>>From the Cube Studios in Palo Alto in Boston, bringing you data driven insights from the cube and etr. This is breaking analysis with Dave Ante. >>Have you ever been driving on the highway and traffic suddenly slows way down and then after a little while it picks up again and you're cruising along and you're thinking, Okay, hey, that was weird. But it's clear sailing now. Off we go, only to find out in a bit that the traffic is building up ahead again, forcing you to pump the brakes as the traffic pattern ebbs and flows well. Welcome to the Seesaw economy. The fed induced fire that prompted an unprecedented rally in tech is being purposefully extinguished now by that same fed. And virtually every sector of the tech industry is having to reset its expectations, including the cloud segment. Hello and welcome to this week's Wikibon Cube Insights powered by etr. In this breaking analysis will review the implications of the earnings announcements from the big three cloud players, Amazon, Microsoft, and Google who announced this week. >>And we'll update you on our quarterly IAS forecast and share the latest from ETR with a focus on cloud computing. Now, before we get into the new data, we wanna review something we shared with you on October 14th, just a couple weeks back, this is sort of a, we told you it was coming slide. It's an XY graph that shows ET R'S proprietary net score methodology on the vertical axis. That's a measure of spending momentum, spending velocity, and an overlap or presence in the dataset that's on the X axis. That's really a measure of pervasiveness. In the survey, the table, you see that table insert there that shows Wiki Bond's Q2 estimates of IAS revenue for the big four hyperscalers with their year on year growth rates. Now we told you at the time, this is data from the July TW 22 ETR survey and the ETR hadn't released its October survey results at that time. >>This was just a couple weeks ago. And while we couldn't share the specific data from the October survey, we were able to get a glimpse and we depicted the slowdown that we saw in the October data with those dotted arrows kind of down into the right, we said at the time that we were seeing and across the board slowdown even for the big three cloud vendors. Now, fast forward to this past week and we saw earnings releases from Alphabet, Microsoft, and just last night Amazon. Now you may be thinking, okay, big deal. The ETR survey data didn't really tell us anything we didn't already know. But judging from the negative reaction in the stock market to these earnings announcements, the degree of softness surprised a lot of investors. Now, at the time we didn't update our forecast, it doesn't make sense for us to do that when we're that close to earning season. >>And now that all the big three ha with all the big four with the exception of Alibaba have announced we've, we've updated. And so here's that data. This chart lays out our view of the IS and PAs worldwide revenue. Basically it's cloud infrastructure with an attempt to exclude any SaaS revenue so we can make an apples to apples comparison across all the clouds. Now the reason that actual is in quotes is because Microsoft and Google don't report IAS revenue, but they do give us clues and kind of directional commentary, which we then triangulate with other data that we have from the channel and ETR surveys and just our own intelligence. Now the second column there after the vendor name shows our previous estimates for q3, and then next to that we show our actuals. Same with the growth rates. And then we round out the chart with that lighter blue color highlights, the full year estimates for revenue and growth. >>So the key takeaways are that we shaved about $4 billion in revenue and roughly 300 basis points of growth off of our full year estimates. AWS had a strong July but exited Q3 in the mid 20% growth rate year over year. So we're using that guidance, you know, for our Q4 estimates. Azure came in below our earlier estimates, but Google actually exceeded our expectations. Now the compression in the numbers is in our view of function of the macro demand climate, we've made every attempt to adjust for constant currency. So FX should not be a factor in this data, but it's sure you know that that ma the the, the currency effects are weighing on those companies income statements. And so look, this is the fundamental dynamic of a cloud model where you can dial down consumption when you need to and dial it up when you need to. >>Now you may be thinking that many big cloud customers have a committed level of spending in order to get better discounts. And that's true. But what's happening we think is they'll reallocate that spend toward, let's say for example, lower cost storage tiers or they may take advantage of better price performance processors like Graviton for example. That is a clear trend that we're seeing and smaller companies that were perhaps paying by the drink just on demand, they're moving to reserve instance models to lower their monthly bill. So instead of taking the easy way out and just spending more companies are reallocating their reserve capacity toward lower cost. So those sort of lower cost services, so they're spending time and effort optimizing to get more for, for less whereas, or get more for the same is really how we should, should, should phrase it. Whereas during the pandemic, many companies were, you know, they perhaps were not as focused on doing that because business was booming and they had a response. >>So they just, you know, spend more dial it up. So in general, as they say, customers are are doing more with, with the same. Now let's look at the growth dynamic and spend some time on that. I think this is important. This data shows worldwide quarterly revenue growth rates back to Q1 2019 for the big four. So a couple of interesting things. The data tells us during the pandemic, you saw both AWS and Azure, but the law of large numbers and actually accelerate growth. AWS especially saw progressively increasing growth rates throughout 2021 for each quarter. Now that trend, as you can see is reversed in 2022 for aws. Now we saw Azure come down a bit, but it's still in the low forties in terms of percentage growth. While Google actually saw an uptick in growth this last quarter for GCP by our estimates as GCP is becoming an increasingly large portion of Google's overall cloud business. >>Now, unfortunately Google Cloud continues to lose north of 850 million per quarter, whereas AWS and Azure are profitable cloud businesses even though Alibaba is suffering its woes from China. And we'll see how they come in when they report in mid-November. The overall hyperscale market grew at 32% in Q3 in terms of worldwide revenue. So the slowdown isn't due to the repatriation or competition from on-prem vendors in our view, it's a macro related trend. And cloud will continue to significantly outperform other sectors despite its massive size. You know, on the repatriation point, it just still doesn't show up in the data. The A 16 Z article from Sarah Wong and Martin Martin Kasa claiming that repatriation was inevitable as a means to lower cost of good sold for SaaS companies. You know, while that was thought provoking, it hasn't shown up in the numbers. And if you read the financial statements of both AWS and its partners like Snowflake and you dig into the, to the, to the quarterly reports, you'll see little notes and comments with their ongoing negotiations to lower cloud costs for customers. >>AWS and no doubt execs at Azure and GCP understand that the lifetime value of a customer is worth much more than near term gross margin. And you can expect the cloud vendors to strike a balance between profitability, near term profitability anyway and customer attention. Now, even though Google Cloud platform saw accelerated growth, we need to put that in context for you. So GCP, by our estimate, has now crossed over the $3 billion for quarter market actually did so last quarter, but its growth rate accelerated to 42% this quarter. And so that's a good sign in our view. But let's do a quick little comparison with when AWS and Azure crossed the $3 billion mark and compare their growth rates at the time. So if you go back to to Q2 2016, as we're showing in this chart, that's around the time that AWS hit 3 billion per quarter and at the same time was growing at 58%. >>Azure by our estimates crossed that mark in Q4 2018 and at that time was growing at 67%. Again, compare that to Google's 42%. So one would expect Google's growth rate would be higher than its competitors at this point in the MO in the maturity of its cloud, which it's, you know, it's really not when you compared to to Azure. I mean they're kind of con, you know, comparable now but today, but, but you'll go back, you know, to that $3 billion mark. But more so looking at history, you'd like to see its growth rate at this point of a maturity model at least over 50%, which we don't believe it is. And one other point on this topic, you know, my business friend Matt Baker from Dell often says it's not a zero sum game, meaning there's plenty of opportunity exists to build value on top of hyperscalers. >>And I would totally agree it's not a dollar for dollar swap if you can continue to innovate. But history will show that the first company in makes the most money. Number two can do really well and number three tends to break even. Now maybe cloud is different because you have Microsoft software estate and the power behind that and that's driving its IAS business and Google ads are funding technology buildouts for, for for Google and gcp. So you know, we'll see how that plays out. But right now by this one measurement, Google is four years behind Microsoft in six years behind aws. Now to the point that cloud will continue to outpace other markets, let's, let's break this down a bit in spending terms and see why this claim holds water. This is data from ET r's latest October survey that shows the granularity of its net score or spending velocity metric. >>The lime green is new adoptions, so they're adding the platform, the forest green is spending more 6% or more. The gray bars spending is flat plus or minus, you know, 5%. The pinkish colors represent spending less down 6% or worse. And the bright red shows defections or churn of the platform. You subtract the reds from the greens and you get what's called net score, which is that blue dot that you can see on each of the bars. So what you see in the table insert is that all three have net scores above 40%, which is a highly elevated measure. Microsoft's net scores above 60% AWS well into the fifties and GCP in the mid forties. So all good. Now what's happening with all three is more customers are keep keeping their spending flat. So a higher percentage of customers are saying, our spending is now flat than it was in previous quarters and that's what's accounting for the compression. >>But the churn of all three, even gcp, which we reported, you know, last quarter from last quarter survey was was five x. The other two is actually very low in the single digits. So that might have been an anomaly. So that's a very good sign in our view. You know, again, customers aren't repatriating in droves, it's just not a trend that we would bet on, maybe makes for a FUD or you know, good marketing head, but it's just not a big deal. And you can't help but be impressed with both Microsoft and AWS's performance in the survey. And as we mentioned before, these companies aren't going to give up customers to try and preserve a little bit of gross margin. They'll do what it takes to keep people on their platforms cuz they'll make up for it over time with added services and improved offerings. >>Now, once these companies acquire a customer, they'll be very aggressive about keeping them. So customers take note, you have negotiating leverage, so use it. Okay, let's look at another cut at the cloud market from the ETR data set. Here's the two dimensional view, again, it's back, it's one of our favorites. Net score or spending momentum plotted against presence. And the data set, that's the x axis net score on the, on the vertical axis, this is a view of et r's cloud computing sector sector. You can see we put that magic 40% dotted red line in the table showing and, and then that the table inserts shows how the data are plotted with net score against presence. I e n in the survey, notably only the big three are above the 40% line of the names that we're showing here. The oth there, there are others. >>I mean if you put Snowflake on there, it'd be higher than any of these names, but we'll dig into that name in a later breaking analysis episode. Now this is just another way of quantifying the dominance of AWS and Azure, not only relative to Google, but the other cloud platforms out there. So we've, we've taken the opportunity here to plot IBM and Oracle, which both own a public cloud. Their performance is largely a reflection of them migrating their install bases to their respective public clouds and or hybrid clouds. And you know, that's fine, they're in the game. That's a point that we've made, you know, a number of times they're able to make it through the cloud, not whole and they at least have one, but they simply don't have the business momentum of AWS and Azure, which is actually quite impressive because AWS and Azure are now as large or larger than IBM and Oracle. >>And to show this type of continued growth that that that Azure and AWS show at their size is quite remarkable and customers are starting to recognize the viability of on-prem hi, you know, hybrid clouds like HPE GreenLake and Dell's apex. You know, you may say, well that's not cloud, but if the customer thinks it is and it was reporting in the survey that it is, we're gonna continue to report this view. You know, I don't know what's happening with H P E, They had a big down tick this quarter and I, and I don't read too much into that because their end is still pretty small at 53. So big fluctuations are not uncommon with those types of smaller ends, but it's over 50. So, you know, we did notice a a a negative within a giant public and private sector, which is often a, a bellwether giant public private is big public companies and large private companies like, like a Mars for example. >>So it, you know, it looks like for HPE it could be an outlier. We saw within the Fortune 1000 HPE E'S cloud looked actually really good and it had good spending momentum in that sector. When you di dig into the industry data within ETR dataset, obviously we're not showing that here, but we'll continue to monitor that. Okay, so where's this Leave us. Well look, this is really a tactical story of currency and macro headwinds as you can see. You know, we've laid out some of the points on this slide. The action in the stock market today, which is Friday after some of the soft earnings reports is really robust. You know, we'll see how it ends up in the day. So maybe this is a sign that the worst is over, but we don't think so. The visibility from tech companies is murky right now as most are guiding down, which indicates that their conservative outlook last quarter was still too optimistic. >>But as it relates to cloud, that platform is not going anywhere anytime soon. Sure, there are potential disruptors on the horizon, especially at the edge, but we're still a long ways off from, from the possibility that a new economic model emerges from the edge to disrupt the cloud and the opportunities in the cloud remain strong. I mean, what other path is there? Really private cloud. It was kind of a bandaid until the on-prem guys could get their a as a service models rolled out, which is just now happening. The hybrid thing is real, but it's, you know, defensive for the incumbents until they can get their super cloud investments going. Super cloud implying, capturing value above the hyperscaler CapEx, you know, call it what you want multi what multi-cloud should have been, the metacloud, the Uber cloud, whatever you like. But there are opportunities to play offense and that's clearly happening in the cloud ecosystem with the likes of Snowflake, Mongo, Hashi Corp. >>Hammer Spaces is a startup in this area. Aviatrix, CrowdStrike, Zeke Scaler, Okta, many, many more. And even the projects we see coming out of enterprise players like Dell, like with Project Alpine and what Pure Storage is doing along with a number of other of the backup vendors. So Q4 should be really interesting, but the real story is the investments that that companies are making now to leverage the cloud for digital transformations will be paying off down the road. This is not 1999. We had, you know, May might have had some good ideas and admittedly at a lot of bad ones too, but you didn't have the infrastructure to service customers at a low enough cost like you do today. The cloud is that infrastructure and so far it's been transformative, but it's likely the best is yet to come. Okay, let's call this a rap. >>Many thanks to Alex Morrison who does production and manages the podcast. Also Can Schiffman is our newest edition to the Boston Studio. Kristin Martin and Cheryl Knight helped get the word out on social media and in our newsletters. And Rob Ho is our editor in chief over@siliconangle.com, who does some wonderful editing for us. Thank you. Remember, all these episodes are available as podcasts. Wherever you listen, just search breaking analysis podcast. I publish each week on wiki bond.com at silicon angle.com. And you can email me at David dot valante@siliconangle.com or DM me at Dante or comment on my LinkedIn posts. And please do checkout etr.ai. They got the best survey data in the enterprise tech business. This is Dave Valante for the Cube Insights powered by etr. Thanks for watching and we'll see you next time on breaking analysis.

>>from around the globe. It's the Cube presenting enterprise. Digital resilience on hybrid and multi cloud Brought to You by Iota Ho. Hello, everyone, and welcome to our continuing Siri's covering data automation brought to you by Io Tahoe. Today we're gonna look at how to ensure enterprise resilience for hybrid and multi cloud. Let's welcome in age. Eva Hora, who is the CEO of Iota A J. Always good to see you again. Thanks for coming on. >>Great to be back. David Pleasure. >>And he's joined by Fozzy Coons, who is a global principal architect for financial services. The vertical of financial services. That red hat. He's got deep experiences in that sector. Welcome, Fozzie. Good to see you. >>Thank you very much. Happy to be here. >>Fancy. Let's start with you. Look, there are a lot of views on cloud and what it is. I wonder if you could explain to us how you think about what is a hybrid cloud and and how it works. >>Sure, yes. So the hybrid cloud is a 90 architecture that incorporates some degree off workload, possibility, orchestration and management across multiple clouds. Those clouds could be private cloud or public cloud or even your own data centers. And how does it all work? It's all about secure interconnectivity and on demand. Allocation of resources across clouds and separate clouds can become hydrate when they're similarly >>interconnected. And >>it is that interconnectivity that allows the workloads workers to be moved and how management can be unified in off the street. You can work and how well you have. These interconnections has a direct impact on how well your hybrid cloud will work. >>Okay, so we'll fancy staying with you for a minute. So in the early days of Cloud that turned private Cloud was thrown a lot around a lot, but often just meant virtualization of an on PREM system and a network connection to the public cloud. Let's bring it forward. What, in your view, does a modern hybrid cloud architecture look like? >>Sure. So for modern public clouds, we see that, um, teams organizations need to focus on the portability off applications across clouds. That's very important, right? And when organizations build applications, they need to build and deploy these applications as small collections off independently, loosely coupled services, and then have those things run on the same operating system which means, in other words, running it on Lenox everywhere and building cloud native applications and being able to manage and orchestrate thes applications with platforms like KUBERNETES or read it open shit, for example. >>Okay, so that Z, that's definitely different from building a monolithic application that's fossilized and and doesn't move. So what are the challenges for customers, you know, to get to that modern cloud? Aziz, you've just described it. Is it skill sets? Is that the ability to leverage things like containers? What's your view there? >>So, I mean, from what we've seen around around the industry, especially around financial services, where I spent most of my time, we see that the first thing that we see is management right now because you have all these clouds and all these applications, you have a massive array off connections off interconnections. You also have massive array off integrations, possibility and resource allocations as well, and then orchestrating all those different moving pieces. Things like storage networks and things like those are really difficult to manage, right? That's one. What s O Management is the first challenge. The second one is workload, placement, placement. Where do you place this? How do you place this cloud? Native applications. Do you or do you keep on site on Prem? And what do you put in the cloud? That is the the the other challenge. The major one. The third one is security. Security now becomes the key challenge and concern for most customers. And we could talk about how hundreds? Yeah, >>we're definitely gonna dig into that. Let's bring a J into the conversation. A J. You know, you and I have talked about this in the past. One of the big problems that virtually every companies face is data fragmentation. Um, talk a little bit about how I owe Tahoe unifies data across both traditional systems legacy systems. And it connects to these modern I t environments. >>Yeah, sure, Dave. I mean, fancy just nailed it. There used to be about data of the volume of data on the different types of data. But as applications become or connected and interconnected at the location of that data really matters how we serve that data up to those those app. So working with red hat in our partnership with Red Hat being able Thio, inject our data Discovery machine learning into these multiple different locations. Would it be in AWS on IBM Cloud or A D. C p R. On Prem being able thio Automate that discovery? I'm pulling that. That single view of where is all my data then allows the CEO to manage cast that can do things like one. I keep the data where it is on premise or in my Oracle Cloud or in my IBM cloud on Connect. The application that needs to feed off that data on the way in which you do that is machine learning. That learns over time is it recognizes different types of data, applies policies to declassify that data. Andi and brings it all together with automation. >>Right? And that's one of the big themes and we've talked about this on earlier episodes. Is really simplification really abstracting a lot of that heavy lifting away so we can focus on things A. J A. Z. You just mentioned e nifaz e. One of the big challenges that, of course, we all talk about his governance across thes disparity data sets. I'm curious as your thoughts. How does Red Hat really think about helping customers adhere to corporate edicts and compliance regulations, which, of course, are are particularly acute within financial services. >>Oh, yeah, Yes. So for banks and the payment providers, like you've just mentioned their insurers and many other financial services firms, Um, you know, they have to adhere Thio standards such as a PC. I. D. S s in Europe. You've got the G g d p g d p r, which requires strange and tracking, reporting documentation. And you know, for them to to remain in compliance and the way we recommend our customers to address these challenges is by having an automation strategy. Right. And that type of strategy can help you to improve the security on compliance off the organization and reduce the risk after the business. Right. And we help organizations build security and compliance from the start without consulting services residencies. We also offer courses that help customers to understand how to address some of these challenges. And that's also we help organizations build security into their applications without open sources. Mueller, where, um, middle offerings and even using a platform like open shift because it allows you to run legacy applications and also continue rights applications in a unified platform right And also that provides you with, you know, with the automation and the truly that you need to continuously monitor, manage and automate the systems for security and compliance >>purposes. Hey, >>Jay, anything. Any color you could add to this conversation? >>Yeah, I'm pleased. Badly brought up Open shift. I mean, we're using open shift to be able. Thio, take that security application of controls to to the data level. It's all about context. So, understanding what data is there being able to assess it to say who should have access to it. Which application permission should be applied to it. Um, that za great combination of Red Hat tonight. Tahoe. >>But what about multi Cloud? Doesn't that complicate the situation even even further? Maybe you could talk about some of the best practices to apply automation across not only hybrid cloud, but multi >>cloud a swell. Yeah, sure. >>Yeah. So the right automation solution, you know, can be the difference between, you know, cultivating an automated enterprise or automation caress. And some of the recommendations we give our clients is to look for an automation platform that can offer the first thing is complete support. So that means have an automation solution that provides that provides, um, you know, promotes I t availability and reliability with your platform so that you can provide, you know, enterprise great support, including security and testing, integration and clear roadmaps. The second thing is vendor interoperability interoperability in that you are going to be integrating multiple clouds. So you're going to need a solution that can connect to multiple clouds. Simples lee, right? And with that comes the challenge off maintain ability. So you you you're going to need to look into a automation Ah, solution that that is easy to learn or has an easy learning curve. And then the fourth idea that we tell our customers is scalability in the in the hybrid cloud space scale is >>is >>a big, big deal here, and you need a to deploy an automation solution that can span across the whole enterprise in a constituent, consistent manner, right? And then also, that allows you finally to, uh, integrate the multiple data centers that you have, >>So A J I mean, this is a complicated situation, for if a customer has toe, make sure things work on AWS or azure or Google. Uh, they're gonna spend all their time doing that, huh? What can you add really? To simplify that that multi cloud and hybrid cloud equation? >>Yeah. I could give a few customer examples here Warming a manufacturer that we've worked with to drive that simplification Onda riel bonuses for them is has been a reduction cost. We worked with them late last year to bring the cost bend down by $10 million in 2021 so they could hit that reduced budget. Andre, What we brought to that was the ability thio deploy using open shift templates into their different environments. Where there is on premise on bond or in as you mentioned, a W s. They had G cps well, for their marketing team on a cross, those different platforms being out Thio use a template, use pre built scripts to get up and running in catalog and discover that data within minutes. It takes away the legacy of having teams of people having Thio to jump on workshop cause and I know we're all on a lot of teens. The zoom cause, um, in these current times, they just sent me is in in of hours in the day Thio manually perform all of this. So yeah, working with red hat applying machine learning into those templates those little recipes that we can put that automation toe work, regardless of which location the data is in allows us thio pull that unified view together. Right? >>Thank you, Fozzie. I wanna come back to you. So the early days of cloud, you're in the big apple, you know, financial services. Really well. Cloud was like an evil word within financial services, and obviously that's changed. It's evolved. We talked about the pandemic, has even accelerated that, Um And when you really, you know, dug into it when you talk to customers about their experiences with security in the cloud it was it was not that it wasn't good. It was great, whatever. But it was different. And there's always this issue of skill, lack of skills and multiple tools suck up teams, they're really overburdened. But in the cloud requires new thinking. You've got the shared responsibility model you've got obviously have specific corporate requirements and compliance. So this is even more complicated when you introduce multiple clouds. So what are the differences that you can share from your experience is running on a sort of either on Prem or on a mono cloud, um, or, you know, and versus across clouds. What? What? What do you suggest there? >>Yeah, you know, because of these complexities that you have explained here, Miss Configurations and the inadequate change control the top security threats. So human error is what we want to avoid because is, you know, as your clouds grow with complexity and you put humans in the mix, then the rate off eras is going to increase, and that is going to exposure to security threat. So this is where automation comes in because automation will streamline and increase the consistency off your infrastructure management. Also application development and even security operations to improve in your protection, compliance and change control. So you want to consistently configure resources according to a pre approved um, you know, pre approved policies and you want to proactively maintain a to them in a repeatable fashion over the whole life cycle. And then you also want to rapid the identified system that require patches and and reconfiguration and automate that process off patching and reconfiguring so that you don't have humans doing this type of thing, right? And you want to be able to easily apply patches and change assistant settings. According Thio, Pre defined, based on like explained before, you know, with the pre approved policies and also you want is off auditing and troubleshooting, right? And from a rate of perspective, we provide tools that enable you to do this. We have, for example, a tool called danceable that enables you to automate data center operations and security and also deployment of applications and also obvious shit yourself, you know, automates most of these things and obstruct the human beings from putting their fingers on, causing, uh, potentially introducing errors right now in looking into the new world off multiple clouds and so forth. The difference is that we're seeing here between running a single cloud or on prem is three main areas which is control security and compliance. Right control here it means if your on premise or you have one cloud, um, you know, in most cases you have control over your data and your applications, especially if you're on Prem. However, if you're in the public cloud, there is a difference there. The ownership, it is still yours. But your resources are running on somebody else's or the public clouds. You know, e w s and so forth infrastructure. So people that are going to do this need to really especially banks and governments need to be aware off the regulatory constraints off running, uh, those applications in the public cloud. And we also help customers regionalize some of these choices and also on security. You will see that if you're running on premises or in a single cloud, you have more control, especially if you're on Prem. You can control this sensitive information that you have, however, in the cloud. That's a different situation, especially from personal information of employees and things like that. You need to be really careful off that. And also again, we help you rationalize some of those choices. And then the last one is compliant. Aziz. Well, you see that if you're running on Prem or a single cloud, um, regulations come into play again, right? And if you're running a problem, you have control over that. You can document everything you have access to everything that you need. But if you're gonna go to the public cloud again, you need to think about that. We have automation, and we have standards that can help you, uh, you know, address some of these challenges for security and compliance. >>So that's really strong insights, Potsie. I mean, first of all, answerable has a lot of market momentum. Red hats in a really good job with that acquisition, your point about repeatability is critical because you can't scale otherwise. And then that idea you're you're putting forth about control, security compliance It's so true is I called it the shared responsibility model. And there was a lot of misunderstanding in the early days of cloud. I mean, yeah, maybe a W s is gonna physically secure the, you know, s three, but in the bucket. But we saw so many Miss configurations early on. And so it's key to have partners that really understand this stuff and can share the experiences of other clients. So this all sounds great. A j. You're sharp, you know, financial background. What about the economics? >>You >>know, our survey data shows that security it's at the top of the spending priority list, but budgets are stretched thin. E especially when you think about the work from home pivot and and all the areas that they had toe the holes that they had to fill their, whether it was laptops, you know, new security models, etcetera. So how do organizations pay for this? What's the business case look like in terms of maybe reducing infrastructure costs so I could, you know, pay it forward or there's a There's a risk reduction angle. What can you share >>their? Yeah. I mean, the perspective I'd like to give here is, um, not being multi cloud is multi copies of an application or data. When I think about 20 years, a lot of the work in financial services I was looking at with managing copies of data that we're feeding different pipelines, different applications. Now what we're saying I talk a lot of the work that we're doing is reducing the number of copies of that data so that if I've got a product lifecycle management set of data, if I'm a manufacturer, I'm just gonna keep that in one location. But across my different clouds, I'm gonna have best of breed applications developed in house third parties in collaboration with my supply chain connecting securely to that. That single version of the truth. What I'm not going to do is to copy that data. So ah, lot of what we're seeing now is that interconnectivity using applications built on kubernetes. Um, that decoupled from the data source that allows us to reduce those copies of data within that you're gaining from the security capability and resilience because you're not leaving yourself open to those multiple copies of data on with that. Couldn't come. Cost, cost of storage on duh cost of compute. So what we're seeing is using multi cloud to leverage the best of what each cloud platform has to offer That goes all the way to Snowflake and Hiroko on Cloud manage databases, too. >>Well, and the people cost to a swell when you think about yes, the copy creep. But then you know when something goes wrong, a human has to come in and figured out um, you brought up snowflake, get this vision of the data cloud, which is, you know, data data. I think this we're gonna be rethinking a j, uh, data architectures in the coming decade where data stays where it belongs. It's distributed, and you're providing access. Like you said, you're separating the data from the applications applications as we talked about with Fozzie. Much more portable. So it Z really the last 10 years will be different than the next 10 years. A. >>J Definitely. I think the people cast election is used. Gone are the days where you needed thio have a dozen people governing managing black policies to data. Ah, lot of that repetitive work. Those tests can be in power automated. We've seen examples in insurance were reduced teams of 15 people working in the the back office China apply security controls compliance down to just a couple of people who are looking at the exceptions that don't fit. And that's really important because maybe two years ago the emphasis was on regulatory compliance of data with policies such as GDP are in CCP a last year, very much the economic effect of reduce headcounts on on enterprises of running lean looking to reduce that cost. This year, we can see that already some of the more proactive cos they're looking at initiatives such as net zero emissions how they use data toe under understand how cape how they can become more have a better social impact. Um, and using data to drive that, and that's across all of their operations and supply chain. So those regulatory compliance issues that may have been external we see similar patterns emerging for internal initiatives that benefiting the environment, social impact and and, of course, course, >>great perspectives. Yeah, Jeff Hammer, Bucker once famously said, The best minds of my generation are trying to get people to click on ads and a J. Those examples that you just gave of, you know, social good and moving. Uh, things forward are really critical. And I think that's where Data is gonna have the biggest societal impact. Okay, guys, great conversation. Thanks so much for coming on the program. Really appreciate your time. Keep it right there from, or insight and conversation around, creating a resilient digital business model. You're watching the >>Cube digital resilience, automated compliance, privacy and security for your multi cloud. Congratulations. You're on the journey. You have successfully transformed your organization by moving to a cloud based platform to ensure business continuity in these challenging times. But as you scale your digital activities, there is an inevitable influx of users that outpaces traditional methods of cybersecurity, exposing your data toe underlying threats on making your company susceptible toe ever greater risk to become digitally resilient. Have you applied controls your data continuously throughout the data Lifecycle? What are you doing to keep your customer on supply data private and secure? I owe Tahoe's automated, sensitive data. Discovery is pre programmed with over 300 existing policies that meet government mandated risk and compliance standards. Thes automate the process of applying policies and controls to your data. Our algorithm driven recommendation engine alerts you to risk exposure at the data level and suggests the appropriate next steps to remain compliant on ensure sensitive data is secure. Unsure about where your organization stands In terms of digital resilience, Sign up for a minimal cost commitment. Free data Health check. Let us run our sensitive data discovery on key unmapped data silos and sources to give you a clear understanding of what's in your environment. Book time within Iot. Tahoe Engineer Now >>Okay, let's now get into the next segment where we'll explore data automation. But from the angle of digital resilience within and as a service consumption model, we're now joined by Yusuf Khan, who heads data services for Iot, Tahoe and Shirish County up in. Who's the vice president and head of U. S. Sales at happiest Minds? Gents, welcome to the program. Great to have you in the Cube. >>Thank you, David. >>Trust you guys talk about happiest minds. This notion of born digital, foreign agile. I like that. But talk about your mission at the company. >>Sure. >>A former in 2011 Happiest Mind is a born digital born a child company. The reason is that we are focused on customers. Our customer centric approach on delivering digitals and seamless solutions have helped us be in the race. Along with the Tier one providers, Our mission, happiest people, happiest customers is focused to enable customer happiness through people happiness. We have Bean ranked among the top 25 i t services company in the great places to work serving hour glass to ratings off 41 against the rating off. Five is among the job in the Indian nineties services company that >>shows the >>mission on the culture. What we have built on the values right sharing, mindful, integrity, learning and social on social responsibilities are the core values off our company on. That's where the entire culture of the company has been built. >>That's great. That sounds like a happy place to be. Now you said you had up data services for Iot Tahoe. We've talked in the past. Of course you're out of London. What >>do you what? Your >>day to day focus with customers and partners. What you focused >>on? Well, David, my team work daily with customers and partners to help them better understand their data, improve their data quality, their data governance on help them make that data more accessible in a self service kind of way. To the stakeholders within those businesses on dis is all a key part of digital resilience that will will come on to talk about but later. You're >>right, e mean, that self service theme is something that we're gonna we're gonna really accelerate this decade, Yussef and so. But I wonder before we get into that, maybe you could talk about the nature of the partnership with happiest minds, you know? Why do you guys choose toe work closely together? >>Very good question. Um, we see Hyo Tahoe on happiest minds as a great mutual fit. A Suresh has said, uh, happiest minds are very agile organization um, I think that's one of the key things that attracts their customers on Io. Tahoe is all about automation. Uh, we're using machine learning algorithms to make data discovery data cataloging, understanding, data done. See, uh, much easier on. We're enabling customers and partners to do it much more quickly. So when you combine our emphasis on automation with the emphasis on agility that happiest minds have that that's a really nice combination work works very well together, very powerful. I think the other things that a key are both businesses, a serious have said, are really innovative digital native type type companies. Um, very focused on newer technologies, the cloud etcetera on. Then finally, I think they're both Challenger brands on happiest minds have a really positive, fresh ethical approach to people and customers that really resonates with us at Ideo Tahoe to >>great thank you for that. So Russia, let's get into the whole notion of digital resilience. I wanna I wanna sort of set it up with what I see, and maybe you can comment be prior to the pandemic. A lot of customers that kind of equated disaster recovery with their business continuance or business resilient strategy, and that's changed almost overnight. How have you seen your clients respond to that? What? I sometimes called the forced march to become a digital business. And maybe you could talk about some of the challenges that they faced along the way. >>Absolutely. So, uh, especially during this pandemic, times when you say Dave, customers have been having tough times managing their business. So happiest minds. Being a digital Brazilian company, we were able to react much faster in the industry, apart from the other services company. So one of the key things is the organisation's trying to adopt onto the digital technologies. Right there has bean lot off data which has been to manage by these customers on There have been lot off threats and risk, which has been to manage by the CEO Seo's so happiest minds digital resilient technology, right where we bring in the data. Complaints as a service were ableto manage the resilience much ahead off other competitors in the market. We were ableto bring in our business continuity processes from day one, where we were ableto deliver our services without any interruption to the services. What we were delivered to our customers So that is where the digital resilience with business community process enabled was very helpful for us. Toe enable our customers continue their business without any interruptions during pandemics. >>So I mean, some of the challenges that customers tell me they obviously they had to figure out how to get laptops to remote workers and that that whole remote work from home pivot figure out how to secure the end points. And, you know, those were kind of looking back there kind of table stakes, But it sounds like you've got a digital business. Means a data business putting data at the core, I like to say, but so I wonder if you could talk a little bit more about maybe the philosophy you have toward digital resilience in the specific approach you take with clients? >>Absolutely. They seen any organization data becomes. The key on that, for the first step is to identify the critical data. Right. So we this is a six step process. What we following happiest minds. First of all, we take stock off the current state, though the customers think that they have a clear visibility off their data. How are we do more often assessment from an external point off view on see how critical their data is, then we help the customers to strategies that right. The most important thing is to identify the most important critical herself. Data being the most critical assert for any organization. Identification off the data's key for the customers. Then we help in building a viable operating model to ensure these identified critical assets are secure on monitor dearly so that they are consumed well as well as protected from external threats. Then, as 1/4 step, we try to bring in awareness, toe the people we train them >>at >>all levels in the organization. That is a P for people to understand the importance off the digital ourselves and then as 1/5 step, we work as a back up plan in terms of bringing in a very comprehensive and a holistic testing approach on people process as well as in technology. We'll see how the organization can withstand during a crisis time, and finally we do a continuous governance off this data, which is a key right. It is not just a one step process. We set up the environment, we do the initial analysis and set up the strategy on continuously govern this data to ensure that they are not only know managed will secure as well as they also have to meet the compliance requirements off the organization's right. That is where we help organizations toe secure on Meet the regulations off the organizations. As for the privacy laws, so this is a constant process. It's not on one time effort. We do a constant process because every organization goes towards their digital journey on. They have to face all these as part off the evolving environment on digital journey. And that's where they should be kept ready in terms off. No recovering, rebounding on moving forward if things goes wrong. >>So let's stick on that for a minute, and then I wanna bring yourself into the conversation. So you mentioned compliance and governance when when your digital business, you're, as you say, you're a data business, so that brings up issues. Data sovereignty. Uh, there's governance, this compliance. There's things like right to be forgotten. There's data privacy, so many things. These were often kind of afterthoughts for businesses that bolted on, if you will. I know a lot of executives are very much concerned that these air built in on, and it's not a one shot deal. So do you have solutions around compliance and governance? Can you deliver that as a service? Maybe you could talk about some of the specifics there, >>so some of way have offered multiple services. Tow our customers on digital against. On one of the key service is the data complaints. As a service here we help organizations toe map the key data against the data compliance requirements. Some of the features includes in terms off the continuous discovery off data right, because organizations keep adding on data when they move more digital on helping the helping and understanding the actual data in terms off the residents of data, it could be a heterogeneous data soldiers. It could be on data basis, or it could be even on the data legs. Or it could be a no even on compromise all the cloud environment. So identifying the data across the various no heterogeneous environment is very key. Feature off our solution. Once we identify classify this sensitive data, the data privacy regulations on the traveling laws have to be map based on the business rules So we define those rules on help map those data so that organizations know how critical their digital assets are. Then we work on a continuous marching off data for anomalies because that's one of the key teachers off the solution, which needs to be implemented on the day to day operational basis. So we're helping monitoring those anomalies off data for data quality management on an ongoing basis. On finally, we also bringing the automated data governance where we can manage the sensory data policies on their later relationships in terms off mapping on manage their business roots on we drive reputations toe Also suggest appropriate actions to the customers. Take on those specific data sets. >>Great. Thank you, Yousef. Thanks for being patient. I want to bring in Iota ho thio discussion and understand where your customers and happiest minds can leverage your data automation capability that you and I have talked about in the past. I'm gonna be great if you had an example is well, but maybe you could pick it up from there, >>John. I mean, at a high level, assertions are clearly articulated. Really? Um, Hyoty, who delivers business agility. So that's by, um accelerating the time to operationalize data, automating, putting in place controls and actually putting helping put in place digital resilience. I mean way if we step back a little bit in time, um, traditional resilience in relation to data often met manually, making multiple copies of the same data. So you have a d b A. They would copy the data to various different places, and then business users would access it in those functional style owes. And of course, what happened was you ended up with lots of different copies off the same data around the enterprise. Very inefficient. ONDA course ultimately, uh, increases your risk profile. Your risk of a data breach. Um, it's very hard to know where everything is. And I realized that expression. They used David the idea of the forced march to digital. So with enterprises that are going on this forced march, what they're finding is they don't have a single version of the truth, and almost nobody has an accurate view of where their critical data is. Then you have containers bond with containers that enables a big leap forward so you could break applications down into micro services. Updates are available via a p I s on. So you don't have the same need thio to build and to manage multiple copies of the data. So you have an opportunity to just have a single version of the truth. Then your challenge is, how do you deal with these large legacy data states that the service has been referring Thio, where you you have toe consolidate and that's really where I attack comes in. Um, we massively accelerate that process of putting in a single version of the truth into place. So by automatically discovering the data, discovering what's dubica? What's redundant? Uh, that means you can consolidate it down to a single trusted version much more quickly. We've seen many customers have tried to do this manually, and it's literally taken years using manual methods to cover even a small percentage of their I T estates. With our tire, you could do it really very quickly on you can have tangible results within weeks and months on Ben, you can apply controls to the data based on context. So who's the user? What's the content? What's the use case? Things like data quality validations or access permissions on. Then, once you've done there. Your applications and your enterprise are much more secure, much more resilient. As a result, you've got to do these things whilst retaining agility, though. So coming full circle. This is where the partnership with happiest minds really comes in as well. You've got to be agile. You've gotta have controls. Um, on you've got a drug toward the business outcomes. Uh, and it's doing those three things together that really deliver for the customer. >>Thank you. Use f. I mean you and I. In previous episodes, we've looked in detail at the business case. You were just talking about the manual labor involved. We know that you can't scale, but also there's that compression of time. Thio get to the next step in terms of ultimately getting to the outcome. And we talked to a number of customers in the Cube, and the conclusion is, it's really consistent that if you could accelerate the time to value, that's the key driver reducing complexity, automating and getting to insights faster. That's where you see telephone numbers in terms of business impact. So my question is, where should customers start? I mean, how can they take advantage of some of these opportunities that we've discussed today. >>Well, we've tried to make that easy for customers. So with our Tahoe and happiest minds, you can very quickly do what we call a data health check. Um, this is a is a 2 to 3 week process, uh, to really quickly start to understand on deliver value from your data. Um, so, iota, who deploys into the customer environment? Data doesn't go anywhere. Um, we would look at a few data sources on a sample of data. Onda. We can very rapidly demonstrate how they discovery those catalog e on understanding Jupiter data and redundant data can be done. Um, using machine learning, um, on how those problems can be solved. Um, And so what we tend to find is that we can very quickly, as I say in the matter of a few weeks, show a customer how they could get toe, um, or Brazilian outcome on then how they can scale that up, take it into production on, then really understand their data state? Better on build. Um, Brasiliense into the enterprise. >>Excellent. There you have it. We'll leave it right there. Guys, great conversation. Thanks so much for coming on the program. Best of luck to you and the partnership Be well, >>Thank you, David Suresh. Thank you. Thank >>you for watching everybody, This is Dave Volonte for the Cuban are ongoing Siris on data automation without >>Tahoe, digital resilience, automated compliance, privacy and security for your multi cloud. Congratulations. You're on the journey. You have successfully transformed your organization by moving to a cloud based platform to ensure business continuity in these challenging times. But as you scale your digital activities, there is an inevitable influx of users that outpaces traditional methods of cybersecurity, exposing your data toe underlying threats on making your company susceptible toe ever greater risk to become digitally resilient. Have you applied controls your data continuously throughout the data lifecycle? What are you doing to keep your customer on supply data private and secure? I owe Tahoe's automated sensitive data. Discovery is pre programmed with over 300 existing policies that meet government mandated risk and compliance standards. Thes automate the process of applying policies and controls to your data. Our algorithm driven recommendation engine alerts you to risk exposure at the data level and suggests the appropriate next steps to remain compliant on ensure sensitive data is secure. Unsure about where your organization stands in terms of digital resilience. Sign up for our minimal cost commitment. Free data health check. Let us run our sensitive data discovery on key unmapped data silos and sources to give you a clear understanding of what's in your environment. Book time within Iot. Tahoe Engineer. Now. >>Okay, now we're >>gonna go into the demo. We want to get a better understanding of how you can leverage open shift. And I owe Tahoe to facilitate faster application deployment. Let me pass the mic to Sabetta. Take it away. >>Uh, thanks, Dave. Happy to be here again, Guys, uh, they've mentioned names to be the Davis. I'm the enterprise account executive here. Toyota ho eso Today we just wanted to give you guys a general overview of how we're using open shift. Yeah. Hey, I'm Noah Iota host data operations engineer, working with open ship. And I've been learning the Internets of open shift for, like, the past few months, and I'm here to share. What a plan. Okay, so So before we begin, I'm sure everybody wants to know. Noel, what are the benefits of using open shift. Well, there's five that I can think of a faster time, the operation simplicity, automation control and digital resilience. Okay, so that that's really interesting, because there's an exact same benefits that we had a Tahoe delivered to our customers. But let's start with faster time the operation by running iota. Who on open shift? Is it faster than, let's say, using kubernetes and other platforms >>are >>objective iota. Who is to be accessible across multiple cloud platforms, right? And so by hosting our application and containers were able to achieve this. So to answer your question, it's faster to create and use your application images using container tools like kubernetes with open shift as compared to, like kubernetes with docker cry over container D. Okay, so we got a bit technical there. Can you explain that in a bit more detail? Yeah, there's a bit of vocabulary involved, uh, so basically, containers are used in developing things like databases, Web servers or applications such as I have top. What's great about containers is that they split the workload so developers can select the libraries without breaking anything. And since Hammond's can update the host without interrupting the programmers. Uh, now, open shift works hand in hand with kubernetes to provide a way to build those containers for applications. Okay, got It s basically containers make life easier for developers and system happens. How does open shift differ from other platforms? Well, this kind of leads into the second benefit I want to talk about, which is simplicity. Basically, there's a lot of steps involved with when using kubernetes with docker. But open shift simplifies this with their source to image process that takes the source code and turns it into a container image. But that's not all. Open shift has a lot of automation and features that simplify working with containers, an important one being its Web console. Here. I've set up a light version of open ship called Code Ready Containers, and I was able to set up her application right from the Web console. And I was able to set up this entire thing in Windows, Mac and Lennox. So its environment agnostic in that sense. Okay, so I think I've seen the top left that this is a developers view. What would a systems admin view look like? It's a good question. So here's the administrator view and this kind of ties into the benefit of control. Um, this view gives insights into each one of the applications and containers that are running, and you could make changes without affecting deployment. Andi can also, within this view, set up each layer of security, and there's multiple that you can prop up. But I haven't fully messed around with it because with my luck, I'd probably locked myself out. So that seems pretty secure. Is there a single point security such as you use a log in? Or are there multiple layers of security? Yeah, there are multiple layers of security. There's your user login security groups and general role based access controls. Um, but there's also a ton of layers of security surrounding like the containers themselves. But for the sake of time, I won't get too far into it. Okay, eso you mentioned simplicity In time. The operation is being two of the benefits. You also briefly mention automation. And as you know, automation is the backbone of our platform here, Toyota Ho. So that's certainly grabbed my attention. Can you go a bit more in depth in terms of automation? Open shift provides extensive automation that speeds up that time the operation. Right. So the latest versions of open should come with a built in cryo container engine, which basically means that you get to skip that container engine insulation step and you don't have to, like, log into each individual container host and configure networking, configure registry servers, storage, etcetera. So I'd say, uh, it automates the more boring kind of tedious process is Okay, so I see the iota ho template there. What does it allow me to do? Um, in terms of automation in application development. So we've created an open shift template which contains our application. This allows developers thio instantly, like set up our product within that template. So, Noah Last question. Speaking of vocabulary, you mentioned earlier digital resilience of the term we're hearing, especially in the banking and finance world. Um, it seems from what you described, industries like banking and finance would be more resilient using open shift, Correct. Yeah, In terms of digital resilience, open shift will give you better control over the consumption of resource is each container is using. In addition, the benefit of containers is that, like I mentioned earlier since Hammond's can troubleshoot servers about bringing down the application and if the application does go down is easy to bring it back up using templates and, like the other automation features that open ship provides. Okay, so thanks so much. Know us? So any final thoughts you want to share? Yeah. I just want to give a quick recap with, like, the five benefits that you gained by using open shift. Uh, the five are timeto operation automation, control, security and simplicity. You could deploy applications faster. You could simplify the workload you could automate. A lot of the otherwise tedious processes can maintain full control over your workflow. And you could assert digital resilience within your environment. Guys, >>Thanks for that. Appreciate the demo. Um, I wonder you guys have been talking about the combination of a Iot Tahoe and red hat. Can you tie that in subito Digital resilience >>Specifically? Yeah, sure, Dave eso when we speak to the benefits of security controls in terms of digital resilience at Io Tahoe, we automated detection and apply controls at the data level, so this would provide for more enhanced security. >>Okay, But so if you were trying to do all these things manually. I mean, what what does that do? How much time can I compress? What's the time to value? >>So with our latest versions, Biota we're taking advantage of faster deployment time associated with container ization and kubernetes. So this kind of speeds up the time it takes for customers. Start using our software as they be ableto quickly spin up io towel on their own on premise environment are otherwise in their own cloud environment, like including aws. Assure or call GP on IBM Cloud a quick start templates allow flexibility deploy into multi cloud environments all just using, like, a few clicks. Okay, so so now just quickly add So what we've done iota, Who here is We've really moved our customers away from the whole idea of needing a team of engineers to apply controls to data as compared to other manually driven work flows. Eso with templates, automation, previous policies and data controls. One person can be fully operational within a few hours and achieve results straight out of the box on any cloud. >>Yeah, we've been talking about this theme of abstracting the complexity. That's really what we're seeing is a major trend in in this coming decade. Okay, great. Thanks, Sabina. Noah, How could people get more information or if they have any follow up questions? Where should they go? >>Yeah, sure. They've. I mean, if you guys are interested in learning more, you know, reach out to us at info at iata ho dot com to speak with one of our sales engineers. I mean, we love to hear from you, so book a meeting as soon as you can. All >>right. Thanks, guys. Keep it right there from or cube content with.

>>from around the globe. It's the Cube presenting innovation for good, brought to you by on shape. >>Hello, everyone, and welcome to Innovation for Good Program, hosted by the Cuban. Brought to You by on Shape, which is a PTC company. My name is Dave Valentin. I'm coming to you from our studios outside of Boston. I'll be directing the conversations today. It's a very exciting, all live program. We're gonna look at how product innovation has evolved and where it's going and how engineers, entrepreneurs and educators are applying cutting edge, cutting edge product development techniques and technology to change our world. You know, the pandemic is, of course, profoundly impacted society and altered how individuals and organizations they're gonna be thinking about an approaching the coming decade. Leading technologists, engineers, product developers and educators have responded to the new challenges that we're facing from creating lifesaving products to helping students learn from home toe how to apply the latest product development techniques and solve the world's hardest problems. And in this program, you'll hear from some of the world's leading experts and practitioners on how product development and continuous innovation has evolved, how it's being applied toe positive positively affect society and importantly where it's going in the coming decades. So let's get started with our first session fueling Tech for good. And with me is John Hirschbeck, who is the president of the Suffers, a service division of PTC, which acquired on shape just over a year ago, where John was the CEO and co founder, and Dana Grayson is here. She is the co founder and general partner at Construct Capital, a new venture capital firm. Folks, welcome to the program. Thanks so much for coming on. >>Great to be here, Dave. >>All right, John. >>You're very welcome. Dana. Look, John, let's get into it for first Belated congratulations on the acquisition of Von Shape. That was an awesome seven year journey for your company. Tell our audience a little bit about the story of on shape, but take us back to Day zero. Why did you and your co founders start on shape? Well, >>actually, start before on shaping the You know, David, I've been in this business for almost 40 years. The business of building software tools for product developers and I had been part of some previous products in the industry and companies that had been in their era. Big changes in this market and about, you know, a little Before founding on shape, we started to see the problems product development teams were having with the traditional tools of that era years ago, and we saw the opportunity presented by Cloud Web and Mobile Technology. And we said, Hey, we could use Cloud Web and Mobile to solve the problems of product developers make their Their business is run better. But we have to build an entirely new system, an entirely new company, to do it. And that's what on shapes about. >>Well, so notwithstanding the challenges of co vid and difficulties this year, how is the first year been as, Ah, division of PTC for you guys? How's business? Anything you can share with us? >>Yeah, our first year of PTC has been awesome. It's been, you know, when you get acquired, Dave, you never You know, you have great optimism, but you never know what life will really be like. It's sort of like getting married or something, you know, until you're really doing it, you don't know. And so I'm happy to say that one year into our acquisition, um, PTC on shape is thriving. It's worked out better than I could have imagined a year ago. Along always, I mean sales are up. In Q four, our new sales rate grew 80% vs Excuse me, our fiscal Q four Q three. In the calendar year, it grew 80% compared to the year before. Our educational uses skyrocketing with around 400% growth, most recently year to year of students and teachers and co vid. And we've launched a major cloud platform using the core of on shape technology called Atlas. So, um, just tons of exciting things going on a TTC. >>That's awesome. But thank you for sharing some of those metrics. And of course, you're very humble individual. You know, people should know a little bit more about you mentioned, you know, we founded Solid Works, co founded Solid where I actually found it solid works. You had a great exit in the in the late nineties. But what I really appreciate is, you know, you're an entrepreneur. You've got a passion for the babies that you you helped birth. You stayed with the salt systems for a number of years. The company that quiet, solid works well over a decade. And and, of course, you and I have talked about how you participated in the the M I T. Blackjack team. You know, back in the day, a zai say you're very understated, for somebody was so accomplished. Well, >>that's kind of you, but I tend to I tend Thio always keep my eye more on what's ahead. You know what's next, then? And you know, I look back Sure to enjoy it and learn from it about what I can put to work making new memories, making new successes. >>Love it. Okay, let's bring Dana into the conversation. Hello, Dana. You look you're a fairly early investor in in on shape when you were with any A And and I think it was like it was a serious B, but it was very right close after the A raise. And and you were and still are a big believer in industrial transformation. So take us back. What did you see about on shape back then? That excited you. >>Thanks. Thanks for that. Yeah. I was lucky to be a early investment in shape. You know, the things that actually attracted me. Don shape were largely around John and, uh, the team. They're really setting out to do something, as John says humbly, something totally new, but really building off of their background was a large part of it. Um, but, you know, I was really intrigued by the design collaboration side of the product. Um, I would say that's frankly what originally attracted me to it. What kept me in the room, you know, in terms of the industrial world was seeing just if you start with collaboration around design what that does to the overall industrial product lifecycle accelerating manufacturing just, you know, modernizing all the manufacturing, just starting with design. So I'm really thankful to the on shape guys, because it was one of the first investments I've made that turned me on to the whole sector. And while just such a great pleasure to work with with John and the whole team there. Now see what they're doing inside PTC. >>And you just launched construct capital this year, right in the middle of a pandemic and which is awesome. I love it. And you're focused on early stage investing. Maybe tell us a little bit about construct capital. What your investment thesis is and you know, one of the big waves that you're hoping to ride. >>Sure, it construct it is literally lifting out of any what I was doing there. Um uh, for on shape, I went on to invest in companies such as desktop metal and Tulip, to name a couple of them form labs, another one in and around the manufacturing space. But our thesis that construct is broader than just, you know, manufacturing and industrial. It really incorporates all of what we'd call foundational industries that have let yet to be fully tech enabled or digitized. Manufacturing is a big piece of it. Supply chain, logistics, transportation of mobility or not, or other big pieces of it. And together they really drive, you know, half of the GDP in the US and have been very under invested. And frankly, they haven't attracted really great founders like they're on in droves. And I think that's going to change. We're seeing, um, entrepreneurs coming out of the tech world orthe Agnelli into these industries and then bringing them back into the tech world, which is which is something that needs to happen. So John and team were certainly early pioneers, and I think, you know, frankly, obviously, that voting with my feet that the next set, a really strong companies are going to come out of the space over the next decade. >>I think it's a huge opportunity to digitize the sort of traditionally non digital organizations. But Dana, you focused. I think it's it's accurate to say you're focused on even Mawr early stage investing now. And I want to understand why you feel it's important to be early. I mean, it's obviously riskier and reward e er, but what do you look for in companies and and founders like John >>Mhm, Um, you know, I think they're different styles of investing all the way up to public market investing. I've always been early stage investors, so I like to work with founders and teams when they're, you know, just starting out. Um, I happened to also think that we were just really early in the whole digital transformation of this world. You know, John and team have been, you know, back from solid works, etcetera around the space for a long time. But again, the downstream impact of what they're doing really changes the whole industry. And and so we're pretty early and in digitally transforming that market. Um, so that's another reason why I wanna invest early now, because I do really firmly believe that the next set of strong companies and strong returns for my own investors will be in the spaces. Um, you know, what I look for in Founders are people that really see the world in a different way. And, you know, sometimes some people think of founders or entrepreneurs is being very risk seeking. You know, if you asked John probably and another successful entrepreneurs, they would call themselves sort of risk averse, because by the time they start the company, they really have isolated all the risk out of it and think that they have given their expertise or what they're seeing their just so compelled to go change something, eh? So I look for that type of attitude experience a Z. You can also tell from John. He's fairly humble. So humility and just focus is also really important. Um, that there's a That's a lot of it. Frankly, >>Excellent. Thank you, John. You got such a rich history in the space. Uh, and one of you could sort of connect the dots over time. I mean, when you look back, what were the major forces that you saw in the market in in the early days? Particularly days of on shape on? And how is that evolved? And what are you seeing today? Well, >>I think I touched on it earlier. Actually, could I just reflect on what Dana said about risk taking for just a quick one and say, throughout my life, from blackjack to starting solid works on shape, it's about taking calculated risks. Yes, you try to eliminate the risk Sa's much as you can, but I always say, I don't mind taking a risk that I'm aware of, and I've calculated through as best I can. I don't like taking risks that I don't know I'm taking. That's right. You >>like to bet on >>sure things as much as you sure things, or at least where you feel you. You've done the research and you see them and you know they're there and you know, you, you you keep that in mind in the room, and I think that's great. And Dana did so much for us. Dana, I want to thank you again. For all that, you did it every step of the way, from where we started to to, you know, your journey with us ended formally but continues informally. Now back to you, Dave, I think, question about the opportunity and how it's shaped up. Well, I think I touched on it earlier when I said It's about helping product developers. You know, our customers of the people build the future off manufactured goods. Anything you think of that would be manufacturing factory. You know, the chair you're sitting in machine that made your coffee. You know, the computer you're using, the trucks that drive by on the street, all the covert product research, the equipment being used to make vaccines. All that stuff is designed by someone, and our job is given the tools to do it better. And I could see the problems that those product developers had that we're slowing them down with using the computing systems of the time. When we built solid works, that was almost 30 years ago. If people don't realize that it was in the early >>nineties and you know, we did the >>best we could for the early nineties, but what we did. We didn't anticipate the world of today. And so people were having problems with just installing the systems. Dave, you wouldn't believe how hard it is to install these systems. You need toe speck up a special windows computer, you know, and make sure you've got all the memory and graphics you need and getting to get that set up. You need to make sure the device drivers air, right, install a big piece of software. Ah, license key. I'm not making this up. They're still around. You may not even know what those are. You know, Dennis laughing because, you know, zero cool people do things like this anymore. Um, and it only runs some windows. You want a second user to use it? They need a copy. They need a code. Are they on the same version? It's a nightmare. The teams change, you know? You just say, Well, get everyone on the software. Well, who's everyone? You know, you got a new vendor today? A new customer tomorrow, a new employee. People come on and off the team. The other problem is the data stored in files, thousands of files. This isn't like a spreadsheet or word processor, where there's one file to pass around these air thousands of files to make one, even a simple product. People were tearing their hair out. John, what do we do? I've got copies everywhere. I don't know where the latest version is. We tried like, you know, locking people out so that only one person can change it At the time that works against speed, it works against innovation. We saw what was happening with Cloud Web and mobile. So what's happened in the years since is every one of the forces that product developers experience the need for speed, the need for innovation, the need to be more efficient with their people in their capital. Resource is every one of those trends have been amplified since we started on shape by a lot of forces in the world. And covert is amplified all those the need for agility and remote work cove it is amplified all that the same time, The acceptance of cloud. You know, a few years ago, people were like cloud, you know, how is that gonna work now They're saying to me, You know, increasingly, how would you ever even have done this without the cloud. How do you make solid works work without the cloud? How would that even happen? You know, once people understand what on shapes about >>and we're the >>Onley full SAS solution software >>as a service, >>full SAS solution in our industry. So what's happened in those years? Same problems we saw earlier, but turn up the gain, their bigger problems. And with cloud, we've seen skepticism of years ago turn into acceptance. And now even embracement in the cova driven new normal. >>Yeah. So a lot of friction in the previous environments cloud obviously a huge factor on, I guess. I guess Dana John could see it coming, you know, in the early days of solid works with, you know, had Salesforce, which is kind of the first major independent SAS player. Well, I guess that was late nineties. So his post solid works, but pre in shape and their work day was, you know, pre on shape in the mid two thousands. And and but But, you know, the bet was on the SAS model was right for Crick had and and product development, you know, which maybe the time wasn't a no brainer. Or maybe it was, I don't know, but Dana is there. Is there anything that you would invest in today? That's not Cloud based? >>Um, that's a great question. I mean, I think we still see things all the time in the manufacturing world that are not cloud based. I think you know, the closer you get to the shop floor in the production environment. Um e think John and the PTC folks would agree with this, too, but that it's, you know, there's reliability requirements, performance requirements. There's still this attitude of, you know, don't touch the printing press. So the cloud is still a little bit scary sometimes. And I think hybrid cloud is a real thing for those or on premise. Solutions, in some cases is still a real thing. What what we're more focused on. And, um, despite whether it's on premise or hybrid or or SAS and Cloud is a frictionless go to market model, um, in the companies we invest in so sass and cloud, or really make that easy to adopt for new users, you know, you sign up, started using a product, um, but whether it's hosted in the cloud, whether it's as you can still distribute buying power. And, um, I would I'm just encouraging customers in the customer world and the more industrial environment to entrust some of their lower level engineers with more budget discretionary spending so they can try more products and unlock innovation. >>Right? The unit economics are so compelling. So let's bring it, you know, toe today's you know, situation. John, you decided to exit about a year ago. You know? What did you see in PTC? Other than the obvious money? What was the strategic fit? >>Yeah, Well, David, I wanna be clear. I didn't exit anything. Really? You >>know, I love you and I don't like that term exit. I >>mean, Dana had exit is a shareholder on and so it's not It's not exit for me. It's just a step in the journey. What we saw in PTC was a partner. First of all, that shared our vision from the top down at PTC. Jim Hempleman, the CEO. He had a great vision for for the impact that SAS can make based on cloud technology and really is Dana of highlighted so much. It's not just the technology is how you go to market and the whole business being run and how you support and make the customers successful. So Jim shared a vision for the potential. And really, really, um said Hey, come join us and we can do this bigger, Better, faster. We expanded the vision really to include this Atlas platform for hosting other SAS applications. That P D. C. I mean, David Day arrived at PTC. I met the head of the academic program. He came over to me and I said, You know, and and how many people on your team? I thought he'd say 5 40 people on the PTC academic team. It was amazing to me because, you know, we were we were just near about 100 people were required are total company. We didn't even have a dedicated academic team and we had ah, lot of students signing up, you know, thousands and thousands. Well, now we have hundreds of thousands of students were approaching a million users and that shows you the power of this team that PTC had combined with our product and technology whom you get a big success for us and for the teachers and students to the world. We're giving them great tools. So so many good things were also putting some PTC technology from other parts of PTC back into on shape. One area, a little spoiler, little sneak peek. Working on taking generative design. Dana knows all about generative design. We couldn't acquire that technology were start up, you know, just to too much to do. But PTC owns one of the best in the business. This frustrated technology we're working on putting that into on shaping our customers. Um, will be happy to see it, hopefully in the coming year sometime. >>It's great to see that two way exchange. Now, you both know very well when you start a company, of course, a very exciting time. You know, a lot of baggage, you know, our customers pulling you in a lot of different directions and asking you for specials. You have this kind of clean slate, so to speak in it. I would think in many ways, John, despite you know, your install base, you have a bit of that dynamic occurring today especially, you know, driven by the forced march to digital transformation that cove it caused. So when you sit down with the team PTC and talk strategy. You now have more global resource is you got cohorts selling opportunities. What's the conversation like in terms of where you want to take the division? >>Well, Dave, you actually you sounds like we should have you coming in and talking about strategy because you've got the strategy down. I mean, we're doing everything said global expansion were able to reach across selling. We got some excellent PTC customers that we can reach reach now and they're finding uses for on shape. I think the plan is to, you know, just go, go, go and grow, grow, grow where we're looking for this year, priorities are expand the product. I mentioned the breath of the product with new things PTC did recently. Another technology that they acquired for on shape. We did an acquisition. It was it was small, wasn't widely announced. It, um, in an area related to interfacing with electrical cad systems. So So we're doing We're expanding the breath of on shape. We're going Maura, depth in the areas were already in. We have enormous opportunity to add more features and functions that's in the product. Go to market. You mentioned it global global presence. That's something we were a little light on a year ago. Now we have a team. Dana may not even know what we have. A non shape, dedicated team in Barcelona, based in Barcelona but throughout Europe were doing multiple languages. Um, the academic program just introduced a new product into that space that z even fueling more success and growth there. Um, and of course, continuing to to invest in customer success and this Atlas platform story I keep mentioning, we're going to soon have We're gonna soon have four other major PTC brands shipping products on our Atlas Saas platform. And so we're really excited about that. That's good for the other PTC products. It's also good for on shape because now there's there's. There's other interesting products that are on shape customers can use take advantage of very easily using, say, a common log in conventions about user experience there, used to invest of all they're SAS based, so they that makes it easier to begin with. So that's some of the exciting things going on. I think you'll see PTC, um, expanding our lead in SAS based applications for this sector for our our target, uh, sectors not just in, um, in cat and data management, but another area. PTC's Big and his augmented reality with of euphoria, product line leader and industrial uses of a R. That's a whole other story we should do. A whole nother show augmented reality. But these products are amazing. You can you can help factory workers people on, uh, people who are left out of the digital transformation. Sometimes we're standing from machine >>all day. >>They can't be sitting like we are doing Zoom. They can wear a R headset in our tools, let them create great content. This is an area Dana is invested in other companies. But what I wanted to note is the new releases of our authoring software. For this, our content getting released this month, used through the Atlas platform, the SAS components of on shape for things like revision management and collaboration on duh workflow activity. All that those are tools that we're able to share leverage. We get a lot of synergy. It's just really good. It's really fun to have a good time. That's >>awesome. And then we're gonna be talking to John MacLean later about that. Let's do a little deeper Dive on that. And, Dana, what is your involvement today with with on shape? But you're looking for you know, which of their customers air actually adopting. And they're gonna disrupt their industries. And you get good pipeline from that. How do you collaborate today? >>That sounds like a great idea. Um, Aziz, John will tell you I'm constantly just asking him for advice and impressions of other entrepreneurs and picking his brain on ideas. No formal relationship clearly, but continue to count John and and John and other people in on shaping in the circle of experts that I rely on for their opinions. >>All right, so we have some questions from the crowd here. Uh, one of the questions is for the dream team. You know, John and Dana. What's your next next collective venture? I don't think we're there yet, are we? No. >>I just say, as Dana said, we love talking to her about. You know, Dana, you just returned the compliment. We would try and give you advice and the deals you're looking at, and I'm sort of casually mentoring at least one of your portfolio entrepreneurs, and that's been a lot of fun for May on, hopefully a value to them. But also Dana. We uran important pipeline to us in the world of some new things that are happening that we wouldn't see if you know you've shown us some things that you've said. What do you think of this business? And for us, it's like, Wow, it's cool to see that's going on And that's what's supposed to work in an ecosystem like this. So we we deeply value the ongoing relationship. And no, we're not starting something new. I got a lot of work left to do with what I'm doing and really happy. But we can We can collaborate in this way on other ventures. >>I like this question to somebody asking With the cloud options like on shape, Wilmore students have stem opportunities s Oh, that's a great question. Are you because of sass and cloud? Are you able to reach? You know, more students? Much more cost effectively. >>Yeah, Dave, I'm so glad that that that I was asked about this because Yes, and it's extremely gratified us. Yes, we are because of cloud, because on shape is the only full cloud full SAS system or industry were able to reach. Stem education brings able to be part of bringing step education to students who couldn't get it otherwise. And one of most gratifying gratifying things to me is the emails were getting from teachers, um, that that really, um, on the phone calls that were they really pour their heart out and say We're able to get to students in areas that have very limited compute resource is that don't have an I T staff where they don't know what computer that the students can have at home, and they probably don't even have a computer. We're talking about being able to teach them on a phone to have an android phone a low end android phone. You can do three D modeling on there with on shape. Now you can't do it any other system, but with on shape, you could do it. And so the teacher can say to the students, They have to have Internet access, and I know there's a huge community that doesn't even have Internet access, and we're not able, unfortunately to help that. But if you have Internet and you have even an android phone, we can enable the educator to teach them. And so we have case after case of saving a stem program or expanding it into the students that need it most is the ones we're helping here. So really excited about that. And we're also able to let in addition to the run on run on whatever computing devices they have, we also offer them the tools they need for remote teaching with a much richer experience. Could you teach solid works remotely? Well, maybe if the student ran it had a windows workstation. You know, big, big, high end workstation. Maybe it could, but it would be like the difference between collaborating with on shape and collaborate with solid works. Like the difference between a zoom video call and talking on the landline phone. You know, it's a much richer experience, and that's what you need. And stem teaching stem is hard, So yeah, we're super super. Um, I'm excited about bringing stem to more students because of cloud yond >>we're talking about innovation for good, and then the discussion, John, you just had it. Really? There could be a whole another vector here. We could discuss on diversity, and I wanna end with just pointing out. So, Dana, your new firm, it's a woman led firm, too. Two women leaders, you know, going forward. So that's awesome to see, so really? Yeah, thumbs up on that. Congratulations on getting that off the ground. >>Thank you. Thank you. >>Okay, so thank you guys. Really appreciate It was a great discussion. I learned a lot and I'm sure the audience did a swell in a moment. We're gonna talk with on shaped customers to see how they're applying tech for good and some of the products that they're building. So keep it right there. I'm Dave Volonte. You're watching innovation for good on the Cube, the global leader in digital tech event coverage. Stay right there. >>Oh, yeah, it's >>yeah, yeah, around >>the globe. It's the Cube presenting innovation for good. Brought to you by on shape. >>Okay, we're back. This is Dave Volonte and you're watching innovation for good. A program on Cuba 3 65 made possible by on shape of PTC company. We're live today really live tv, which is the heritage of the Cube. And now we're gonna go to the sources and talkto on shape customers to find out how they're applying technology to create real world innovations that are changing the world. So let me introduce our panel members. Rafael Gomez Furberg is with the Chan Zuckerberg bio hub. A very big idea. And collaborative nonprofit was initiative that was funded by Mark Zuckerberg and his wife, Priscilla Chan, and really around diagnosing and curing and better managing infectious diseases. So really timely topic. Philip Tabor is also joining us. He's with silver side detectors, which develops neutron detective detection systems. Yet you want to know if early, if neutrons and radiation or in places where you don't want them, So this should be really interesting. And last but not least, Matthew Shields is with the Charlottesville schools and is gonna educate us on how he and his team are educating students in the use of modern engineering tools and techniques. Gentlemen, welcome to the Cuban to the program. This should be really interesting. Thanks for coming on. >>Hi. Or pleasure >>for having us. >>You're very welcome. Okay, let me ask each of you because you're all doing such interesting and compelling work. Let's start with Rafael. Tell us more about the bio hub and your role there, please. >>Okay. Yeah. So you said that I hope is a nonprofit research institution, um, funded by Mark Zuckerberg and his wife, Priscilla Chan. Um, and our main mission is to develop new technologies to help advance medicine and help, hopefully cure and manage diseases. Um, we also have very close collaborations with Universe California, San Francisco, Stanford University and the University California Berkeley on. We tried to bring those universities together, so they collaborate more of biomedical topics. And I manage a team of engineers. They by joining platform. Um, and we're tasked with creating instruments for the laboratory to help the scientist boats inside the organization and also in the partner universities Do their experiments in better ways in ways that they couldn't do before >>in this edition was launched Well, five years ago, >>it was announced at the end of 2016, and we actually started operation with at the beginning of 2017, which is when I joined, um, So this is our third year. >>And how's how's it going? How does it work? I mean, these things take time. >>It's been a fantastic experience. Uh, the organization works beautifully. Um, it was amazing to see it grow From the beginning, I was employee number 12, I think eso When I came in, it was just a nem P office building and empty labs. And very quickly we had something running about. It's amazing eso I'm very proud of the work that we have done to make that possible. Um And then, of course, that's you mentioned now with co vid, um, we've been able to do a lot of very cool work attire being of the pandemic in March, when there was a deficit of testing, uh, capacity in California, we spun up a testing laboratory in record time in about a week. It was crazy. It was a crazy project, Um, but but incredibly satisfying. And we ended up running all the way until the beginning of November, when the lab was finally shut down. We could process about 3000 samples a day. I think at the end of it all, we were able to test about 100 on the order of 100 and 50,000 samples from all over the state. We were providing free testing toe all of the Department of Public Health Department of Public Health in California, which at the media pandemic, had no way to do testing affordably and fast. So I think that was a great service to the state. Now the state has created that testing system that would serve those departments. So then we decided that it was unnecessary to keep going with testing in the other biopsy that would shut down. >>All right. Thank you for that. Now, Now, Philip, you What you do is mind melting. You basically helped keep the world safe. Maybe describe a little bit more about silver sod detectors and what your role is there and how it all works. >>Tour. So we make a nuclear bomb detectors and we also make water detectors. So we try and do our part thio keep the world from blowing up and make it a better place at the same time. Both of these applications use neutron radiation detectors. That's what we make. Put them out by import border crossing places like that. They can help make sure that people aren't smuggling. Shall we say very bad things. Um, there's also a burgeoning field of research and application where you can use neutrons with some pretty cool physics to find water so you could do things. Like what? A detector up in the mountains and measure snowpack. Put it out in the middle of the field and measure soil moisture content. And as you might imagine, there's some really cool applications in, uh, research and agronomy and public policy for this. >>All right, so it's OK, so it's a It's much more than, you know, whatever fighting terrorism, it's there's a riel edge or I kind of i o t application for what you guys >>do. We do both its's to plowshares. You might >>say a mat. I I look at your role is kind of scaling the brain power for for the future. Maybe tell us more about Charlottesville schools and in the mission that you're pursuing and what you do. >>Thank you. Um, I've been in Charlottesville City schools for about 11 or 12 years. I started their teaching, um, a handful of classes, math and science and things like that. But Thescore board and my administration had the crazy idea of starting an engineering program about seven years ago. My background is an engineering is an engineering. My masters is in mechanical and aerospace engineering and um, I basically spent a summer kind of coming up with what might be a fun engineering curriculum for our students. And it started with just me and 30 students about seven years ago, Um, kind of a home spun from scratch curriculum. One of my goals from the outset was to be a completely project based curriculum, and it's now grown. We probably have about six or 700 students, five or six full time teachers. We now have pre engineering going on at the 5th and 6th grade level. I now have students graduating. Uh, you know, graduating after senior year with, like, seven years of engineering under their belt and heading off to doing some pretty cool stuff. So it's It's been a lot of fun building a program and, um, and learning a lot in the process. >>That's awesome. I mean, you know, Cuba's. We've been passionate about things like women in tech, uh, diversity stem. You know, not only do we need more, more students and stem, we need mawr underrepresented women, minorities, etcetera. We were just talking to John Herstek and integrate gration about this is Do you do you feel is though you're I mean, first of all, the work that you do is awesome, but but I'll go one step further. Do you feel as though it's reaching, um, or diverse base? And how is that going? >>That's a great question. I think research shows that a lot of people get funneled into one kind of track or career path or set of interests really early on in their educational career, and sometimes that that funnel is kind of artificial. And so that's one of the reasons we keep pushing back. Um, so our school systems introducing kindergartners to programming on DSO We're trying to push back how we expose students to engineering and to stem fields as early as possible. And we've definitely seen the first of that in my program. In fact, my engineering program, uh, sprung out of an after school in Extracurricular Science Club that actually three girls started at our school. So I think that actually has helped that three girls started the club that eventually is what led to our engineering programs that sort of baked into the DNA and also our eyes a big public school. And we have about 50% of the students are under the poverty line and we e in Charlottesville, which is a big refugee town. And so I've been adamant from Day one that there are no barriers to entry into the program. There's no test you have to take. You don't have to have be taking a certain level of math or anything like that. That's been a lot of fun. To have a really diverse set of kids enter the program and be successful, >>that's final. That's great to hear. So, Philip, I wanna come back to you. You know, I think about maybe some day we'll be able to go back to a sporting events, and I know when I when I'm in there, there's somebody up on the roof looking out for me, you know, watching the crowd, and they have my back. And I think in many ways, the products that you build, you know, our similar. I may not know they're there, but they're keeping us safe or they're measuring things that that that I don't necessarily see. But I wonder if you could talk about a little bit more detail about the products you build and how they're impacting society. >>Sure, so There are certainly a lot of people who are who are watching, trying to make sure things were going well in keeping you safe that you may or may not be aware of. And we try and support ah lot of them. So we have detectors that are that are deployed in a variety of variety of uses, with a number of agencies and governments that dio like I was saying, ports and border crossing some other interesting applications that are looking for looking for signals that should not be there and working closely to fit into the operations these folks do. Onda. We also have a lot of outreach to researchers and scientists trying to help them support the work they're doing. Um, using neutron detection for soil moisture monitoring is a some really cool opportunities for doing it at large scale and with much less, um, expense or complication than would have been done. Previous technologies. Um, you know, they were talking about collaboration in the previous segment. We've been able to join a number of conferences for that, virtually including one that was supposed to be held in Boston, but another one that was held out of the University of Heidelberg in Germany. And, uh, this is sort of things that in some ways, the pandemic is pushing people towards greater collaboration than they would have been able to do. Had it all but in person. >>Yeah, we did. Uh, the cube did live works a couple years ago in Boston. It was awesome show. And I think, you know, with this whole trend toward digit, I call it the Force march to digital. Thanks to cove it I think that's just gonna continue. Thio grow. Rafael. What if you could describe the process that you use to better understand diseases? And what's your organization's involvement? Been in more detail, addressing the cove in pandemic. >>Um, so so we have the bio be structured in, Um um in a way that foster so the combination of technology and science. So we have to scientific tracks, one about infectious diseases and the other one about understanding just basic human biology, how the human body functions, and especially how the cells in the human body function on how they're organized to create tissues in the body. On Ben, it has this set of platforms. Um, mind is one of them by engineering that are all technology rated. So we have data science platform, all about data analysis, machine learning, things like that. Um, we have a mass spectrometry platform is all about mass spectrometry technologies to, um, exploit those ones in service for the scientist on. We have a genomics platform that it's all about sequencing DNA and are gonna, um and then an advanced microscopy. It's all about developing technologies, uh, to look at things with advanced microscopes and developed technologies to marry computation on microscopy. So, um, the scientists set the agenda and the platforms, we just serve their needs, support their needs, and hopefully develop technologies that help them do their experiments better, faster, or allow them to the experiment that they couldn't do in any other way before. Um And so with cove, it because we have that very strong group of scientists that work on have been working on infectious disease before, and especially in viruses, we've been able to very quickly pivot to working on that s O. For example, my team was able to build pretty quickly a machine to automatically purified proteins on is being used to purify all these different important proteins in the cove. It virus the SARS cov to virus Onda. We're sending some of those purified proteins all over the world. Two scientists that are researching the virus and trying to figure out how to develop vaccines, understand how the virus affects the body and all that. Um, so some of the machines we built are having a very direct impact on this. Um, Also for the copy testing lab, we were able to very quickly develop some very simple machines that allowed the lab to function sort of faster and more efficiently. Sort of had a little bit of automation in places where we couldn't find commercial machines that would do it. >>Um, eso Matt. I mean, you gotta be listening to this and thinking about Okay, So someday your students are gonna be working at organizations like like, like Bio Hub and Silver Side. And you know, a lot of young people they're just don't know about you guys, but like my kids, they're really passionate about changing the world. You know, there's way more important than you know, the financial angles and it z e. I gotta believe you're seeing that you're right in the front lines there. >>Really? Um, in fact, when I started the curriculum six or seven years ago, one of the first bits of feedback I got from my students is they said Okay, this is a lot of fun. So I had my students designing projects and programming microcontrollers raspberry, PiS and order we nose and things like that. The first bit of feedback I got from students was they said Okay, when do we get to impact the world? I've heard engineering >>is about >>making the world a better place, and robots are fun and all, but, you know, where is the real impact? And so um, dude, yeah, thanks to the guidance of my students, I'm baking that Maurin. Now I'm like day one of engineering one. We talk about how the things that the tools they're learning and the skills they're gaining, uh, eventually, you know, very soon could be could be used to make the world a better place. >>You know, we all probably heard that famous line by Jeff Hammer Barker. The greatest minds of my generation are trying to figure out how to get people to click on ads. I think we're really generally generationally, finally, at the point where young students and engineering a really, you know, a passionate about affecting society. I wanna get into the product, you know, side and understand how each of you are using on shape and and the value that that it brings. Maybe Raphael, you could start how long you've been using it. You know, what's your experience with it? Let's let's start there. >>I begin for about two years, and I switched to it with some trepidation. You know, I was used to always using the traditional product that you have to install on your computer, that everybody uses that. So I was kind of locked into that. But I started being very frustrated with the way it worked, um, and decided to give on ship chance. Which reputation? Because any change always, you know, causes anxiety. Um, but very quickly my engineers started loving it, Uh, just because it's it's first of all, the learning curve wasn't very difficult at all. You can transfer from one from the traditional product to entree very quickly and easily. You can learn all the concepts very, very fast. It has all the functionality that we needed and and what's best is that it allows to do things that we couldn't do before or we couldn't do easily. Now we can access the our cat documents from anywhere in the world. Um, so when we're in the lab fabricating something or testing a machine, any computer we have next to us or a tablet or on iPhone, we can pull it up and look at the cad and check things or make changes. That's something that couldn't do before because before you had to pay for every installation off the software for the computer, and I couldn't afford to have 20 installations to have some computers with the cat ready to use them like once every six months would have been very inefficient. So we love that part. And the collaboration features are fantastic, especially now with Kobe, that we have to have all the remote meetings eyes fantastic, that you can have another person drive the cad while the whole team is watching that person change the model and do things and point to things that is absolutely revolutionary. We love it. The fact that you have very, very sophisticated version control before it was always a challenge asking people, please, if you create anniversary and apart, how do we name it so that people find it? And then you end up with all these collection of files with names that nobody ever remembers, what they are, the person left. And now nobody knows which version is the right one. A mess with on shape on the version ING system it has, and the fact that you can go back in history off the document and go back to previous version so easily and then go back to the press and version and explore the history of the part that is truly, um, just world changing for us, that we can do that so easily on for me as a manager to manage this collection of information that is critical for our operations. It makes it so much easier because everything is in one place. I don't have to worry about file servers that go down that I have to administer that have to have I t taken care off that have to figure how to keep access to people to those servers when they're at home, and they need a virtual private network and all of that mess disappears. I just simply give give a person in accounting on shape and then magically, they have access to everything in the way I want. And we can manage the lower documents and everything in a way that is absolutely fantastic. >>Feel what was your what? What were some of the concerns you had mentioned? You had some trepidation. Was it a performance? Was it security? You know some of the traditional cloud stuff, and I'm curious as to how, How, whether any of those act manifested really that you had to manage. What were your concerns? >>Look, the main concern is how long is it going to take for everybody in the team to learn to use the system like it and buy into it? Because I don't want to have my engineers using tools against their will write. I want everybody to be happy because that's how they're productive. They're happy, and they enjoyed the tools they have. That was my main concern. I was a little bit worried about the whole concept of not having the files in a place where I couldn't quote unquote seat in some server and on site, but that That's kind of an outdated concept, right? So that took a little bit of a mind shift, but very quickly. Then I started thinking, Look, I have a lot of documents on Google Drive. Like, I don't worry about that. Why would I worry about my cat on on shape, right? Is the same thing. So I just needed to sort of put things in perspective that way. Um, the other, um, you know, the concern was the learning curve, right? Is like, how is he Will be for everybody to and for me to learn it on whether it had all of the features that we needed. And there were a few features that I actually discussed with, um uh, Cody at on shape on, they were actually awesome about using their scripting language in on shape to sort of mimic some of the features of the old cat, uh, in on, shaped in a way that actually works even better than the old system. So it was It was amazing. Yeah, >>Great. Thank you for that, Philip. What's your experience been? Maybe you could take us through your journey within shape. >>Sure. So we've been we've been using on shaped silver side for coming up on about four years now, and we love it. We're very happy with it. We have a very modular product line, so we make anything from detectors that would go into backpacks. Two vehicles, two very large things that a shipping container would go through and saw. Excuse me. Shape helps us to track and collaborate faster on the design. Have multiple people working a same time on a project. And it also helps us to figure out if somebody else comes to us and say, Hey, I want something new how we congrats modules from things that we already have put them together and then keep track of the design development and the different branches and ideas that we have, how they all fit together. A za design comes together, and it's just been fantastic from a mechanical engineering background. I will also say that having used a number of different systems and solid works was the greatest thing since sliced bread. Before I got using on shape, I went, Wow, this is amazing and I really don't want to design in any other platform. After after getting on Lee, a little bit familiar with it. >>You know, it's funny, right? I'll have the speed of technology progression. I was explaining to some young guns the other day how I used to have a daytime er and that was my life. And if I lost that daytime, er I was dead. And I don't know how we weigh existed without, you know, Google maps eso we get anywhere, I don't know, but, uh but so So, Matt, you know, it's interesting to think about, you know, some of the concerns that Raphael brought up, you hear? For instance, you know, all the time. Wow. You know, I get my Amazon bill at the end of the month that zip through the roof in, But the reality is that Yeah, well, maybe you are doing more, but you're doing things that you couldn't have done before. And I think about your experience in teaching and educating. I mean, you so much more limited in terms of the resource is that you would have had to be able to educate people. So what's your experience been with With on shape and what is it enabled? >>Um, yeah, it was actually talking before we went with on shape. We had a previous CAD program, and I was talking to my vendor about it, and he let me know that we were actually one of the biggest CAD shops in the state. Because if you think about it a really big program, you know, really big company might employ. 5, 10, 15, 20 cad guys, right? I mean, when I worked for a large defense contractor, I think there were probably 20 of us as the cad guys. I now have about 300 students doing cat. So there's probably more students with more hours of cat under their belt in my building than there were when I worked for the big defense contractor. Um, but like you mentioned, uh, probably our biggest hurdle is just re sources. And so we want We want one of things I've always prided myself and trying to do in this. Programs provide students with access two tools and skills that they're going to see either in college or in the real world. So it's one of the reason we went with a big professional cad program. There are, you know, sort of K 12 oriented software and programs and things. But, you know, I want my kids coding and python and using slack and using professional type of tools on DSO when it comes to cat. That's just that That was a really hurt. I mean, you know, you could spend $30,000 on one seat of, you know, professional level cad program, and then you need a $30,000 computer to run it on if you're doing a heavy assemblies, Um and so one of my dreams And it was always just a crazy dream. And I was the way I would always pitcher in my school system and say, someday I'm gonna have a kid on a school issued chromebook in subsidized housing, on public WiFi doing professional level bad and that that was a crazy statement until a couple of years ago. So we're really excited that I literally and you know, March and you said the forced march, the forced march into, you know, modernity, March 13th kids sitting in my engineering lab that we spent a lot of money on doing cad March 14th. Those kids were at home on their school issued chromebooks on public WiFi, uh, keeping their designs going and collaborating. And then, yeah, I could go on and on about some of the things you know, the features that we've learned since then they're even better. So it's not like this is some inferior, diminished version of Academy. There's so much about it. Well, I >>wanna I wanna ask you that I may be over my skis on this, but we're seeing we're starting to see the early days of the democratization of CAD and product design. It is the the citizen engineer, I mean, maybe insulting to the engineers in the room, But but is that we're beginning to see that >>I have to believe that everything moves into the cloud. Part of that is democratization that I don't need. I can whether you know, I think artists, you know, I could have a music studio in my basement with a nice enough software package. And Aiken, I could be a professional for now. My wife's a photographer. I'm not allowed to say that I could be a professional photographer with, you know, some cloud based software, and so, yeah, I do think that's part of what we're seeing is more and more technology is moving to the cloud. >>Philip. Rafael Anything you Dad, >>I think I mean, yeah, that that that combination of cloud based cat and then three d printing that is becoming more and more affordable on ubiquitous It's truly transformative, and I think for education is fantastic. I wish when I was a kid I had the opportunity to play with those kinds of things because I was always the late things. But, you know, the in a very primitive way. So, um, I think this is a dream for kids. Teoh be able to do this. And, um, yeah, there's so many other technologies coming on, like Arduino on all of these electronic things that live kids play at home very cheaply with things that back in my day would have been unthinkable. >>So we know there's a go ahead. Philip, please. >>We had a pandemic and silver site moved to a new manufacturing facility this year. I was just on the shop floor, talking with contractors, standing 6 ft apart, pointing at things. But through it all, our CAD system was completely unruffled. Nothing stopped in our development work. Nothing stopped in our support for existing systems in the field. We didn't have to think about it. We had other server issues, but none with our, you know, engineering cad, platform and product development in support world right ahead, which was cool, but also a in that's point. I think it's just really cool what you're doing with the kids. The most interesting secondary and college level engineering work that I did was project based, taken important problem to the world. Go solve it and that is what we do here. That is what my entire career has been. And I'm super excited to see. See what your students are going to be doing, uh, in there home classrooms on their chromebooks now and what they do building on that. >>Yeah, I'm super excited to see your kids coming out of college with engineering degrees because, yeah, I think that Project based experience is so much better than just sitting in a classroom, taking notes and doing math problems on day. I think it will give the kids a much better flavor. What engineering is really about Think a lot of kids get turned off by engineering because they think it's kind of dry because it's just about the math for some very abstract abstract concept on they are there. But I think the most important thing is just that hands on a building and the creativity off, making things that you can touch that you can see that you can see functioning. >>Great. So, you know, we all know the relentless pace of technology progression. So when you think about when you're sitting down with the folks that on shape and there the customer advisor for one of the things that that you want on shape to do that it doesn't do today >>I could start by saying, I just love some of the things that does do because it's such a modern platform. And I think some of these, uh, some some platforms that have a lot of legacy and a lot of history behind them. I think we're dragging some of that behind them. So it's cool to see a platform that seemed to be developed in the modern era, and so that Z it is the Google docks. And so the fact that collaboration and version ing and link sharing is and like platform agnostic abilities, the fact that that seems to be just built into the nature of the thing so far, That's super exciting. As far as things that, uh, to go from there, Um, I don't know, >>Other than price. >>You can't say >>I >>can't say lower price. >>Yeah, so far on P. D. C. S that work with us. Really? Well, so I'm not complaining. There you there, >>right? Yeah. Yeah. No gaps, guys. Whitespace, Come on. >>We've been really enjoying the three week update. Cadence. You know, there's a new version every three weeks and we don't have to install it. We just get all the latest and greatest goodies. One of the trends that we've been following and enjoying is the the help with a revision management and release work flows. Um, and I know that there's more than on shape is working on that we're very excited for, because that's a big important part about making real hardware and supporting it in the field. Something that was cool. They just integrated Cem markup capability. In the last release that took, we were doing that anyway, but we were doing it outside of on shapes. And now we get to streamline our workflow and put it in the CAD system where We're making those changes anyway when we're reviewing drawings and doing this kind of collaboration. And so I think from our perspective, we continue to look forward. Toa further progress on that. There's a lot of capability in the cloud that I think they're just kind of scratching the surface on you, >>right? I would. I mean, you're you're asking to knit. Pick. I would say one of the things that I would like to see is is faster regeneration speed. There are a few times with convicts, necessities that regenerating the document takes a little longer than I would like. It's not a serious issue, but anyway, I I'm being spoiled, >>you know? That's good. I've been doing this a long time, and I like toe ask that question of practitioners and to me, it It's a signal like when you're nit picking and that's what you're struggling to knit. Pick that to me is a sign of a successful product, and and I wonder, I don't know, uh, have the deep dive into the architecture. But are things like alternative processors. You're seeing them hit the market in a big way. Uh, you know, maybe helping address the challenge, But I'm gonna ask you the big, chewy question now. Then we maybe go to some audience questions when you think about the world's biggest problems. I mean, we're global pandemics, obviously top of mind. You think about nutrition, you know, feeding the global community. We've actually done a pretty good job of that. But it's not necessarily with the greatest nutrition, climate change, alternative energy, the economic divides. You've got geopolitical threats and social unrest. Health care is a continuing problem. What's your vision for changing the world and how product innovation for good and be applied to some of the the problems that that you all are passionate about? Big question. Who wants toe start? >>Not biased. But for years I've been saying that if you want to solve the economy, the environment, uh, global unrest, pandemics, education is the case. If you wanna. If you want to, um, make progress in those in those realms, I think funding funding education is probably gonna pay off pretty well. >>Absolutely. And I think Stam is key to that. I mean, all of the ah lot of the well being that we have today and then industrialized countries. Thanks to science and technology, right improvements in health care, improvements in communication, transportation, air conditioning. Um, every aspect of life is touched by science and technology. So I think having more kids studying and understanding that is absolutely key. Yeah, I agree, >>Philip, you got anything to add? >>I think there's some big technical problems in the world today, Raphael and ourselves there certainly working on a couple of them. Think they're also collaboration problems and getting everybody to be able to pull together instead of pulling separately and to be able to spur the ideas on words. So that's where I think the education side is really exciting. What Matt is doing and it just kind of collaboration in general when we could do provide tools to help people do good work. Uh, that is, I think, valuable. >>Yeah, I think that's a very good point. And along those lines, we have some projects that are about creating very low cost instruments for low research settings, places in Africa, Southeast Asia, South America, so that they can do, um, um, biomedical research that it's difficult to do in those place because they don't have the money to buy the fancy lab machines that cost $30,000 an hour. Um, so we're trying to sort of democratize some of those instruments. And I think thanks to tools like Kahn shape then is easier, for example, to have a conversation with somebody in Africa and show them the design that we have and discuss the details of it with them on. But it's amazing, right to have somebody, you know, 10 time zones away, Um, looking really life in real time with you about your design and discussing the details or teaching them how to build a machine, right? Because, um, you know, they have a three D printer. You can you can just give them the design and say like, you build it yourself, uh, even cheaper than and, you know, also billing and shipping it there. Um, so all that that that aspect of it is also super important. I think for any of these efforts to improve some of the hardest part was in the world for climate change. Do you say, as you say, poverty, nutrition issues? Um, you know, availability of water. You have that project at about finding water. Um, if we can also help deploy technologies that teach people remotely how to create their own technologies or how to build their own systems that will help them solve those forms locally. I think that's very powerful. >>Yeah, the point about education is right on. I think some people in the audience may be familiar with the work of Erik Brynjolfsson and Andrew McAfee, the second machine age where they sort of put forth the premise that, uh, is it laid it out. Look, for the first time in history, machines air replacing humans from a cognitive perspective. Machines have always replaced humans, but that's gonna have an impact on jobs. But the answer is not toe protect the past from the future. The answer is education and public policy that really supports that. So I couldn't agree more. I think it's a really great point. Um, we have We do have some questions from the audience. If if we could If I can ask you guys, um, you know, this one kind of stands out. How do you see artificial intelligence? I was just talking about machine intelligence. Um, how do you see that? Impacting the design space guys trying to infuse a I into your product development. Can you tell me? >>Um, absolutely, like, we're using AI for some things, including some of these very low cost instruments that will hopefully help us diagnose certain diseases, especially this is that are very prevalent in the Third World. Um, and some of those diagnostics are these days done by thes armies of technicians that are trained to look under the microscope. But, um, that's a very slow process. Is very error prone and having machine learning systems that can to the same diagnosis faster, cheaper and also little machines that can be taken to very remote places to these villages that have no access to a fancy microscope. To look at a sample from a patient that's very powerful. And I we don't do this, but I have read quite a bit about how certain places air using a Tribune attorneys to actually help them optimize designs for parts. So you get these very interesting looking parts that you would have never thought off a person would have never thought off, but that are incredibly light ink. Earlier, strong and I have all sort of properties that are interesting thanks to artificial intelligence machine learning in particular >>yet another. The advantage you get when when your work is in the cloud I've seen. I mean, there's just so many applications that so if the radiology scan is in the cloud and the radiologist is goes to bed at night, Radiologist could come in in the morning and and say, Oh, the machine while you were sleeping was using artificial intelligence to scan these 40,000 images. And here's the five that we picked out that we think you should take a closer look at. Or like Raphael said, I can design my part. My, my, my, my, my you know, mount or bracket or whatever and go to sleep. And then I wake up in the morning. The machine has improved. It for me has made it strider strider stronger and lighter. Um And so just when your when your work is in the cloud, that's just that's a really cool advantage that you get that you can have machines doing some of your design work for you. >>Yeah, we've been watching, uh, you know, this week is this month, I guess is AWS re invent and it's just amazing to see how much effort is coming around machine learning machine intelligence. You know Amazon has sage maker Google's got, you know, embedded you no ML and big query. Uh, certainly Microsoft with Azure is doing tons of stuff and machine learning. I think the point there is that that these things will be infused in tow R and D and in tow software product by the vendor community. And you all will apply that to your business and and build value through the unique data that your collecting, you know, in your ecosystems. And and that's how you add value. You don't have to be necessarily, you know, developers of artificial intelligence, but you have to be practitioners to apply that. Does that make sense to you, Philip? >>Yeah, absolutely. And I think your point about value is really well chosen. We see AI involved from the physics simulations all the way up to interpreting radiation data, and that's where the value question, I think, is really important because it's is the output of the AI giving helpful information that the people that need to be looking at it. So if it's curating a serious of radiation alert, saying, Hey, like these air the anomalies. You need to look at eyes it, doing that in a way that's going to help a good response on. In some cases, the II is only as good as the people. That sort of gave it a direction and turn it loose. And you want to make sure that you don't have biases or things like that underlying your AI that they're going to result in less than helpful outcomes coming from it. So we spend quite a lot of time thinking about how do we provide the right outcomes to people who are who are relying on our systems? >>That's a great point, right? Humans air biased and humans build models, so models are inherently biased. But then the software is hitting the market. That's gonna help us identify those biases and help us, you know? Of course. Correct. So we're entering Cem some very exciting times, guys. Great conversation. I can't thank you enough for spending the time with us and sharing with our audience the innovations that you're bringing to help the world. So thanks again. >>Thank you so much. >>Thank you. >>Okay. Welcome. Okay. When we come back, John McElheny is gonna join me. He's on shape. Co founder. And he's currently the VP of strategy at PTC. He's gonna join the program. We're gonna take a look at what's next and product innovation. I'm Dave Volonte and you're watching innovation for good on the Cube, the global leader. Digital technology event coverage. We'll be right back. >>Okay? Okay. Yeah. Okay. >>From around >>the globe, it's the Cube. Presenting innovation for good. Brought to you by on shape. >>Okay, welcome back to innovation. For good. With me is John McElheny, who is one of the co founders of On Shape and is now the VP of strategy at PTC. John, it's good to see you. Thanks for making the time to come on the program. Thanks, Dave. So we heard earlier some of the accomplishments that you've made since the acquisition. How has the acquisition affected your strategy? Maybe you could talk about what resource is PTC brought to the table that allowed you toe sort of rethink or evolve your strategy? What can you share with us? >>Sure. You know, a year ago, when when John and myself met with Jim Pepperman early on is we're we're pondering. Started joining PTC one of things became very clear is that we had a very clear shared vision about how we could take the on shape platform and really extended for, for all of the PTC products, particular sort of their augmented reality as well as their their thing works or the i o. T business and their product. And so from the very beginning there was a clear strategy about taking on shape, extending the platform and really investing, um, pretty significantly in the product development as well as go to market side of things, uh, toe to bring on shape out to not only the PTC based but sort of the broader community at large. So So So PTC has been a terrific, terrific, um, sort of partner as we've we've gonna go on after this market together. Eso We've added a lot of resource and product development side of things. Ah, lot of resource and they go to market and customer success and support. So, really, on many fronts, that's been both. Resource is as well a sort of support at the corporate level from from a strategic standpoint and then in the field, we've had wonderful interactions with many large enterprise customers as well as the PTC channels. So it's been really a great a great year. >>Well, and you think about the challenges of in your business going to SAS, which you guys, you know, took on that journey. You know, 78 years ago. Uh, it's not trivial for a lot of companies to make that transition, especially a company that's been around as long as PTC. So So I'm wondering how much you know, I was just asking you How about what PCP TC brought to the table? E gotta believe you're bringing a lot to the table to in terms of the mindset, uh, even things is, is mundane is not the right word, but things like how you compensate salespeople, how you interact with customers, the notion of a service versus a product. I wonder if you could address >>that. Yeah, it's a it's a really great point. In fact, after we had met Jim last year, John and I one of the things we walked out in the seaport area in Boston, one of things we sort of said is, you know, Jim really gets what we're trying to do here and and part of let me bring you into the thinking early on. Part of what Jim talked about is there's lots of, you know, installed base sort of software that's inside of PTC base. That's helped literally thousands of customers around the world. But the idea of moving to sass and all that it entails both from a technology standpoint but also a cultural standpoint. Like How do you not not just compensate the sales people as an example? But how do you think about customer success? In the past, it might have been that you had professional services that you bring out to a customer, help them deploy your solutions. Well, when you're thinking about a SAS based offering, it's really critical that you get customers successful with it. Otherwise, you may have turned, and you know it will be very expensive in terms of your business long term. So you've got to get customers success with software in the very beginning. So you know, Jim really looked at on shape and he said that John and I, from a cultural standpoint, you know, a lot of times companies get acquired and they've acquired technology in the past that they integrate directly into into PTC and then sort of roll it out through their products, are there just reached channel, he said. In some respects, John John, think about it as we're gonna take PTC and we want to integrate it into on shape because we want you to share with us both on the sales side and customer success on marketing on operations. You know all the things because long term, we believe the world is a SAS world, that the whole industry is gonna move too. So really, it was sort of an inverse in terms of the thought process related to normal transactions >>on That makes a lot of sense to me. You mentioned Sharon turns the silent killer of a SAS company, and you know, there's a lot of discussion, you know, in the entrepreneurial community because you live this, you know what's the best path? I mean today, You see, you know, if you watch Silicon Valley double, double, triple triple, but but there's a lot of people who believe, and I wonder, if you come in there is the best path to, you know, in the X Y axis. If if it's if it's uh, growth on one and retention on the other axis. What's the best way to get to the upper right on? Really? The the best path is probably make sure you've nailed obviously the product market fit, But make sure that you can retain customers and then throw gas on the fire. You see a lot of companies they burn out trying to grow too fast, but they haven't figured out, you know that. But there's too much churn. They haven't figured out those metrics. I mean, obviously on shape. You know, you were sort of a pioneer in here. I gotta believe you've figured out that customer retention before you really, You know, put the pedal to the >>metal. Yeah, and you know, growth growth can mask a lot of things, but getting getting customers, especially the engineering space. Nobody goes and sits there and says, Tomorrow we're gonna go and and, you know, put 100 users on this and and immediately swap out all of our existing tools. These tools are very rich and deep in terms of capability, and they become part of the operational process of how a company designs and builds products. So any time anybody is actually going through the purchasing process. Typically, they will run a try along or they'll run a project where they look at. Kind of What? What is this new solution gonna help them dio. How are we gonna orient ourselves for success? Longer term. So for us, you know, getting new customers and customer acquisition is really critical. But getting those customers to actually deploy the solution to be successful with it. You know, we like to sort of, say, the marketing or the lead generation and even some of the initial sales. That's sort of like the Kindle ing. But the fire really starts when customers deploy it and get successful. The solution because they bring other customers into the fold. And then, of course, if they're successful with it, you know, then in fact, you have negative turn which, ironically, means growth in terms of your inside of your install. Bates. >>Right? And you've seen that with some of the emerging, you know, SAS companies, where you're you're actually you know, when you calculate whatever its net retention or renew ALS, it's actually from a dollar standpoint. It's up in the high nineties or even over 100%. >>So >>and that's a trend we're gonna continue. See, I >>wonder >>if we could sort of go back. Uh, and when you guys were starting on shape, some of the things that you saw that you were trying to strategically leverage and what's changed, you know, today we were talking. I was talking to John earlier about in a way, you kinda you kinda got a blank slate is like doing another startup. >>You're >>not. Obviously you've got installed base and customers to service, but But it's a new beginning for you guys. So one of the things that you saw then you know, cloud and and sas and okay, but that's we've been there, done that. What are you seeing? You know today? >>Well, you know, So So this is a journey, of course, that that on shape on its own has gone through it had I'll sort of say, you know, several iterations, both in terms of of of, you know, how do you How do you get customers? How do you How do you get them successful? How do you grow those customers? And now that we've been part of PTC, the question becomes okay. One, There is certainly a higher level of credibility that helps us in terms of our our megaphone is much bigger than it was when we're standalone company. But on top of that now, figuring out how to work with their channel with their direct sales force, you know, they have, um, for example, you know, very large enterprises. Well, many of those customers are not gonna go in forklift out their existing solution to replace it with with on shape. However, many of them do have challenges in their supply chain and communications with contractors and vendors across the globe. And so, you know, finding our fit inside of those large enterprises as they extend out with their their customers is a very interesting area that we've really been sort of incremental to to PTC. And then, you know, they they have access to lots of other technology, like the i o. T business. And now, of course, the augmented reality business that that we can bring things to bear. For example, in the augmented reality world, they've they've got something called expert capture. And this is essentially imagine, you know, in a are ah, headset that allows you to be ableto to speak to it, but also capture images still images in video. And you could take somebody who's doing their task and capture literally the steps that they're taking its geo location and from their builds steps for new employees to be, we'll learn and understand how todo use that technology to help them do their job better. Well, when they do that, if there is replacement products or variation of of some of the tools that that they built the original design instruction set for they now have another version. Well, they have to manage multiple versions. Well, that's what on shape is really great at doing and so taking our technology and helping their solutions as well. So it's not only expanding our customer footprint, it's expanding the application footprint in terms of how we can help them and help customers. >>So that leads me to the tam discussion and again, as part of your strategist role. How do you think about that? Was just talking to some of your customers earlier about the democratization of cat and engineering? You know, I kind of joked, sort of like citizen engineering, but but so that you know, the demographics are changing the number of users potentially that can access the products because the it's so much more of a facile experience. How are you thinking about the total available market? >>It really is a great question, You know, it used to be when you when you sold boxes of software, it was how many engineers were out there. And that's the size of the market. The fact that matter is now when, When you think about access to that information, that data is simply a pane of glass. Whether it's a computer, whether it's a laptop, UH, a a cell phone or whether it's a tablet, the ability to to use different vehicles, access information and data expands the capabilities and power of a system to allow feedback and iteration. I mean, one of the one of the very interesting things is in technology is when you can take something and really unleash it to a larger audience and builds, you know, purpose built applications. You can start to iterate, get better feedback. You know there's a classic case in the clothing industry where Zara, you know, is a fast sort of turnaround. Agile manufacturer. And there was a great New York Times article written a couple years ago. My wife's a fan of Zara, and I think she justifies any purchases by saying, You know, Zara, you gotta purchase it now. Otherwise it may not be there the next time. Yet you go back to the store. They had some people in a store in New York that had this woman's throw kind of covering Shaw. And they said, Well, it would be great if we could have this little clip here so we can hook it through or something. And they sent a note back toe to the factory in Spain, and literally two weeks later they had, you know, 4000 of these things in store, and they sold out because they had a closed loop and iterative process. And so if we could take information and allow people access in multiple ways through different devices and different screens, that could be very specific information that, you know, we remove a lot of the engineering data book, bring the end user products conceptually to somebody that would have had to wait months to get the actual physical prototype, and we could get feedback well, Weaken have a better chance of making sure whatever product we're building is the right product when it ultimately gets delivered to a customer. So it's really it's a much larger market that has to be thought of rather than just the kind of selling A boxes software to an engineer. >>That's a great story. And again, it's gonna be exciting for you guys to see that with. The added resource is that you have a PTC, Um, so let's talk. I promise people we wanna talk about Atlas. Let's talk about the platform. A little bit of Atlas was announced last year. Atlas. For those who don't know it's a SAS space platform, it purports to go beyond product lifecycle management and you You're talking cloud like agility and scale to CAD and product design. But John, you could do a better job than I. What do >>we need to know about Atlas? Well, I think Atlas is a great description because it really is metaphorically sort of holding up all of the PTC applications themselves. But from the very beginning, when John and I met with Jim, part of what we were intrigued about was that he shared a vision that on shape was more than just going to be a cad authoring tool that, in fact, you know, in the past these engineering tools were very powerful, but they were very narrow in their purpose and focus. And we had specialty applications to manage the versions, etcetera. What we did in on shape is we kind of inverted that thinking. We built this collaboration and sharing engine at the core and then kind of wrap the CAD system around it. But that collaboration sharing and version ING engine is really powerful. And it was that vision that Jim had that he shared that we had from the beginning, which was, how do we take this thing to make a platform that could be used for many other applications inside of inside of any company? And so not only do we have a partner application area that is is much like the APP store or Google play store. Uh, that was sort of our first Stan Shih ation of this. This this platform. But now we're extending out to broader applications and much meatier applications. And internally, that's the thing works in the in the augmented reality. But there'll be other applications that ultimately find its way on top of this platform. And so they'll get all the benefits of of the collaboration, sharing the version ing the multi platform, multi device. And that's an extremely extremely, um, strategic leverage point for the company. >>You know, it's interesting, John, you mentioned the seaport before. So PTC, for those who don't know, built a beautiful facility down at the Seaport in Boston. And, of course, when PTC started, you know, back in the mid 19 eighties, there was nothing at the seaport s. >>So it's >>kind of kind of ironic, you know, we were way seeing the transformation of the seaport. We're seeing the transformation of industry and of course, PTC. And I'm sure someday you'll get back into that beautiful office, you know? Wait. Yeah, I'll bet. And, uh and but I wanna bring this up because I want I want you to talk about the future. How you how you see that our industry and you've observed this has moved from very product centric, uh, plat platform centric with sass and cloud. And now we're seeing ecosystems form around those products and platforms and data flowing through the ecosystem powering, you know, new innovation. I wonder if you could paint a picture for us of what the future looks like to you from your vantage point. >>Yeah, I think one of the key words you said there is data because up until now, data for companies really was sort of trapped in different applications. And it wasn't because people were nefarious and they want to keep it limited. It was just the way in which things were built. And, you know, when people use an application like on shape, what ends up happening is there their day to day interaction and everything that they do is actually captured by the platform. And, you know, we don't have access to that data. Of course it's it's the customer's data. But as as an artifact of them using the system than doing their day to day job, what's happening is they're creating huge amounts of information that can then be accessed and analyzed to help them both improve their design process, improve their efficiencies, improve their actual schedules in terms of making sure they can hit delivery times and be able to understand where there might be roadblocks in the future. So the way I see it is companies now are deploying SAS based tools like on shape and an artifact of them. Using that platform is that they have now analytics and tools to better understand and an instrument and manage their business. And then from there, I think you're going to see, because these systems are all you know extremely well. Architected allow through, you know, very structured AP. I calls to connect other SAS based applications. You're gonna start seeing closed loop sort of system. So, for example, people design using on shape, they end up going and deploying their system or installing it, or people use the end using products. People then may call back into the customers support line and report issues, problems, challenges. They'll be able to do traceability back to the underlying design. They'll be able to do trend analysis and defect analysis from the support lines and tie it back and closed loop the product design, manufacture, deployment in the field sort of cycles. In addition, you can imagine there's many things that air sort of as designed. But then when people go on site and they have to install it. There's some alterations modifications. Think about think about like a large air conditioning units for buildings. You go and you go to train and you get a large air conditioning unit that put up on top of building with a crane. They have to build all kinds of adaptors to make sure that that will fit inside of the particulars of that building. You know, with on shape and tools like this, you'll be able to not only take the design of what the air conditioning system might be, but also the all the adapter plates, but also how they installed it. So it sort of as designed as manufactured as stalled. And all these things can be traced, just like if you think about the transformation of customer service or customer contacts. In the early days, you used to have tools that were PC based tools called contact management solution, you know, kind of act or gold mine. And these were basically glorified Elektronik role in Texas. It had a customer names and they had phone numbers and whatever else. And Salesforce and Siebel, you know, these types of systems really broadened out the perspective of what a customer relationship? Waas. So it wasn't just the contact information it was, you know, How did they come to find out about you as a company? So all of the pre sort of marketing and then kind of what happens after they become a customer and it really was a 3 60 view. I think that 3 60 view gets extended to not just to the customers, but also tools and the products they use. And then, of course, the performance information that could come back to the manufacturer. So, you know, as an engineer, one of the things you learn about with systems is the following. And if you remember, when the CD first came out CDs that used to talk about four times over sampling or eight times over sampling and it was really kind of, you know, the fidelity the system. And we know from systems theory that the best way to improve the performance of a system is to actually have more feedback. The more feedback you have, the better system could be. And so that's why you get 16 60 for example, etcetera. Same thing here. The more feedback we have of different parts of a company that a better performance, The company will be better customer relationships. Better, uh, overall financial performance as well. So that's that's the view I have of how these systems all tied together. >>It's a great vision in your point about the data is I think right on. It used to be so fragmented in silos, and in order to take a system view, you've gotta have a system view of the data. Now, for years, we've optimized maybe on one little component of the system and that sometimes we lose sight of the overall outcome. And so what you just described, I think is, I think sets up. You know very well as we exit. Hopefully soon we exit this this covert era on John. I hope that you and I can sit down face to face at a PTC on shape event in the near term >>in the seaport in the >>seaport would tell you that great facility toe have have an event for sure. It >>z wonderful >>there. So So John McElhinney. Thanks so much for for participating in the program. It was really great to have you on, >>right? Thanks, Dave. >>Okay. And I want to thank everyone for participating. Today we have some great guest speakers. And remember, this is a live program. So give us a little bit of time. We're gonna flip this site over toe on demand mode so you can share it with your colleagues and you, or you can come back and and watch the sessions that you heard today. Uh, this is Dave Volonte for the Cube and on shape PTC. Thank you so much for watching innovation for good. Be well, Have a great holiday. And we'll see you next time. Yeah.

>> Announcer: From theCUBE Studios in Palo Alto and Boston, connecting with thought leaders all around the world, this is a Cube conversation. >> Hey welcome back everybody, Jeff Frick here with theCUBE. We are in our Palo Alto studios, COVID is still going on, so all of the interviews continue to be remote, but we're excited to have a Cube alumni, he hasn't been on for a long time, and this guy has been in the weeds of the storage industry for a very very long time and we're happy to have him on and get an update because there continues to be a lot of exciting developments. He's Phil Bullinger, he is the SVP and general manager, data center business unit from Western Digital joining us, I think for Colorado, so Phil, great to see you, how's the weather in Colorado today? >> Hi Jeff, it's great to be here. Well, it's a hot, dry summer here, I'm sure like a lot of places. But yeah, enjoying the summer through these unusual times. >> It is unusual times, but fortunately there's great things like the internet and heavy duty compute and store out there so we can get together this way. So let's jump into it. You've been in the he business a long time, you've been at Western Digital, you were at EMC, you worked on Isilon, and you were at storage companies before that. And you've seen kind of this never-ending up and to the right slope that we see kind of ad nauseum in terms of the amount of storage demands. It's not going anywhere but up, and please increase complexity in terms of unstructure data, sources of data, speed of data, you know the kind of classic big V's of big data. So I wonder, before we jump into specifics, if you can kind of share your perspective 'cause you've been kind of sitting in the Catford seat, and Western Digital's a really unique company; you not only have solutions, but you also have media that feeds other people solutions. So you guys are really seeing and ultimately all this compute's got to put this data somewhere, and a whole lot of it's sitting on Western Digital. >> Yeah, it's a great intro there. Yeah, it's been interesting, through my career, I've seen a lot of advances in storage technology. Speeds and feeds like we often say, but the advancement through mechanical innovation, electrical innovation, chemistry, physics, just the relentless growth of data has been driven in many ways by the relentless acceleration and innovation of our ability to store that data, and that's been a very virtuous cycle through what, for me, has been 30 years in enterprise storage. There are some really interesting changes going on though I think. If you think about it, in a relatively short amount of time, data has gone from this artifact of our digital lives to the very engine that's driving the global economy. Our jobs, our relationships, our health, our security, they all kind of depend on data now, and for most companies, kind of irrespective of size, how you use data, how you store it, how you monetize it, how you use it to make better decisions to improve products and services, it becomes not just a matter of whether your company's going to thrive or not, but in many industries, it's almost an existential question; is your company going to be around in the future, and it depends on how well you're using data. So this drive to capitalize on the value of data is pretty significant. >> It's a really interesting topic, we've had a number of conversations around trying to get a book value of data, if you will, and I think there's a lot of conversations, whether it's accounting kind of way, or finance, or kind of good will of how do you value this data? But I think we see it intrinsically in a lot of the big companies that are really data based, like the Facebooks and the Amazons and the Netflixes and the Googles, and those types of companies where it's really easy to see, and if you see the valuation that they have, compared to their book value of assets, it's really baked into there. So it's fundamental to going forward, and then we have this thing called COVID hit, which I'm sure you've seen all the memes on social media. What drove your digital transformation, the CEO, the CMO, the board, or COVID-19? And it became this light switch moment where your opportunities to think about it are no more; you've got to jump in with both feet, and it's really interesting to your point that it's the ability to store this and think about it now differently as an asset driving business value versus a cost that IT has to accommodate to put this stuff somewhere, so it's a really different kind of a mind shift and really changes the investment equation for companies like Western Digital about how people should invest in higher performance and higher capacity and more unified and kind of democratizing the accessibility that data, to a much greater set of people with tools that can now start making much more business line and in-line decisions than just the data scientist kind of on Mahogany Row. >> Yeah, as you mentioned, Jeff, here at Western Digital, we have such a unique kind of perch in the industry to see all the dynamics in the OEM space and the hyperscale space and the channel, really across all the global economies about this growth of data. I have worked at several companies and have been familiar with what I would have called big data projects and fleets in the past. But at Western Digital, you have to move the decimal point quite a few digits to the right to get the perspective that we have on just the volume of data that the world has just relentless insatiably consuming. Just a couple examples, for our drive projects we're working on now, our capacity enterprise drive projects, you know, we used to do business case analysis and look at their lifecycle capacities and we measured them in exabytes, and not anymore, now we're talking about zettabyte, we're actually measuring capacity enterprise drive families in terms of how many zettabyte they're going to ship in their lifecycle. If we look at just the consumption of this data, the last 12 months of industry TAM for capacity enterprise compared to the 12 months prior to that, that annual growth rate was north of 60%. And so it's rare to see industries that are growing at that pace. And so the world is just consuming immense amounts of data, and as you mentioned, the COVID dynamics have been both an accelerant in some areas, as well as headwinds in others, but it's certainly accelerated digital transformation. I think a lot of companies we're talking about, digital transformation and hybrid models and COVID has really accelerated that, and it's certainly driving, continues to drive just this relentless need to store and access and take advantage of data. >> Yeah, well Phil, in advance of this interview, I pulled up the old chart with all the different bytes, kilobytes, megabytes, gigabytes, terabytes, petabytes, exabytes, and zettabytes, and just per the Wikipedia page, what is a zettabyte? It's as much information as there are grains of sand in all the world's beaches. For one zettabyte. You're talking about thinking in terms of those units, I mean, that is just mind boggling to think that that is the scale in which we're operating. >> It's really hard to get your head wrapped around a zettabyte of storage, and I think a lot of the industry thinks when we say zettabyte scale era, that it's just a buzz word, but I'm here to say it's a real thing. We're measuring projects in terms of zettabytes now. >> That's amazing. Well, let's jump into some of the technology. So I've been fortunate enough here at theCUBE to be there at a couple of major announcements along the way. We talked before we turned the cameras on, the helium announcement and having the hard drive sit in the fish bowl to get all types of interesting benefits from this less dense air that is helium versus oxygen. I was down at the Mammer and Hammer announcement, which was pretty interesting; big heavy technology moves there, to again, increase the capacity of the hard drive's base systems. You guys are doing a lot of stuff on RISC-V I know is an Open source project, so you guys have a lot of things happening, but now there's this new thing, this new thing called zonedd storage. So first off, before we get into it, why do we need zoned storage, and really what does it now bring to the table in terms of a capability? >> Yeah, great question, Jeff. So why now, right? Because I mentioned storage, I've been in storage for quite some time. In the last, let's just say in the last decade, we've seen the advent of the hyperscale model and certainly a whole nother explosion level of data and just the veracity with which they hyperscalers can create and consume and process and monetize data. And of course with that, has also come a lot of innovation, frankly, in the compute space around how to process that data and moving from what was just a general purpose CPU model to GPU's and DPU's and so we've seen a lot of innovation on that side, but frankly, in the storage side, we haven't seen much change at all in terms of how operating systems, applications, file systems, how they actually use the storage or communicate with the storage. And sure, we've seen advances in storage capacities; hard drives have gone from two to four, to eight, to 10 to 14, 16, and now our leading 18 and 20 terabyte hard drives. And similarly, on the SSD side, now we're dealing with the capacities of seven, and 15, and 30 terabytes. So things have gotten larger, as you expect. And some interfaces have improved, I think NVME, which we'll talk about, has been a nice advance in the industry; it's really now brought a very modern scalable low latency multi-threaded interface to a NAM flash to take advantage of the inherent performance of transistor based persistent storage. But really when you think about it, it hasn't changed a lot. But what has changed is workloads. One thing that definitely has evolved in the space of the last decade or so is this, the thing that's driving a lot of this explosion of data in the industry is around workloads that I would characterize as sequential in nature, they're serial, you can capture it in written. They also have a very consistent life cycle, so you would write them in a big chunk, you would read them maybe in smaller pieces, but the lifecycle of that data, we can treat more as a chunk of data, but the problem is applications, operating systems, vial systems continue to interface with storage using paradigms that are many decades old. The old 512 byte or even Forte, Sector size constructs were developed in the hard drive industry just as convenient paradigms to structure what is an unstructured sea of magnetic grains into something structured that can be used to store and access data. But the reality is when we talk about SSDs, structure really matters, and so what has changed in the industry is the workloads are driving very very fresh looks at how more intelligence can be applied to that application OS storage device interface to drive much greater efficiency. >> Right, so there's two things going on here that I want to drill down on. On one hand, you talked about kind of the introduction of NAND and flash, and treating it like you did, generically you did a regular hard drive. But you could get away and you could do some things because the interface wasn't taking full advantage of the speed that was capable in the NAND. But NVME has changed that, and now forced kind of getting rid of some of those inefficient processes that you could live with, so it's just kind of classic next level step up and capabilities. One is you get the better media, you just kind of plug it into the old way. Now actually you're starting to put in processes that take full advantage of the speed that that flash has. And I think obviously prices have come down dramatically since the first introduction, where before it was always kind of a clustered off or super high end, super low latency, super high value apps, it just continues to spread and proliferate throughout the data center. So what did NVME force you to think about in terms of maximizing the return on the NAND and flash? >> Yeah, NVME, which we've been involved in the standardization, I think it's been a very successful effort, but we have to remember NVME is about a decade old, or even more when the original work started around defining this interface, but it's been very successful. The NVME standard's body is very productive cross company effort, it's really driven a significant change, and what we see now is the rapid adoption of NVME in all of data center architectures, whether it's very large hyperscale to classic on prem enterprise to even smaller applications, it's just a very efficient interface mechanism for connecting SSDs into a server. So we continue to see evolution at NVME, which is great, and we'll talk about ZNS today as one of those evolutions. We're also very keenly interested in NVME protocol over fabrics, and so one of the things that Western Digital has been talking about a lot lately is incorporating NVME over fabrics as a mechanism for now connecting shared storage into multiple post architectures. We think this is a very attractive way to build shared storage architectures of the future that are scalable, that are composable, that really have a lot more agility with respect to rack level infrastructure and applying that infrastructure to applications. >> Right, now one thing that might strike some people as kind of counterintuitive is within the zoned storage in zoning off parts of the media, to think of the data also kind of in these big chunks, is it feels contrary to kind of atomization that we're seeing in the rest of the data center, right? So smaller units of compute, smaller units of store, so that you can assemble and disassemble them in different quantities as needed. So what was the special attribute that you had to think about and actually come back and provide a benefit in actually kind of re-chunking, if you will, in these zones versus trying to get as atomic as possible? >> Yeah, it's a great question, Jeff, and I think it's maybe not intuitive in terms of why zoned storage actually creates a more efficient storage paradigm when you're storing stuff essentially in larger blocks of data, but this is really where the intersection of structure and workload and sort of the nature of the data all come together. If you turn back the clock maybe four or five years when SMR hard drives host managers SMR hard drives first emerged on the scene. This was really taking advantage of the fact that the right head on a hard disk drive is larger than the read head, or the read head can be much smaller, and so the notion of overlapping or shingling the data on the drive, giving the read head a smaller target to read, but the writer a larger write pad to write the data could actually, what we found was it increases aerial density significantly. And so that was really the emergence of this notion of sequentially written larger blocks of data being actually much more efficiently stored when you think about physically how it's being stored. What's very new now and really gaining a lot of traction is the SSD corollary to SMR on the hard drive, on the SSD side, we had the ZNS specification, which is, very similarly where you'd divide up the name space of an SSD into fixed size zones, and those zones are written sequentially, but now those zones are intimately tied to the underlying physical architecture of the NAND itself; the dyes, the planes, the read pages, the erase pages. So that, in treating data as a block, you're actually eliminating a lot of the complexity and the work that an SSD has to do to emulate a legacy hard drive, and in doing so, you're increasing performance and endurance and the predictable performance of the device. >> I just love the way that you kind of twist the lens on the problem, and on one hand, by rule, just looking at my notes here, the zoned storage device is the ZSD's introduce a number of restrictions and limitations and rules that are outside the full capabilities of what you might do. But in doing so, an aggregate, the efficiency, and the performance of the system in the whole is much much better, even though when you first look at it, you think it's more of a limiter, but it's actually opens up. I wonder if there's any kind of performance stats you can share or any kind of empirical data just to give people kind of a feel for what that comes out as. >> So if you think about the potential of zoned storage in general and again, when I talk about zoned storage, there's two components; there's an HDD component of zoned storage that we refer to as SMR, and there's an SSD version of that that we call ZNS. So we think about SMR, the value proposition there is additional capacity. So effectively in the same drive architecture, with roughly the same bill of material used to build the drive, we can overlap or shingle the data on the drive. And generally for the customer, additional capacity. Today with our 18, 20 terabyte offerings that's on the order of just over 10%, but that delta is going to increase significantly going forward to 20% or more. And when you think about a hyperscale customer that has not hundreds or thousands of racks, but tens of thousands of racks. A 10 or 20% improvement in effective capacity is a tremendous TCO benefit, and the reason we do that is obvious. I mean, the economic paradigm that drives large at-scale data centers is total custom ownership, both acquisition costs and operating costs. And if you can put more storage in a square tile of data center space, you're going to generally use less power, you're going to run it more efficiently, you're actually, from an acquisition cost, you're getting a more efficient purchase of that capacity. And in doing that, our innovation, we benefit from it and our customers benefit from it. So the value proposition for zoned storage in capacity enterprise HDV is very clear, it's additional capacity. The exciting thing is, in the SSD side of things, or ZNS, it actually opens up even more value proposition for the customer. Because SSDs have had to emulate hard drives, there's been a lot of inefficiency and complexity inside an enterprise SSD dealing with things like garbage collection and right amplification reducing the endurance of the device. You have to over-provision, you have to insert as much as 20, 25, even 28% additional man bits inside the device just to allow for that extra space, that working space to deal with delete of data that are smaller than the block erase that the device supports. So you have to do a lot of reading and writing of data and cleaning up. It creates for a very complex environment. ZNS by mapping the zoned size with the physical structure of the SSD essentially eliminates garbage collection, it reduces over-provisioning by as much as 10x. And so if you were over provisioning by 20 or 25% on an enterprise SSD, and a ZNS SSD, that can be one or two percent. The other thing I have to keep in mind is enterprise SSD is typically incorporate D RAM and that D RAM is used to help manage all those dynamics that I just mentioned, but with a much simpler structure where the pointers to the data can be managed without all the D RAM. We can actually reduce the amount of D RAM in an enterprise SSD by as much as eight X. And if you think about the MILA material of an enterprise SSD, D RAM is number two on the list in terms of the most expensive bomb components. So ZNS and SSDs actually have a significant customer total cost of ownership impact. It's an exciting standard, and now that we have the standard ratified through the NVME working group, it can really accelerate the development of the software ecosystem around. >> Right, so let's shift gears and talk a little bit about less about the tech and more about the customers and the implementation of this. So you talked kind of generally, but are there certain types of workloads that you're seeing in the marketplace where this is a better fit or is it just really the big heavy lifts where they just need more and this is better? And then secondly, within these hyperscale companies, as well as just regular enterprises that are also seeing their data demands grow dramatically, are you seeing that this is a solution that they want to bring in for kind of the marginal kind of next data center, extension of their data center, or their next cloud region? Or are they doing lift and shift and ripping stuff out? Or do they enough data growth organically that there's plenty of new stuff that they can put in these new systems? >> Yeah, I love that. The large customers don't rip and shift; they ride their assets for a long lifecycle, 'cause with the relentless growth of data, you're primarily investing to handle what's coming in over the transom. But we're seeing solid adoption. And in SMRS you know we've been working on that for a number of years. We've got significant interest and investment, co-investment, our engineering, and our customer's engineering adapting the application environment's to take advantage of SMR. The great thing is now that we've got the NVME, the ZNS standard gratified now in the NVME working group, we've got a very similar, and all approved now, situation where we've got SMR standards that have been approved for some time, and the SATA and SCSI standards. Now we've got the same thing in the NVME standard, and the great thing is once a company goes through the lift, so to speak, to adapt an application, file system, operating system, ecosystem, to zoned storage, it pretty much works seamlessly between HDD and SSD, and so it's not an incremental investment when you're switching technologies. Obviously the early adopters of these technologies are going to be the large companies who design their own infrastructure, who have mega fleets of racks of infrastructure where these efficiencies really really make a difference in terms of how they can monetize that data, how they compete against the landscape of competitors they have. For companies that are totally reliant on kind of off the shelf standard applications, that adoption curve is going to be longer, of course, because there are some software changes that you need to adapt to enable zoned storage. One of the things Western Digital has done and taken the lead on is creating a landing page for the industry with zoned storage.io. It's a webpage that's actually an area where many companies can contribute Open source tools, code, validation environments, technical documentation. It's not a marketeering website, it's really a website built to land actual Open source content that companies can use and leverage and contribute to to accelerate the engineering work to adapt software stacks to zoned storage devices, and to share those things. >> Let me just follow up on that 'cause, again, you've been around for a while, and get your perspective on the power of Open source. And it used to be the best secrets, the best IP were closely guarded and held inside, and now really we're in an age where it's not necessarily. And the brilliant minds and use cases and people out there, just by definition, it's more groups of engineers, more engineers outside your building than inside your building, and how that's really changed kind of a strategy in terms of development when you can leverage Open source. >> Yeah, Open source clearly has accelerated innovation across the industry in so many ways, and it's the paradigm around which companies have built business models and innovated on top of it, I think it's always important as a company to understand what value ad you're bringing, and what value ad the customers want to pay for. What unmet needs in your customers are you trying to solve for, and what's the best mechanism to do that? And do you want to spend your RND recreating things, or leveraging what's available and innovating on top of it? It's all about ecosystem. I mean, the days where a single company could vertically integrate top to bottom a complete end solution, you know, those are fewer and far between. I think it's about collaboration and building ecosystems and operating within those. >> Yeah, it's such an interesting change, and one more thing, again, to get your perspective, you run the data center group, but there's this little thing happening out there that we see growing, IOT, in the industrial internet of things, and edge computing as we try to move more compute and store and power kind of outside the pristine world of the data center and out towards where this data is being collected and processed when you've got latency issues and all kinds of reasons to start to shift the balance of where the compute is and where the store and relies on the network. So when you look back from the storage perspective in your history in this industry and you start to see basically everything is now going to be connected, generating data, and a lot of it is even Opensource. I talked to somebody the other day doing kind of Opensource computer vision on surveillance video. So the amount of stuff coming off of these machines is growing in crazy ways. At the same time, it can't all be processed at the data center, it can't all be kind of shipped back and then have a decision and then ship that information back out to. So when you sit back and look at Edge from your kind of historical perspective, what goes through your mind, what gets you excited, what are some opportunities that you see that maybe the laymen is not paying close enough attention to? >> Yeah, it's really an exciting time in storage. I get asked that question from time to time, having been in storage for more than 30 years, you know, what was the most interesting time? And there's been a lot of them, but I wouldn't trade today's environment for any other in terms of just the velocity with which data is evolving and how it's being used and where it's being used. A TCO equation may describe what a data center looks like, but data locality will determine where it's located, and we're excited about the Edge opportunity. We see that as a pretty significant, meaningful part of the TAM as we look three to five years. Certainly 5G is driving much of that, I think just any time you speed up the speed of the connected fabric, you're going to increase storage and increase the processing the data. So the Edge opportunity is very interesting to us. We think a lot of it is driven by low latency work loads, so the concept of NVME is very appropriate for that, we think, in general SSDs deployed and Edge data centers defined as anywhere from a meter to a few kilometers from the source of the data. We think that's going to be a very strong paradigm. The workloads you mentioned, especially IOT, just machine-generated data in general, now I believe, has eclipsed human generated data, in terms of just the amount of data stored, and so we think that curve is just going to keep going in terms of machine generated data. Much of that data is so well suited for zoned storage because it's sequential, it's sequentially written, it's captured, and it has a very consistent and homogenous lifecycle associated with it. So we think what's going on with zoned storage in general and ZNS and SMR specifically are well suited for where a lot of the data growth is happening. And certainly we're going to see a lot of that at the Edge. >> Well, Phil, it's always great to talk to somebody who's been in the same industry for 30 years and is excited about today and the future. And as excited as they have been throughout their whole careers. So that really bodes well for you, bodes well for Western Digital, and we'll just keep hoping the smart people that you guys have over there, keep working on the software and the physics, and the mechanical engineering and keep moving this stuff along. It's really just amazing and just relentless. >> Yeah, it is relentless. What's exciting to me in particular, Jeff, is we've driven storage advancements largely through, as I said, a number of engineering disciplines, and those are still going to be important going forward, the chemistry, the physics, the electrical, the hardware capabilities. But I think as widely recognized in the industry, it's a diminishing curve. I mean, the amount of energy, the amount of engineering effort, investment, that cost and complexity of these products to get to that next capacity step is getting more difficult, not less. And so things like zoned storage, where we now bring intelligent data placement to this paradigm, is what I think makes this current juncture that we're at very exciting. >> Right, right, well, it's applied AI, right? Ultimately you're going to have more and more compute power driving the storage process and how that stuff is managed. As more cycles become available and they're cheaper, and ultimately compute gets cheaper and cheaper, as you said, you guys just keep finding new ways to move the curve in. And we didn't even get into the totally new material science, which is also coming down the pike at some point in time. >> Yeah, very exciting times. >> It's been great to catch up with you, I really enjoy the Western Digital story; I've been fortunate to sit in on a couple chapters, so again, congrats to you and we'll continue to watch and look forward to our next update. Hopefully it won't be another four years. >> Okay, thanks Jeff, I really appreciate the time. >> All right, thanks a lot. All right, he's Phil, I'm Jeff, you're watching theCUBE. Thanks for watching, we'll see you next time.

>> Narrator: From theCUBE's studios in Palo Alto in Boston, connecting with thought leaders all around the world, this is theCUBE Conversation. >> You know, businesses have a staggering number of options today to support mission-critical applications. And much of the world's mission-critical data happens to live on converged infrastructure. Converged infrastructure is really designed to support the most demanding workloads. Words like resilience, performance, scalability, recoverability, et cetera. Those are the attributes that define converged infrastructure. Now with COVID-19 the digital transformation mandate, as we all know has been accelerated and buyers are demanding more from their infrastructure, and in particular converged infrastructure. Hi everybody this is Dave Vellante and welcome to this power panel where we're going to explore converged infrastructure, look at its past, its present and its future. And we're going to explore several things. The origins of converged infrastructure, why CI even came about. And what's its historic role been in terms of supporting mission-critical applications. We're going to look at modernizing workloads. What are the opportunities and the risks and what's converged infrastructures role in that regard. How has converged infrastructure evolved? And how will it support cloud and multicloud? And ultimately what's the future of converged infrastructure look like? And to examine these issues, we have three great guests, Trey Layton is here. He is the senior vice president for converged infrastructure and software engineering and architecture at Dell Technologies. And he's joined by Joakim Zetterblad. Who's the director of the SAP practice for EMEA at Dell technologies. And our very own Stu Miniman. Stu is a senior analyst at Wikibon. Guys, great to see you all welcome to theCUBE. Thanks for coming on. >> Thanks for having us. >> Great. >> Trey, I'm going to start with you. Take us back to the early days of converged infrastructure. Why was it even formed? Why was it created? >> Well, if you look back just over a decade ago, a lot of organizations were deploying virtualized environments. Everyone was consolidated on virtualization. A lot of technologies were emerging to enhance that virtualization outcome, meaning acceleration capabilities and storage arrays, networking. And there was a lot of complexity in integrating all of those underlying infrastructure technologies into a solution that would work reliably. You almost had to have a PhD and all of the best practices of many different companies integrations. And so we decided as Dell EMC, Dell Technologies to invest heavily in this area of manufacturing best practices and packaging them so that customers could acquire those technologies and already integrated fully regression tested architecture that could sustain virtually any type of workload that a company would run. And candidly that packaging, that rigor around testing produced a highly reliable product that customers now rely on heavily to operationalize greater efficiencies and run their most critical applications that power their business and ultimately the world economy. >> Now Stu, cause you were there. I was as well at the early days of the original announcement of CI. Looking back and sort of bringing it forward Stu, what was the business impact of converged infrastructure? >> Well, Dave as Trey was talking about it was that wave of virtualization had gone from, you know, just supporting many applications to being able to support all of your applications. And especially if you talk about those high value, you know business mission, critical applications, you want to make sure that you've got a reliable foundation. What the Dell tech team has done for years is make sure that they fully understand, you know the life cycle of testing that needs to happen. And you don't need to worry about, you know, what integration testing you need to do, looking at support major CS and doing a lot of your own sandbox testing, which for the most part was what enterprises needed to do. You said, okay, you know, I get the gear, I load the virtualization and then I have to see, you know, tweak everything to figure out how my application works. The business impact Dave, is you want to spend more time focusing on the business, not having to turn all the dials and worry about, do I get the performance I need? Does it have the reliability uptime that we need? And especially if we're talking about those business critical applications, of course, these are the ones that are running 24 by seven and if they go down, my business goes down with it. >> Yeah, and of course, you know, one of the other major themes we saw with conversion infrastructure was really attacking the IT labor problem. You had separate compute or server teams, storage teams, networking teams, they oftentimes weren't talking together. So there was a lot of inefficiency that converged infrastructure was designed to attack. But I want to come to the SAP expert. Joakim, that's really your wheelhouse. What is it about converged infrastructure that makes it suitable for SAP application specifically? >> You know, if you look at a classic SAP client today, there's really three major transformational waves that all SAP customers are faced with today, it's the move to S/4HANA, the introduction of this new platform, which needs to happen before 2027. It's the introduction of a multicloud cloud or operating model. And last but not least, it is the introduction of new digitization or intelligent technologies such as IOT, machine learning or artificial intelligence. And that drove to the need of a platform that could address all these three transformational waves. It came with a lot of complexity, increased costs, increased risk. And what CI did so uniquely was to provide that Edge to Core to Cloud strategy. Fully certified for both HANA, non HANA workloads for the classical analytical and transactional workloads, as well as the new modernization technologies such as IOT, machine learning, big data and analytics. And that created a huge momentum for converged in our SAP accounts. >> So Trey, I want to go to you cause you're the deep technical expert here. Joakim just mentioned uniqueness. So what are the unique characteristics of converged infrastructure that really make it suitable for handling the most demanding workloads? >> Well, converged infrastructure by definition is the integration of an external storage array with a highly optimized compute platform. And when we build best practices around integrating those technologies together, we essentially package optimizations that allow a customer to increase the quantity of users that are accessing those workloads or the applications that are driving database access in such a way where you can predictably understand consumption and utilization in your environment. Those packaged integrations are kind of like. You know, I have a friend that owns a race car shop and he has all kinds of expertise to build cars, but he has a vehicle that he buys is his daily driver. The customization that they've created to build race cars are great for the race cars that go on the track, but he's building a car on his own, it didn't make any sense. And so what customers found was the ability to acquire a packaged infrastructure with all these infrastructure optimizations, where we package these best practices that gave customers a reliable, predictable, and fully supported integration, so they didn't have to spend 20 hour support calls trying to discover and figure out what particular customization that they had employed for their application, that had some issue that they needed to troubleshoot and solve. This became a standard out of the box integration that the best and the brightest package so that customers can consume it at scale. >> So Joakim, I want to ask you let's take the sort of application view. Let's sort of flip the picture a little bit and come at it from that prism. How, if you think about like core business applications, how have they evolved over the better part of the last decade and specifically with regard to the mission-critical processes? >> So what we're seeing in the process industry and in the industry of mission-critical applications is that they have gone from being very monolithic systems where we literally saw a single ERP components such as all three or UCC. Whereas today customers are faced with a landscape of multiple components. Many of them working both on and off premise, there are multicloud strategies in place. And as we mentioned before, with the introduction of new IOT technologies, we see that there is a flow of information of data that requires a whole new set of infrastructure of components of tools to make these new processes happen. And of course, the focus in the end of the day is all on business outcomes. So what industries and companies doesn't want to do is to focus all their time in making sure that these new technologies are working together, but really focusing on how can I make an impact? How can I start to work in a better way with my clients? So the focus on business outcome, the focus on integrating multiple systems into a single consolidated approach has become so much more important, which is why the modernization of the underlying infrastructure is absolutely key. Without consolidation, without a simplification of the management and orchestration. And without the cloud enabled platform, you won't get there. >> So Stu that's key, what Joakim just said in terms of modernizing the application as being able to manage them, not as one big monolith, but integration with other key systems. So what are the options? Wikibon has done some research on this, but what are the options for modernizing workloads, whether it's on-Prem or off-prem and what are some of the trade offs there? >> Yeah, so Dave, first of all, you know, one of the biggest challenges out there is you don't just want to, you know, lift and shift. If anybody's read research for it from Wikibon, Dave, for a day, for the 10 years, I've been part of it talks about the challenges, if you just talk about migrating, because while it sounds simple, we understand that there are individual customizations that every customer's made. So you might get part of the way there, but there's often the challenges that will get in the way that could cause failure. And as we talked about for you, especially your mission-critical applications, those are the ones that you can't have downtime. So absolutely customers are reevaluating their application portfolio. You know, there are a lot of things to look at. First of all, if you can, certain things can be moved to SaaS. You've seen certain segments of the market. Absolutely SaaS can be preferred methodology, if you can go there. One of the biggest hurdles for SaaS of course, is there's retraining of the workforce. Certain applications they will embracing of that because they can take advantage of new features, get to be able to use that wherever they are. But in other cases, there are the SaaS doesn't have the capability or it doesn't fit into the workflow of the business. The cloud operating model is something we've been talking about it with you Dave, for many years. When you've seen rapid maturation of what originally was called "private cloud", but really was just virtualization plus with a little bit of a management layer on top. But now much of the automation that you build in AI technologies, you know, Trey's got a whole team working on things that if you talk to his team, it sounds very similar to what you had the same conversation should have with cloud providers. So "cloud" as an operating model, not a destination is what we're going for and being able to take advantage of automation and the like. So where your application sits, absolutely some consideration. And what we've talked about Dave, you know, the governance, the security, the reliability, the performance are all reasons why being able to keep things, you know, under my environment with an infrastructure that I have control over is absolutely one of the reasons why I might keep things more along a converged infrastructure, rather than just saying to go through the challenge of migration and optimizing and changing to something in a more of a cloud native methodology. >> What about technical debt? Trey, people talk about technical debt as a bad thing, what is technical debt? Why do I want to avoid it? And how can I avoid it? And specifically, I know, Trey, I've thrown a lot of questions at you yet, but what is it about converged infrastructure and its capabilities that helped me avoid that technical debt? >> Well, it's an interesting thing, when you deploy an environment to support a mission-critical application, you have to make a lot of implementation decisions. Some of those decisions may take you down a path that may have a finite life. And that once you reached the life expectancy of that particular configuration, you now have debt that you have to reconcile. You have to change that architecture, that configuration. And so what we do with converged infrastructure is we dedicate a team of product management, an entire product management organization, a team of engineers that treat the integrations of the architecture as a releases. And we think long range about how do we avoid not having to change the underlying architecture. And one of the greatest testaments to this is in our conversion infrastructure products over the last 11 years, we've only saw two major architectural changes while supporting generational changes in underlying infrastructure capabilities well beyond when we first started. So converged infrastructure approach is about how do we build an architecture that allows you to avoid those dead-end pathways in those integration decisions that you would normally have to make on your own. >> Joakim, I wanted to ask you, you've mentioned monolithic applications before. That's sort of, we're evolving beyond that with application architectures, but there's still a lot of monoliths out there so. And a lot of customers want to modernize those application and workloads. What, in your view, what are you seeing as the best path and the best practice for modernizing some of those monolithic workloads? >> Yeah, so Dave, as clients today are trying to build a new intelligent enterprise, which is one of SAP's leading a guidance today. They needed to start to look at how to integrate all these different systems and applications that we talked about before into the common business process framework that they have. So consolidating workloads from big data to HANA, non HANA systems, cloud, non-cloud applications into a single framework is an absolute key to that modernization strategy. The second thing which I also mentioned before is to take a new grip around orchestration and management. We know that as customers seek this intelligent approach with both analytical data, as well as experience and transactional data, we must look for new ways to orchestrate and manage those application workloads and data flows. And this is where we slowly, slowly enter into the world of a enterprise data strategy. And that's again, where converged as a very important part to play in order to build these next generation platforms that can both consolidate, simplify. And at the same time enable us to work in a cloud enabled fashion with our cloud operating model that most of our clients seek today. >> So Stu, why can't I just shove all this stuff into the public cloud and call it a day? >> Yeah, well, Dave, we've seen some people that, you know, I have a cloud first strategy and often those are the same companies that are quickly doing what we call "repatriation". I bristle a little bit when I hear these, because often it's, I've gone to the cloud without understanding how I take advantage of it, not understanding the full financial ramifications what I'm going to need to do. And therefore they quickly go back to a world that they understand. So, cloud is not a silver bullet. We understand in technology, Dave, you know, things are complicated. There's all the organizational operational pieces they do. There are excellent cloud services and it's really it's innovation. You know, how do I take advantage of the data that I have, how I allow my application to move forward and respond to the business. And really that is not something that only happens in the public clouds. If I can take advantage of infrastructure that gets me along that journey to more of a cloud model, I get the business results. So, you know, automation and APIs and everything and the Ops movement are not something that are only in the public clouds, but something that we should be embracing holistically. And absolutely, that ties into where today and tomorrow's converge infrastructure are going. >> Yeah, and to me, it comes down to the business case too. I mean, you have to look at the risk-reward. The risk of changing something that's actually working for your business versus what the payback is going to be. You know, if it ain't broken, don't fix it, but you may want to update it, change the oil every now and then, you know, maybe prune some deadwood and modernize it. But Trey, I want to come back to you. Let's take a look at some of the options that customers have. And there are a lot of options, as I said at the top. You've got do it yourself, you got a hyper-converged infrastructure, of course, converged infrastructure. What are you seeing as the use case for each of these deployment options? >> So, build your own. We're really talking about an organization that has the expertise in-house to understand the integration standards that they need to deploy to support their environment. And candidly, there are a lot of customers that have very unique application requirements that have very much customized to their environment. And they've invested in the expertise to be able to sustain that on an ongoing basis. And build your own is great for those folks. The next in converged infrastructure, where we're really talking about an external storage array with applications that need to use data services native to a storage array. And self-select compute for scaling that compute for their particular need, and owning that three tiers architecture and its associated integration, but not having to sustain it because it's converged. There are enormous number of applications out there that benefit from that. I think the third one was, you talked about hyper-converged. I'll go back to when we first introduced our hyper-converged product to the market. Which is now leading the industry for quite some time, VxRail. We had always said that customers will consume hyper-converged and converged for different use cases and different applications. The maturity of hyper-converged has come to the point where you can run virtually any application that you would like on it. And this comes down to really two vectors of consideration. One, am I going to run hyper-converged versus converged based on my operational preference? You know, hyper-converged incorporates software defined storage, predominantly a compute operating plane. Converge as mentioned previously uses that external storage array has some type of systems fabric and dedicated compute resources with access into those your operational preference is one aspect of it. And then having applications that need the data services of an external storage, primary storage array are the other aspect of deciding whether those two things are needed in your particular environment. We find more and more customers out there that have an investment of both, not one versus the other. That's not to say that there aren't customers that only have one, they exist, but a majority of customers have both. >> So Joakim, I want to come back to the sort of attributes from the application requirements perspective. When you think about mission-critical, you think about availability, scale, recoverability, data protection. I wonder if you could talk a little bit about those attributes. And again, what is it about converged infrastructure that that is the best fit and the right strategic fit for supporting those demanding applications and workloads? >> Now, when it comes to SAP, we're talking about clients and customers, most mission-critical data and information and applications. And hence the requirements on the underlying infrastructure is absolutely on the very top of what the IT organization needs to deliver. This is why, when we talk about SAP, the requirements for high availability protection disaster recovery is very, very high. And it doesn't only involve a single system. As mentioned before, SAP is not a standalone application, but rather a landscape of systems that needs to be kept consistent. And that's what a CI platform does so well. It can consolidate workloads, whether it's big data or the transactional standard workloads of SAP, ERP or UCC. The converged platforms are able to put the very highest of availability protection standards into this whole landscape and making a really unique platform for CI workloads. And at the same time, it enables our customers to accelerate those modernization journeys into things such as ML, AI, IOT, even blockchain scenarios, where we've built out our capabilities to accelerate these implementations with the help of the underlying CI platforms and the rest of the SAP environment. >> Got it. Stu, I want to go to you. You had mentioned before the cloud operating model and something that we've been talking about for a long time and Wikibon. So can converged infrastructure substantially mimic that cloud operating model and how so? What are the key ingredients of being able to create that experience on-prem? >> Yeah, well, Dave as, we've watched for more than the last decade, the cloud has looked more and more like some of the traditional enterprise things that we would look for and the infrastructure in private clouds have gone more and more cloud-like and embrace that model. So, you know, I got, I think back to the early days, Dave, we talked about how cloud was supposed to just be, you know, "simple". If you look at deploying in the cloud today, it is not simple at all that. There are so many choices out there, you know, way more than I had an initial data center. In the same way, you know, I think, you know, the original converged infrastructure from Dell, if you look at the feedback, the criticism was, you know, oh, you can have it in any color you want, as long as black, just like the Ford model T. But it was that simplicity and consistency that helped build out most of what we were talking about the cloud models I wanted to know that I had a reliable substrate platform to build on top of it. But if you talk about Dave today and in the future, what do we want? First of all, I need that operating model in a multicloud world. So, you know, we look at the environments that can spread, but beyond just a single cloud, because customers today have multiple environments, absolutely hybrid is a big piece of that. We look at what VMware's doing, look at Microsoft, Red Hat, even Amazon are extended beyond just a cloud and going into hybrid and multicloud models. Automation, a critical piece of that. And we've seen, you know, great leaps and bounds in the last couple of generations of what's happening in CI to take advantage of automation. Because we know we've gone beyond what humans can just manage themselves and therefore, you know, true automation is helping along those environments. So yes, absolutely, Dave. You know, that the lines are blurred between what the private cloud and the public cloud. And it's just that overall cloud operating model and helping customers to deal with their data and their applications, regardless of where it lives. >> Well, you know, Trey in the early days of cloud and conversion infrastructure, that homogeneity that Stu was talking about any color, as long as it's black. That was actually an advantage to removing labor costs, that consistency and that standardization. But I'm interested in how CI has evolved, its, you know, added in optionality. I mean Joakim was just talking about blockchain, so all kinds of new services. But how has CCI evolved in the better part of the last decade and what are some of the most recent innovations that people should be thinking about or aware of? >> So I think the underlying experience of CI has remained relatively constant. And we talk about the experience that customers get. So if you just look at the data that we've analyzed for over a decade now, you know, one of the data points that I love is 99% of our customers who buy CI say they have virtually no downtime anymore. And, that's a great testament. 84% of our customers say that they have that their IT operations run more efficiently. The reality around how we delivered that in the past was through services and humans performing these integrations and the upkeep associated with the sustaining of the architecture. What we've focused on at Dell Technologies is really bringing technologies that allow us to automate those human integrations and best practices. In such a way where they can become more repeatable and consumable by more customers. We don't have to have as many services folks deploying these systems as we did in the past. Because we're using software intelligence to embed that human knowledge that we used to rely on individuals exclusively for. So that's one of the aspects of the architecture. And then just taking advantage of all the new technologies that we've seen introduce over the last several years from all flash architectures and NVMe on the horizon, NVMe over fabric. All of these things as we orchestrate them in software will enable them to be more consumable by the average everyday customer. Therefore it becomes more economical for them to deploy infrastructure on premises to support mission-critical applications. >> So Stu, what about cloud and multicloud, how does CI support that? Where do those fit in? Are they relevant? >> Yeah, Dave, so absolutely. As I was talking about before, you know, customers have hybrid and multicloud environments and managing across these environments are pretty important. If I look at the Dell family, obviously they're leveraging heavily VMware as the virtualization layer. And VMware has been moving heavily as to how support containerized and incubates these environments and extend their management to not only what's happening in the data center, but into the cloud environment with VMware cloud. So, you know, management in a multicloud world Dave, is one of those areas that we definitely have some work to do. Something we've looked at Wikibon for the last few years. Is how will multicloud be different than multi-vendor? Because that was not something that the industry had done a great job of solving in the past. But you know, customers are looking to take advantage of the innovation, where it is in the services. And you know, the data first architecture is something that we see and therefore that will bring them to many services and many places. >> Oh yeah, I was talking before about in the early days of CI and even a lot of organizations, some organizations, anyway, there's still these sort of silos of, you know, storage, networking, compute resources. And you think about DevOps, where does DevOps fit into this whole equation? Maybe Stu you could take a stab at it and anybody else who wants to chime in. >> Yeah, so Dave, great, great point there. So, you know, when we talk about those silos, DevOps is one of those movements to really help the unifying force to help customers move faster. And so therefore the development team and the operations team are working together. Things like security are not a bolt-in but something that can happen along the entire path. A more recent addition to the DevOps movement also is something like FinOps. So, you know, how do we make sure that we're not just having finance sign off on things and look back every quarter, but in real time, understand how we're architecting things, especially in the cloud so that we remain responsible for that model. So, you know, speed is, you know, one of the most important pieces for business and therefore the DevOps movement, helping customers move faster and, you know, leverage and get value out of their infrastructure, their applications and their data. >> Yeah, I would add to this that I think the big transition for organizations, cause I've seen it in developing my own organization, is getting IT operators to think programmatically instead of configuration based. Use the tool to configure a device. Think about how do we create programmatic instruction to interacts with all of the devices that creates that cloud-like adaptation. Feeds in application level signaling to adapt and change the underlying configuration about that infrastructure to better run the application without relying upon an IT operator, a human to make a change. This, sort of thinking programmatically is I think one of the biggest obstacles that the industry face. And I feel really good about how we've attacked it, but there is a transformation within that dialogue that every organization is going to navigate through at their own pace. >> Yeah, infrastructure is code automation, this a fundamental to digital transformation. Joakim, I wonder if you could give us some insight as you talk to SAP customers, you know, in Europe, across the EMEA, how does the pandemic change this? >> I think the pandemic has accelerated some of the movements that we already saw in the SAP world. There is obviously a force for making sure that we get our financial budgets in shape and that we don't over spend on our cost levels. And therefore it's going to be very important to see how we can manage all these new revenue generating projects that IT organizations and business organizations have planned around new customer experience initiatives, new supply chain optimization. They know that they need to invest in these projects to stay competitive and to gain new competitive edge. And where CI plays an important part is in order to, first of all, keep costs down in all of these projects, make sure to deliver a standardized common platform upon which all these projects can be introduced. And then of course, making sure that availability and risks are kept high versus at a minimum, right? Risk low and availability at a record high, because we need to stay on with our clients and their demands. So I think again, CI is going to play a very important role. As we see customers go through this pandemic situation and needing to put pressure on both innovation and cost control at the same time. And this is where also our new upcoming data strategies will play a really important part as we need to leverage the data we have better, smarter and more efficient way. >> Got it. Okay guys, we're running out of time, but Trey, I wonder if you could, you know break out your telescope or your crystal ball, give us some visibility into the futures of converged infrastructure. What should we be expecting? >> So if you look at the last release of this last technology that we released in power one, it was all about automation. We'll build on that platform to integrate other converged capability. So if you look at the converged systems market hyper-converged is very much an element of that. And I think that we're trending to is recognizing that we can deliver an architecture that has hyper-converged and converged attributes all in a single architecture and then dial up the degrees of automation to create more adaptations for different type of application workloads, not just your traditional three tier application workloads, but also those microservices based applications that one may historically think, maybe it's best to that off premises. We feel very confident that we are delivering platforms out there today that can run more economically on premises, provide better security, better data governance, and a lot of the adaptations, the enhancements, the optimizations that we'll deliver in our converged platforms of the future about colliding new infrastructure models together, and introducing more levels of automation to have greater adaptations for applications that are running on it. >> Got it. Trey, we're going to give you the last word. You know, if you're an architect of a large organization, you've got some mission-critical workloads that, you know, you're really trying to protect. What's the takeaway? What's really the advice that you would give those folks thinking about the sort of near and midterm and even longterm? >> My advice is to understand that there are many options. We sell a lot of independent component technologies and data centers that run every organization's environment around the world. We sell packaged outcomes and hyper-converged and converged. And a lot of companies buy a little bit of build your own, they buy some converged, they buy some hyper-converged. I would employ everyone, especially in this climate to really evaluate the packaged offerings and understand how they can benefit their environment. And we recognize that everything that there's not one hammer and everything is a nail. That's why we have this broad portfolio of products that are designed to be utilized in the most efficient manners for those customers who are consuming our technologies. And converged and hyper-converge are merely another way to simplify the ongoing challenges that organizations have in managing their data estate and all of the technologies they're consuming at a rapid pace in concert with the investments that they're also making off premises. So this is very much the technologies that we talked today are very much things that organizations should research, investigate and utilize where they best fit in their organization. >> Awesome guys, and of course there's a lot of information at dell.com about that. Wikibon.com has written a lot about this and the many, many sources of information out there. Trey, Joakim, Stu thanks so much for the conversation. Really meaty, a lot of substance, really appreciate your time, thank you. >> Thank you guys. >> Thank you Dave. >> Thanks Dave. >> And everybody for watching. This is Dave Vellante for theCUBE and we'll see you next time. (soft music)

>> Narrator: From theCUBE's studios in Palo Alto in Boston, connecting with thought leaders all around the world, this is theCUBE Conversation. >> You know, businesses have a staggering number of options today to support mission-critical applications. And much of the world's mission-critical data happens to live on converged infrastructure. Converged infrastructure is really designed to support the most demanding workloads. Words like resilience, performance, scalability, recoverability, et cetera. Those are the attributes that define converged infrastructure. Now with COVID-19 the digital transformation mandate, as we all know has been accelerated and buyers are demanding more from their infrastructure, and in particular converged infrastructure. Hi everybody this is Dave Vellante and welcome to this power panel where we're going to explore converged infrastructure, look at its past, its present and its future. And we're going to explore several things. The origins of converged infrastructure, why CI even came about. And what's its historic role been in terms of supporting mission-critical applications. We're going to look at modernizing workloads. What are the opportunities and the risks and what's converged infrastructures role in that regard. How has converged infrastructure evolved? And how will it support cloud and multicloud? And ultimately what's the future of converged infrastructure look like? And to examine these issues, we have three great guests, Trey Layton is here. He is the senior vice president for converged infrastructure and software engineering and architecture at Dell Technologies. And he's joined by Joakim Zetterblad. Who's the director of the SAP practice for EMEA at Dell technologies. And our very own Stu Miniman. Stu is a senior analyst at Wikibon. Guys, great to see you all welcome to theCUBE. Thanks for coming on. >> Thanks for having us. >> Great. >> Trey, I'm going to start with you. Take us back to the early days of converged infrastructure. Why was it even formed? Why was it created? >> Well, if you look back just over a decade ago, a lot of organizations were deploying virtualized environments. Everyone was consolidated on virtualization. A lot of technologies were emerging to enhance that virtualization outcome, meaning acceleration capabilities and storage arrays, networking. And there was a lot of complexity in integrating all of those underlying infrastructure technologies into a solution that would work reliably. You almost had to have a PhD and all of the best practices of many different companies integrations. And so we decided as Dell EMC, Dell Technologies to invest heavily in this area of manufacturing best practices and packaging them so that customers could acquire those technologies and already integrated fully regression tested architecture that could sustain virtually any type of workload that a company would run. And candidly that packaging, that rigor around testing produced a highly reliable product that customers now rely on heavily to operationalize greater efficiencies and run their most critical applications that power their business and ultimately the world economy. >> Now Stu, cause you were there. I was as well at the early days of the original announcement of CI. Looking back and sort of bringing it forward Stu, what was the business impact of converged infrastructure? >> Well, Dave as Trey was talking about it was that wave of virtualization had gone from, you know, just supporting many applications to being able to support all of your applications. And especially if you talk about those high value, you know business mission, critical applications, you want to make sure that you've got a reliable foundation. What the Dell tech team has done for years is make sure that they fully understand, you know the life cycle of testing that needs to happen. And you don't need to worry about, you know, what integration testing you need to do, looking at support major CS and doing a lot of your own sandbox testing, which for the most part was what enterprises needed to do. You said, okay, you know, I get the gear, I load the virtualization and then I have to see, you know, tweak everything to figure out how my application works. The business impact Dave, is you want to spend more time focusing on the business, not having to turn all the dials and worry about, do I get the performance I need? Does it have the reliability uptime that we need? And especially if we're talking about those business critical applications, of course, these are the ones that are running 24 by seven and if they go down, my business goes down with it. >> Yeah, and of course, you know, one of the other major themes we saw with conversion infrastructure was really attacking the IT labor problem. You had separate compute or server teams, storage teams, networking teams, they oftentimes weren't talking together. So there was a lot of inefficiency that converged infrastructure was designed to attack. But I want to come to the SAP expert. Joakim, that's really your wheelhouse. What is it about converged infrastructure that makes it suitable for SAP application specifically? >> You know, if you look at a classic SAP client today, there's really three major transformational waves that all SAP customers are faced with today, it's the move to S/4HANA, the introduction of this new platform, which needs to happen before 2027. It's the introduction of a multicloud cloud or operating model. And last but not least, it is the introduction of new digitization or intelligent technologies such as IOT, machine learning or artificial intelligence. And that drove to the need of a platform that could address all these three transformational waves. It came with a lot of complexity, increased costs, increased risk. And what CI did so uniquely was to provide that Edge to Core to Cloud strategy. Fully certified for both HANA, non HANA workloads for the classical analytical and transactional workloads, as well as the new modernization technologies such as IOT, machine learning, big data and analytics. And that created a huge momentum for converged in our SAP accounts. >> So Trey, I want to go to you cause you're the deep technical expert here. Joakim just mentioned uniqueness. So what are the unique characteristics of converged infrastructure that really make it suitable for handling the most demanding workloads? >> Well, converged infrastructure by definition is the integration of an external storage array with a highly optimized compute platform. And when we build best practices around integrating those technologies together, we essentially package optimizations that allow a customer to increase the quantity of users that are accessing those workloads or the applications that are driving database access in such a way where you can predictably understand consumption and utilization in your environment. Those packaged integrations are kind of like. You know, I have a friend that owns a race car shop and he has all kinds of expertise to build cars, but he has a vehicle that he buys is his daily driver. The customization that they've created to build race cars are great for the race cars that go on the track, but he's building a car on his own, it didn't make any sense. And so what customers found was the ability to acquire a packaged infrastructure with all these infrastructure optimizations, where we package these best practices that gave customers a reliable, predictable, and fully supported integration, so they didn't have to spend 20 hour support calls trying to discover and figure out what particular customization that they had employed for their application, that had some issue that they needed to troubleshoot and solve. This became a standard out of the box integration that the best and the brightest package so that customers can consume it at scale. >> So Joakim, I want to ask you let's take the sort of application view. Let's sort of flip the picture a little bit and come at it from that prism. How, if you think about like core business applications, how have they evolved over the better part of the last decade and specifically with regard to the mission-critical processes? >> So what we're seeing in the process industry and in the industry of mission-critical applications is that they have gone from being very monolithic systems where we literally saw a single ERP components such as all three or UCC. Whereas today customers are faced with a landscape of multiple components. Many of them working both on and off premise, there are multicloud strategies in place. And as we mentioned before, with the introduction of new IOT technologies, we see that there is a flow of information of data that requires a whole new set of infrastructure of components of tools to make these new processes happen. And of course, the focus in the end of the day is all on business outcomes. So what industries and companies doesn't want to do is to focus all their time in making sure that these new technologies are working together, but really focusing on how can I make an impact? How can I start to work in a better way with my clients? So the focus on business outcome, the focus on integrating multiple systems into a single consolidated approach has become so much more important, which is why the modernization of the underlying infrastructure is absolutely key. Without consolidation, without a simplification of the management and orchestration. And without the cloud enabled platform, you won't get there. >> So Stu that's key, what Joakim just said in terms of modernizing the application as being able to manage them, not as one big monolith, but integration with other key systems. So what are the options? Wikibon has done some research on this, but what are the options for modernizing workloads, whether it's on-Prem or off-prem and what are some of the trade offs there? >> Yeah, so Dave, first of all, you know, one of the biggest challenges out there is you don't just want to, you know, lift and shift. If anybody's read research for it from Wikibon, Dave, for a day, for the 10 years, I've been part of it talks about the challenges, if you just talk about migrating, because while it sounds simple, we understand that there are individual customizations that every customer's made. So you might get part of the way there, but there's often the challenges that will get in the way that could cause failure. And as we talked about for you, especially your mission-critical applications, those are the ones that you can't have downtime. So absolutely customers are reevaluating their application portfolio. You know, there are a lot of things to look at. First of all, if you can, certain things can be moved to SAS. You've seen certain segments of the market. Absolutely SAS can be preferred methodology, if you can go there. One of the biggest hurdles for SAS of course, is there's retraining of the workforce. Certain applications they will embracing of that because they can take advantage of new features, get to be able to use that wherever they are. But in other cases, there are the SAS doesn't have the capability or it doesn't fit into the workflow of the business. The cloud operating model is something we've been talking about it with you Dave, for many years. When you've seen rapid maturation of what originally was called "private cloud", but really was just virtualization plus with a little bit of a management layer on top. But now much of the automation that you build in AI technologies, you know, Trey's got a whole team working on things that if you talk to his team, it sounds very similar to what you had the same conversation should have with cloud providers. So "cloud" as an operating model, not a destination is what we're going for and being able to take advantage of automation and the like. So where your application sits, absolutely some consideration. And what we've talked about Dave, you know, the governance, the security, the reliability, the performance are all reasons why being able to keep things, you know, under my environment with an infrastructure that I have control over is absolutely one of the reasons why am I keep things more along a converged infrastructure, rather than just saying to go through the challenge of migration and optimizing and changing to something in a more of a cloud native methodology. >> What about technical debt? Trey, people talk about technical debt as a bad thing, what is technical debt? Why do I want to avoid it? And how can I avoid it? And specifically, I know, Trey, I've thrown a lot of questions at you yet, but what is it about converged infrastructure and its capabilities that helped me avoid that technical debt? >> Well, it's an interesting thing, when you deploy an environment to support a mission-critical application, you have to make a lot of implementation decisions. Some of those decisions may take you down a path that may have a finite life. And that once you reached the life expectancy of that particular configuration, you now have debt that you have to reconcile. You have to change that architecture, that configuration. And so what we do with converged infrastructure is we dedicate a team of product management, an entire product management organization, a team of engineers that treat the integrations of the architecture as a releases. And we think long range about how do we avoid not having to change the underlying architecture. And one of the greatest testaments to this is in our conversion infrastructure products over the last 11 years, we've only saw two major architectural changes while supporting generational changes in underlying infrastructure capabilities well beyond when we first started. So converged infrastructure approach is about how do we build an architecture that allows you to avoid those dead-end pathways in those integration decisions that you would normally have to make on your own. >> Joakim, I wanted to ask you, you've mentioned monolithic applications before. That's sort of, we're evolving beyond that with application architectures, but there's still a lot of monoliths out there so. And a lot of customers want to modernize those application and workloads. What, in your view, what are you seeing as the best path and the best practice for modernizing some of those monolithic workloads? >> Yeah, so Dave, as clients today are trying to build a new intelligent enterprise, which is one of SAP's leading a guidance today. They needed to start to look at how to integrate all these different systems and applications that we talked about before into the common business process framework that they have. So consolidating workloads from big data to HANA, non HANA systems, cloud, non-cloud applications into a single framework is an absolute key to that modernization strategy. The second thing which I also mentioned before is to take a new grip around orchestration and management. We know that as customers seek this intelligent approach with both analytical data, as well as experience and transactional data, we must look for new ways to orchestrate and manage those application workloads and data flows. And this is where we slowly, slowly enter into the world of a enterprise data strategy. And that's again, where converged as a very important part to play in order to build these next generation platforms that can both consolidate, simplify. And at the same time enable us to work in a cloud enabled fashion with our cloud operating model that most of our clients seek today. >> So Stu, why can't I just shove all this stuff into the public cloud and call it a day? >> Yeah, well, Dave, we've seen some people that, you know, I have a cloud first strategy and often those are the same companies that are quickly doing what we call "repatriation". I bristle a little bit when I hear these, because often it's, I've gone to the cloud without understanding how I take advantage of it, not understanding the full financial ramifications what I'm going to need to do. And therefore they quickly go back to a world that they understand. So, cloud is not a silver bullet. We understand in technology, Dave, you know, things are complicated. There's all the organizational operational pieces they do. There are excellent cloud services and it's really it's innovation. You know, how do I take advantage of the data that I have, how I allow my application to move forward and respond to the business. And really that is not something that only happens in the public clouds. If I can take advantage of infrastructure that gets me along that journey to more of a cloud model, I get the business results. So, you know, automation and APIs and everything and the Ops movement are not something that are only in the public clouds, but something that we should be embracing holistically. And absolutely, that ties into where today and tomorrow's converge infrastructure are going. >> Yeah, and to me, it comes down to the business case too. I mean, you have to look at the risk-reward. The risk of changing something that's actually working for your business versus what the payback is going to be. You know, if it ain't broken, don't fix it, but you may want to update it, change the oil every now and then, you know, maybe prune some deadwood and modernize it. But Trey, I want to come back to you. Let's take a look at some of the options that customers have. And there are a lot of options, as I said at the top. You've got do it yourself, you got a hyper-converged infrastructure, of course, converged infrastructure. What are you seeing as the use case for each of these deployment options? >> So, build your own. We're really talking about an organization that has the expertise in-house to understand the integration standards that they need to deploy to support their environment. And candidly, there are a lot of customers that have very unique application requirements that have very much customized to their environment. And they've invested in the expertise to be able to sustain that on an ongoing basis. And build your own is great for those folks. The next in converged infrastructure, where we're really talking about an external storage array with applications that need to use data services native to a storage array. And self-select compute for scaling that compute for their particular need, and owning that three tiers architecture and its associated integration, but not having to sustain it because it's converged. There are enormous number of applications out there that benefit from that. I think the third one was, you talked about hyper-converged. I'll go back to when we first introduced our hyper-converged product to the market. Which is now leading the industry for quite some time, VxRail. We had always said that customers will consume hyper-converged and converged for different use cases and different applications. The maturity of hyper-converged has come to the point where you can run virtually any application that you would like on it. And this comes down to really two vectors of consideration. One, am I going to run hyper-converged versus converged based on my operational preference? You know, hyper-converged incorporates software defined storage, predominantly a compute operating plane. Converge as mentioned previously uses that external storage array has some type of systems fabric and dedicated compute resources with access into those your operational preference is one aspect of it. And then having applications that need the data services of an external storage, primary storage array are the other aspect of deciding whether those two things are needed in your particular environment. We find more and more customers out there that have an investment of both, not one versus the other. That's not to say that there aren't customers that only have one, they exist, but a majority of customers have both. >> So Joakim, I want to come back to the sort of attributes from the application requirements perspective. When you think about mission-critical, you think about availability, scale, recoverability, data protection. I wonder if you could talk a little bit about those attributes. And again, what is it about converged infrastructure that that is the best fit and the right strategic fit for supporting those demanding applications and workloads? >> Now, when it comes to SAP, we're talking about clients and customers, most mission-critical data and information and applications. And hence the requirements on the underlying infrastructure is absolutely on the very top of what the IT organization needs to deliver. This is why, when we talk about SAP, the requirements for high availability protection disaster recovery is very, very high. And it doesn't only involve a single system. As mentioned before, SAP is not a standalone application, but rather a landscape of systems that needs to be kept consistent. And that's what a CI platform does so well. It can consolidate workloads, whether it's big data or the transactional standard workloads of SAP, ERP or UCC. The converged platforms are able to put the very highest of availability protection standards into this whole landscape and making a really unique platform for CI workloads. And at the same time, it enables our customers to accelerate those modernization journeys into things such as ML, AI, IOT, even blockchain scenarios, where we've built out our capabilities to accelerate these implementations with the help of the underlying CI platforms and the rest of the SAP environment. >> Got it. Stu, I want to go to you. You had mentioned before the cloud operating model and something that we've been talking about for a long time and Wikibon. So can converged infrastructure substantially mimic that cloud operating model and how so? What are the key ingredients of being able to create that experience on-prem? >> Yeah, well, Dave is, we've watched for more than the last decade, the cloud has looked more and more like some of the traditional enterprise things that we would look for and the infrastructure in private clouds have gone more and more cloud-like and embrace that model. So, you know, I got, I think back to the early days, Dave, we talked about how cloud was supposed to just be, you know, "simple". If you look at deploying in the cloud today, it is not simple at all that. There are so many choices out there, you know, way more than I had an initial data center. In the same way, you know, I think, you know, the original converged infrastructure from Dell, if you look at the feedback, the criticism was, you know, oh, you can have it in any color you want, as long as black, just like the Ford model T. But it was that simplicity and consistency that helped build out most of what we were talking about the cloud models I wanted to know that I had a reliable substrate platform to build on top of it. But if you talk about Dave today and in the future, what do we want? First of all, I need that operating model in a multicloud world. So, you know, we look at the environments that can spread, but beyond just a single cloud, because customers today have multiple environments, absolutely hybrid is a big piece of that. We look at what VMware's doing, look at Microsoft, Red Hat, even Amazon are extended beyond just a cloud and going into hybrid and multicloud models. Automation, a critical piece of that. And we've seen, you know, great leaps and bounds in the last couple of generations of what's happening in CI to take advantage of automation. Because we know we've gone beyond what humans can just manage themselves and therefore, you know, true automation is helping along those environments. So yes, absolutely, Dave. You know, that the lines are blurred between what the private cloud and the public cloud. And it's just that overall cloud operating model and helping customers to deal with their data and their applications, regardless of where it is. >> Well, you know, Trey in the early days of cloud and conversion infrastructure, that homogeneity that Stu was talking about any color, as long as it's black. That was actually an advantage to removing labor costs, that consistency and that standardization. But I'm interested in how CI has evolved, its, you know, added in optionality. I mean Joakim was just talking about blockchain, so all kinds of new services. But how has CCI evolved in the better part of the last decade and what are some of the most recent innovations that people should be thinking about or aware of? >> So I think the underlying experience of CI has remained relatively constant. And we talk about the experience that customers get. So if you just look at the data that we've analyzed for over a decade now, you know, one of the data points that I love is 99% of our customers who buy CI say they have virtually no downtime anymore. And, that's a great testament. 84% of our customers say that they have that their IT operations run more efficiently. The reality around how we delivered that in the past was through services and humans performing these integrations and the upkeep associated with the sustaining of the architecture. What we've focused on at Dell Technologies is really bringing technologies that allow us to automate those human integrations and best practices. In such a way where they can become more repeatable and consumable by more customers. We don't have to have as many services folks deploying these systems as we did in the past. Because we're using software intelligence to embed that human knowledge that we used to rely on individuals exclusively for. So that's one of the aspects of the architecture. And then just taking advantage of all the new technologies that we've seen introduce over the last several years from all flash architectures and NVMe on the horizon, NVMe over fabric. All of these things as we orchestrate them in software will enable them to be more consumable by the average everyday customer. Therefore it becomes more economical for them to deploy infrastructure on premises to support mission-critical applications. >> So Stu, what about cloud and multicloud, how does CI support that? Where do those fit in? Are they relevant? >> Yeah, Dave, so absolutely. As I was talking about before, you know, customers have hybrid and multicloud environments and managing across these environments are pretty important. If I look at the Dell family, obviously they're leveraging heavily VMware as the virtualization layer. And VMware has been moving heavily as to how support containerized and incubates these environments and extend their management to not only what's happening in the data center, but into the cloud environment with VMware cloud. So, you know, management in a multicloud world Dave, is one of those areas that we definitely have some work to do. Something we've looked at Wikibon for the last few years. Is how will multicloud be different than multi-vendor? Because that was not something that the industry had done a great job of solving in the past. But you know, customers are looking to take advantage of the innovation, where it is in the services. And you know, the data first architecture is something that we see and therefore that will bring them to many services and many places. >> Oh yeah, I was talking before about in the early days of CI and even a lot of organizations, some organizations, anyway, there's still these sort of silos of, you know, storage, networking, compute resources. And you think about DevOps, where does DevOps fit into this whole equation? Maybe Stu you could take a stab at it and anybody else who wants to chime in. >> Yeah, so Dave, great, great point there. So, you know, when we talk about those silos, DevOps is one of those movements to really help the unifying force to help customers move faster. And so therefore the development team and the operations team are working together. Things like security are not a built-in but something that can happen along the entire path. A more recent addition to the DevOps movement also is something like FinOps. So, you know, how do we make sure that we're not just having finance sign off on things and look back every quarter, but in real time, understand how we're architecting things, especially in the cloud so that we remain responsible for that model. So, you know, speed is, you know, one of the most important pieces for business and therefore the DevOps movement, helping customers move faster and, you know, leverage and get value out of their infrastructure, their applications and their data. >> Yeah, I would add to this that I think the big transition for organizations, cause I've seen it in developing my own organization, is getting IT operators to think programmatically instead of configuration based. Use the tool to configure a device. Think about how do we create programmatic instruction to interacts with all of the devices that creates that cloud-like adaptation. Feeds in application level signaling to adapt and change the underlying configuration about that infrastructure to better run the application without relying upon an IT operator, a human to make a change. This, sort of thinking programmatically is I think one of the biggest obstacles that the industry face. And I feel really good about how we've attacked it, but there is a transformation within that dialogue that every organization is going to navigate through at their own pace. >> Yeah, infrastructure is code automation, this a fundamental to digital transformation. Joakim, I wonder if you could give us some insight as you talk to SAP customers, you know, in Europe, across the EMEA, how does the pandemic change this? >> I think the pandemic has accelerated some of the movements that we already saw in the SAP world. There is obviously a force for making sure that we get our financial budgets in shape and that we don't over spend on our cost levels. And therefore it's going to be very important to see how we can manage all these new revenue generating projects that IT organizations and business organizations have planned around new customer experience initiatives, new supply chain optimization. They know that they need to invest in these projects to stay competitive and to gain new competitive edge. And where CI plays an important part is in order to, first of all, keep costs down in all of these projects, make sure to deliver a standardized common platform upon which all these projects can be introduced. And then of course, making sure that availability and risks are kept high versus at a minimum, right? Risk low and availability at a record high, because we need to stay on with our clients and their demands. So I think again, CI is going to play a very important role. As we see customers go through this pandemic situation and needing to put pressure on both innovation and cost control at the same time. And this is where also our new upcoming data strategies will play a really important part as we need to leverage the data we have better, smarter and more efficient way. >> Got it. Okay guys, we're running out of time, but Trey, I wonder if you could, you know break out your telescope or your crystal ball, give us some visibility into the futures of converged infrastructure. What should we be expecting? So if you look at the last release of this last technology that we released in power one, it was all about automation. We'll build on that platform to integrate other converged capability. So if you look at the converged systems market hyper-converged is very much an element of that. And I think that we're trending to is recognizing that we can deliver an architecture that has hyper-converged and converged attributes all in a single architecture and then dial up the degrees of automation to create more adaptations for different type of application workloads, not just your traditional three tier application workloads, but also those microservices based applications that one may historically think, maybe it's best to that off premises. We feel very confident that we are delivering platforms out there today that can run more economically on premises, provide better security, better data governance, and a lot of the adaptations, the enhancements, the optimizations that we'll deliver in our converged platforms of the future about colliding new infrastructure models together, and introducing more levels of automation to have greater adaptations for applications that are running on it. >> Got it. Trey, we're going to give you the last word. You know, if you're an architect of a large organization, you've got some mission-critical workloads that, you know, you're really trying to protect. What's the takeaway? What's really the advice that you would give those folks thinking about the sort of near and midterm and even longterm? >> My advice is to understand that there are many options. We sell a lot of independent component technologies and data centers that run every organization's environment around the world. We sell packaged outcomes and hyper-converged and converged. And a lot of companies buy a little bit of build your own, they buy some converged, they buy some hyper-converged. I would employ everyone, especially in this climate to really evaluate the packaged offerings and understand how they can benefit their environment. And we recognize that everything that there's not one hammer and everything is a nail. That's why we have this broad portfolio of products that are designed to be utilized in the most efficient manners for those customers who are consuming our technologies. And converged and hyper-converge are merely another way to simplify the ongoing challenges that organizations have in managing their data estate and all of the technologies they're consuming at a rapid pace in concert with the investments that they're also making off premises. So this is very much the technologies that we talked today are very much things that organizations should research, investigate and utilize where they best fit in their organization. >> Awesome guys, and of course there's a lot of information at dell.com about that. Wikibon.com has written a lot about this and the many, many sources of information out there. Trey, Joakim, Stu thanks so much for the conversation. Really meaty, a lot of substance, really appreciate your time, thank you. >> Thank you guys. >> Thank you Dave. >> Thanks Dave. >> And everybody for watching. This is Dave Vellante for theCUBE and we'll see you next time. (soft music)

>> connecting with thought leaders all around the world, this is a CUBE Conversation. Hi, everybody this is Dave Vellante of theCUBE, and welcome back to my CXO series. I've been running this through really since the start of the COVID-19 crisis to really understand how leaders are dealing with this pandemic. Sri Ambati is here, he's the CEO and founder of H20. Sri, it's great to see you again, thanks for coming on. >> Thank you for having us. >> Yeah, so this pandemic has obviously given people fits, no question, but it's also given opportunities for companies to kind of reassess where they are. Automation is a huge watchword, flexibility, business resiliency and people who maybe really hadn't fully leaned into things like the cloud and AI and automation are now realizing, wow, we have no choice, it's about survival. Your thought as to what you're seeing in the marketplace. >> Thanks for having us. I think first of all, kudos to the frontline health workers who have been ruthlessly saving lives across the country and the world, and what you're really doing is a fraction of what we could have done or should be doing to stay away the next big pandemic. But that apart I think, I usually tend to say BC is before COVID. So if the world was thinking about going digital after COVID-19, they have been forced to go digital and as a result, you're seeing tremendous transformation across our customers, and a lot of application to kind of go in and reinvent their business models that allow them to scale as effortlessly as they could using the digital means. >> So, think about, doctors and diagnosis machines, in some cases, are helping doctors make diagnoses, they're sometimes making even better diagnosis, (mumbles) is informing. There's been a lot of talk about the models, you know how... Yeah, I know you've been working with a lot of healthcare organizations, you may probably familiar with that, you know, the Medium post, The Hammer and the Dance, and if people criticize the models, of course, they're just models, right? And you iterate models and machine intelligence can help us improve. So, in this, you know, you talk about BC and post C, how have you seen the data and in machine intelligence informing the models and proving that what we know about this pandemic, I mean, it changed literally daily, what are you seeing? >> Yeah, and I think it started with Wuhan and we saw the best application of AI in trying to trace, literally from Alipay, to WeChat, track down the first folks who were spreading it across China and then eventually the rest of the world. I think contact tracing, for example, has become a really interesting problem. supply chain has been disrupted like never before. We're beginning to see customers trying to reinvent their distribution mechanisms in the second order effects of the COVID, and the the prime center is hospital staffing, how many ventilator, is the first few weeks so that after COVID crisis as it evolved in the US. We are busy predicting working with some of the local healthcare communities to predict how staffing in hospitals will work, how many PPE and ventilators will be needed and so henceforth, but that quickly and when the peak surge will be those with the beginning problems, and many of our customers have begin to do these models and iterate and improve and kind of educate the community to practice social distancing, and that led to a lot of flattening the curve and you're talking flattening the curve, you're really talking about data science and analytics in public speak. That led to kind of the next level, now that we have somewhat brought a semblance of order to the reaction to COVID, I think what we are beginning to figure out is, is there going to be a second surge, what elective procedures that were postponed, will be top of the mind for customers, and so this is the kind of things that hospitals are beginning to plan out for the second half of the year, and as businesses try to open up, certain things were highly correlated to surgeon cases, such as cleaning supplies, for example, the obvious one or pantry buying. So retailers are beginning to see what online stores are doing well, e-commerce, online purchases, electronic goods, and so everyone essentially started working from home, and so homes needed to have the same kind of bandwidth that offices and commercial enterprises needed to have, and so a lot of interesting, as one side you saw airlines go away, this side you saw the likes of Zoom and video take off. So you're kind of seeing a real divide in the digital divide and that's happening and AI is here to play a very good role to figure out how to enhance your profitability as you're looking about planning out the next two years. >> Yeah, you know, and obviously, these things they get, they get partisan, it gets political, I mean, our job as an industry is to report, your job is to help people understand, I mean, let the data inform and then let public policy you know, fight it out. So who are some of the people that you're working with that you know, as a result of COVID-19. What's some of the work that H2O has done, I want to better understand what role are you playing? >> So one of the things we're kind of privileged as a company to come into the crisis, with a strong balance and an ability to actually have the right kind of momentum behind the company in terms of great talent, and so we have 10% of the world's top data scientists in the in the form of Kaggle Grand Masters in the company. And so we put most of them to work, and they started collecting data sets, curating data sets and making them more qualitative, picking up public data sources, for example, there's a tremendous amount of job loss out there, figuring out which are the more difficult kind of sectors in the economy and then we started looking at exodus from the cities, we're looking at mobility data that's publicly available, mobility data through the data exchanges, you're able to find which cities which rural areas, did the New Yorkers as they left the city, which places did they go to, and what's to say, Californians when they left Los Angeles, which are the new places they have settled in? These are the places which are now busy places for the same kind of items that you need to sell if you're a retailer, but if you go one step further, we started engaging with FEMA, we start engaging with the universities, like Imperial College London or Berkeley, and started figuring out how best to improve the models and automate them. The SEER model, the most popular SEER model, we added that into our Driverless AI product as a recipe and made that accessible to our customers in testing, to customers in healthcare who are trying to predict where the surge is likely to come. But it's mostly about information right? So the AI at the end of it is all about intelligence and being prepared. Predictive is all about being prepared and that's kind of what we did with general, lots of blogs, typical blog articles and working with the largest health organizations and starting to kind of inform them on the most stable models. What we found to our not so much surprise, is that the simplest, very interpretable models are actually the most widely usable, because historical data is actually no longer as effective. You need to build a model that you can quickly understand and retry again to the feedback loop of back testing that model against what really happened. >> Yeah, so I want to double down on that. So really, two things I want to understand, if you have visibility on it, sounds like you do. Just in terms of the surge and the comeback, you know, kind of what those models say, based upon, you know, we have some advanced information coming from the global market, for sure, but it seems like every situation is different. What's the data telling you? Just in terms of, okay, we're coming into the spring and the summer months, maybe it'll come down a little bit. Everybody says it... We fully expect it to come back in the fall, go back to college, don't go back to college. What is the data telling you at this point in time with an understanding that, you know, we're still iterating every day? >> Well, I think I mean, we're not epidemiologists, but at the same time, the science of it is a highly local response, very hyper local response to COVID-19 is what we've seen. Santa Clara, which is just a county, I mean, is different from San Francisco, right, sort of. So you beginning to see, like we saw in Brooklyn, it's very different, and Bronx, very different from Manhattan. So you're seeing a very, very local response to this disease, and I'm talking about US. You see the likes of Brazil, which we're worried about, has picked up quite a bit of cases now. I think the silver lining I would say is that China is up and running to a large degree, a large number of our user base there are back active, you can see the traffic patterns there. So two months after their last research cases, the business and economic activity is back and thriving. And so, you can kind of estimate from that, that this can be done where you can actually contain the rise of active cases and it will take masking of the entire community, masking and the healthy dose of increase in testing. One of our offices is in Prague, and Czech Republic has done an incredible job in trying to contain this and they've done essentially, masked everybody and as a result they're back thinking about opening offices, schools later this month. So I think that's a very, very local response, hyper local response, no one country and no one community is symmetrical with other ones and I think we have a unique situation where in United States you have a very, very highly connected world, highly connected economy and I think we have quite a problem on our hands on how to safeguard our economy while also safeguarding life. >> Yeah, so you can't just, you can't just take Norway and apply it or South Korea and apply it, every situation is different. And then I want to ask you about, you know, the economy in terms of, you know, how much can AI actually, you know, how can it work in this situation where you have, you know, for example, okay, so the Fed, yes, it started doing asset buys back in 2008 but still, very hard to predict, I mean, at this time of this interview you know, Stock Market up 900 points, very difficult to predict that but some event happens in the morning, somebody, you know, Powell says something positive and it goes crazy but just sort of even modeling out the V recovery, the W recovery, deep recession, the comeback. You have to have enough data, do you not? In order for AI to be reasonably accurate? How does it work? And how does at what pace can you iterate and improve on the models? >> So I think that's exactly where I would say, continuous modeling, instead of continuously learning continuous, that's where the vision of the world is headed towards, where data is coming, you build a model, and then you iterate, try it out and come back. That kind of rapid, continuous learning would probably be needed for all our models as opposed to the typical, I'm pushing a model to production once a year, or once every quarter. I think what we're beginning to see is the kind of where companies are beginning to kind of plan out. A lot of people lost their jobs in the last couple of months, right, sort of. And so up scaling and trying to kind of bring back these jobs back both into kind of, both from the manufacturing side, but also lost a lot of jobs in the transportation and the kind of the airlines slash hotel industries, right, sort of. So it's trying to now bring back the sense of confidence and will take a lot more kind of testing, a lot more masking, a lot more social empathy, I think well, some of the things that we are missing while we are socially distant, we know that we are so connected as a species, we need to kind of start having that empathy for we need to wear a mask, not for ourselves, but for our neighbors and people we may run into. And I think that kind of, the same kind of thinking has to kind of parade, before we can open up the economy in a big way. The data, I mean, we can do a lot of transfer learning, right, sort of there are new methods, like try to model it, similar to the 1918, where we had a second bump, or a lot of little bumps, and that's kind of where your W shaped pieces, but governments are trying very well in seeing stimulus dollars being pumped through banks. So some of the US case we're looking for banks is, which small medium business in especially, in unsecured lending, which business to lend to, (mumbles) there's so many applications that have come to banks across the world, it's not just in the US, and banks are caught up with the problem of which and what's growing the concern for this business to kind of, are they really accurate about the number of employees they are saying they have? Do then the next level problem or on forbearance and mortgage, that side of the things are coming up at some of these banks as well. So they're looking at which, what's one of the problems that one of our customers Wells Fargo, they have a question which branch to open, right, sort of that itself, it needs a different kind of modeling. So everything has become a very highly good segmented models, and so AI is absolutely not just a good to have, it has become a must have for most of our customers in how to go about their business. (mumbles) >> I want to talk a little bit about your business, you have been on a mission to democratize AI since the beginning, open source. Explain your business model, how you guys make money and then I want to help people understand basic theoretical comparisons and current affairs. >> Yeah, that's great. I think the last time we spoke, probably about at the Spark Summit. I think Dave and we were talking about Sparkling Water and H2O our open source platforms, which are premium platforms for democratizing machine learning and math at scale, and that's been a tremendous brand for us. Over the last couple of years, we have essentially built a platform called Driverless AI, which is a license software and that automates machine learning models, we took the best practices of all these data scientists, and combined them to essentially build recipes that allow people to build the best forecasting models, best fraud prevention models or the best recommendation engines, and so we started augmenting traditional data scientists with this automatic machine learning called AutoML, that essentially allows them to build models without necessarily having the same level of talent as these great Kaggle Grand Masters. And so that has democratized, allowed ordinary companies to start producing models of high caliber and high quality that would otherwise have been the pedigree of Google, Microsoft or Amazon or some of these top tier AI houses like Netflix and others. So what we've done is democratize not just the algorithms at the open source level. Now, we've made it easy for kind of rapid adoption of AI across every branch inside a company, a large organization, also across smaller organizations which don't have the access to the same kind of talent. Now, third level, you know, what we've brought to market, is ability to augment data sets, especially public and private data sets that you can, the alternative data sets that can increase the signal. And that's where we've started working on a new platform called Q, again, more license software, and I mean, to give you an idea there from business models endpoint, now majority of our software sales is coming from closed source software. And sort of so, we've made that transition, we still make our open source widely accessible, we continue to improve it, a large chunk of the teams are improving and participating in building the communities but I think from a business model standpoint as of last year, 51% of our revenues are now coming from closed source software and that change is continuing to grow. >> And this is the point I wanted to get to, so you know, the open source model was you know, Red Hat the one company that, you know, succeeded wildly and it was, put it out there open source, come up with a service, maintain the software, you got to buy the subscription okay, fine. And everybody thought that you know, you were going to do that, they thought that Databricks was going to do and that changed. But I want to take two examples, Hortonworks which kind of took the Red Hat model and Cloudera which does IP. And neither really lived up to the expectation, but now there seems to be sort of a new breed I mentioned, you guys, Databricks, there are others, that seem to be working. You with your license software model, Databricks with a managed service and so there's, it's becoming clear that there's got to be some level of IP that can be licensed in order to really thrive in the open source community to be able to fund the committers that you have to put forth to open source. I wonder if you could give me your thoughts on that narrative. >> So on Driverless AI, which is the closest platform I mentioned, we opened up the layers in open source as recipes. So for example, different companies build their zip codes differently, right, the domain specific recipes, we put about 150 of them in open source again, on top of our Driverless AI platform, and the idea there is that, open source is about freedom, right? It is not necessarily about, it's not a philosophy, it's not a business model, it allows freedom for rapid adoption of a platform and complete democratization and commodification of a space. And that allows a small company like ours to compete at the level of an SaaS or a Google or a Microsoft because you have the same level of voice as a very large company and you're focused on using code as a community building exercise as opposed to a business model, right? So that's kind of the heart of open source, is allowing that freedom for our end users and the customers to kind of innovate at the same level of that a Silicon Valley company or one of these large tech giants are building software. So it's really about making, it's a maker culture, as opposed to a consumer culture around software. Now, if you look at how the the Red Hat model, and the others who have tried to replicate that, the difficult part there was, if the product is very good, customers are self sufficient and if it becomes a standard, then customers know how to use it. If the product is crippled or difficult to use, then you put a lot of services and that's where you saw the classic Hadoop companies, get pulled into a lot of services, which is a reasonably difficult business to scale. So I think what we chose was, instead, a great product that builds a fantastic brand, that makes AI, even when other first or second.ai domain, and for us to see thousands of companies which are not AI and AI first, and even more companies adopting AI and talking about AI as a major way that was possible because of open source. If you had chosen close source and many of your peers did, they all vanished. So that's kind of how the open source is really about building the ecosystem and having the patience to build a company that takes 10, 20 years to build. And what we are expecting unfortunately, is a first and fast rise up to become unicorns. In that race, you're essentially sacrifice, building a long ecosystem play, and that's kind of what we chose to do, and that took a little longer. Now, if you think about the, how do you truly monetize open source, it takes a little longer and is much more difficult sales machine to scale, right, sort of. Our open source business actually is reasonably positive EBITDA business because it makes more money than we spend on it. But trying to teach sales teams, how to sell open source, that's a much, that's a rate limiting step. And that's why we chose and also explaining to the investors, how open source is being invested in as you go closer to the IPO markets, that's where we chose, let's go into license software model and scale that as a regular business. >> So I've said a few times, it's kind of like ironic that, this pandemic is as we're entering a new decade, you know, we've kind of we're exiting the era, I mean, the many, many decades of Moore's law being the source of innovation and now it's a combination of data, applying machine intelligence and being able to scale and with cloud. Well, my question is, what did we expect out of AI this decade if those are sort of the three, the cocktail of innovation, if you will, what should we expect? Is it really just about, I suggest, is it really about automating, you know, businesses, giving them more agility, flexibility, you know, etc. Or should we should we expect more from AI this decade? >> Well, I mean, if you think about the decade of 2010 2011, that was defined by software is eating the world, right? And now you can say software is the world, right? I mean, pretty much almost all conditions are digital. And AI is eating software, right? (mumbling) A lot of cloud transitions are happening and are now happening much faster rate but cloud and AI are kind of the leading, AI is essentially one of the biggest driver for cloud adoption for many of our customers. So in the enterprise world, you're seeing rebuilding of a lot of data, fast data driven applications that use AI, instead of rule based software, you're beginning to see patterned, mission AI based software, and you're seeing that in spades. And, of course, that is just the tip of the iceberg, AI has been with us for 100 years, and it's going to be ahead of us another hundred years, right, sort of. So as you see the discovery rate at which, it is really a fundamentally a math, math movement and in that math movement at the beginning of every century, it leads to 100 years of phenomenal discovery. So AI is essentially making discoveries faster, AI is producing, entertainment, AI is producing music, AI is producing choreographing, you're seeing AI in every walk of life, AI summarization of Zoom meetings, right, you beginning to see a lot of the AI enabled ETF peaking of stocks, right, sort of. You're beginning to see, we repriced 20,000 bonds every 15 seconds using H2O AI, corporate bonds. And so you and one of our customers is on the fastest growing stock, mostly AI is powering a lot of these insights in a fast changing world which is globally connected. No one of us is able to combine all the multiple dimensions that are changing and AI has that incredible opportunity to be a partner for every... (mumbling) For a hospital looking at how the second half will look like for physicians looking at what is the sentiment of... What is the surge to expect? To kind of what is the market demand looking at the sentiment of the customers. AI is the ultimate money ball in business and then I think it's just showing its depth at this point. >> Yeah, I mean, I think you're right on, I mean, basically AI is going to convert every software, every application, or those tools aren't going to have much use, Sri we got to go but thanks so much for coming to theCUBE and the great work you guys are doing. Really appreciate your insights. stay safe, and best of luck to you guys. >> Likewise, thank you so much. >> Welcome, and thank you for watching everybody, this is Dave Vellante for the CXO series on theCUBE. We'll see you next time. All right, we're clear. All right.

>> Starting the record, Dave in five, four, three. Hi, everybody this is Dave Vellante, theCUBE, and welcome back to my CXO series. I've been running this through really since the start of the COVID-19 crisis to really understand how leaders are dealing with this pandemic. Sri Ambati is here, he's the CEO and founder of H20. Sri, it's great to see you again, thanks for coming on. >> Thank you for having us. >> Yeah, so this pandemic has obviously given people fits, no question, but it's also given opportunities for companies to kind of reassess where they are. Automation is a huge watchword, flexibility, business resiliency and people who maybe really hadn't fully leaned into things like the cloud and AI and automation are now realizing, wow, we have no choice, it's about survival. Your thought as to what you're seeing in the marketplace. >> Thanks for having us. I think first of all, kudos to the frontline health workers who have been ruthlessly saving lives across the country and the world, and what you're really doing is a fraction of what we could have done or should be doing to stay away the next big pandemic. But that apart I think, I usually tend to say BC is before COVID. So if the world was thinking about going digital after COVID-19, they have been forced to go digital and as a result, you're seeing tremendous transformation across our customers, and a lot of application to kind of go in and reinvent their business models that allow them to scale as effortlessly as they could using the digital means. >> So, think about, doctors and diagnosis machines, in some cases, are helping doctors make diagnoses, they're sometimes making even better diagnosis, (mumbles) is informing. There's been a lot of talk about the models, you know how... Yeah, I know you've been working with a lot of healthcare organizations, you may probably familiar with that, you know, the Medium post, The Hammer and the Dance, and if people criticize the models, of course, they're just models, right? And you iterate models and machine intelligence can help us improve. So, in this, you know, you talk about BC and post C, how have you seen the data and in machine intelligence informing the models and proving that what we know about this pandemic, I mean, it changed literally daily, what are you seeing? >> Yeah, and I think it started with Wuhan and we saw the best application of AI in trying to trace, literally from Alipay, to WeChat, track down the first folks who were spreading it across China and then eventually the rest of the world. I think contact tracing, for example, has become a really interesting problem. supply chain has been disrupted like never before. We're beginning to see customers trying to reinvent their distribution mechanisms in the second order effects of the COVID, and the the prime center is hospital staffing, how many ventilator, is the first few weeks so that after COVID crisis as it evolved in the US. We are busy predicting working with some of the local healthcare communities to predict how staffing in hospitals will work, how many PPE and ventilators will be needed and so henceforth, but that quickly and when the peak surge will be those with the beginning problems, and many of our customers have begin to do these models and iterate and improve and kind of educate the community to practice social distancing, and that led to a lot of flattening the curve and you're talking flattening the curve, you're really talking about data science and analytics in public speak. That led to kind of the next level, now that we have somewhat brought a semblance of order to the reaction to COVID, I think what we are beginning to figure out is, is there going to be a second surge, what elective procedures that were postponed, will be top of the mind for customers, and so this is the kind of things that hospitals are beginning to plan out for the second half of the year, and as businesses try to open up, certain things were highly correlated to surgeon cases, such as cleaning supplies, for example, the obvious one or pantry buying. So retailers are beginning to see what online stores are doing well, e-commerce, online purchases, electronic goods, and so everyone essentially started working from home, and so homes needed to have the same kind of bandwidth that offices and commercial enterprises needed to have, and so a lot of interesting, as one side you saw airlines go away, this side you saw the likes of Zoom and video take off. So you're kind of seeing a real divide in the digital divide and that's happening and AI is here to play a very good role to figure out how to enhance your profitability as you're looking about planning out the next two years. >> Yeah, you know, and obviously, these things they get, they get partisan, it gets political, I mean, our job as an industry is to report, your job is to help people understand, I mean, let the data inform and then let public policy you know, fight it out. So who are some of the people that you're working with that you know, as a result of COVID-19. What's some of the work that H2O has done, I want to better understand what role are you playing? >> So one of the things we're kind of privileged as a company to come into the crisis, with a strong balance and an ability to actually have the right kind of momentum behind the company in terms of great talent, and so we have 10% of the world's top data scientists in the in the form of Kaggle Grand Masters in the company. And so we put most of them to work, and they started collecting data sets, curating data sets and making them more qualitative, picking up public data sources, for example, there's a tremendous amount of job loss out there, figuring out which are the more difficult kind of sectors in the economy and then we started looking at exodus from the cities, we're looking at mobility data that's publicly available, mobility data through the data exchanges, you're able to find which cities which rural areas, did the New Yorkers as they left the city, which places did they go to, and what's to say, Californians when they left Los Angeles, which are the new places they have settled in? These are the places which are now busy places for the same kind of items that you need to sell if you're a retailer, but if you go one step further, we started engaging with FEMA, we start engaging with the universities, like Imperial College London or Berkeley, and started figuring out how best to improve the models and automate them. The SaaS model, the most popular SaaS model, we added that into our Driverless AI product as a recipe and made that accessible to our customers in testing, to customers in healthcare who are trying to predict where the surge is likely to come. But it's mostly about information right? So the AI at the end of it is all about intelligence and being prepared. Predictive is all about being prepared and that's kind of what we did with general, lots of blogs, typical blog articles and working with the largest health organizations and starting to kind of inform them on the most stable models. What we found to our not so much surprise, is that the simplest, very interpretable models are actually the most widely usable, because historical data is actually no longer as effective. You need to build a model that you can quickly understand and retry again to the feedback loop of back testing that model against what really happened. >> Yeah, so I want to double down on that. So really, two things I want to understand, if you have visibility on it, sounds like you do. Just in terms of the surge and the comeback, you know, kind of what those models say, based upon, you know, we have some advanced information coming from the global market, for sure, but it seems like every situation is different. What's the data telling you? Just in terms of, okay, we're coming into the spring and the summer months, maybe it'll come down a little bit. Everybody says it... We fully expect it to come back in the fall, go back to college, don't go back to college. What is the data telling you at this point in time with an understanding that, you know, we're still iterating every day? >> Well, I think I mean, we're not epidemiologists, but at the same time, the science of it is a highly local response, very hyper local response to COVID-19 is what we've seen. Santa Clara, which is just a county, I mean, is different from San Francisco, right, sort of. So you beginning to see, like we saw in Brooklyn, it's very different, and Bronx, very different from Manhattan. So you're seeing a very, very local response to this disease, and I'm talking about US. You see the likes of Brazil, which we're worried about, has picked up quite a bit of cases now. I think the silver lining I would say is that China is up and running to a large degree, a large number of our user base there are back active, you can see the traffic patterns there. So two months after their last research cases, the business and economic activity is back and thriving. And so, you can kind of estimate from that, that this can be done where you can actually contain the rise of active cases and it will take masking of the entire community, masking and the healthy dose of increase in testing. One of our offices is in Prague, and Czech Republic has done an incredible job in trying to contain this and they've done essentially, masked everybody and as a result they're back thinking about opening offices, schools later this month. So I think that's a very, very local response, hyper local response, no one country and no one community is symmetrical with other ones and I think we have a unique situation where in United States you have a very, very highly connected world, highly connected economy and I think we have quite a problem on our hands on how to safeguard our economy while also safeguarding life. >> Yeah, so you can't just, you can't just take Norway and apply it or South Korea and apply it, every situation is different. And then I want to ask you about, you know, the economy in terms of, you know, how much can AI actually, you know, how can it work in this situation where you have, you know, for example, okay, so the Fed, yes, it started doing asset buys back in 2008 but still, very hard to predict, I mean, at this time of this interview you know, Stock Market up 900 points, very difficult to predict that but some event happens in the morning, somebody, you know, Powell says something positive and it goes crazy but just sort of even modeling out the V recovery, the W recovery, deep recession, the comeback. You have to have enough data, do you not? In order for AI to be reasonably accurate? How does it work? And how does at what pace can you iterate and improve on the models? >> So I think that's exactly where I would say, continuous modeling, instead of continuously learning continuous, that's where the vision of the world is headed towards, where data is coming, you build a model, and then you iterate, try it out and come back. That kind of rapid, continuous learning would probably be needed for all our models as opposed to the typical, I'm pushing a model to production once a year, or once every quarter. I think what we're beginning to see is the kind of where companies are beginning to kind of plan out. A lot of people lost their jobs in the last couple of months, right, sort of. And so up scaling and trying to kind of bring back these jobs back both into kind of, both from the manufacturing side, but also lost a lot of jobs in the transportation and the kind of the airlines slash hotel industries, right, sort of. So it's trying to now bring back the sense of confidence and will take a lot more kind of testing, a lot more masking, a lot more social empathy, I think well, some of the things that we are missing while we are socially distant, we know that we are so connected as a species, we need to kind of start having that empathy for we need to wear a mask, not for ourselves, but for our neighbors and people we may run into. And I think that kind of, the same kind of thinking has to kind of parade, before we can open up the economy in a big way. The data, I mean, we can do a lot of transfer learning, right, sort of there are new methods, like try to model it, similar to the 1918, where we had a second bump, or a lot of little bumps, and that's kind of where your W shaped pieces, but governments are trying very well in seeing stimulus dollars being pumped through banks. So some of the US case we're looking for banks is, which small medium business in especially, in unsecured lending, which business to lend to, (mumbles) there's so many applications that have come to banks across the world, it's not just in the US, and banks are caught up with the problem of which and what's growing the concern for this business to kind of, are they really accurate about the number of employees they are saying they have? Do then the next level problem or on forbearance and mortgage, that side of the things are coming up at some of these banks as well. So they're looking at which, what's one of the problems that one of our customers Wells Fargo, they have a question which branch to open, right, sort of that itself, it needs a different kind of modeling. So everything has become a very highly good segmented models, and so AI is absolutely not just a good to have, it has become a must have for most of our customers in how to go about their business. (mumbles) >> I want to talk a little bit about your business, you have been on a mission to democratize AI since the beginning, open source. Explain your business model, how you guys make money and then I want to help people understand basic theoretical comparisons and current affairs. >> Yeah, that's great. I think the last time we spoke, probably about at the Spark Summit. I think Dave and we were talking about Sparkling Water and H2O or open source platforms, which are premium platforms for democratizing machine learning and math at scale, and that's been a tremendous brand for us. Over the last couple of years, we have essentially built a platform called Driverless AI, which is a license software and that automates machine learning models, we took the best practices of all these data scientists, and combined them to essentially build recipes that allow people to build the best forecasting models, best fraud prevention models or the best recommendation engines, and so we started augmenting traditional data scientists with this automatic machine learning called AutoML, that essentially allows them to build models without necessarily having the same level of talent as these Greek Kaggle Grand Masters. And so that has democratized, allowed ordinary companies to start producing models of high caliber and high quality that would otherwise have been the pedigree of Google, Microsoft or Amazon or some of these top tier AI houses like Netflix and others. So what we've done is democratize not just the algorithms at the open source level. Now, we've made it easy for kind of rapid adoption of AI across every branch inside a company, a large organization, also across smaller organizations which don't have the access to the same kind of talent. Now, third level, you know, what we've brought to market, is ability to augment data sets, especially public and private data sets that you can, the alternative data sets that can increase the signal. And that's where we've started working on a new platform called Q, again, more license software, and I mean, to give you an idea there from business models endpoint, now majority of our software sales is coming from closed source software. And sort of so, we've made that transition, we still make our open source widely accessible, we continue to improve it, a large chunk of the teams are improving and participating in building the communities but I think from a business model standpoint as of last year, 51% of our revenues are now coming from closed source software and that change is continuing to grow. >> And this is the point I wanted to get to, so you know, the open source model was you know, Red Hat the one company that, you know, succeeded wildly and it was, put it out there open source, come up with a service, maintain the software, you got to buy the subscription okay, fine. And everybody thought that you know, you were going to do that, they thought that Databricks was going to do and that changed. But I want to take two examples, Hortonworks which kind of took the Red Hat model and Cloudera which does IP. And neither really lived up to the expectation, but now there seems to be sort of a new breed I mentioned, you guys, Databricks, there are others, that seem to be working. You with your license software model, Databricks with a managed service and so there's, it's becoming clear that there's got to be some level of IP that can be licensed in order to really thrive in the open source community to be able to fund the committers that you have to put forth to open source. I wonder if you could give me your thoughts on that narrative. >> So on Driverless AI, which is the closest platform I mentioned, we opened up the layers in open source as recipes. So for example, different companies build their zip codes differently, right, the domain specific recipes, we put about 150 of them in open source again, on top of our Driverless AI platform, and the idea there is that, open source is about freedom, right? It is not necessarily about, it's not a philosophy, it's not a business model, it allows freedom for rapid adoption of a platform and complete democratization and commodification of a space. And that allows a small company like ours to compete at the level of an SaaS or a Google or a Microsoft because you have the same level of voice as a very large company and you're focused on using code as a community building exercise as opposed to a business model, right? So that's kind of the heart of open source, is allowing that freedom for our end users and the customers to kind of innovate at the same level of that a Silicon Valley company or one of these large tech giants are building software. So it's really about making, it's a maker culture, as opposed to a consumer culture around software. Now, if you look at how the the Red Hat model, and the others who have tried to replicate that, the difficult part there was, if the product is very good, customers are self sufficient and if it becomes a standard, then customers know how to use it. If the product is crippled or difficult to use, then you put a lot of services and that's where you saw the classic Hadoop companies, get pulled into a lot of services, which is a reasonably difficult business to scale. So I think what we chose was, instead, a great product that builds a fantastic brand, that makes AI, even when other first or second.ai domain, and for us to see thousands of companies which are not AI and AI first, and even more companies adopting AI and talking about AI as a major way that was possible because of open source. If you had chosen close source and many of your peers did, they all vanished. So that's kind of how the open source is really about building the ecosystem and having the patience to build a company that takes 10, 20 years to build. And what we are expecting unfortunately, is a first and fast rise up to become unicorns. In that race, you're essentially sacrifice, building a long ecosystem play, and that's kind of what we chose to do, and that took a little longer. Now, if you think about the, how do you truly monetize open source, it takes a little longer and is much more difficult sales machine to scale, right, sort of. Our open source business actually is reasonably positive EBITDA business because it makes more money than we spend on it. But trying to teach sales teams, how to sell open source, that's a much, that's a rate limiting step. And that's why we chose and also explaining to the investors, how open source is being invested in as you go closer to the IPO markets, that's where we chose, let's go into license software model and scale that as a regular business. >> So I've said a few times, it's kind of like ironic that, this pandemic is as we're entering a new decade, you know, we've kind of we're exiting the era, I mean, the many, many decades of Moore's law being the source of innovation and now it's a combination of data, applying machine intelligence and being able to scale and with cloud. Well, my question is, what did we expect out of AI this decade if those are sort of the three, the cocktail of innovation, if you will, what should we expect? Is it really just about, I suggest, is it really about automating, you know, businesses, giving them more agility, flexibility, you know, etc. Or should we should we expect more from AI this decade? >> Well, I mean, if you think about the decade of 2010 2011, that was defined by software is eating the world, right? And now you can say software is the world, right? I mean, pretty much almost all conditions are digital. And AI is eating software, right? (mumbling) A lot of cloud transitions are happening and are now happening much faster rate but cloud and AI are kind of the leading, AI is essentially one of the biggest driver for cloud adoption for many of our customers. So in the enterprise world, you're seeing rebuilding of a lot of data, fast data driven applications that use AI, instead of rule based software, you're beginning to see patterned, mission AI based software, and you're seeing that in spades. And, of course, that is just the tip of the iceberg, AI has been with us for 100 years, and it's going to be ahead of us another hundred years, right, sort of. So as you see the discovery rate at which, it is really a fundamentally a math, math movement and in that math movement at the beginning of every century, it leads to 100 years of phenomenal discovery. So AI is essentially making discoveries faster, AI is producing, entertainment, AI is producing music, AI is producing choreographing, you're seeing AI in every walk of life, AI summarization of Zoom meetings, right, you beginning to see a lot of the AI enabled ETF peaking of stocks, right, sort of. You're beginning to see, we repriced 20,000 bonds every 15 seconds using H2O AI, corporate bonds. And so you and one of our customers is on the fastest growing stock, mostly AI is powering a lot of these insights in a fast changing world which is globally connected. No one of us is able to combine all the multiple dimensions that are changing and AI has that incredible opportunity to be a partner for every... (mumbling) For a hospital looking at how the second half will look like for physicians looking at what is the sentiment of... What is the surge to expect? To kind of what is the market demand looking at the sentiment of the customers. AI is the ultimate money ball in business and then I think it's just showing its depth at this point. >> Yeah, I mean, I think you're right on, I mean, basically AI is going to convert every software, every application, or those tools aren't going to have much use, Sri we got to go but thanks so much for coming to theCUBE and the great work you guys are doing. Really appreciate your insights. stay safe, and best of luck to you guys. >> Likewise, thank you so much. >> Welcome, and thank you for watching everybody, this is Dave Vellante for the CXO series on theCUBE. We'll see you next time. All right, we're clear. All right.

>> From theCUBE studios in Palo Alto in Boston, connecting with our leaders all around the world, this is theCUBE Conversation. >> Hello everyone, and welcome to this week's Wiki Bond CUBE Insights powered by ETR. In this breaking analysis, we're changing the format a little bit, we're going right to the new data from ETR. You might recall that last week, ETR received survey results from over 1000 CIOs and IT practitioners. And they made a call at that time, which said that actually surprisingly, a large number of respondents about 40% said they didn't expect a change in their 2020 IT spending. At the same time about 20% of the survey said they're going to spend more largely related to Work From Home infrastructure. ETR was really the first to report on this. And it wasn't just collaboration tool like zoom and video conferencing. It was infrastructure around that security, network bandwidth and other types of infrastructure to support Work From Home like desktop virtualization. ETR made the call at that time, that it looked like budgets, were going to be flat for 2020. Now, you also might recall consensus estimates for 2020 came into the year at about 4%, slightly ahead of GDP. Obviously, that's all is changed. Last week, ETR took the forecast down, and we're going to update you today. We're now gone slightly negative. And with me to talk about that again, is Sagar Kadakia, who's the Director of Research at ETR. Sagar, great to see you again, thank you for coming on. >> Thanks for having me again David, really appreciate it. >> Let's get right into it. I mean, if you look at the time series chart that we showed last week, you can see how sentiment changed over time. That blue line was basically people who responded to the survey starting at 3/11. Now you've updated that, that forecast, really tracking after the COVID-19 really kicked in. Can you explain what we're seeing here in this chart? >> Yeah, no problem. The last time we spoke, we were around an N or sample size of about 1000. And we were right around that zero percent growth rate. One of the unique things that we've done is we've left this survey open. And so what that allows us to do is really track the impact on annual IP growth, essentially daily. And so as things have progressed, as you look at that blue line, you can really see the growth rate has continued to trend downwards. And as of just a day or two ago, we're now below zero. And so I think because of what's occurring right now, the overall current climate continues to slightly deteriorate. You're seeing that in a lot of the CIOs responses. >> If you bring that slide back up Andrew, I want to just sort of stay on this for a second. What I really like about what you guys are doing is you're essentially bringing event analysis in this. So if you see that blue line, you see on 3/13, a national emergency was declared and that's really when the blue line started to decline. What ETR has done is kind of reset that, reset the data since 3/13. Because it's now a more accurate reflection of what's actually happening happening in the market. Notice in the upper right, it says the US approved... The Senate last night approved a stimulus package. Actually, they're calling it an Aid Package. It's really not a stimulus package. It's an aid package that they're injecting to help. A number of our workers actually sounds like existing workers and small businesses and even large businesses like Boeing. Boeing was up significantly yesterday powering the Dow and potentially airlines. As you can see ETR is going to continue to monitor the impact, and roll this out. Really ETR is the only company that I know of anyway, that can track this stuff on a daily basis. So Sagar, that event analysis is really key, and you're going to be watching the impact of this stimulus slash aid packet. >> Yeah, so here's what we're doing on that chart. If you look at that yellow line again, effectively what you're seeing is, if we remove the first I think six or seven 100 respondents that took the survey and start tracking how budgets are changing as a 3/13, that's when the US declared a national emergency. We can recalculate the growth rate. And we can see it's around... It's almost negative one and a half. And so the beauty of doing this, really polling daily, is it allows us to be just as dynamic, as a lot of these organizations are. I think one of the things we talked about the last time was some of these budget changes are going to be temporary. And organizations are figuring out what they're doing day by day. And a lot of that is dictated based on government actions. And so uniquely here, what we're able to do is kind of give people a range and also say, "based on these events, "this is how things are changing."" And so I think we think the first biggest event was on 3/13, where the US effectively declared a national emergency over COVID-19. And now what we're going to start tracking between today and over the weekend, and Monday is: Are people getting more positive? Is there no change? Or is there further deterioration because of this aid package that got passed this morning? >> Now I want to share with our audience. I've been down to ETR's headquarters in New York, it's staffed with a number of data scientists and statistical experts. The ends here are well over 1000. I think we're over 1100 now, is that correct? What is the end that we're at today? >> That's right. Yeah, we're we're pushing right over 1200. And we're going to expect a few more hundred respondents. The good thing is it's balanced, which is important. All these events that are occurring, we want to make sure that we have at least a few hundred more CIOs and IT executives answering. And so every week as we kind of continue to do some of these breaking analysis, there are going to be a few more hundred CIOs. And we'll really be able to zero in or hone in on what they're saying. The growth rate on the IT side, it's going to continue to fluctuate. It's going to continue to be dynamic over the next few weeks, but right now versus (murmurs). We are in negative territory now. >> I want to also explain I mean, the end is important. But in and of itself, it's not the be all end all, what's important about the end, the larger it is, the more cuts you can make. And I want to share... You guys have been doing this for the better part of a decade. And so you have firm level data. And you've got indicators and markers that you've tracked over the years. For example, one of the things that ETR tracks is Giant Public and Private GDP we call it. And that's for example, I'm not saying that, that Mars is one of the companies but Mars is a huge private company, UPS before they went public, huge private company. ETR tracks firm level data, they of course anonymize that, but they can see markers and trackers and trends, and probably have, I don't know dozens of those types of segments. So the bigger the end is, the more... The higher the end within those buckets, and the better the confidence interval. And you guys are experts at really digging into that in trying to understand and read the tea leaves. >> That's right. The key to this survey is, it's not anonymous, we know who is taking the survey. Now to your point, we do anonymize and aggregate it when we display those results. But one of the unique capabilities is we're able to see all of these trend lines. The entire drill down survey that we did on COVID-19 through the lenses of different verticals so we can take a look at industrials materials manufacturing, healthcare, pharma, airlines, delivery services, health, and all these other verticals and get a feel for which ones are deteriorating the most, which ones look stable. And, we talked about last week and it continues to remain true this week. And again, the ends have gone up on all these verticals on the supply chain side. Industrials, materials manufacturing, healthcare, pharma, they continue and they also anticipate to see these things in the next few months, broken supply chains and on the demand side, it's really retail consumer airlines delivery services. That's coming down quite substantial. And I think, based on what United and some of these other airlines have done these last few days in terms of cutting capacity, that's just a reflection of what we're seeing. >> Let's dig into the data a little bit more and bring up the next chart. Last week, we're about 40% actually, exactly 40% where that gray line that said: CIOs and IT practitioners said, "no change." They're like the budget of the green. The green was actually at about 20 21%. So it's slightly up now at 22%. And you can see, most of the the green is in that one to 10% range. And you can see in the left hand side, it's obviously changing. Now we're at 37% in the gray line, slightly up in the green, and a little bit more down and in the red. So take us through what's changed Sagar. >> Yeah, to reiterate what we were talking about last week, and then I'll kind of talk about some of the change is, I think the market and a lot of our clients, they were expecting the growth rate to be more negative. Last week when we talked about zero percent. The reason that, it wasn't more negative is because we saw all these organizations accelerating spend because they had to keep employees productive. They don't want to catastrophe in productivity. And so you saw this acceleration, as you mentioned earlier in the interview around Work From Home tools, like collaboration tools, increasing bandwidth on the VPN networking side, laptops, MDM, so forth and so on. That continues to hold true today. Again, if we use the same example that we talked about last week, (mumbles) organizations, they have 40 50 60,000 employees or more working from home. You have to be able to support these individuals and that's why we're actually seeing some organizations accelerate spend and the majority organizations even though they are declining spend, some of that is still being offset by having to spend more on what we're calling kind of this Work From Home infrastructure. But I will say this: you are seeing more organizations versus last week, which is why the growth rate has come down, moving more and more towards the negative buckets. Again, there is some offset there. But the offset we talked about last week, Work From Home infrastructure is not a one-for-one when it comes to taking down your IT budget, and that continues to hold true. >> Let's talk a little bit about some of the industries retail, airlines, industrials, pharma, healthcare, what are you seeing in terms of the industry impact, particularly when it relates to supply chains, but other industry data that went through? >> I think the biggest takeaway is that healthcare pharma, industry materials, manufacturing organizations, they've indicated the highest levels of broken supply chains today. And they think in three months from now, it's actually going to get worse. And so we spoke about this last time, I don't think this is going to be a V shaped recovery from the standpoint of things are going to get better in the next few weeks or the next month or two. CIOs are indicating that they expect conditions to worsen over the next three months on the supply chain side and even demand the ones that are getting hit the hardest on the retail consumer side airlines, delivery services, they are again indicating that they anticipate demand to be worse three months from now. The goal is to continue serving and pulling these individuals over the next few weeks and months and to see if we can get a better timeline as we get into two edge but for the next few months, conditions look like they're going to get worse. >> I want to highlight some of the industries and let's make some comments here. Retail... You guys called out retail airlines, delivery services, industrials, materials, manufacturing, pharma and healthcare, there's some of the highest impact. I'll just make a few comments here. I think retail really, this accelerates the whole digital transformation. We already saw this starting, I think you'll see further consolidation and some permanence in the way in which companies are pivoting to digital. Obviously, the big guys like Walmart and the like are competing very effectively with Amazon. But, there's going to be some more consolidation there. I would say potentially the same thing in airlines that really are closely watching what the government is going to do. But, do we need this this many airlines? Do we need all this capacity? Maybe yes, maybe no. So watching that. And of course, healthcare right now, as I said last week in the braking analysis, they're just too distracted right now to buy anything. And they're overwhelmed. Now, of course, pharma, they're manufacturing, so they've got disruptions in supply chain and obviously the business. But there could be an upside down the road as COVID-19 vaccines come to the market. >> On the upside, I think you kind of hit it, right on the nail. When you get these type of events that occur. Sometimes it speeds up digital transformation. one of the things that the team and I have been talking about internally is: this is not your father's Keep The Lights On strategy so to speak. Organizations are very focused on maintaining productivity versus significantly cutting costs. What does that mean? Maybe three to five years ago, if this had occurred, you would have seen a lot of infrastructure as a service platform, as a service... A lot of these cloud providers, you'd have seen those projects decline as organization spent more on on plan. And we're not seeing that. We're seeing continued elevated budgets on the Cloud side and Micron just reported this morning and again, cited strong demand on the Cloud and data center side. That just goes to show that organizations are trying to maintain productivity. They want to continue these IT roadmaps and they're going to cut budgets where they can, but it's not going to be on the Cloud side. >> You know what, that's a really important point. This is not post Y2K, not 2008, 2007, 2008, 2009 because we've, pretended but a 10 year bull market, companies are doing pretty well, balance sheets are generally strong. They somewhat in whether, it was used to stronger companies, whether they're so they're not focused right now anyway, on cut cut cut as it was in the last few downturns. Let's go into some of the vendor data and some of the sector data, Andrew if you'd bring up the next chart. What we're showing here is really comparing the the blue is the January survey to the current survey in the yellow, and you're seeing some of the sectors that are up taking. You've identified mobile device management, big data and Cloud, some of the productivity, you mentioned DocuSign, Adobe zoom, Citrix, even VMware with the desktop virtualization. We've talked about security, you've got marketing and LinkedIn, my LinkedIn inbound is going through the roof as people are probably signing up for a LinkedIn premium. Let's talk about this a little bit. What you're seeing... Help us interpret this data. >> Yeah, sure. One of the things that everybody wants to know is, okay, so Work From Home infrastructures getting more spend for the vendors that are benefiting the most. One of the unique things that we can do is because we're kind of collecting all the DNA, from a tech stack aside from these organizations, we can overlap, how they're spending on these vendors. And also with the data that they provide in terms of whether they are increasing or decelerating their IT budgets because of COVID-19. What you're looking at here, is we isolated to all of those organizations and customers that indicated that they're increasing their budgets because of COVID-19. Because of the Work From Home infrastructure. And what we're doing is we're then isolating to vendors that are getting the most upticks in spend. This actually really nicely aligns with a lot of the themes that we were talking about collaboration tools. You see that VMware, they're all right on the virtualization side, MDM with Microsoft. And you're seeing a lot of other vendors with Citrix and Zoom and Adobe. These are the ones that we think are going to benefit from this kind of Work From home infrastructure movement. And again, it's all very... It's not just the qualitative and the commentary. This is all analytics, we really went in and analyzed every single one of these organizations that were increasing their budgets and tried to pinpoint using different data analysis techniques, and to see which vendors were really getting the majority or the largest, pie of that span. >> We had Sanjay Poonen, who's the CEO of VMware on yesterday and he was very sensitive but not trying to hear as your ambulance chasing because obviously they do desktop virtualization and VDI big workload. At the same time. I think he was also being cautious because there's probably portions of their business that are going to get hit, Michael Dell similarly, I think he was quoted in CRN as saying, "hey, are we seeing momentum in our laptop "business in our mobile business?" But as you guys pointed out, the flip side of that is their on prem business is probably going to suffer somewhat. It's a kind of like the Work From Home is a partial offset, but it's not a total offset. You're seeing that with a lot of these companies. Obviously, Microsoft, AWS, a lot of the cloud companies are very well positioned, how about some of the guys that are going to get impacted? Obviously, as I said that the on-prem folks, you guys talked about earlier it's not your father's Keep Your Lights On strategy. Okay but this... You asked the question, is this a reprieve for the legacy guys? Not quite, was your conclusion. What did you mean by that? >> I think a lot of times when you have these sub-events, the clients a lot of the market think okay, "some of the legacy vendors are going to do well "because, we're in malicious times, "and we don't want to keep on this kind "of next generation strategy." We're not seeing that and to the point that you highlighted earlier. There are... Even though these companies like Dell, like Cisco, where they're seeing some products accelerate, there are products to your point that are not doing as well The desktops, right? As an example for Dell or the storage. On the negative side or the legacy side where we're just not seeing any traction, the IBM's the Oracle on-prem, Symantec, which got acquired by Broadcom, checkpoint MicroStrategy. And there's another half dozen other vendors that we're seeing where they are not capitalizing. There is no reprieve for these legacy names. And we don't anticipate them getting additional spend, because of this Work From Home infrastructure kind of movement. >> Let's unpack that a little bit. It's interesting Symantec and checkpoint in security, security you think would get an uplift there, but what you're seeing here is... Let me just tell the audience who you called out. Symantec Teradata MicroStrategy, NET app Checkpoint Oracle and IBM, and I know there are others. But I would say this: These are companies that are getting impacted in a big way by the Cloud. Particularly like Symantec and checkpoint. That's a Cloud security companies are actually probably still doing pretty well. You take Teradata, their data is getting impact by the Cloud from folks like Snowflake and Redshift, MicroStrategy a lot of modern BI coming out. NetApp here's a company that's embraced the Cloud, but the vast majority of the business changess to be on-prem. I think IBM and Oracle are interesting. They're somewhat different. Actually a lot different IBM has services exposure, and you guys call that out, particularly around outsourcing. At the same time, it's going to be interesting to see IBM is going to get a lot of resources. Going to be interesting to see if they start coming out with corona virus related services. So watching for that, and then Oracle, their whole story is, "okay, we got Gen 2 Cloud and Mission Critical in the Cloud, but they're on-prem businesses, I think clearly going to be affected here is kind of what you guys pointed out, and I would agree with your thoughts. >> I think what we're seeing is organizations they had a Cloud roadmap, and that roadmap is continuing. The one thing that is changing in some of that roadmap is we need to be able to support employees as they work from home as we achieve this roadmap. And so that's why we're not seeing a reprieve on the legacy side. But we are seeing upticks and spin where we just wouldn't anticipate them right on maybe on Citrix, on Dell laptops, Adobe and a few other areas. Now, in terms of security side, some of the next gen security vendors like CrowdStrike APi, which is an MFA, those vendors are doing well. It makes sense, where you have more people working from home, you have more devices that are connecting to data applications. Just a component itself. And so you would expect spend to continue going up as you need more authentication, more Endpoint Protection. Cisco Meraki they do Cloud Networking. That piece is looking very good, even though Hardware networking is not looking very good at all. The Cloud Networking is looking good, which again makes sense, as you're increasing bandwidth on that side. >> Definitely stories of two sides of that coin. >> That's right >> I want to... Andrew, if you want to... If you wouldn't mind bringing up the next job, we're going to go back to the first one that we showed you with the time series. This is a very important point. Again, we can't stress it enough. We want to understand the impact of the stimulus or aid package. And ETR is going to continue to track that. What can we expect from you guys over the next week or so? >> The goal is to determine whether or not the stimulus is having an impact on how people are responding to our survey as a relates to how they're changing their budgets. The next four or five days, if we start seeing an uptick in this yellow and blue lines here, I think that's a positive. I think that shows that people are kind of wrapping their heads around, great government is taking action here. There is a roadmap in place to help us get out of this. But if the line continues coming down, it just may be that the last few weeks or the last month or so, there was just so much damage. There's not really... There's no coming back from this at least in the near term. So we are kind of watching out for that. >> Well, the Fed is definitely active. >> They're doing right what they can, they're pushing liquidity into the marketplace. People think out of bullets. I don't agree with the Fed. Fed has a quite a bit of of headroom and some dry powder, (murmurs) which is awesome. But the Fed itself, can't do it. You needed to have this fiscal stimulus. So we're excited to see that come to market. I think what I would say to our audiences, my concern is uncertainty. The markets don't like uncertainty and right now there's a lot of uncertainty. If you saw the piece on medium of The Hammer And The Dance it lays out some scenarios about what could happen to the healthcare system. You see people who say, "hey, we should shut down for 10 weeks." The president saying, "hey, we want "to get back to work by by April." The big concern that I have is: okay, maybe we can stamp it out in the near term and get back to work by late April, early May. But then what happens? Are people going to start traveling again? Are people going to start holding events again? And I think there's going to be some real question marks around that. That uncertainty I think, is something that we obviously have to watch. I think there is light at the end of the tunnel, when you look at China and some of the other things that are happening around the world, but we still don't know how long that tunnel is. I'll give you final thoughts before we wrap. >> I think and that's the biggest thing here is the uncertainty, which is why we're doing a lot of this event analysis. We're trying to figure out: after each one of these big events, is there more certainty in people's responses? And just we were talking about, sectors and verticals and vendors that are not doing well. Because the uncertainty we're seeing a lot of down ticks and spend amongst outsource IT and IT consulting vendors. And as long as the uncertainty continues, you're going to see more and more IT projects frozen, less and less spend on those outsource IT and IT consulting vendors and others. And until there's something really in place here where people feel comfortable, you're going to probably see budgets remain where they are, which right now they're negative. >> Folks as we said last week, Sagar and I, ETR is committed, theCUBE is committed to keep you updated on a regular basis. Right now on a weekly cadence. As we have new information, we will bring it to you. Sagar, thanks so much for coming on and supporting us. >> You're welcome and thanks for having me again. >> You're welcome. Thank you for watching this CUBE Insights powered by ETR. And remember all these breaking analysis available on podcast, go to etr.plus that's where all the action is in terms of the survey work. siliconangle.comm covers these breaking analysis and I published weekly on wikibond.com. Thanks for watching everybody. Stay safe. And we'll see you next time.

>>Fly from San Francisco. It's the cube covering RSA conference, 2020 San Francisco brought to you by Silicon angle media. >>Hi everyone. Welcome back to the cubes coverage here at in San Francisco, the Moscone center for RSA conference 2020 I'm job for your host. We are the very special guests, the COO of VMware, Sanjay Poonen, cube alumni. When you talk about security, talk about the modern enterprise as it transforms new use cases, new problems emerge. New opportunities exist here to break it down. Sanjay, welcome back. Thank you John. Always a pleasure to be on your show and I think it's my first time at RSA. We've talked a number of times, but nice to see you here. Well, it's a security guard. Well, this is really why I wanted you to talk, talk to you because operations is become now the big conversation around security. So you know, security was once part of it. It comes out and part of the board conversation, but when you look at security, all the conversations that we're seeing that are the most important conversations are almost a business model conversation. >>Almost like if you're the CEO of the company, you've got HR people, HR, organizational behavior, collaboration, technology, stack compliance and risk management. So the threat of cyber has to cut across now multiple operational functions of the business. It's no longer one thing, it's everything. So this is really kind of makes it the pressure of the business owners to be mindful of a bigger picture. And the attack velocity is happening so much faster, more volume of attacks, milliseconds and nanosecond attacks. So this is a huge, huge problem. I need you to break it down for me. >> Good. But then wonderful intro. No, I would say you're absolutely right. First off, security is a boardroom topic. Uh, audit committees are asking, you know, the CIO so often, you know, reports a report directly, sometimes, often not even to the CIO, to the head of legal or finance and often to the audit. >>So it's a boardroom topic then. You're right, every department right now cares about security because they've got both threat and security of nation state, all malicious, organized crime trying to come at them. But they've also got physical security mind. I mean, listen, growing a virus is a serious threat to our physical security. And we're really concerned about employees and the idea of a cyber security and physical security. We've put at VMware, cybersecurity and, and um, um, physical security. One guy, the CIO. So he actually runs vote. So I think you're absolutely right and if you're a head of HR, you care about your employees. If you're care ahead of communications, you care about your reputation and marketing the same way. If you're a finance, you care about your accounting systems and having all of the it systems that are. So we certainly think that holistic approach does, deserves a different approach to security, which is it can't be silo, silo, silo. >>It has to be intrinsic. And I've talked on your show about why intrinsic and how differentiated that intrinsic security, what I talked about this morning in my keynote. >> Well, and then again, the connect the dots there. It's not just security, it's the applications that are being built on mobile. For instance, I've got a mobile app. I have milliseconds, serious bond to whether something's yes or no. That's the app on mobile. But still the security threat is still over here and I've got the app over here. This is now the reality. And again, AirWatch was a big acquisition that you did. I also had some security. Carbon black was a $2 billion acquisition that VMware made. That's a security practice. How's it all coming together? Can you think of any questions? Blame the VMware because it's not just security, it's what's around it. >> Yeah. I think we began to see over the course of the last several years that there were certain control points and security that could help, you know, bring order to this chaos of 5,000 security vendors. >>They're all legitimate. They're all here at the show. They're good vendors. But you cannot, if you are trying to say healthy, go to a doctor and expect the doctor to tell you, eat 5,000 tablets and sailed. He just is not sustainable. It has to be baked into your diet. You eat your proteins, your vegetables, your fruit, your drink, your water. The same way we believe security needs to become intrinsically deeper parts, the platform. So what were the key platforms and control points? We decided to focus on the network, the endpoint, and you could think of endpoint as to both client and workload identity, cloud analytics. You take a few of those and network. We've been laboring the last seven years to build a definitive networking company and now a networking security company where we can do everything from data center networking, Dell firewalls to load balancing to SDN in this NSX platform. >>You remember where you bought an nice syrup. The industry woke up like what's VM ever doing in networking? We've now built on that 13,000 customers really good growing revenue business in networking and and now doing that working security. That space is fragmented across Cisco, Palo Alto, FIU, NetScaler, checkpoint Riverbed, VMware cleans that up. You get to the end point side. We saw the same thing. You know you had an endpoint management now workspace one the sequel of what AirWatch was, but endpoint security again, fragmented. You had Symantec McAfee, now CrowdStrike, tenable Qualis, you know, I mean just so many fragmented IOM. We felt like we could come in now and clean that up too, so I have to worry about to do >> well basically explaining that, but I want to get now to the next conversation point that I'm interested in operational impact because when you have all these things to operationalize, you saw that with dev ops and cloud now hybrid, you got to operationalize this stuff. >>You guys have been in the operations side of the business for our VMware. That's what you're known for and the developers and now on the horizon I gotta operationalize all the security. What do I do? I'm the CSO. I think it's really important that in understanding operations of the infrastructure, we have that control point called vSphere and we're now going to take carbon black and make it agentless on the silverside workloads, which has never been done before. That's operationalizing it at the infrastructure level. At the end point we're going to unify carbon black and workspace one into a unified agent, never been done before. That's operationalizing it on the client side. And then on the container and the dev ops site, you're going to start bringing security into the container world. We actually happened in our grade point of view in containers. You've seen us do stuff with Tansu and Kubernetes and pivotal. >>Bringing that together and data security is a very logical thing that we will add there. So we have a very good view of where the infrastructure and operations parts that we know well, a vSphere, NSX workspace one containers with 10 Xu, we're going to bring security to all of them and then bake it more and more in so it's not feeling like it's a point tool. The same platform, carbon black will be able to handle the security of all of those use cases. One platform, several use cases. Are you happy with the carbon black acquisition? Listen, you know, you stay humble and hungry. Uh, John for a fundamental reason, I've been involved with number of acquisitions from my SAP VMware days, billion dollar plus. We've done talking to us. The Harvard business review had an article several years ago, which Carney called acquisitions and majority of them fail and they feel not because of process of product they feel because good people leave. >>One of the things that we have as a recipe does acquisition. We applied that to AirWatch, we apply the deny Sera. There is usually some brain trust. You remember in the days of nice area, it was my team Cosato and the case of AirWatch. It was John Marshall and that team. We want to preserve that team to help incubate this and then what breve EV brings a scale, so I'm delighted about Patrick earlier. I want to have him on your show next time because he's now the head of our security business unit. He's culturally a fit for the mr. humble, hungry. He wants to see just, we were billion dollar business now with security across networking endpoint and then he wants to take just he's piece of it, right? The common black piece of it, make it a billion dollar business while the overall security business goes from three to five. >>And I think we're going to count them for many years to come to really be a key part of VMware's fabric, a great leader. So we're successful. If he's successful, what's my job then? He reports to me is to get all the obstacles out of the way. Get every one of my core reps to sell carbon black. Every one of the partners like Dell to sell carbon black. So one of the deals we did within a month is Dell has now announced that their preferred solution on at Dell laptops, this carbon bike, they will work in the past with silence and crowd CrowdStrike. Now it's common black every day laptop now as a default option. That's called blank. So as we do these, John, the way we roll is one on here to basically come in and occupy that acquisition, get the obstacles out of the way, and that let Patrick scaled us the same way. >>Martine Casado or jumbo. So we have a playbook. We're gonna apply that playbook. Stay humble and hungry. And you ask me that question every year. How are we doing a carbon black? I will be saying, I love you putting a check on you. It will be checking in when we've done an AirWatch. What do you think? Pretty good. Very good. I think good. Stayed line to the radar. Kept growing. It's top right. Known every magic quadrant. That business is significant. Bigger than the 100 million while nice here. How do we do a nice hero? NSX? It's evolved quite a bit. It's evolved. So this is back to the point. VMware makes bets. So unlike other acquisitions where they're big numbers, still big numbers, billions or billions, but they're bets. AirWatch was a good bet. Turned out okay. That the betting, you're being conservative today anyway. That's it. You're making now. >>How would you classify those bets? What are the big bets that you're making right now? Listen, >> I think there's, um, a handful of them. I like to think of things as no more than three to five. We're making a big bet. A multi-cloud. Okay. The world is going to be private, public edge. You and us have talked a lot about VMware. AWS expanded now to Azure and others. We've a big future that private cloud, public cloud edge number two, we're making a big bet on AB motorization with the container level 10 zoos. I think number three, we're making a big bet in virtual cloud networking cause we think longterm there's going to be only two networking companies in matter, VMware and Cisco. Number four, we're making a big bet in the digital workspace and build on what we've done with AirWatch and other technologies. Number five, and make it a big bet security. >>So these five we think of what can take the company from 10 to 20 billion. So we, you know, uh, we, we've talked about the $10 billion Mark. Um, and the next big milestone for the company is a 20 billion ball Mark. And you have to ask yourself, can you see this company with these five bets going from where they are about a 10 billion revenue company to 20. Boom. We hope again, >> Dave, a lot that's doing a braking and now he might've already shipped the piece this morning on multi-cloud. Um, he and I were commenting that, well, I said it's the third wave of cloud computing, public cloud, hybrid multi-cloud and hybrids, the first step towards multi-cloud. Everyone kind of knows that. Um, but I want to ask you, because I told Dave and we kind of talked about this is a multi-decade growth opportunity, wealth creation, innovation, growth, new opportunity multicloud for the generation. >>Take the, this industry the next level. How do you see that multicloud wave? Do you agree on the multigenerational and if so, what specifically do you see that unfolding into this? And I'm deeply inspired by what Andy Jassy, Satya Nadella, you know, the past leading up to Thomas Korea and these folks are creating big cloud businesses. Amazon's the biggest, uh, in the iOS pass world. Azure is second, Google is third, and just market shares. These folks collectively are growing, growing really well. In some senses, VM-ware gets to feed off that ecosystem in the public cloud. So we are firm believers in what you're described. Hybrid cloud is the pot to the multicloud. We coined that term hybrid thought. In fact, the first incantation of eco there was called via cloud hybrid service. So we coined the term hybrid cloud, but the world is not multi-cloud. The the, the key though is that I don't think you're gonna walk away from those three clouds I mentioned have deep pockets. >>Then none of them are going away and they're going to compete hard with each other. The market shares may stay the same. Our odd goal is to be a Switzerland player that can help our customers take VM or workloads, optimize them in the private cloud first. Okay? When a bank of America says on their earnings caller, Brian Warren and said, I can run a private cloud better than a public cloud and I can save 2 billion doing that, okay? It turns off any of the banks are actually running on VMware. That's their goal. But there are other companies like Freddie Mac, we're going all in with Amazon. We want to ride the best of both worlds. If you're a private cloud, we're going to make you the most efficient private cloud, VMware software, well public cloud, and going to Amazon like a Freddie Mac will help you ride your apps into that through VMware. >>So sometimes history can be a predictor of future behavior. And just to kind of rewind the computer industry clock, if you looked at mainframe mini-computers, inter networking, internet proprietary network operating systems dominated it, but you saw the shift and it was driven by choice for customers, multiple vendors, interoperability. So to me, I think cloud multicloud is going to come down to the best choice for the workload and then the environment of the business. And that's going to be a spectrum. But the key in that is multi-vendor, multi, a friend choice, multi-vendor, interoperability. This is going to be the next equation in the modern error. It's not gonna look the same as mainframe mini's networking, but it'll create the next Cisco, the create the next new brand that may or may not be out there yet that might be competing with you or you might be that next brand. >>So interoperability, multi-vendor choice has been a theme in open systems for a long time. Your reactions, I think it's absolutely right, John, you're onto something there. Listen, the multicloud world is almost a replay of the multi hardware system world. 20 years ago, if you asked who was a multi hardware player before, it was Dell, HP at the time, IBM, now, Lenovo, EMC, NetApp, so and so forth and Silva storage, networking. The multicloud world today is Amazon, Azure, Google. If you go to China, Alibaba, so on and so forth. A Motiva somebody has to be a Switzerland player that can serve the old hardware economy and the new hardware economy, which is the, which is the cloud and then of course, don't forget the device economy of Apple, Google, Microsoft, there too. I think that if you have some fundamental first principles, you expressed one of them. >>Listen where open source exists, embrace it. That's why we're going big on Kubernetes. If there are multiple clouds, embrace it. Do what's right for the customer, abstract away. That's what virtualization is. Managed common infrastructure across Ahmed, which is what our management principles are, secure things. At the point of every device and every workload. So those are the principles. Now the engineering of it changes. The way in which we're doing virtualization today in 2020 is slightly different from when Diane started the company and around the year 2020 years ago. But the principals are saying, we're just not working just with the hardware vendors working toward the cloud vendors. So using choices where it's at, the choice is what they want. Absolutely, absolutely. And you're right. It's choice because it was the big workloads. We see, for example, Amazon having a headstart in the public cloud markets, but there's some use cases where Azure is applicable. >>Some use his word, Google's applicable, and to us, if the entire world was only one hardware player or only one cloud player, only one device player, you don't need VMware. We thrive in heterogeneity. It's awesome. I love that word. No heterogeneity provides not 3000 vendors. There's almost three, three of every kind, three silver vendors, three storage vendors, three networking vendors, three cloud vendors, three device vendors. We was the middle of all of it. And yeah, there may be other companies who tried to do that too. If they are, we should learn from them, do it better than them. And competition even to us is a good thing. All right. My final question for you is in the, yeah, the Dell technologies family of which VMware is a part of, although big part of it, the crown jewel as we've been calling them the cube, they announced RSA is being sold to a private equity company. >>What's the general reaction amongst VMware folks and the, and the Dell technology family? Good move, no impact. What we support Dell and you know, all the moves that they've made. Um, and from our perspective, you know, if we're not owning it, we're going to partner it. So I see no overlap with RSA. We partner with them. They've got three core pillars, secure ID, net witness and Archer. We partnered with them very well. We have no aspirations to get into those aspects of governance. Risk and compliance or security has been, so it's a partner. So whoever's running it, Rohit runs on very well. He also owns the events conference. We have a great relationship and then we'll keep doing that. Well, we are focused in the areas I described, network, endpoint security. And I think what Michael has done brilliantly through the course of the last few years is set up a hardware and systems company in Dell and allow the software company called Vima to continue to operate. >>And I think, you know, the movement of some of these assets between the companies like pivotal to us and so on and so forth, cleans it up so that now you've got both these companies doing well. Dell has gone public, we Hammer's gone public and he has said on the record, what's good for Dell is good, what's good for VMware and vice versa and good for the customer. And I think the key is there's no visibility on what cloud native looks like. Hybrid, public, multi, multi, not so much. But you get almost, it's an easy bridge to get across and get there. AI, cyber are all big clear trends. They're waves. Sasha. Great. Thank you. Thanks for coming on. Um, your thoughts on the security show here. Uh, what's your, what's your take to, uh, definitive security shows? I hope it stays that way. Even with the change of where RSA is. >>Ownership goes is this conference in black hat and we play in both, uh, Amazon's conference. I was totally starting to, uh, reinforce, reinforce cloud security will show up there too. Uh, but we, we think, listen, there's what, 30,000 people here. So it's a force. It's a little bit like VMworld. We will play here. We'll play a big, we've got, you know, it just so happens because the acquisition happened before we told them, but we have two big presences here. We were at carbon black, um, and it's an important business for us. And I said, like I said, we have $1 billion business and security today by 30,000 customers using us in a security network, endpoints cloud. I want to take that to be a multi, multiple times that size. And I think there's a pot to do that because it's an adjacent us and security. So we have our own kind of selfish motives here in terms of getting more Mindshare and security. >>We did a keynote this morning, which was well received with Southwest airlines. She did a great job. Carrie Miller, she was a fantastic speaker and it was our way of showing in 20 minutes, not just to our point of view, because you don't want to be self serving a practitioner's point of view. And that's what's really important. Well finally on a personal note, um, you know, I always use the term tech athlete, which I think you are one, you really work hard and smart, but I got to get your thoughts. But then I saw you're not on Twitter. I'm on. When IBM announced a new CEO, Arvin, um, fishnet Indian American, another CEO, this is a pattern. We're starting to see Indian American CEOs running cup American companies because this is the leadership and it's really a great thing in my mind, I think is one of the most successful stories of meritocracy of all time. >>You're quick. I'm a big fan of oven, big fan of Shantanu, Sundar Pichai, something that Ellen, many of them are close friends of mine. Uh, many of them have grown up in Southern India. We're a different ages. Some of them are older than me and in many cases, you know, we were falling behind other great players like Vino Cosla who came even 10 to 15 years prior. And you know, it's hard for an immigrant in this country. You know, um, when I first got here and I came as an immigrant to Dartmouth college, there may have been five or 10 Brown skin people in the town of Hanover, New Hampshire. I don't know if you've been to New Hampshire. I've been there, there's not many at that time. And then the late 1980s, now of course, there's much more, uh, so, you know, uh, we stay humble and hungry. >>There's a part of our culture in India that's really valued education and hard work and people like Arvin and some of these other people are products. I look up to them, the things I learned from them. And um, you know, it's true of India. It's a really good thing to see these people be successful at name brand American companies, whether it's IBM or Microsoft or Google or Adobe or MasterCard. So we're, we're, I'm in that fan club and there's a lot I learned from that. I just love being around people who love entrepreneurship, love innovation, love technology, and work hard. So congratulations. Thank you so much for your success. Great to see you again soon as you put in the COO of VM-ware here on the ground floor here at RSA conference at Moscone, sharing his insight into the security practice that is now carbon black and VMware. All the good things that are going on there. Thanks for watching.

>>Live from Denver, Colorado. It's the cube covering comm vault. Go 2019 brought to you by Combolt. >>Hey, welcome back to the cubes coverage of combo go 19. Stu Miniman is here with me, Lisa Martin and we are wrapping up two days of really exciting wall to wall coverage of the new vault and we're very pleased to welcome a couple of special guests onto the program. To help us wrap up our two days, we have Miranda foster, the vice president of worldwide communications for comm vault and Al Bunty is here, the co founder, former COO and board member. Welcome Miranda and Al. Great to have you on the program. Thanks Lisa. So a lot of energy at this event and I don't think it has anything to do with our rarefied air here in the mile high city. Al, let's start with you. >>Well, there's other things in Colorado. >>There are, yeah, they don't talk about it. They talked about that on stage yesterday. So owl, you have been with convo ball as I mentioned, co-founder. What an evolution over the last 20 years. Can you take us back? >>Surely. So, um, yeah and it's been, it's, it's really kind of cool to see it coming together at this point. But if you go back 20 years when we started this, the whole idea was around data. And remember we walked into a company that was focused on optical storage. Um, we decided it would be a good company to invest in. Um, for two reasons. One, we thought they were really great people here, very creative and innovative and two, it was a great space. So if we believed we believe data would grow and that was a pretty decent thesis to go with. Yeah. And then, then it started moving from there. So I tell people I wasn't burdened with facts so I didn't understand why all these copies were being made of the same set of data. So we developed a platform and an architecture focused on indexing it so you just index at once and then could use it for many different purposes. >>And that just kept moving through the years with this very data centric approach to storage, management, backup protection, etc. It was all about the data. I happened to be lucky and said, you know, I think there's something to this thing called NAS and sand and storage networks and all those things. And I also said we have to plan for fur on scale on our solution of a million X. Now it was only off a magnitude of about a thousand on that, but it was the right idea. You know, you had to build something to scale and, and we came in and we wanted to build a company. We didn't want to just flip a company but we thought there is a longterm vision in it and if you take it all the way to the present here it's, it's really, um, it's, it feels really good to see where the company came from. It's a great foundation and now it will propel off this foundation, um, with a similar vision with great modern execution and management. >>Yeah. Al, when we had the chance to talk with you last year at the show in Nashville, it was setting up for that change. So I want to get your view there. There are some things that the company was working on and are being continued, but there's some things that, you know, Bob hammer would not have happened under his regime. So want to get your viewpoint as to the new Convolt, you know, what, what is, what are some of those new things that are moving forward with the company that might not have in the previous days? >>Yeah, that's a good questions. Do I think Mo, a lot of the innovation that you've seen here, um, would have happened maybe not as quickly. Um, we, the company obviously acquired Hedvig. Uh, we were on a very similar path but to do it ourselves. So you had kind of been a modern, we need to get to market quicker with some real pros. I think, um, the, the evolution of redoing sales management essentially was probably the biggest shift that needed to be under a new regime, if you will. Yeah. >>So Miranda, making these transitions can be really tricky from a marketing standpoint. Talk, talk us through a bit, some of the, how do you make sure trusted yet innovative and new that you've accomplished at this show? >>Well, trust it is obviously the most important because the Bob, the brand that Bob and Al built really embodies reliability for what we provide to our customers. I mean that's what gives them the peace of mind to sleep at night. But I'll tell you, Sanjay has been with us for just eight months now, February of 2019 and it's been busy. We've done a lot of things from a points on J transition with Bob and now to his point we've, we've acquired Hedvig, we've introduced this new SAS portfolio and you're exactly right. What we need to do is make sure that the reliability that customers have come to rely on Convolt for translates into what we're doing with the new Convolt and I think we've done a really good job. We've put a lot of muscle behind making sure, particularly with metallic that it was tried, it was trusted, it was beta tested, we got input from customers, partners, industry influencers. We really built it around the customer. So I think the brand that comm brings will translate well into the things that we've done with these, with these new shifts and movements within the company >>on, on that questions too as well. Um, I think Miranda is a good example of somebody that was with the company before a tremendous talent. She's got new opportunities here and she's run with it. So it's kinda that balance of some, uh, understood the fundamentals and the way we're trying to run the business. And she's grasped the new world as well. So, >>and Rob as well, right? Robin in his new, >>yeah, that's another good point. So that was all part of the transitioning here and Sanjay and the team had been very careful on trying to keep that balance. >>Change is really difficult anywhere, right? Dissect to any element of life. And you look at a business that's been very successful, has built a very strong, reliable brand for 20 years. Big leadership changes, not just with Sanjay, but all of the leadership changes. You know, analysts said, all right, you've got to upgrade your Salesforce. We're seeing a lot of movement in the area. You got to enhance your marketing. We're seeing metallic has the new routes to market, new partner focus, so PSI focuses. We're also seeing this expansion in the market, so what folks were saying, you know a year ago come on is answering in a big way and to your point in a fast way that's not easy to do. You've been here nine years since the beginning. Can you give us a little bit of a perspective, Miranda, about some of the things that were announced at the show? >>How excited everybody is, customers, partners, combo folks. How do you now extend the message and the communications from go globally after the show ends? That's an awesome question. I'm really passionate about this. So you know, Monday we announced metallic, we announced a new head of channels and alliances and Mercer Rowe, we had crazy technology innovation announcements with activate, with the acceleration of the integration with Hedvig with the momentum release that we put out today. We're also doing cool stuff with our corporate social responsibility in terms of sponsoring the new business Avengers coalition. That's something that Chris Powell is really championing here at, at the show and also within combo. So we're very excited about that. And then when you add people like yourselves, you know the tech field day folks, because not everybody can be here, right? Not everybody can be at go. So being able to extend the opportunity for, for folks to participate in combo, go through things like the cube through things like tech field day and using our social media tools and just getting all of the good vibes that are here. Because as Al says, this really is an intimate show, but we try to extend that to anybody who wants to follow us, to anybody who wants to be a part of it. And that's something that we've really focused on the last couple of years to make sure that folks who aren't here can, can get an embrace the environment here at Commonweal go. >>It's such an important piece that you're here helping with the transition I talked about. It's important that some of the existing >>get new roles and do responsibility going forward. What's your role going to be and what should we expect to see from you personally? Somebody has got to mow the lawn. >>Yeah. >>But yes, do I, I'll stay on the board. Um, we're talking through that. I think I'll be a very active board, not just the legal side of the equation. Um, try and stay involved with customers and, and strategies and, and even, uh, potential acquisitions, those kinds of things. Um, I'm also wandering off into the university environment. Uh, my Alma mater is a university of Iowa. I'm on the board there and uh, I'm involved in setting up innovation centers and entrepreneurial programs and that kind of thing. Um, I'll keep doing my farming thing and uh, actually have some ideas on that. There's a lot of technology as you guys know, attacking Nat space. So, and like I said, I'll try to keep a lot of things linked back into a combo. >>What Al can have confidence in is that I will keep him busy. So there's that. And then I will also put on the table, we agree to disagree with our college athletic loyalties. So I'm a big kid just because we don't compete really. Right. So I mean, but if I won Kansas wherever to play, then we would just politely disagree. Yeah. Well that's good that you have this agreement in place. I would love to get some anecdotal feedback from you of some of the things that you've heard over the last three days with all this news, all these changes. What are you hearing from customers and partners who you've had relationships with for a very long time? >>I think they're, I think they're all really excited, but, and maybe I'm biased, but they liked the idea that we're trying to not throw out all the old focus on customers, focus on technologies, continue the innovation. I'm pleased that we, Miranda and the team started taking this theme of what we do to a personal level, you know, recovery and those kinds of things. It isn't just the money in the business outages. It's a really a effect on a personal lives. And that resonates. I hear that a lot. Um, I asked our bigger customers and they've loved us for our support, how we take care of them. The, the intimacy of the partnership, you know, and I think they feel pleased that that's staying yet there's lot of modern Emity if that's a good word. I think fokai was what you, I think it's the blend of things and I think that really excites people. >>We've heard that a lot. You guys did a great job with having customers on stage and as a marketer who does customer marketing programs, I think there's nothing more validating than the voice of a customer. But suddenly today that I thought was a pivot on that convo, did well as Sonic healthcare was on main stage. And then he came onto the program and I really liked how he talked about some of the failures that they've been through. You know, we had the NASA talking yesterday, NASA, 60 years young, very infamous, probably for failure is not an option, but it is a very real possibility whether you're talking about space flight or you're talking about data protection and cyber attacks and the rise of that. And it was really, I'd say, refreshing to hear the voice of a customer say, these are the areas in which we failed. This is how come they've helped us recover and how much better and stronger are they? Not just as a company as Sonic healthcare, but even as an individual person responsible for that. That was a really great message that you guys were able to extend to the audience today and we wanted to get that out. >>I loved that as well. I think that was good. I have also back on driving innovation, I always felt one of my biggest jobs was to not punish people that failed. Yeah. I, you know, with the whole engineering team, the bright people in marketing, I, I would be very down on them if they didn't try, but I never wanted them to feel bad about trying and never punish them. >>And one of the things Matthew said on main stage, first of all, I love him. He's great. He's been a longtime CommonWell supporter. I love his sense of humor. He said, you know, combo came to me and said, can you identify, you know, your biggest disaster recovery moment? And he was like, no, because there's so many. Yes. Right? Like there's so many when you're responsible for this. It's just the unpredictability of it is crazy. And so he couldn't identify one, but he had a series of anecdotes that I think really helped the audience identify with and understand this is, these are big time challenges that we're up against today. And hearing his use case and how con ball is helping him solve his heart problems, I think was really cool. You're right. I loved that too. He said, I couldn't name one. There are so many. That's reality, right? As data proliferates, which every industry is experiencing, there's a tremendous amount of opportunity. There's also great risk as technology advances for good. The bad actors also have access to that sort of technology. So his honesty, I thought was, was refreshing, but spot on. And what a great example for other customers to listen to the RA. To your point, I, if I punish people for failure, we're not going to learn from it. >>Yeah, you'll never move forward. >>Miranda. So much that we learn this week at the shows. Some, a lot of branding, a lot of customers, I know some people might be taking a couple of days off, but what should we expect to be seeing from con vault post go this year, >>continue to innovation. We're not letting our foot off the gas at all. Just continuing innovation as as as we integrate with Hedvig continued acceleration with metallic. I mean those guys are aggressive. They were built as a startup within an enterprise company built on Comvalt enterprise foundation. Those guys are often running, they are motivated, they're highly talented, highly skilled and they're going to market with a solution that is targeted at a specific market and those guys are really, really ready to go. So continued innovation with Hedvig integrate, sorry, integration with Hedvig with metallic. I think you're just going to be seeing a lot more from Combalt in the future on the heels of what we consider humbled, proud leadership with the Gartner magic quadrant. You know the one two punch with the Forrester wave. I think that you're just going to be seeing a lot more from Combalt and in terms of how we're really getting out there and aggressive. And that's not to mention Al, you know what we do with our core solutions. I mean today we just announced a bunch of enhancements to the core technology, which is, which is the bread and butter of, of what we do. So we're not letting the foot off the gas to be sure >>the team stay in really, really aggressive too. And the other thing I'd add as a major investor that I'm expecting is sales. Now I'd love to just your, your final thoughts that the culture of Convolt because while there's some acceleration and there's some change, I think some of the fundamentals stay the same. Yeah, it's, it's right to, and again, that's why I feel we're at a good point on this transition process. You alluded to it earlier, but I feel really good about the leadership that's in, they've treated me terrifically. I'm almost almost part of the team. I love that they're, they're trying to leverage off all the assets that were created in his company. Technology, obviously platform architecture, support base, our support capabilities. I, I told Sandy today I wish she really would have nailed the part about, and by the way, support and our capabilities with customers as a huge differentiator and it was part of our original, Stu knows he's heard me forever. Our original DNA, we wanted to focus on two things. Great technology, keep the great technology lead and customer support and satisfaction. So those elements, now you blend that stew with really terrific Salesforce. As Ricardo says, have you guys talk with Ricardo soon? But anyway, the head of sales is hiring great athletes, particularly for the enterprise space. Then you take it with a real terrific marketing organization that's focused, Oh, had modern techniques and analytics on all those things. You know, it's, it's in my opinion, as an investor especially, I'm expecting really good things >>bar's been set well. I can't think of a better way for Sue and me to our coverage owl veranda. Thank you. This has been fantastic. You've got to go. You get a lawn to mow, you've got a vacation to get onto and you need some wordsmithing would focus your rights. You have a flight ticket. They do five hours. Hi guys. Thank you. This has been awesome. Hashtag new comm vault for our guests and I, Lisa Martin, you've been watching the cubes coverage of Convault go and 19 we will see you next time.

>>Live from Denver, Colorado. It's the cube covering com vault go 2019 brought to you by Combolt. >>Welcome back to the cubes coverage of day one of convo go and 19 from Colorado. I'm Lisa Martin with Stu minimum and we have a cube alumni back with us. Arch, not van Venkatraman. You are the research manager for storage and data center for IDC. Welcome back. Thank you. Always a pleasure. Likewise, so here we are. Day one of con BOGO, lots of stuff. Nutrition's I stopped coming out in the last day and a half or so, but also lots of momentum that really kind of the dust kicked up when Sanjay Mirchandani took over the home from Bob hammer just about nine months ago. You've been covering combo for about three years. Just love to get your perspective on the last three years and what you've seen particularly in the last nine months. Yeah, yeah. Interesting. I've been tracking them for three years and they've been slowly making that pivot to the cloud world to changing how they're pricing to, you know, to really break free from that perception that they're very traditional, they're very cumbersome, they're expensive, they're trying to break through that and hiring Sanjay was kind of validation that Hey we are committed to the future and Sanjay comes from this very agile DevOps seed, open sores, containerized property worlds. >>So he, he is new culture and Sandra came in and he started, I think he started making a lot more changes. We saw that their journey to the cloud was a lot more accelerated and they're starting to talk this new language that is attracting developers. So they talk about cloud native technologies. They're talking about database and data as the bottleneck in development life cycle, which is all new music to develop us ears. And then that means you're going to bring in data management, which is a huge issue right to the developer strategy, right to the boardroom strategy. That's where it needs to be because data is actually at the heart of what companies are doing. And we keep talking about speed of fins, speed of development and speed of applications. I think it's time we start talking about speed of intelligence and speed of insights because that's what's going to give companies a competitive difference. >>And that's what Sanjay brought in in the last nine months. And I was tracking the Hedwig acquisition as well and a lot of companies, a lot of people who I spoke to here were extremely excited about what Hedwig brings into the table and there was a lot of interest in what they bring in. So I think Sanjay brought in a new culture to come ball and he cemented that new culture with Hedwig because with Hedwig they acquired that new startup culture as well. So it's really coming together of a lot of new culture and that's going to overpower the old culture and going to bring a lot transformation within. >>So as arch and I, but I'd love to get your insights into how that that changed and you said, right. Do you know Sandra came from puppet? We talked to them earlier today about moving faster and CIC D and all this wonderful things. But how that aligned with customers. We talked to customers that are seven or 10 years working with convolve inside the organization. You know the person that owned the backup and recovery process, you know, how familiar are they with their developer team and how that's coming together in an organization. So is Convolt meeting the customers where they are? Are they skating to the puck? How does that alignment? >>Yeah, yeah, absolutely. It's, it's imperative that come moved and a lot of traditional data protection vendors move because customers are moving as well and they are forced to move because they are seeing lot of onslaught of data. Data's corporate data is growing 50 to 60% every year. That's just business data. So they're grappling with data growth and they're expected to do more with less and data is fragmented everywhere. So they are forced to make that change as well. So they are employing data protection officers, but at the same time they're also employing data scientists and newer data model architects to do new things with data because they are under pressure to deliver that better customer experiences. So companies are going through that change and we, in August we did a research and asked organizations, are you happy with your existing data protection tools and are you going to change it? >>And interestingly, 60% of those who are operating in multicloud environments want to change their data protection environment. And that shows because until now there was this huge power of incumbency, right? I will, I'm okay with this, I'll probably buy the next version of this and try and do iterative improvements. But now companies realize that this data growth and fragmentation and multicloud environment represents a new frontier and they need to move from this thinking that they've had and they're willing to change and work with the newer kind of companies that provide them what they want around unification and simplification. >>Yeah, I think you brought up some great points there. We've found when we talked to customers, they seem to be more open than ever to try something new. I kind of wonder if that's why metallic almost has a separate brand, a separate web website. It is a Convult venture because you know Combalt has incumbency and it has a pedigree. But if I'm trying something new, Convolt might not be the first one that I think of. >>Yeah. So today was the first time I heard about metallic and there is some, I love the branding and there's so much of gloss and shines, I need to get behind the gloss and shine. But I've seen that was one of the busiest places that we have seen today in the exhibition. And that shows commitment to the, it's, it's, it's, it's, they're entering the SAS world and they're talking that cloud likes scalability and it's also more than applications. They're talking about the pricing is a like consumption base, that cloud language and it's going to propel them along the way. And your perspective as customers that you talk to in any industry have so much choice. You're saying, Hey, the customers are recognizing in this multicloud world in which they find themselves operating. We've gotta be able to change our data protection strategy. I imagine things like the rise in cyber attacks or GDPR or the new law in California. >>That's coming are some compelling events. But when customers look at the landscape, and as was saying, they're so much more open to maybe trying new vendors, for example, how does Combalt part, you know, significant part and combat maybe new part with Hedvig and with metallic as a sort of this startup within combo. How did they elevate and differentiate themselves in your opinion, in a competitive landscape? Interesting. Yep. So when you look at startups, they have a lot of agility, but they're not able to bring that enterprise grade skill. Excuse me. And if you look at a lot of traditional vendors, they have that scale and enterprise grade guarantees, but they don't have that agility. But with this initiative, they've done some clever things and brought agility and skill together. That's their differentiator to see no, grab some water, we'll talk for a second. You probably even taught all day. >>That's the hazard, right, of going to these events is your voice, especially with the altitude. But, but as, as we've seen other large incumbents do the same thing. Absolutely. Everyone's pivoting to the same. It is. But also integration of technologies is not easy. Right. And that's sort of the table stakes is how are they, for example, going to integrate Hedvig such that one had bigs installed. ACE has a smooth, seamless transition and this opens up more opportunity for them and vice versa that that Combolt's install base now has more opportunity. Talk to us about what you've seen. They talked a little bit yesterday about some of the integration connections that they've made so far, but that's really key because a lot of companies don't do integrations. Well yeah, there've been some big acquisitions and they do integrations for years and years, right? It's been just 13 days since the acquisition closed. >>So it's still early days, but they need to keep that momentum up and I see a lot of synergy. So bringing storage and data management together is a good idea. But at the same time, I heard Sanjay alluded to it on the stage as well, where they're talking about application and data and moving away from that infrastructure. Right. And that that view is very important because companies need to move from protecting data centers to protecting centers of data. That's what they need to think about. So they need to abstract from infrastructure, but which is why when you look at it all though it's software defined storage. The language that they use is very clever. They're talking about APIs, they're talking about newer workflows, they're talking about changing business processes, they're talking about enabling data, they're talking about controlling data and using it data, using data for insights. >>So they're putting in a lot of newer perspective to this infrastructure view and taking a software defined container defined API defined view, and that's kind of very, very modern. I think that's going to bring a huge amount of difference. So thinking about some of the customers that you've spoken to will say in the last year that are either using Combolt or evaluating combo, some of the positioning that you just talked about to kind of very interesting, but I presume quite strategic with how they're talking about protect, use, manage control data. Are you hear from Comvalt are you hearing and seeing this is what I've been hearing from customers, is there an alignment? Are you hearing from custom what you heard from customers? I'll start over like in the last year, what combat is now delivering and the messaging that they're articulating. Are you now, are you seeing alignment like they're going in the direction that I'm hearing with what customers are wanting. >>He has, the customers are grappling with multicloud data services, so it's not just data protection but they need to get visibility of data across their, all the data sets across the board that they're challenged not just with structured data but growth in unstructured and semi-structured data as well. So they need to look at newer kinds of storage like object storage and all that. So they are grappling with newer kinds of challenges and that's why this new language is going to be hugely useful. And that's why this coming together of storage and data management can actually make a big difference because together they can paint a picture for the organization and tell them these are the challenges you're grappling. You don't need to buying different solutions from different places and buy it and bring it all together. We have deeper level of integration and we can solve it and convert. >>We'll be able to get to the customer at the storage level before they hit the customer, hits the data management problem and then starts hunting for a newer solution. So they're getting in early before the problem actually becomes an operational issue and that the Hey red, they are ready with the solution when the customer gets there. You might, you mentioned data visibility a minute ago and that's critical, right? For organizations that are, whether it's a smaller organization or one that's heavily matrix, if you don't have, and a lot of them don't have visibility into all of the data. Something that you talked about in the very beginning of the interview, that speed of intelligence and speed of insights, it can't take advantage of that. Yeah, yeah. Yes. So companies are investing into a lot of data scientists. But then so, so I was talking to actually three, I was doing a CIO executive dinner on this whole topic about data driven. >>And then so some of organizations, some of the CIS put their hands up and said, Hey, we have actually employed new data scientists. These data engineers and data scientists don't come cheap, right? They're very heavily skilled, talented, talented professionals. So you employ them. And now we're working backwards. Now we are trying to do what we can do with the data models and there's so much problem we are facing. We don't know what data is good data to be analyzed, what data we can delete, what data is cold data that we can send to archives and what do we need to, what are the use cases that we need big data analytics for? So they're working backwards and they're not able to leverage and capitalize on all the resources that they've spent on hiring these kinds of data scientists and data engineers. So I think they need to start that. Organizations need to get a hygiene about their data first and then take the next step around analytics and hiring these kind of data scientists is the first step. Sorry >>are tryna just, I was curious if you could comment on a statement that Sanjay Mirchandani made this morning. He says we need to rethink the kind of the lines and into definitions between primary and secondary storage. What do you think of that statement and where do you think vault ultimately will fit in the broader marketplace? >>You's quite aligned with what I see when I talk to customers as well. So, so companies, data is growing and it's fragmented, but at the same time the lines between primary storage and secondary storage are blurring as well. So the data that's cold today may be hot data tomorrow. So they need to understand, get visibility into data. Just 10% of data is hard data today. So that data needs to sit in the most expensive storage environments. They can leverage it and the rest needs to be, needs to go into tiered, into other colder storage, cheaper alternatives. But at the same time, when you want to access that data, it should not be difficult because now when you push it to a cloud archive your, that's your archive and be damned, right? You're not going to get that data back on in the format you want at the time you want, at the cost you want. So you need to make sure that you invest in storage technologies and you make that data tiering in such a way that when that called data is suddenly becoming warm data or hot data, you need to have access to it instantly in the format you like. Archna thank you for sharing your insights and recommendations and just your view on the industry and combat. We appreciate your time. No problem at all. Thank you very much. First, zoom and a man. I am Lisa Martin and you're watching the cube from combat go 19.

>>Live from Denver, Colorado. It's the cube covering com vault go 2019 brought to you by Combolt. Hey, >>welcome to the cube at Lisa Martin in Colorado at convo go 19 I'm assuming a man and stew and I are pleased to welcome back to the cube and Alon my who hasn't visited us in awhile, but he's kind of a big deal is the CEO of Commonwealth's on Jay Mirchandani. Sanjay, welcome back. >>Thank you Lisa. Good to be a good too. >>So exciting. This is the fourth go. I love the name go and lots of stuff. So you have come onboard to combo in about about nine months ago and man, are you making some changes? You know the analysts said combo, you gotta, you gotta upgrade your sales force, you gotta expand your marketing, you've gotta shift gears and really expand your market share. And we've seen what Combolt is doing in all three of those areas along with some pretty big announcements in the last couple of days. Talk to us about this, this first nine months here. And really maybe even, I would start with the cultural change that you have brought to a company that's been run by the Bob hammer for 20 years >>right now. Firstly, I'm very fortunate to be here because the company is, it has incredible foundation. The bones of the company, if you would, are solid a great balance sheet, um, over 800 patents, no debt, cash on the books, profitable. It's just, you know, and great, great technology wrapped around some amazing people. So when I look at the, when I look at it and you go, this is this, this is an incredible asset. My role really when I came in when I transitioned with Bob and Al for a period of time was really about making sure we didn't break anything, making sure that we kept the momentum, understood the culture, took time to talk to customers, talk to partners, talk to our employees, shareholders and understand, um, what are the focus areas that we needed to go after. And the last nine months has been about, you know, a lot of learning on my part. >>But also a very receptive group of employees and partners saying, you know, we'll give you a chance. Let's get this done, let's see where it goes. So that's where the nine months had been around and it's been a, it's been fabulous. >> So that's actually one of the things I've heard from your team is you've come in loud and clear with the voice of the CIO. Having been a CIO yourself, that's something you want them to focus on. Everybody, we always talk about listening to the customers, but you know, the role of the CIO has changed an awful lot. You know, since you first became a CIO, clouds change everything in a Nicholas CARF said for a while, does it even matter? Right. Um, so you know, Ferguson side a little bit as to how you want to make sure you're delivering for what the CIO is need. >>Not necessarily what, you know, they were saying that they want. No, it's fair. And, and as much as the role of the CIO has evolved, I don't think it's changed fundamentally. They still, you know, the guardians of the data, the, you know, the compliance and everything else and of course more than anything else, the productivity and the competitive edge that businesses need, technology and business, regardless of which business you're in, are interested intrinsically tied. Your delivery of anything you do today is tied to technology. If you, if you want to be future proof. So if anything, the role of the CIO has only been elevated. I'm, I say this playfully, but I do say it. I said, if I wasn't running this great company that I am now, I'd love to be the CIO of a dysfunctional it organization at a large company because there's so much you can do. >>Many of the decisions that we would spend an inordinate amount of time on the infrastructure, the application, how do you bind it, what are the protocols? Which data center, how much, who runs it, which partner? I kind of dissipated if you're not going to the cloud in some form of fashion, come on, right? If you're not building cloud native applications, come on. If you're not using dev ops, come on. So you've got all this time back now where you're not hopefully having conversations that don't matter and you're really go and building new things. So I think it matters. That's great stuff. And absolutely we agree. We've talked many times on the cube. It definitely actually matters more than today. If anything. Not only did they need to be responsive to the business, but oftentimes it can be one of those drivers for innovation in change in the business. >>Um, I love something you said in your keynote, you said data is at the center of everything you do because right. Most CEO's, hopefully infrastructure is something they might have under their purview, but it's not what drives the business. It's the data, it's the application, it's their customers that matters. So to speak a little bit to the role of data has changed a lot. You know, you and I worked for that big storage company where we even didn't talk as much about storage back about data back in the day. Today it's the life blood of the company. It's everything like that. >> And you know that that is one of the reasons I'm at Convolt because for the past 30 years I've been in technology, I've done app side, I've done infrastructure side, I've done a mix of all of those. And the more I think of an dev ops, I've done that. >>The more I think about it. If I were, if I was sitting with a CEO today and having a conversation about what matters in technology, who's maybe a CEO is not a technologist, I would say data matters. I would say the asset of your company is the data. It's gone from something that you used to manage down, compress deduplicate and hope it went away and you wanted to minimize its footprint to something where you want to maximize its value. And those aren't just words. I mean that is what makes great companies, great companies today, the way they use data to their competitive advantage. So this is, this is exactly the mindset where the mindset, the Guppy do to convo because all we do, all we do is help our customers be data ready. As I was saying this morning, that's, I love that term because that kind of encapsulates it for me. So that's, that's where my head's at. >> Yeah. I mean, we've always said that the thing that defines a company that's gone through debt, that digital transformation is that data drives the business. >>It, it absolutely should, but we're, when you talk with customers that have, whether it's a big university, a research university, healthcare organization or whatever type of organization that has multiple departments, so much data that potentially has a tremendous amount of value that they actually aren't managing well or can't get visibility out of. When you say we want to help you be data ready, w what does that mean to them? >>It means a few things. You summed it up perfectly. That's the world, the customer, the chaos that customers could live in because fundamentally, Lisa, if I had over-simplified applications, we're intrinsically to date data that you use for tied intrinsically to the application to build. So if you had an SAP system, your data was very tightly tied to that. If an Oracle ERP system, it was very tight detail yet it'll supply chain system. You were tied to that. And once data side of getting released from the abstracted, from the system that was built on, you've got a little bit of chaos, then you had to figure out who had access, where, how, how are you replicating and how are you backing it up over the policies, your plan compliance. And then it became chaos. And what I say to customers being data ready, saying do you have a strategy and a capability, more importantly to protect, manage, control and use that information in the way you wish to for competitive advantage. >>Just protecting it is like a life insurance policy, controlling, managing and using it as where you get the value out of it. Right? And so as companies become more data driven, this is where we help them. So the whole concept of the show, what we're sort of bringing to market is the fact that we can help our customers be data ready. And some of the technologies we've talked about today lend themselves to exactly that. Alright. So Sanjay, one of the questions many of us had coming into the show is how exactly Hedvig your, your first acquisition was going to play out. You made a comment in your, your opening keynote this morning that we need to rethink primary and secondary storage. So some of us read the tea leaves and be like, well, you know, you're selling an SDS storage, your, you're in the primary storage market as we would've called it before. >>Yes, the lines are blurring. I don't think those there. So I want to give you the chance to let us know where we're going. Years primary and secondary storage as we classified them, we're looking grayer and grayer mean they'll always be primary storage because there's always a certain user use cases for, for high-performance scale up capabilities. But a lot of the stuff was getting murky. You know, is it really primary? Is is it lower end primary, is it secondary and it doesn't, it shouldn't really matter. And with that, would that segmentation game a set of other capabilities like Oh, you know, file block, object cloud, more, more segmentation, more silo and more fragmentation. And I'm a big believer that this is all about software. The magic is in the software. And if you, if you forget for a minute that it's software defined storage as we call it today, but a set of capability's, a universal plane that allows you to truly define how customers get that ubiquity between any infrastructure that they run. >>Okay. Which in turn gives them the abstraction from the data that they bill. Okay. We've just taken a lot of workload and pressure off the customer to figure all that stuff out, keep whole manage. So I wouldn't get, I wouldn't get wrapped up on the whole storage thing as much as I would on the SA on the universal data plane or the data brain as I called it, nicknamed it in the show, you know, earlier as the left and right side one size, the data management, the other sizes, you know, traditional storage management. Yeah. Maybe I was reading too much in this. There's two brains. I think you've, you turn them sideways. They look like clouds too. But uh, yeah. Yeah. Um, partners wonder if you could speak, you know, we're talking about obviously the channel hugely important, we're going to talk to a lot of your team, but from a technology standpoint, you've got a lot of those hardware providers as well as different software companies that are here in the expo hall. >>Does metallic and Hedvig in those, you know, how will that change the relationships? I mean there's one, I've never built a business in my life that wasn't partner centric and partnerships to me is where both sides feel like they won. They went together. And so I've been very clear with our team, our channel, our board, our ecosystem that we're not doing this alone. That's not my intent. And our goal is to work together. Now we have partners in across the spectrum, cloud partners, technology partners like NetApp, HPE, Cisco. We've got ecosystem partners, the up the, the startups that are building new capabilities that we want to be, they want to be part of our ecosystem and vice versa. Traditional channel. Okay. so we've got the whole run of those, of those partnerships and we've been very focused. But we've also being very clear that we're in this for the long haul with them. Hedvig is today sold through channel and will continue to and metallic is built to be only sold through the channel. >>And you guys also, I was looking at some of the strategic changes that you've implemented since you've been here. Leadership changes to the sales organization, but even on the marketing side go to market. You mentioned that the channel opportunities for Hedvig as well as metallic, but also you guys have a new partner programmed, really aimed at going after and cultivating those large global enterprises with your SIS. So in terms of of you know, partner first, it really seems like the strategic directions that you're moving in are really underscoring that. >>Absolutely. Everything we do, every single thing we do is, you know, the question, the reviews we do, the internal inspection we do with the business. The, the way I look at the, the, the go to market conversations as to uh, the, you know, the pipeline is always about which partners involved, who's the partner involved, you know, and on an exception where we don't have a partner involved. My um, my F it's a flag to me going why? Um, no, we're, I don't know if you're speaking with Ricardo today or at some point he'll, he'll, he'll let you know exactly what we're doing there and how we think about it. And then we've just hired Marissa Rowe, I don't know, you know, Mercer and so Mercer's just come on board as our sort of partner lead worldwide. Yup. >>We're going to be talking with him as well. >>It's a cultural shift folks and we're completely committed to it. 100% committed. >>So one of the things that, that Stu and I were chatting about earlier today that you guys talked about in the keynote is in terms of how quickly metallic was conceived, design built really fast. Does that come from kind of a nod to your days at puppet where you are used to much shorter cycles? And how did, how did internally, the Combolt folks kind of react and we're able to get that done so quick. >>They embraced it. And I'll tell you, I'm, people will tell you that I'm used to saying this, this, this thing. I say that competition and time are not our friends. So we have to, we have to get out there before somebody else does. And if you're coming out with something, it's gotta be better than anybody else has. And so we all agreed there was a need for world-class solution, but we also understood that we had to do a differently doing it the way we've always built something probably probably wasn't the best answer. We needed to go shake things up because it's a different audience, a different delivery capability. But the beauty of the whole thing was that we had core technology at vault that was truly multi-tenanted, truly secure, truly scalable, which we had. This was years of, of great IP, which we took and we built on top of. >>And so we ended up focusing on the user experience and the capabilities of a SAS solution, the modern SAS solution as opposed to putting a wrapper of SAS around substandard technology. So in full credit to the team, we do 90 day releases on our core technology today. Right. So yeah, I think, I think that refresh cycle is what customers expect of us. That you know the and, and then that's what we do today. Right. So something, I don't think it's, I'm not giving myself any credit for it. Yeah. And Sanjay actually we had a customer on earlier talking about that cadence release cycle and he said to Combolt's credit, they're hitting it and it makes my life more predictable when the channels yeah. You know, and so they know when to expect something. So we have a 90 day and Tom will talk to you about this when he, when he comes on, how we get our channel ready for it, how are we enabled them, our own support so we give, so we are completely buttoned up and taking advantage of that release cycle. >>All right. Great. Sunday, nine months, you've already made quite a few moves in the test board, making a lot of pieces there from what we hear, you know, this is just the beginning. Give us a little bit going forward though those people watching what does Sanjay's next nine to 12 months, you know, foretold and as much as you think it's a lot of moving parts that we've, we've changed, um, there we're all part of a, of a roadmap that and so that, and I've been very open and public about it. When I came in there was a lot we had to do and I wanted to be really focused about getting this company back to growth and really helping you realize the potential that it had with, with its heritage of great technology, great customer base, great ecosystem. So I laid out a very simple three point plan, simplify, innovate, execute and tell. >>People are tired of me talking about it and giving me proof points that I'm done. I'm going to keep talking about it. And so simplify is everything about how we use the product, the user experience with us and how you engage with us. OK. innovators innovate in everything we do, products, experiences, everything we have to, we have to challenge the status quo and say it's a smarter way of doing it. Metallic is a complete encapsulation of that, of that energy. Okay. And the last is execute. It's all about getting out there and getting it done. Doing what we say and saying what we do. Just get it out there, get it done. And um, and I think the team has been amazing. They've just rallied around it. And if I embraced it, this is what I think this is what they want. So the changes, sorry, just sorry, I didn't mean to cut you off but it, I'll sum it up by saying that, you know, the nine months have been very focused in the direction making. Now it's about really making sure we help the company and how customers realize its true potential because the technology is great. The people are great. We're a good company. People love our technology. They stay with us forever. Because it does what it's supposed to. We just think we have a lot more to offer. Now. >>I know we're only day one at the show. Things did kick off a little bit yesterday with partners. What's some of the feedback that you've heard from those customers? Either those that have been using vault for 10 years or those that are maybe newer to the bandwagon? >>Well, somebody asked me if I had 10 cups of coffee before I went on stage in the sporting, but I think it's a good proxy for what I feel on the show. I feel incredible energy. I think that the customers, the partners, our own people, it's just, there's a buzz and you've been to shows before and some of them are just, you know, some of them have that energy and some of them are flat. Well this one's just full of energy and uh, and it's, it feels like a lot of adrenaline here and this people are excited and um, you know, I'm excited to go walk the floor. >>Well, your competitors are taking notice. There was some interesting digital signage yesterday at the airport. I noticed that that wasn't okay. I didn't, I missed it. Invitation. Highest form of flattery. Sanjay, >>I got the notice that there's, there's a lot of investment that goes into this. Uh, this, this segment of the market. It's been really hot. Um, what, what's your take on all the startups in as well as the, the, the big companies that have been putting a lot of it that it's an important space, right? Um, it's, it's, it's in the top three to five depending on which study you look at data protections back because it's one thing to have data and nothing to know that it is the way you want it. It's also a testimony to the a, it's not an easy space to get into when you're telling your customer that you're protecting them. That's a big word. Okay. I believe that you earn your way there day on day release, on release. And we've done that. I mean the animals the same good things about as in half a years we had customers on stage, you know, and it, customers don't just come up on stage and they, they really believe it. We have a, we had a pretty decent turnout at the partner event yesterday. You know, I think we're, we're in a great space at a great time and we've got 20 years of, of great pedigree that I don't take for granted as much as people sort of go, Oh, you're an old company. I go, Oh, don't mistake pedigree for anything else. You know, we've got some incredible IP over 800 active. >>Yes. >>You were sharing some of those thoughts this morning. I was looking to see where I put them. How are you guys leveraging the data that you have under management to make combos technology even better and to help make some of those strategic, >>it's this deep learning. It gives as much, you know, we applying AI implicitly. I don't want it to be an AI washing my technology for my customers. It's in there. It just works for them and it's my job to make my product better so they get more value out of it as opposed to for them to bolt on something to make my product better. So I don't, I really don't care what other shit about it. What I care about is I'm building that right into, into the intelligence. We have all the data, we know we, our customers use it, how they back it up, what their expectations are, what the SLS are, what their protocols are. We know this stuff and you, you have to, you know, we've been around enough to know this stuff. So now we're taking all of that with technologies like deep learning and machine learning and making the product better. >>So Sunday, one of the toughest things to do out there is have people learn, learn about somebody again for the, for the second time, you know, you only get one chance to make a first impression. So maybe I'd love your insight. You've been on board for nine months, you know, everybody knows Combolt it has a strong pedigree as you said, has a lot of patents. There's the culture there, but anything you've learned in the last nine months that you didn't know from the outside, he was still a pretty good secret. And there's a lot of people that don't know us as long as even though we've been around in the enterprise and and have have achieved a ton, there's still a ton of customers that don't know us and you know in our chops to get it out there. And if you've looked at our digital presence, if you've looked at how we're engaging online, it's a different Convolt. In fact, one of my favorite hashtags that's a, that that's trending at the show is a hashtag new comm vault. Is that right? I like that one. >>As I say, I might have started it, I don't know. But it is, it's an opportunity, right as to said, you know, we all wish sometimes in certain situations we could make a first impression. Again, I think you have that opportunity is you're saying there's, you have I she was saying close to 80% of, I think I read the other day, 75 80% of Commonweal's revenue comes from the fortune 500 you have the big presence with Bleagh global enterprises. This sustainability initiative that you were doing with the U N that Chris talked about. So there's, there's a lot of momentum behind that as well to take and really kind of maybe even leverage the voice of those enterprises to share with the world the benefits that Convolt provides. Like you said, data protection is hot. Again, if you have the data and it's, and you don't have the insight and it's not protected and you can't recover it quickly, then what value >>or used, if you can't use that know, why does it have to be compartmentalized where you say, Oh, that is my archive. Why can't I, why can't I say that? Yes, it is my archive, but I can, I can leverage that data for other things in my business. Okay. And so our product orchestrate allows customers to discovery to do, sorry, activate, not orchestrate to do eDiscovery, to curate information to use it for R and D to have a policy on sensitive governance needs. There's so much we can do with that, with with the data that's just sitting there, that and from different sources that I believe that at some level, protecting and protecting, managing and controlling our almost table stakes. So I'm raising the stakes uses where the magic is. >>All right, raising the stakes. Well, Sanjay, thank you so much for joining Stu and me on the cube today. Can't wait to see where those stakes are going to be. Combo go 2020 hashtag new comm volt hashtag new comm vault. Thanks Lisa. Thanks. Thank you so much. Hashtag new cobalt for Stewman eman and Sanjay Mirchandani and Lisa Martin, you're watching the cube from Cannonball. Go.

>> Hey, welcome back already, Jeffrey. Here with the Cube, we are high top San Francisco in the Salesforce Tower in the newest center offices. It's really beautiful and is part of that. They have their San Francisco innovation hubs, so it's five floors of maker's labs and three D printing and all kinds of test facilities and best practices Innovation theater and in this studio, which is really fun to be at. So we're talking about hybrid cloud in the development of cloud and multi cloud. And, you know, we're, you know, continuing on this path. Not only your customers on this path, but everyone's kind of on this path is the same kind of evolved and transformed. We're excited. Have a couple experts in the field. We got Larry Soccer. He's the global managing director of Intelligent Cloud Infrastructure Service's growth and strategy at a center. Very good to see you again. Great to be here. And the Jay Patel. He's the senior vice president and general manager, cloud provider, software business unit, being where enemies of the people are nice. Well, so, uh so first off, how you like the digs appear >> beautiful place and the fact we're part of the innovation team. Thank you for that. It's so let's just >> dive into it. So a lot of crazy stuff happening in the market place a lot of conversations about hybrid cloud, multi cloud, different cloud, public cloud movement of Back and forth from Cloud. Just wanted. Get your perspective a day. You guys have been in the Middle East for a while. Where are we in this kind of evolution? It still kind of feeling themselves out. Is it? We're kind of past the first inning, so now things are settling down. How do you kind of you. Evolution is a great >> question, and I think that was a really nice job of defining the two definitions. What's hybrid worse is multi and simply put hybrid. We look at hybrid as when you have consistent infrastructure. It's the same infrastructure, regardless of location. Multi is when you have disparate infrastructure. We're using them in a collective. So just from a level setting perspective, the taxonomy starting to get standardized industry starting to recognize hybrid is a reality. It's not a step in the long journey. It is an operating model that's gonna be exists for a long time, so it's no longer about location. It's a lot harder. You operate in a multi cloud and a hybrid cloud world and together, right extension BM would have a unique opportunity. Also, the technology provider Accenture, as a top leader in helping customers figure out where best to land their workload in this hybrid multicolored world, because workloads are driving decisions right and one of the year in this hybrid medical world for many years to come. But >> do I need another layer of abstraction? Cause I probably have some stuff that's in hybrid. I probably have some stuff in multi, right, because those were probably not much in >> the way we talked a lot about this, and Larry and I were >> chatting as well about this. And the reality is, the reason you choose a specific cloud is for those native different share capability. Abstraction should be just enough so you can make were close portable, really use the caper berry natively as possible right, and by fact, that we now with being where have a native VM we're running on every major hyper scaler, right? And on. Prem gives you that flexibility. You want off not having to abstract away the goodness off the cloud while having a common and consistent infrastructure. What tapping into the innovations that the public cloud brings. So it is a evolution of what we've been doing together from a private cloud perspective to extend that beyond the data center to really make it operating model. That's independent location, right? >> Solarium cures your perspective. When you work with customers, how do you help them frame this? I mean, I always feel so sorry for corporate CEOs. I mean, they got >> complexities on the doors are already going on >> like crazy that GDP are now, I think, right, The California regs. That'll probably go national. They have so many things to be worried about. They got to keep up on the latest technology. What's happening in containers away. I thought it was Dr Knight. Tell me it's kubernetes. I mean, it's really tough. So how >> do you help them? Kind of. It's got a shot with the foundation. >> I mean, you look at cloud, you look at infrastructure more broadly. I mean, it's there to serve the applications, and it's the applications that really drive business value. So I think the starting point has to be application lead. So we start off. We have are intelligent. Engineering guys are platform guys. You really come in and look And do you know an application modernisation strategy? So they'll do an assessment. You know, most of our clients, given their scale and complexity, usually have from 520,000 applications, very large estates, and they got to start to freak out. Okay, what's my current application's? You know, you're a lot of times I use the six R's methodology, and they say, OK, what is it that I I'm gonna retire. This I'm no longer needed no longer is business value, or I'm gonna, you know, replace this with sass. Well, you know, Yeah, if I move it to sales force, for example, or service now mattress. Ah, and then they're gonna start to look at their their workloads and say OK, you know, I don't need to re factor reform at this, you know, re hosted. You know, when one and things obviously be Emily has done a fantastic job is allowing you to re hosted using their softer to find a data center in the hyper scale er's environments >> that we called it just, you know, my great and then modernized. But >> the modern eyes can't be missed. I think that's where a lot of times you see clients kind of getting the trap Hammer's gonna migrate and then figure it out. You need to start tohave a modernisation strategy and then because that's ultimately going to dictate your multi and your hybrid cloud approaches, is how they're zaps evolve and, you know, they know the dispositions of those abs to figure out How do they get replaced? What data sets need to be adjacent to each other? So >> right, so a j you know, we were there when when Pat was with Andy and talking about, you know, Veum, Where on AWS. And then, you know, Sanjay has shown up, but everybody else's conferences a Google cloud talking about you know, Veum. Where? On Google Cloud. I'm sure there was a Microsoft show I probably missed. You guys were probably there to know it. It's kind of interesting, right from the outside looking in You guys are not a public cloud per se. And yet you've come up with this great strategy to give customers the options to adopt being We're in a public hot. And then now we're seeing where even the public cloud providers are saying here, stick this box in your data center and Frank, this little it's like a little piece of our cloud of floating around in your data center. So talk about the evolution of the strategy is kind of what you guys are thinking about because you know, you're cleared in a leadership position, making a lot of interesting acquisitions. How are you guys see this evolving? And how are you placing your bets? >> You know, that has been always consistent about this. Annie. Any strategy, whether it's any cloud, was any device, you know, any workload if you will, or application. And as we started to think about it, right, one of the big things be focused on was meeting the customer where he's out on its journey. Depending on the customer, let me simply be trying to figure out looking at the data center all the way to how the drive in digital transformation effort in a partner like Accenture, who has the breadth and depth and something, the vertical expertise and the insight. That's what customers looking for. Help me figure out in my journey. First tell me where, Matt, Where am I going and how I make that happen? And what we've done in a clever way, in many ways is we've created the market. We've demonstrated that VM where's the omen? Consistent infrastructure that you can bet on and leverage the benefits of the private or public cloud. And I You know, I often say hybrids a two way street. Now, which is you're bringing Maur more hybrid Cloud service is on Prem. And where is he? On Premise now the edge. I was talking to the centering folks and they were saying the mitral edge. So you're starting to see the workloads, And I think you said almost 40 plus percent off future workers that are gonna be in the central cloud. >> Yeah, actually, is an interesting stat out there. 20 years 2020 to 70% of data will be produced and processed outside the cloud. So I mean, the the edges about, you know, as we were on the tipping point of, you know, I ot finally taking off beyond, you know, smart meters. You know, we're gonna see a huge amount of data proliferate out there. So, I mean, the lines between public and private income literary output you look at, you know, Anthony, you know, as your staff for ages. So you know, And that's where you know, I think I am where strategy is coming to fruition >> sometime. It's great, >> you know, when you have a point of view and you stick with it >> against a conventional wisdom, suddenly end up together and then all of a sudden everyone's falling to hurt and you're like, This is great, but I >> hit on the point about the vertical ization. Every one of our client wth e different industries have very different has there and to the meeting that you know the customer, you know, where they're on their journey. I mean, if you talk to a pharmaceutical, you know, geekspeak compliance. Big private cloud started to dip their toes into public. You know, you go to minds and they're being very aggressive public. So >> every manufacturing with EJ boat back in >> the back, coming to it really varies by industry. >> And that's, you know, that's a very interesting here. Like if you look at all the ot environment. So the manufacturing we started see a lot of end of life of environment. So what's that? Next generation, you know, of control system's gonna run on >> interesting on the edge >> because and you've brought of networking a couple times where we've been talking it, you know, and as as, ah, potential gate right when I was still in the gates. But we're seeing Maura where we're at a cool event Churchill Club, when they had Xilinx micron and arm talking about, you know, shifting Maur that compute and store on these edge devices ti to accommodate, which you said, you know, how much of that stuff can you do at the adverse is putting in. But what I think is interesting is how are you going to manage that? There is a whole different level of management complexity when now you've got this different level of you're looting and security times many, many thousands of these devices all over the place. >> You might have heard >> recent announcements from being where around the carbon black acquisition right that combined with our work space one and the pulse I ot well, >> I'm now >> giving you a management framework with It's what people for things or devices and that consistency. Security on the client tied with the network security with NSX all the way to the data center, security were signed. A look at what we call intrinsic security. How do we bake and securing the platform and start solving these end to end and have a park. My rec center helped design these next generation application architectures are distributed by design. Where >> do you put a fence? You're you could put a fence around your data center, >> but your APP is using service now. Another SAS service is so hard to talk to an application boundary in the sea security model around that. It's a very interesting time. >> You hear a lot of you hear a >> lot about a partnership around softer to find data center on networking with Bello and NSX. But we're actually been spending a lot of time with the i o. T. Team and really looking at and a lot of our vision, the lines. I mean, you actually looked that they've been work similarly, agent technology with Leo where you know, ultimately the edge computing for io ti is gonna have to be containerized because you can need multiple middleware stacks supporting different vertical applications, right? We're actually you know what we're working with with one mind where we started off doing video analytics for predictive, you know, maintenance on tires for tractors, which are really expensive. The shovels, It's after we started pushing the data stream up it with a video stream up into azure. But the network became a bottleneck looking into fidelity. So we gotta process there. They're not looking autonomous vehicles which need eight megabits low laden C band with, you know, sitting at the the edge. Those two applications will need to co exist. And you know why we may have as your edge running, you know, in a container down, you know, doing the video analytics. If Caterpillar chooses, you know, Green Grass or Jasper that's going to co exist. So you see how the whole container ization that were started seeing the data center push out there on the other side of the pulse of the management of the edge is gonna be very difficult. I >> need a whole new frontier, absolutely >> moving forward. And with five g and telco. And they're trying to provide evaluated service is So what does that mean from an infrastructure perspective. Right? Right, Right. When do you stay on the five g radio network? Worse is jumping on the back line. And when do you move data? Where's his process? On the edge. Those all business decisions that need to be doing to some framework. >> You guys were going, >> we could go on. Go on, go. But I want to Don't fall upon your Segway from containers because containers were such an important part of this story and an enabler to the story. And, you know, you guys been aggressive. Move with hefty Oh, we've had Craig McCloskey, honor. He was still at Google and Dan great guys, but it's kind of funny, right? Cause three years ago, everyone's going to Dr Khan, right? I was like that were about shows that was hot show. Now doctors kind of faded and and kubernetes has really taken off. Why, for people that aren't familiar with kubernetes, they probably here to cocktail parties. If they live in the Bay Area, why's containers such an important enabler? And what's so special about Coburn? 80 specifically. >> Do you wanna go >> on the way? Don't talk about my products. I mean, if you >> look at the world is getting much more dynamics on the, you know, particularly you start to get more digitally to couple applications you started. You know, we've gone from a world where a virtual machine might have been up for months or years. Toe, You know, obviously you have containers that are much more dynamic, allowed to scale quickly, and then they need to be orchestrated. That's essential. Kubernetes does is just really starts to orchestrate that. And as we get more distributed workloads, you need to coordinate them. You need to be able to scale up as you need it for performance, etcetera. So kubernetes an incredible technology that allows you really to optimize, you know, the placement of that. So just like the virtual machine changed, how we compute containers now gives us a much more flexible portable. You know that, you know you can run on anything infrastructure, any location, you know, closer to the data, et cetera. To do that. And I >> think the bold movie >> made is, you know, we finally, after working with customers and partners like century, we have a very comprehensive strategy. We announced Project Enzo, a philosophy in world and Project tansy really focused on three aspects of containers. How do you build applications, which is pivotal in that mansion? People's driven around. How do we run these arm? A robust enterprise class run time. And what if you could take every V sphere SX out there and make it a container platform? Now we have half a million customers. 70 million be EMS, all of sudden that run time. We're continue enabling with the Project Pacific Soviets. Year seven becomes a commonplace for running containers, and I am so that debate of'em czar containers done gone well, one place or just spin up containers and resource is. And then the more important part is How do I manage this? You said, becoming more of a platform not just an orchestration technology, but a platform for how do I manage applications where I deploy them where it makes most sense, right? Have decoupled. My application needs from the resource is, and Coburn is becoming the platform that allows me to port of Lee. I'm the old job Web logic guy, right? >> So this is like distributed Rabb logic job on steroids, running across clouds. Pretty exciting for a middle where guy This is the next generation and the way you just said, >> And two, that's the enabling infrastructure that will allow it to roll into future things like devices. Because now you've got that connection >> with the fabric, and that's working. Becomes a key part of one of the key >> things, and this is gonna be the hard part is optimization. So how do we optimize across particularly performance, but even costs? >> You're rewiring secure, exact unavailability, >> Right? So still, I think my all time favorite business book is Clayton Christians. An innovator's dilemma. And in one of the most important lessons in that book is What are you optimizing four. And by rule, you can't optimize for everything equally you have to you have to rank order. But what I find really interesting in this conversation in where we're going in the complexity of the throughput, the complexity of the size of the data sets the complexity of what am I optimizing for now? Just begs for applied a I or this is not This is not a people problem to solve. This is this >> is gonna be all right. So you look at >> that, you know, kind of opportunity to now apply A I over the top of this thing opens up tremendous opportunity. >> Standardize infrastructural auditory allows you to >> get more metrics that allows you to build models to optimize infrastructure over time. >> And humans >> just can't get their head around me because you do have to optimize across multiple mentions. His performances cost, but then that performances gets compute. It's the network, I mean. In fact, the network's always gonna be the bottlenecks. You look at it even with five G, which is an order of magnitude, more bandwidth from throughput, the network will still lag. I mean, you go back to Moore's Law, right? It's Ah, even though it's extended to 24 months, price performance doubles. The amount of data potentially can kick in and you know exponentially grow on. Networks don't keep pays, so that optimization is constantly going to be tuned. And as we get even with increases in network, we have to keep balancing that right. >> But it's also the business >> optimization beyond the infrastructure optimization. For instance, if you're running a big power generation field of a bunch of turbines, right, you may wanna optimize for maintenance because things were running at some steady state. But maybe there's oil crisis or this or that. Suddenly the price, right? You're like, forget the maintenance. Right now we've got you know, we >> got a radio controlled you start about other >> than a dynamic industry. How do I really time change the behavior, right? Right. And more and more policy driven. Where the infrastructure smart enough to react based on the policy change you made. >> That's the world we >> want to get to. And we're far away from that, right? >> Yeah. I mean, I think so. Ultimately, I think the Cuban honeys controller gets an A I overlay and the operators of the future of tuning the Aye aye engines that optimizing, >> right? Right. And then we run into the whole thing, which we've talked about many times in this building with Dr Room, A child re from a center. Then you got the whole ethics overlay on top of the thing. That's a whole different conversation from their day. So before we wrap kind of just want to give you kind of last thoughts. Um, as you know, customers Aaron, all different stages of their journey. Hopefully, most of them are at least at least off the first square, I would imagine on the monopoly board What does you know, kind of just top level things that you would tell people that they really need just to keep always at the top is they're starting to make these considerations, starting to make these investments starting to move workloads around that they should always have kind of top >> of mind. For me, it's very simple. It's really about focused on the business outcome. Leverage the best resource for the right need and design. Architectures are flexible that give you a choice. You're not locked in and look for strategic partners with this technology partners or service's partners that alive you to guide because the complexities too high the number of choices that too high. You need someone with the breath in depth to give you that platform in which you can operate on. So we want to be the digital kind of the ubiquitous platform. From a software perspective, Neck Centuries wants to be that single partner who can help them guide on the journey. So I think that would be my ask. It's not thinking about who are your strategic partners. What is your architecture and the choices you're making that gave you that flexibility to evolve. Because this is a dynamic market. What should make decisions today? I mean, I'll be the one you need >> six months even. Yeah. And And it's And that that dynamic that dynamics is, um is accelerating if you look at it. I mean, we've all seen change in the industry of decades in the industry, but the rate of change now the pace, you know, things are moving so quickly. >> I mean, little >> respond competitive or business or in our industry regulations, right. You have to be prepared for >> Yeah. Well, gentlemen, thanks for taking a few minutes and ah, great conversation. Clearly, you're in a very good space because it's not getting any less complicated in >> Thank you. Thank you. All right. Thanks, Larry. Ajay, I'm Jeff. You're watching the Cube. >> We are top of San Francisco in the Salesforce Tower at the center Innovation hub. Thanks for watching. We'll see next time. Quick