospital environment. And that came directly out of frankly a day zero exploit that the NSA had identified years earlier within Microsoft's operating system. And, uh, somehow others got ahold of that and used it for nefarious means. So the intent to stockpile and hang onto these things is always, um, noble, but sometimes the result is, uh, less than desirable. So that's, it'll be an interesting conversation. >>We'd be remiss if we didn't mention the, the casting acquisition, the, the, the container data protection, small piece of the business today. Uh, but strategic in the sense that, yeah, absolutely. If you want to appeal to developers, if, if, if, if, if you want to be in the cloud, you know, you better be able to talk containers generally in Kubernetes specifically. So they gotta play there as well. >>Well, they, they, they hit virtualization cloud containers. Maybe I'm missing something in between, but they seem to be >>Ransomware >>Catching waves effectively. Yeah. Ransomware, uh, catching waves effectively, uh, again, not in an artificial buzzword driven way, but in a legitimate disciplined business growth approach that, uh, that's impressive. >>And I, and I think Danny mentioned this, we, he said we've been a PLG product led growth company. Um, and I think they're evolving now. We talked about platforms versus product. We still got still a product company. Uh, but they're bill wants to build out a Supercloud. So we're watching that very closely. I, I think it is a thing. You got a lot of grief for the term, super cloud. Some people wince at it, but it's, there's something brewing. There's something different. That's not just cloud public cloud, not hybrid cloud, not private cloud it's across cloud it's super cloud. All right, Dave, Hey, it was a pleasure working with you this week. Always kind of funny. I mean, we're, the crew was out in, uh, in Valencia, Spain. Yeah. Uh, they'll in fact, they'll be broadcasting, I believe all the way through Friday. Uh, that's an early morning thing for the, uh, for the west coast and, but east coast should be able to catch that easily. >>Of course you can all check out all the replays on the cube.net, also YouTube, youtube.com/silicon angle go to wikibon.com. There's some, you know, research there I publish every week and, and others do, uh, as well, maybe not as frequently, but, uh, we have a great relationship with ETR. I'm gonna poke into some data protection stuff in their survey. See if I can find some interesting, uh, data there. And don't forget to go to Silicon an angle.com, which is all the news. This is the cube, our flagship production we're out at VEON 2022. Thanks for watching.

>> From "theCUBE" studios in Palo Alto, in Boston, bringing you data driven insights from "theCUBE" and ETR. This is "Breaking Analysis" with Dave Vellante. >> There are very few political issues that get bipartisan support these days, nevermind consensus spanning geopolitical boundaries. But whether we're talking across the aisle or over the pond, there seems to be common agreement that the power of big tech firms should be regulated. But the government's track record when it comes to antitrust aimed at big tech is actually really mixed, mixed at best. History has shown that market forces rather than public policy have been much more effective at curbing monopoly power in the technology industry. Hello, and welcome to this week's "Wikibon CUBE" insights powered by ETR. In this "Breaking Analysis" we welcome in frequent "CUBE" contributor Dave Moschella, author and senior fellow at the Information Technology and Innovation Foundation. Dave, welcome, good to see you again. >> Hey, thanks Dave, good to be here. >> So you just recently published an article, we're going to bring it up here and I'll read the title, "Theory Aside, Antitrust Advocates Should Keep Their "Big Tech" Ambitions Narrow". And in this post you argue that big sweeping changes like breaking apart companies to moderate monopoly power in the tech industry have been ineffective compared to market forces, but you're not saying government shouldn't be involved rather you're suggesting that more targeted measures combined with market forces are the right answer. Can you maybe explain a little bit more the premise behind your research and some of your conclusions? >> Sure, and first let's go back to that title, when I said, theory aside, that is referring to a huge debate that's going on in global antitrust circles these days about whether antitrust should follow the traditional path of being invoked when there's real harm, demonstrable harm to consumers or a new theory that says that any sort of vast monopoly power inevitably will be bad for competition and consumers at some point, so your best to intervene now to avoid harms later. And that school, which was a very minor part of the antitrust world for many, many years is now quite ascendant and the debate goes on doesn't matter which side of that you're on the questions sort of there well, all right, well, if you're going to do something to take on big tech and clearly many politicians, regulators are sort of issuing to do something, what would you actually do? And what are the odds that that'll do more good than harm? And that was really the origins of the piece and trying to take a historical view of that. >> Yeah, I learned a new word, thank you. Neo-brandzian had to look it up, but basically you're saying that traditionally it was proving consumer harm versus being proactive about the possibility or likelihood of consumer harm. >> Correct, and that's a really big shift that a lot of traditional antitrust people strongly object to, but is now sort of the trendy and more send and view. >> Got it, okay, let's look a little deeper into the history of tech monopolies and government action and see what we can learn from that. We put together this slide that we can reference. It shows the three historical targets in the tech business and now the new ones. In 1969, the DOJ went after IBM, Big Blue and it's 13 years later, dropped its suit. And then in 1984 the government broke Ma Bell apart and in the late 1990s, went after Microsoft, I think it was 1998 in the Wintel monopoly. And recently in an interview with tech journalist, Kara Swisher, the FTC chair Lena Khan claimed that the government played a major role in moderating the power of tech giants historically. And I think she even specifically referenced Microsoft or maybe Kara did and basically said the industry and consumers from the dominance of companies like Microsoft. So Dave, let's briefly talk about and Kara by the way, didn't really challenge that, she kind of let it slide. But let's talk about each of these and test this concept a bit. Were the government actions in these instances necessary? What were the outcomes and the consequences? Maybe you could start with IBM and AT&T. >> Yeah, it's a big topic and there's a lot there and a lot of history, but I might just sort of introduce by saying for whatever reasons antitrust has been part of the entire information technology industry history from mainframe to the current period and that slide sort of gives you that. And the reasons for that are I think once that we sort of know the economies of scale, network effects, lock in safe choices, lot of things that explain it, but the good bit about that is we actually have so much history of this and we can at least see what's happened in the past and when you look at IBM and AT&T they both were massive antitrust cases. The one against IBM was dropped and it was dropped in as you say, in 1980. Well, what was going on in at that time, IBM was sort of considered invincible and unbeatable, but it was 1981 that the personal computer came around and within just a couple of years the world could see that the computing paradigm had change from main frames and minis to PCs lines client server and what have you. So IBM in just a couple of years went from being unbeatable, you can't compete with them, we have to break up with them to being incredibly vulnerable and in trouble and never fully recovered and is sort of a shell of what it once was. And so the market took care of that and no action was really necessary just by everybody thinking there was. The case of AT&T, they did act and they broke up the company and I would say, first question is, was that necessary? Well, lots of countries didn't do that and the reality is 1980 breaking it up into long distance and regional may have made some sense, but by the 1990 it was pretty clear that the telecom world was going to change dramatically from long distance and fixed wires services to internet services, data services, wireless services and all of these things that we're going to restructure the industry anyways. But AT& T one to me is very interesting because of the unintended consequences. And I would say that the main unintended consequence of that was America's competitiveness in telecommunications took a huge hit. And today, to this day telecommunications is dominated by European, Chinese and other firms. And the big American sort of players of the time AT&T which Western Electric became Lucent, Lucent is now owned by Nokia and is really out of it completely and most notably and compellingly Bell Labs, the Bell Labs once the world's most prominent research institution now also a shell of itself and as it was part of Lucent is also now owned by the Finnish company Nokia. So that restructuring greatly damaged America's core strength in telecommunications hardware and research and one can argue we've never recovered right through this 5IG today. So it's a very good example of the market taking care of, the big problem, but meddling leading to some unintended consequences that have hurt the American competitiveness and as we'll talk about, probably later, you can see some of that going on again today and in the past with Microsoft and Intel. >> Right, yeah, Bell Labs was an American gem, kind of like Xerox PARC and basically gone now. You mentioned Intel and Microsoft, Microsoft and Intel. As many people know, some young people don't, IBM unwillingly handed its monopoly to Intel and Microsoft by outsourcing the micro processor and operating system, respectively. Those two companies ended up with IBM ironically, agreeing to take OS2 which was its proprietary operating system and giving Intel, Microsoft Windows not realizing that its ability to dominate a new disruptive market like PCs and operating systems had been vaporized to your earlier point by the new Wintel ecosystem. Now Dave, the government wanted to break Microsoft apart and split its OS business from its application software, in the case of Intel, Intel only had one business. You pointed out microprocessors so it couldn't bust it up, but take us through the history here and the consequences of each. >> Well, the Microsoft one is sort of a classic because the antitrust case which was raging in the sort of mid nineties and 1998 when it finally ended, those were the very, once again, everybody said, Bill Gates was unstoppable, no one could compete with Microsoft they'd buy them, destroy them, predatory pricing, whatever they were accusing of the attacks on Netscape all these sort of things. But those the very years where it was becoming clear first that Microsoft basically missed the early big years of the internet and then again, later missed all the early years of the mobile phone business going back to BlackBerrys and pilots and all those sorts of things. So here we are the government making the case that this company is unstoppable and you can't compete with them the very moment they're entirely on the defensive. And therefore wasn't surprising that that suit eventually was dropped with some minor concessions about Microsoft making it a little bit easier for third parties to work with them and treating people a little bit more, even handling perfectly good things that they did. But again, the more market took care of the problem far more than the antitrust activities did. The Intel one is also interesting cause it's sort of like the AT& T one. On the one hand antitrust actions made Intel much more likely and in fact, required to work with AMD enough to keep that company in business and having AMD lowered prices for consumers certainly probably sped up innovation in the personal computer business and appeared to have a lot of benefits for those early years. But when you look at it from a longer point of view and particularly when look at it again from a global point of view you see that, wow, they not so clear because that very presence of AMD meant that there's a lot more pressure on Intel in terms of its pricing, its profitability, its flexibility and its volumes. All the things that have made it harder for them to A, compete with chips made in Taiwan, let alone build them in the United States and therefore that long term effect of essentially requiring Intel to allow AMD to exist has undermined Intel's position globally and arguably has undermined America's position in the long run. And certainly Intel today is far more vulnerable to an ARM and Invidia to other specialized chips to China, to Taiwan all of these things are going on out there, they're less capable of resisting that than they would've been otherwise. So, you thought we had some real benefits with AMD and lower prices for consumers, but the long term unintended consequences are arguably pretty bad. >> Yeah, that's why we recently wrote in Intel two "Strategic To Fail", we'll see, Okay. now we come to 2022 and there are five companies with anti-trust targets on their backs. Although Microsoft seems to be the least susceptible to US government ironically intervention at this this point, but maybe not and we show "The Cincos Comas Club" in a homage to Russ Hanneman of the show "Silicon Valley" Apple, Microsoft, Google, and Amazon all with trillion dollar plus valuations. But meta briefly crossed that threshold like Mr. Hanneman lost a comma and is now well under that market cap probably around five or 600 million, sorry, billion. But under serious fire nonetheless Dave, people often don't realize the immense monopoly power that IBM had which relatively speaking when measured its percent of industry revenue or profit dwarf that of any company in tech ever, but the industry is much smaller then, no internet, no cloud. Does it call for a different approach this time around? How should we think about these five companies their market power, the implications of government action and maybe what you suggested more narrow action versus broad sweeping changes. >> Yeah, and there's a lot there. I mean, if you go back to the old days IBM had what, 70% of the computer business globally and AT&T had 90% or so of the American telecom market. So market shares that today's players can only dream of. Intel and Microsoft had 90% of the personal computer market. And then you look at today the big five and as wealthy and as incredibly successful as they've been, you sort of have almost the argument that's wrong on the face of it. How can five companies all of which compete with each other to at least some degree, how can they all be monopolies? And the reality is they're not monopolies, they're all oligopolies that are very powerful firms, but none of them have an outright monopoly on anything. There are competitors in all the spaces that they're in and increasing and probably increasingly so. And so, yeah, I think people conflate the extraordinary success of the companies with this belief that therefore they are monopolist and I think they're far less so than those in the past. >> Great, all right, I want to do a quick drill down to cloud computing, it's a key component of digital business infrastructure in his book, "Seeing Digital", Dave Moschella coined a term the matrix or the key which is really referred to the key technology platforms on which people are going to build digital businesses. Dave, we joke you should have called it the metaverse you were way ahead of your time. But I want to look at this ETR chart, we show spending momentum or net score on the vertical access market share or pervasiveness in the dataset on the horizontal axis. We show this view a lot, we put a dotted line at the 40% mark which indicates highly elevated spending. And you can sort of see Microsoft in the upper right, it's so far up to the right it's hidden behind the January 22 and AWS is right there. Those two dominate the cloud far ahead of the pack including Google Cloud. Microsoft and to a lesser extent AWS they dominate in a lot of other businesses, productivity, collaboration, database, security, video conferencing. MarTech with LinkedIn PC software et cetera, et cetera, Googles or alphabets of business of course is ads and we don't have similar spending data on Apple and Facebook, but we know these companies dominate their respective business. But just to give you a sense of the magnitude of these companies, here's some financial data that's worth looking at briefly. The table ranks companies by market cap in trillions that's the second column and everyone in the club, but meta and each has revenue well over a hundred billion dollars, Amazon approaching half a trillion dollars in revenue. The operating income and cash positions are just mind boggling and the cash equivalents are comparable or well above the revenues of highly successful tech companies like Cisco, Dell, HPE, Oracle, and Salesforce. They're extremely profitable from an operating income standpoint with the clear exception of Amazon and we'll come back to that in a moment and we show the revenue multiples in the last column, Apple, Microsoft, and Google, just insane. Dave, there are other equally important metrics, CapX is one which kind of sets the stage for future scale and there are other measures. >> Yeah, including our research and development where those companies are spending hundreds of billions of dollars over the years. And I think it's easy to look at those numbers and just say, this doesn't seem right, how can any companies have so much and spend so much? But if you think of what they're actually doing, those companies are building out the digital infrastructure of essentially the entire world. And I remember once meeting some folks at Google, and they said, beyond AI, beyond Search, beyond Android, beyond all the specific things we do, the biggest thing we're actually doing is building a physical infrastructure that can deliver search results on any topic in microseconds and the physical capacity they built costs those sorts of money. And when people start saying, well, we should have lots and lots of smaller companies well, that sounds good, yeah, it's all right, but where are those companies going to get the money to build out what needs to be built out? And every country in the world is trying to build out its digital infrastructure and some are going to do it much better than others. >> I want to just come back to that chart on Amazon for a bit, notice their comparatively tiny operating profit as a percentage of revenue, Amazon is like Bezos giant lifestyle business, it's really never been that profitable like most retail. However, there's one other financial data point around Amazon's business that we want to share and this chart here shows Amazon's operating profit in the blue bars and AWS's in the orange. And the gray line is the percentage of Amazon's overall operating profit that comes from AWS. That's the right most access, so last quarter we were well over a hundred percent underscoring the power of AWS and the horrendous margins in retail. But AWS is essentially funding Amazon's entrance into new markets, whether it's grocery or movies, Bezos moves into space. Dave, a while back you collaborated with us and we asked our audience, what could disrupt Amazon? And we came up with your detailed help, a number of scenarios as shown here. And we asked the audience to rate the likelihood of each scenario in terms of its likelihood of disrupting Amazon with a 10 being highly likely on average the score was six with complacency, arrogance, blindness, you know, self-inflicted wounds really taking the top spot with 6.5. So Dave is breaking up Amazon the right formula in your view, why or why not? >> Yeah, there's a couple of things there. The first is sort of the irony that when people in the sort of regulatory world talk about the power of Amazon, they almost always talk about their power in consumer markets, whether it's books or retail or impact on malls or main street shops or whatever and as you say that they make very little money doing that. The interest people almost never look at the big cloud battle between Amazon, Microsoft and lesser extent Google, Alibaba others, even though that's where they're by far highest market share and pricing power and all those things are. So the regulatory focus is sort of weird, but you know, the consumer stuff obviously gets more appeal to the general public. But that survey you referred to me was interesting because one of the challenges I sort of sent myself I was like okay, well, if I'm going to say that IBM case, AT&T case, Microsoft's case in all those situations the market was the one that actually minimized the power of those firms and therefore the antitrust stuff wasn't really necessary. Well, how true is that going to be again, just cause it's been true in the past doesn't mean it's true now. So what are the possible scenarios over the 2020s that might make it all happen again? And so each of those were sort of questions that we put out to others, but the ones that to me by far are the most likely I mean, they have the traditional one of company cultures sort of getting fat and happy and all, that's always the case, but the more specific ones, first of all by far I think is China. You know, Amazon retail is a low margin business. It would be vulnerable if it didn't have the cloud profits behind it, but imagine a year from now two years from now trade tensions with China get worse and Christmas comes along and China just says, well, you know, American consumers if you want that new exercise bike or that new shoes or clothing, well, anything that we make well, actually that's not available on Amazon right now, but you can get that from Alibaba. And maybe in America that's a little more farfetched, but in many countries all over the world it's not farfetched at all. And so the retail divisions vulnerability to China just seems pretty obvious. Another possible disruption, Amazon has spent billions and billions with their warehouses and their robots and their automated inventory systems and all the efficiencies that they've done there, but you could argue that maybe someday that's not really necessary that you have Search which finds where a good is made and a logistical system that picks that up and delivers it to customers and why do you need all those warehouses anyways? So those are probably the two top one, but there are others. I mean, a lot of retailers as they get stronger online, maybe they start pulling back some of the premium products from Amazon and Amazon takes their cut of whatever 30% or so people might want to keep more of that in house. You see some of that going on today. So the idea that the Amazon is in vulnerable disruption is probably is wrong and as part of the work that I'm doing, as part of stuff that I do with Dave and SiliconANGLE is how's that true for the others too? What are the scenarios for Google or Apple or Microsoft and the scenarios are all there. And so, will these companies be disrupted as they have in the past? Well, you can't say for sure, but the scenarios are certainly plausible and I certainly wouldn't bet against it and that's what history tells us. And it could easily happen once again and therefore, the antitrust should at least be cautionary and humble and realize that maybe they don't need to act as much as they think. >> Yeah, now, one of the things that you mentioned in your piece was felt like narrow remedies, were more logical. So you're not arguing for totally Les Affaire you're pushing for remedies that are more targeted in scope. And while the EU just yesterday announced new rules to limit the power of tech companies and we showed the article, some comments here the regulators they took the social media to announce a victory and they had a press conference. I know you watched that it was sort of a back slapping fest. The comments however, that we've sort of listed here are mixed, some people applauded, but we saw many comments that were, hey, this is a horrible idea, this was rushed together. And these are going to result as you say in unintended consequences, but this is serious stuff they're talking about applying would appear to be to your point or your prescription more narrowly defined restrictions although a lot of them to any company with a market cap of more than 75 billion Euro or turnover of more than 77.5 billion Euro which is a lot of companies and imposing huge penalties for violations up to 20% of annual revenue for repeat offenders, wow. So again, you've taken a brief look at these developments, you watched the press conference, what do you make of this? This is an application of more narrow restrictions, but in your quick assessment did they get it right? >> Yeah, let's break that down a little bit, start a little bit of history again and then get to Europe because although big sweeping breakups of the type that were proposed for IBM, Microsoft and all weren't necessary that doesn't mean that the government didn't do some useful things because they did. In the case of IBM government forces in Europe and America basically required IBM to make it easier for companies to make peripherals type drives, disc drives, printers that worked with IBM mainframes. They made them un-bundle their software pricing that made it easier for database companies and others to sell their of products. With AT&T it was the government that required AT&T to actually allow other phones to connect to the network, something they argued at the time would destroy security or whatever that it was the government that required them to allow MCI the long distance carrier to connect to the AT network for local deliveries. And with that Microsoft and Intel the government required them to at least treat their suppliers more even handly in terms of pricing and policies and support and such things. So the lessons out there is the big stuff wasn't really necessary, but the little stuff actually helped a lot and I think you can see the scenarios and argue in the piece that there's little stuff that can be done today in all the cases for the big five, there are things that you might want to consider the companies aren't saints they take advantage of their power, they use it in ways that sometimes can be reigned in and make for better off overall. And so that's how it brings us to the European piece of it. And to me, the European piece is much more the bad scenario of doing too much than the wiser course of trying to be narrow and specific. What they've basically done is they have a whole long list of narrow things that they're all trying to do at once. So they want Amazon not to be able to share data about its selling partners and they want Apple to open up their app store and they don't want people Google to be able to share data across its different services, Android, Search, Mail or whatever. And they don't want Facebook to be able to, they want to force Facebook to open up to other messaging services. And they want to do all these things for all the big companies all of which are American, and they want to do all that starting next year. And to me that looks like a scenario of a lot of difficult problems done quickly all of which might have some value if done really, really well, but all of which have all kinds of risks for the unintended consequence we've talked before and therefore they seem to me being too much too soon and the sort of problems we've seen in the past and frankly to really say that, I mean, the Europeans would never have done this to the companies if they're European firms, they're doing this because they're all American firms and the sort of frustration of Americans dominance of the European tech industry has always been there going back to IBM, Microsoft, Intel, and all of them. But it's particularly strong now because the tech business is so big. And so I think the politics of this at a time where we're supposedly all this great unity of America and NATO and Europe in regards to Ukraine, having the Europeans essentially go after the most important American industry brings in the geopolitics in I think an unavoidable way. And I would think the story is going to get pretty tense over the next year or so and as you say, the Europeans think that they're taking massive actions, they think they're doing the right thing. They think this is the natural follow on to the GDPR stuff and even a bigger version of that and they think they have more to come and they see themselves as the people taming big tech not just within Europe, but for the world and absent any other rules that they may pull that off. I mean, GDPR has indeed spread despite all of its flaws. So the European thing which it doesn't necessarily get huge attention here in America is certainly getting attention around the world and I would think it would get more, even more going forward. >> And the caution there is US public policy makers, maybe they can provide, they will provide a tailwind maybe it's a blind spot for them and it could be a template like you say, just like GDPR. Okay, Dave, we got to leave it there. Thanks for coming on the program today, always appreciate your insight and your views, thank you. >> Hey, thanks a lot, Dave. >> All right, don't forget these episodes are all available as podcast, wherever you listen. All you got to do is search, "Breaking Analysis Podcast". Check out ETR website, etr.ai. We publish every week on wikibon.com and siliconangle.com. And you can email me david.vellante@siliconangle.com or DM me @davevellante. Comment on my LinkedIn post. This is Dave Vellante for Dave Michelle for "theCUBE Insights" powered by ETR. Have a great week, stay safe, be well and we'll see you next time. (slow tempo music)

(upbeat music) >> Welcome to the CUBE Conversation. I'm Lisa Martin. I'm talking next with Sanzio Bassini, the Head of High Performance Computing at Cineca, at DELL technologies customer. Sanzio, welcome to the CUBE. >> Thank you, it's a pleasure, it's a pleasure. >> Likewise, nice to see you. So tell us a little bit about Cineca. This is a large computing center, but a very large Italian nonprofit consortium. Tell us about it. >> Yes, Cineca been founded 50 years ago, from the university systems in Italy. For a statutory mission, which is to support, the scientific discovery, and the industry innovations, using the High Performance Computing and the correlated methodologies like a, Artificial Intelligence, which is one of the, you see the more, in a, in a adopted in those days, but together with the big data processing and and simulation. Yes, we are a consortium, which means that this is a private not-for-profit organizations. Currently, our member of the consortium, almost all the universities in Italy and also all the national agencies for those selected structures. Uh. The main quarter of Cineca is in Bologna, which is in the heart Nation, with the bunch of presence in Milan, in Rome and in Naples, so we are a consultation organization. >> And I also read that you were, are the top 10 out of the top 500 of the world's fastest super computers. That's a pretty big accomplishment. >> Yes. That is a part of our institutional missions, the last 10 to 15 years we have been to say, frequent flyers in the top 10. There been at least two, three systems that have been ranked at the top 10. Apart, the.., whatever would be the meaning of such an advance market, there's a lot of its criticalities. We are well aware. The idea is that we're enabling the scientific discovery, by means of providing the most advanced systems and the co-designing, the most advanced HPC systems to promote and support the, what is the, excellence in science. And that being part of European high-performance computing IT system. That is the case. >> Excellent. Now, talk to me about some of the challenges that Cineca is trying to solve in particular, the Human Brain Project. Talk to us a little bit about that and how you're leveraging high-performance computing to accelerate scientific discovery. >> Um, The Human Brain Project is one of the flagship project that has been co-founded by the European commission and that the participating member states. Is not as another situations that are undertaking, it's definitely a joint collaboration between members states and the European commission. There are two different right now, flagships together with another, that is in progress, which is that the quantum of flagship, the first two flagship abroad that that has been lost. The commission for operation with the participating states has been one on the digraph vein on which also we are participating in directly together with the CNR, is the national business counselor. And the second for which we are core partners of the HPC that is, the Human Brain Project. That, that is a big flagship, one million offer, of newer investment, co-founded by the participating states and that the European commission. The project it's going to set up, in what to do be the, third strategic grant agreement that they will go over the next three years, the good, the complete that the, the whole process. Then we see what is going to happen at Africa. We thought that their would be some others progress offer these big projects. It's project that would combine both the technology issues, like the designing the off high-performance computing systems that meet the requirements of the community and the big challenge, scientific challenges correlated to the physiological functions of the human brain center, including the different farm show survey to do with the behavior of the human brain. A from the pathological point of view, from the physiological point of view, that better understand the could be the way for, for a facing that. Let's say the pathology, some of those are very much correlated with respect to aging, and that it would impact the, the health, the public health systems. Some other that are correlating with what would be the support for the physiological knowledge of the, of the human brains. And finally that they, let me say, technological transfer stuff that represented the knowing off at the physiological, behavior of the human brain. Just to use a sort of metaphor to have happen from the point of view of there computational performance, the human brain is a, a, a, more than Exoscale systems, but with a energy consumption, which is very low, we are talking about some hundreds of Watts. So some hundreds of watts of energy, would provide a an extreme and computational performance. So if would could organized the technology of the high-performance computing in terms of interconnections now we're morphing the computing systems and exploitations of that kind of technologies, in I build a system that it might provide the computational power that would represent a tremendous and tremendous step ahead, in order to facing the big challenges of our base, like energies, personalized medicine, try not to change food for all those kinds of big socioeconomic challenges that we are facing. >> Yes I was reading that besides, sorry Sanzio I was reading that besides the Human Brain Project, there are other projects going on, such as that you mentioned, I'd like to understand how Cineca is working with Dell technologies. You have to translate, as you've mentioned a minute ago, the scientific requirements for discovery into high-performance computing requirements. Talk to me about how you've been doing that with partners like Dell technologies. >> Yes, in particularly in our computing architectures, we had the need to address the capability to facing the data processing involved with backed off the Human Brain Project and general speaking that is backed off the science vendor, that would combine the capability also to provide the cloud access to the system. So by main soft containers technologies and the capability also, to address what would be the creation of a Federation. So Piper problems with people proceeded in a new world. So at the end that the requirements and the terms of reference of the would matter will decline and the terms of a system that would be capable to manage, let's say, in a holistic approach, the data processing, the cloud computing services and the opportunity before for being integrated that in a Federation of HSBC system in Europe's, and with this backed off, that kind of thing, we manage a competitive dialogue procurement processor, I think I the sentence would share together with the different potential technology providers, what would be the visuals and those are the constraints (inaudible) and those other kinds of constraints like, I don't want to say, I mean, environmental kind of constraints and uh, sharing with this back of the technology provider what would it be the vision for this solution, in a very, let's say hard, the competitive dialogue, and at the end, results in a sort of, I don't want to say Darwinian processes, okay. So I mean, the survivors in terms of the different technology providers being Dell that shown the characteristics of the solution that it will be more, let's say compliant. And at the same time are flexible with respect of the combinations of very different constraints and requirements that has been the, the process that has been the outcomes of such a process. >> I like that you mentioned that Darwinian survival of the fittest and that Dell technologies has been, it sounds like a pretty flexible partner because you've got so many different needs and scientific needs to meet for different researchers. Talk to me about how you mentioned that this is a multi-national effort. How does Cineca serve and work with teams not only in Italy, but in other countries and from other institutes? >> Definitely the volume commitment that together with the, European member states is that by means of scientific merits and the peer review process, roughly speaking the arc of the production capacity, would be shared at the European level. That it's a commitment that, that there's been, that there's been a shared of that together with France, Germany, Spain, and, and with the London. So, I mean, our, half of our production capacity, it's a share of that at the European level, where also of course the Italian scientist can apply in the participates, but in a sort of offer emulations and the advanced competition for addressing what it would be the excellence in science. The remaining 50% of our production capacity is for, for the national community and, somehow to prepare and support the Italian community to be competitive on the worldwide scenario on the European and international scenario, uh that setting up would lead also to the agreement at the international level, with respect of some of the options that, that are promoted the progress in a US and in Japan also. So from this point of view, that mean that in some cases also the, access that it would come from researchers the best collaborations and the sharing options with the US researchers their or Japanese researchers in an open space. >> Open space for, it sounds like the Human Brain Project, which the HPC is powering, which has been around since 2013 is really facilitating global collaboration. Talk to me about some of the results that the high-performance computing environment has helped the Human Brain Project to achieve so far. >> The main outcomes that it will be consolidated in the next phase that will be need the by rural SPC that is the Jared undertaking um entities, that has been created for consolidating and for progressing the high-performance computing ecosystem in Europe. It represented by the Federations of high-performance computing systems at European level, there is a, a, an option that, that has been encapsulated and the elaborated inside the human brain flagship project which is called the FEHIPCSE that stand for Federation of a High-Performance Computing System in Europe. That uh provide the open service based on the two concepts on one, one is the sharing of the Heidi at a European level, so it means that the, the high demand of the users or researchers more properly. It's unique and Universal at the European level. That didn't mean better the same, we see identity management, education management with the open, and the access to the Cineca system, to the SARS system in France, to the unique system in, uh Germany to the, Diocese system in a Switzerland, to the Morocco System in a Spain. That is the part related to what will be the federated, the ID management, the others, et cetera, related to what will be the Federation off the data access. So from the point of view, again, the scientific community, mostly the community of Human Brain Project, but that will be open at other domains and other community, make sure that data in a seamless mode after European language, from the technological point of view, or let's say from the infrastructure point of view, very strong up, from the scientific point of view, uh what they think they may not, will be the most of the options is being supported by Cineca has to do with the two specific target. One is the elaboration of the data that are provided by the lands. The laws are a laboratory facility in that Florence. That is one of the four parts, and from the bottom view of the provisions of the data that is for the scattering, the, the data that would come from the mouse brains, that are use for, for (inaudible) And then the second part is for the Mayor scale studies of the cortex of the of the human brain, and that got add-on by a couple of groups that are believing that action from a European level their group of the National Researcher Counsel the CNR, that are the two main outcome on which we are in some out reference high-performance computing facilities for supporting that kind of research. Then their is in some situations they combinations of the performance a, capability of the Federation systems for addressing what will be the simulations of the overall human brain would take a lot of performance challenge simulation with bacteria that they would happen combining that they SPC facility as at European level. >> Right! So I was reading there's a case study by the way, on Cynic that Dell technologies has published. And some of the results you talked about, those that the HPC is facilitating research and results on epilepsy, spinal cord injury, brain prostheses for the blind, as well as new insights into autism. So incredibly important work that you're doing here for the Human Brain Project. One last question Sanzio, for you, what advice would you give to your peers who might be in similar situations that need to, to build and deploy and maintain high-performance computing environments? Where should they start? >> (coughs laughs) I think that at, at a certain point, that specific know how would became sort of a know how that is been, I mean, accumulated and then by some facilities and institutions around the world. There are the, the federal labs in US, the main nation model centers in Europe, the big facilities in Japan. And of course the, the big university facilities in China that are becoming, how do you say, evident and our progressively occupied increasing the space, that to say that that is somehow it, that, that, that the, those institutions would continues collaborate and sharing that there are periods I would expect off what to do, be the top level systems. Then there is a continuous sharing of uh knowledge, the experience best practices with respect off, let's say the technologies transfers towards productions and services and boosterism. Where the situation is big parenta, in the sense that, their are focused what it would be, uh the integration of the high-performance computing technology into their production workflow. And from the point of view, there is the sharing of the experience in order to provide the, a sort of, let's say, spreads and amplifications of the opportunity for supporting innovation. That is part of are solution means, in a Italy but it also, eh, er sort of um, see objective, that is addressed by the European options er supported by the European commission. I think that that sort of (inaudible) supply that in US, the, that will be coming there, sort of you see the max practice for the technology transfer to support the innovation. >> Excellent, that sharing and that knowledge transfer and collaboration. It seems to be absolutely fundamental and the environment that you've built, facilitates that. Sanzio thank you so much for sharing with us, what Cineca is doing and the great research that's going on there, and across a lot of disciplines, we appreciate you joining the program today. Thank you. >> Thank you, it's been a pleasure, thank you very much for the opportunity. >> Likewise, for Sanzio Bassini. I'm Lisa Martin. You're watching this cube conversation. (calming music)