>> Narrator: TheCUBE's live coverage is made possible by funding from Dell Technologies, creating technologies that drive human progress. (upbeat music intro) (logo background tingles) >> Hi everybody, welcome back to day three of MWC23, my name is Dave Vellante and we're here live at the Theater of Barcelona, Lisa Martin, David Nicholson, John Furrier's in our studio in Palo Alto. Lot of buzz at the show, the Mobile World Daily Today, front page, Netflix chief hits back in fair share row, Greg Peters, the co-CEO of Netflix, talking about how, "Hey, you guys want to tax us, the telcos want to tax us, well, maybe you should help us pay for some of the content. Your margins are higher, you have a monopoly, you know, we're delivering all this value, you're bundling Netflix in, from a lot of ISPs so hold on, you know, pump the brakes on that tax," so that's the big news. Lockheed Martin, FOSS issues, AI guidelines, says, "AI's not going to take over your job anytime soon." Although I would say, your job's going to be AI-powered for the next five years. We're going to talk about data, we've been talking about the disaggregation of the telco stack, part of that stack is a data layer. John Kreisa is here, the CMO of Couchbase, John, you know, we've talked about all week, the disaggregation of the telco stacks, they got, you know, Silicon and operating systems that are, you know, real time OS, highly reliable, you know, compute infrastructure all the way up through a telemetry stack, et cetera. And that's a proprietary block that's really exploding, it's like the big bang, like we saw in the enterprise 20 years ago and we haven't had much discussion about that data layer, sort of that horizontal data layer, that's the market you play in. You know, Couchbase obviously has a lot of telco customers- >> John: That's right. >> We've seen, you know, Snowflake and others launch telco businesses. What are you seeing when you talk to customers at the show? What are they doing with that data layer? >> Yeah, so they're building applications to drive and power unique experiences for their users, but of course, it all starts with where the data is. So they're building mobile applications where they're stretching it out to the edge and you have to move the data to the edge, you have to have that capability to deliver that highly interactive experience to their customers or for their own internal use cases out to that edge, so seeing a lot of that with Couchbase and with our customers in telco. >> So what do the telcos want to do with data? I mean, they've got the telemetry data- >> John: Yeah. >> Now they frequently complain about the over-the-top providers that have used that data, again like Netflix, to identify customer demand for content and they're mopping that up in a big way, you know, certainly Amazon and shopping Google and ads, you know, they're all using that network. But what do the telcos do today and what do they want to do in the future? They're all talking about monetization, how do they monetize that data? >> Yeah, well, by taking that data, there's insight to be had, right? So by usage patterns and what's happening, just as you said, so they can deliver a better experience. It's all about getting that edge, if you will, on their competition and so taking that data, using it in a smart way, gives them that edge to deliver a better service and then grow their business. >> We're seeing a lot of action at the edge and, you know, the edge can be a Home Depot or a Lowe's store, but it also could be the far edge, could be a, you know, an oil drilling, an oil rig, it could be a racetrack, you know, certainly hospitals and certain, you know, situations. So let's think about that edge, where there's maybe not a lot of connectivity, there might be private networks going in, in the future- >> John: That's right. >> Private 5G networks. What's the data flow look like there? Do you guys have any customers doing those types of use cases? >> Yeah, absolutely. >> And what are they doing with the data? >> Yeah, absolutely, we've got customers all across, so telco and transportation, all kinds of service delivery and healthcare, for example, we've got customers who are delivering healthcare out at the edge where they have a remote location, they're able to deliver healthcare, but as you said, there's not always connectivity, so they need to have the applications, need to continue to run and then sync back once they have that connectivity. So it's really having the ability to deliver a service, reliably and then know that that will be synced back to some central server when they have connectivity- >> So the processing might occur where the data- >> Compute at the edge. >> How do you sync back? What is that technology? >> Yeah, so there's, so within, so Couchbase and Couchbase's case, we have an autonomous sync capability that brings it back to the cloud once they get back to whether it's a private network that they want to run over, or if they're doing it over a public, you know, wifi network, once it determines that there's connectivity and, it can be peer-to-peer sync, so different edge apps communicating with each other and then ultimately communicating back to a central server. >> I mean, the other theme here, of course, I call it the software-defined telco, right? But you got to have, you got to run on something, got to have hardware. So you see companies like AWS putting Outposts, out to the edge, Outposts, you know, doesn't really run a lot of database to mind, I mean, it runs RDS, you know, maybe they're going to eventually work with companies like... I mean, you're a partner of AWS- >> John: We are. >> Right? So do you see that kind of cloud infrastructure that's moving to the edge? Do you see that as an opportunity for companies like Couchbase? >> Yeah, we do. We see customers wanting to push more and more of that compute out to the edge and so partnering with AWS gives us that opportunity and we are certified on Outpost and- >> Oh, you are? >> We are, yeah. >> Okay. >> Absolutely. >> When did that, go down? >> That was last year, but probably early last year- >> So I can run Couchbase at the edge, on Outpost? >> Yeah, that's right. >> I mean, you know, Outpost adoption has been slow, we've reported on that, but are you seeing any traction there? Are you seeing any nibbles? >> Starting to see some interest, yeah, absolutely. And again, it has to be for the right use case, but again, for service delivery, things like healthcare and in transportation, you know, they're starting to see where they want to have that compute, be very close to where the actions happen. >> And you can run on, in the data center, right? >> That's right. >> You can run in the cloud, you know, you see HPE with GreenLake, you see Dell with Apex, that's essentially their Outposts. >> Yeah. >> They're saying, "Hey, we're going to take our whole infrastructure and make it as a service." >> Yeah, yeah. >> Right? And so you can participate in those environments- >> We do. >> And then so you've got now, you know, we call it supercloud, you've got the on-prem, you've got the, you can run in the public cloud, you can run at the edge and you want that consistent experience- >> That's right. >> You know, from a data layer- >> That's right. >> So is that really the strategy for a data company is taking or should be taking, that horizontal layer across all those use cases? >> You do need to think holistically about it, because you need to be able to deliver as a, you know, as a provider, wherever the customer wants to be able to consume that application. So you do have to think about any of the public clouds or private networks and all the way to the edge. >> What's different John, about the telco business versus the traditional enterprise? >> Well, I mean, there's scale, I mean, one thing they're dealing with, particularly for end user-facing apps, you're dealing at a very very high scale and the expectation that you're going to deliver a very interactive experience. So I'd say one thing in particular that we are focusing on, is making sure we deliver that highly interactive experience but it's the scale of the number of users and customers that they have, and the expectation that your application's always going to work. >> Speaking of applications, I mean, it seems like that's where the innovation is going to come from. We saw yesterday, GSMA announced, I think eight APIs telco APIs, you know, we were talking on theCUBE, one of the analysts was like, "Eight, that's nothing," you know, "What do these guys know about developers?" But you know, as Daniel Royston said, "Eight's better than zero." >> Right? >> So okay, so we're starting there, but the point being, it's all about the apps, that's where the innovation's going to come from- >> That's right. >> So what are you seeing there, in terms of building on top of the data app? >> Right, well you have to provide, I mean, have to provide the APIs and the access because it is really, the rubber meets the road, with the developers and giving them the ability to create those really rich applications where they want and create the experiences and innovate and change the way that they're giving those experiences. >> Yeah, so what's your relationship with developers at Couchbase? >> John: Yeah. >> I mean, talk about that a little bit- >> Yeah, yeah, so we have a great relationship with developers, something we've been investing more and more in, in terms of things like developer relations teams and community, Couchbase started in open source, continue to be based on open source projects and of course, those are very developer centric. So we provide all the consistent APIs for developers to create those applications, whether it's something on Couchbase Lite, which is our kind of edge-based database, or how they can sync that data back and we actually automate a lot of that syncing which is a very difficult developer task which lends them to one of the developer- >> What I'm trying to figure out is, what's the telco developer look like? Is that a developer that comes from the enterprise and somebody comes from the blockchain world, or AI or, you know, there really doesn't seem to be a lot of developer talk here, but there's a huge opportunity. >> Yeah, yeah. >> And, you know, I feel like, the telcos kind of remind me of, you know, a traditional legacy company trying to get into the developer world, you know, even Oracle, okay, they bought Sun, they got Java, so I guess they have developers, but you know, IBM for years tried with Bluemix, they had to end up buying Red Hat, really, and that gave them the developer community. >> Yep. >> EMC used to have a thing called EMC Code, which was a, you know, good effort, but eh. And then, you know, VMware always trying to do that, but, so as you move up the stack obviously, you have greater developer affinity. Where do you think the telco developer's going to come from? How's that going to evolve? >> Yeah, it's interesting, and I think they're... To kind of get to your first question, I think they're fairly traditional enterprise developers and when we break that down, we look at it in terms of what the developer persona is, are they a front-end developer? Like they're writing that front-end app, they don't care so much about the infrastructure behind or are they a full stack developer and they're really involved in the entire application development lifecycle? Or are they living at the backend and they're really wanting to just focus in on that data layer? So we lend towards all of those different personas and we think about them in terms of the APIs that we create, so that's really what the developers are for telcos is, there's a combination of those front-end and full stack developers and so for them to continue to innovate they need to appeal to those developers and that's technology, like Couchbase, is what helps them do that. >> Yeah and you think about the Apples, you know, the app store model or Apple sort of says, "Okay, here's a developer kit, go create." >> John: Yeah. >> "And then if it's successful, you're going to be successful and we're going to take a vig," okay, good model. >> John: Yeah. >> I think I'm hearing, and maybe I misunderstood this, but I think it was the CEO or chairman of Ericsson on the day one keynotes, was saying, "We are going to monetize the, essentially the telemetry data, you know, through APIs, we're going to charge for that," you know, maybe that's not the best approach, I don't know, I think there's got to be some innovation on top. >> John: Yeah. >> Now maybe some of these greenfield telcos are going to do like, you take like a dish networks, what they're doing, they're really trying to drive development layers. So I think it's like this wild west open, you know, community that's got to be formed and right now it's very unclear to me, do you have any insights there? >> I think it is more, like you said, Wild West, I think there's no emerging standard per se for across those different company types and sort of different pieces of the industry. So consequently, it does need to form some more standards in order to really help it grow and I think you're right, you have to have the right APIs and the right access in order to properly monetize, you have to attract those developers or you're not going to be able to monetize properly. >> Do you think that if, in thinking about your business and you know, you've always sold to telcos, but now it's like there's this transformation going on in telcos, will that become an increasingly larger piece of your business or maybe even a more important piece of your business? Or it's kind of be steady state because it's such a slow moving industry? >> No, it is a big and increasing piece of our business, I think telcos like other enterprises, want to continue to innovate and so they look to, you know, technologies like, Couchbase document database that allows them to have more flexibility and deliver the speed that they need to deliver those kinds of applications. So we see a lot of migration off of traditional legacy infrastructure in order to build that new age interface and new age experience that they want to deliver. >> A lot of buzz in Silicon Valley about open AI and Chat GPT- >> Yeah. >> You know, what's your take on all that? >> Yeah, we're looking at it, I think it's exciting technology, I think there's a lot of applications that are kind of, a little, sort of innovate traditional interfaces, so for example, you can train Chat GPT to create code, sample code for Couchbase, right? You can go and get it to give you that sample app which gets you a headstart or you can actually get it to do a better job of, you know, sorting through your documentation, like Chat GPT can do a better job of helping you get access. So it improves the experience overall for developers, so we're excited about, you know, what the prospect of that is. >> So you're playing around with it, like everybody is- >> Yeah. >> And potentially- >> Looking at use cases- >> Ways tO integrate, yeah. >> Hundred percent. >> So are we. John, thanks for coming on theCUBE. Always great to see you, my friend. >> Great, thanks very much. >> All right, you're welcome. All right, keep it right there, theCUBE will be back live from Barcelona at the theater. SiliconANGLE's continuous coverage of MWC23. Go to siliconangle.com for all the news, theCUBE.net is where all the videos are, keep it right there. (cheerful upbeat music outro)

>>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.

>>Oracle continues to enhance my sequel Heatwave at a very rapid pace. The company is now in its fourth major release since the original announcement in December 2020. 1 of the main criticisms of my sequel, Heatwave, is that it only runs on O. C I. Oracle Cloud Infrastructure and as a lock in to Oracle's Cloud. Oracle recently announced that heat wave is now going to be available in AWS Cloud and it announced its intent to bring my sequel Heatwave to Azure. So my secret heatwave on AWS is a significant TAM expansion move for Oracle because of the momentum AWS Cloud continues to show. And evidently the Heatwave Engineering team has taken the development effort from O. C I. And is bringing that to A W S with a number of enhancements that we're gonna dig into today is senior vice president. My sequel Heatwave at Oracle is back with me on a cube conversation to discuss the latest heatwave news, and we're eager to hear any benchmarks relative to a W S or any others. Nippon has been leading the Heatwave engineering team for over 10 years and there's over 100 and 85 patents and database technology. Welcome back to the show and good to see you. >>Thank you. Very happy to be back. >>Now for those who might not have kept up with the news, uh, to kick things off, give us an overview of my sequel, Heatwave and its evolution. So far, >>so my sequel, Heat Wave, is a fully managed my secret database service offering from Oracle. Traditionally, my secret has been designed and optimised for transaction processing. So customers of my sequel then they had to run analytics or when they had to run machine learning, they would extract the data out of my sequel into some other database for doing. Unlike processing or machine learning processing my sequel, Heat provides all these capabilities built in to a single database service, which is my sequel. He'd fake So customers of my sequel don't need to move the data out with the same database. They can run transaction processing and predicts mixed workloads, machine learning, all with a very, very good performance in very good price performance. Furthermore, one of the design points of heat wave is is a scale out architecture, so the system continues to scale and performed very well, even when customers have very large late assignments. >>So we've seen some interesting moves by Oracle lately. The collaboration with Azure we've we've covered that pretty extensively. What was the impetus here for bringing my sequel Heatwave onto the AWS cloud? What were the drivers that you considered? >>So one of the observations is that a very large percentage of users of my sequel Heatwave, our AWS users who are migrating of Aurora or so already we see that a good percentage of my secret history of customers are migrating from GWS. However, there are some AWS customers who are still not able to migrate the O. C. I to my secret heat wave. And the reason is because of, um, exorbitant cost, which was charges. So in order to migrate the workload from AWS to go see, I digress. Charges are very high fees which becomes prohibitive for the customer or the second example we have seen is that the latency of practising a database which is outside of AWS is very high. So there's a class of customers who would like to get the benefits of my secret heatwave but were unable to do so and with this support of my secret trip inside of AWS, these customers can now get all the grease of the benefits of my secret he trip without having to pay the high fees or without having to suffer with the poorly agency, which is because of the ws architecture. >>Okay, so you're basically meeting the customer's where they are. So was this a straightforward lifted shift from from Oracle Cloud Infrastructure to AWS? >>No, it is not because one of the design girls we have with my sequel, Heatwave is that we want to provide our customers with the best price performance regardless of the cloud. So when we decided to offer my sequel, he headed west. Um, we have optimised my sequel Heatwave on it as well. So one of the things to point out is that this is a service with the data plane control plane and the console are natively running on AWS. And the benefits of doing so is that now we can optimise my sequel Heatwave for the E. W s architecture. In addition to that, we have also announced a bunch of new capabilities as a part of the service which will also be available to the my secret history of customers and our CI, But we just announced them and we're offering them as a part of my secret history of offering on AWS. >>So I just want to make sure I understand that it's not like you just wrapped your stack in a container and stuck it into a W s to be hosted. You're saying you're actually taking advantage of the capabilities of the AWS cloud natively? And I think you've made some other enhancements as well that you're alluding to. Can you maybe, uh, elucidate on those? Sure. >>So for status, um, we have taken the mind sequel Heatwave code and we have optimised for the It was infrastructure with its computer network. And as a result, customers get very good performance and price performance. Uh, with my secret he trade in AWS. That's one performance. Second thing is, we have designed new interactive counsel for the service, which means that customers can now provision there instances with the council. But in addition, they can also manage their schemas. They can. Then court is directly from the council. Autopilot is integrated. The council we have introduced performance monitoring, so a lot of capabilities which we have introduced as a part of the new counsel. The third thing is that we have added a bunch of new security features, uh, expose some of the security features which were part of the My Secret Enterprise edition as a part of the service, which gives customers now a choice of using these features to build more secure applications. And finally, we have extended my secret autopilot for a number of old gpus cases. In the past, my secret autopilot had a lot of capabilities for Benedict, and now we have augmented my secret autopilot to offer capabilities for elderly people. Includes as well. >>But there was something in your press release called Auto thread. Pooling says it provides higher and sustained throughput. High concerns concerns concurrency by determining Apple number of transactions, which should be executed. Uh, what is that all about? The auto thread pool? It seems pretty interesting. How does it affect performance? Can you help us understand that? >>Yes, and this is one of the capabilities of alluding to which we have added in my secret autopilot for transaction processing. So here is the basic idea. If you have a system where there's a large number of old EP transactions coming into it at a high degrees of concurrency in many of the existing systems of my sequel based systems, it can lead to a state where there are few transactions executing, but a bunch of them can get blocked with or a pilot tried pulling. What we basically do is we do workload aware admission control and what this does is it figures out, what's the right scheduling or all of these algorithms, so that either the transactions are executing or as soon as something frees up, they can start executing, so there's no transaction which is blocked. The advantage to the customer of this capability is twofold. A get significantly better throughput compared to service like Aurora at high levels of concurrency. So at high concurrency, for instance, uh, my secret because of this capability Uh oh, thread pulling offers up to 10 times higher compared to Aurora, that's one first benefit better throughput. The second advantage is that the true part of the system never drops, even at high levels of concurrency, whereas in the case of Aurora, the trooper goes up, but then, at high concurrency is, let's say, starting, uh, level of 500 or something. It depends upon the underlying shit they're using the troopers just dropping where it's with my secret heatwave. The truth will never drops. Now, the ramification for the customer is that if the truth is not gonna drop, the user can start off with a small shape, get the performance and be a show that even the workload increases. They will never get a performance, which is worse than what they're getting with lower levels of concurrency. So this let's leads to customers provisioning a shape which is just right for them. And if they need, they can, uh, go with the largest shape. But they don't like, you know, over pay. So those are the two benefits. Better performance and sustain, uh, regardless of the level of concurrency. >>So how do we quantify that? I know you've got some benchmarks. How can you share comparisons with other cloud databases especially interested in in Amazon's own databases are obviously very popular, and and are you publishing those again and get hub, as you have done in the past? Take us through the benchmarks. >>Sure, So benchmarks are important because that gives customers a sense of what performance to expect and what price performance to expect. So we have run a number of benchmarks. And yes, all these benchmarks are available on guitar for customers to take a look at. So we have performance results on all the three castle workloads, ol DB Analytics and Machine Learning. So let's start with the Rdp for Rdp and primarily because of the auto thread pulling feature. We show that for the IPCC for attended dataset at high levels of concurrency, heatwave offers up to 10 times better throughput and this performance is sustained, whereas in the case of Aurora, the performance really drops. So that's the first thing that, uh, tend to alibi. Sorry, 10 gigabytes. B B C c. I can come and see the performance are the throughput is 10 times better than Aurora for analytics. We have done a comparison of my secret heatwave in AWS and compared with Red Ship Snowflake Googled inquiry, we find that the price performance of my secret heatwave compared to read ship is seven times better. So my sequel, Heat Wave in AWS, provides seven times better price performance than red ship. That's a very, uh, interesting results to us. Which means that customers of Red Shift are really going to take the service seriously because they're gonna get seven times better price performance. And this is all running in a W s so compared. >>Okay, carry on. >>And then I was gonna say, compared to like, Snowflake, uh, in AWS offers 10 times better price performance. And compared to Google, ubiquity offers 12 times better price performance. And this is based on a four terabyte p PCH workload. Results are available on guitar, and then the third category is machine learning and for machine learning, uh, for training, the performance of my secret heatwave is 25 times faster compared to that shit. So all the three workloads we have benchmark's results, and all of these scripts are available on YouTube. >>Okay, so you're comparing, uh, my sequel Heatwave on AWS to Red Shift and snowflake on AWS. And you're comparing my sequel Heatwave on a W s too big query. Obviously running on on Google. Um, you know, one of the things Oracle is done in the past when you get the price performance and I've always tried to call fouls you're, like, double your price for running the oracle database. Uh, not Heatwave, but Oracle Database on a W s. And then you'll show how it's it's so much cheaper on on Oracle will be like Okay, come on. But they're not doing that here. You're basically taking my sequel Heatwave on a W s. I presume you're using the same pricing for whatever you see to whatever else you're using. Storage, um, reserved instances. That's apples to apples on A W s. And you have to obviously do some kind of mapping for for Google, for big query. Can you just verify that for me, >>we are being more than fair on two dimensions. The first thing is, when I'm talking about the price performance for analytics, right for, uh, with my secret heat rape, the cost I'm talking about from my secret heat rape is the cost of running transaction processing, analytics and machine learning. So it's a fully loaded cost for the case of my secret heatwave. There has been I'm talking about red ship when I'm talking about Snowflake. I'm just talking about the cost of these databases for running, and it's only it's not, including the source database, which may be more or some other database, right? So that's the first aspect that far, uh, trip. It's the cost for running all three kinds of workloads, whereas for the competition, it's only for running analytics. The second thing is that for these are those services whether it's like shit or snowflakes, That's right. We're talking about one year, fully paid up front cost, right? So that's what most of the customers would pay for. Many of the customers would pay that they will sign a one year contract and pay all the costs ahead of time because they get a discount. So we're using that price and the case of Snowflake. The costs were using is their standard edition of price, not the Enterprise edition price. So yes, uh, more than in this competitive. >>Yeah, I think that's an important point. I saw an analysis by Marx Tamer on Wiki Bond, where he was doing the TCO comparisons. And I mean, if you have to use two separate databases in two separate licences and you have to do et yelling and all the labour associated with that, that that's that's a big deal and you're not even including that aspect in in your comparison. So that's pretty impressive. To what do you attribute that? You know, given that unlike, oh, ci within the AWS cloud, you don't have as much control over the underlying hardware. >>So look hard, but is one aspect. Okay, so there are three things which give us this advantage. The first thing is, uh, we have designed hateful foreign scale out architecture. So we came up with new algorithms we have come up with, like, uh, one of the design points for heat wave is a massively partitioned architecture, which leads to a very high degree of parallelism. So that's a lot of hype. Each were built, So that's the first part. The second thing is that although we don't have control over the hardware, but the second design point for heat wave is that it is optimised for commodity cloud and the commodity infrastructure so we can have another guys, what to say? The computer we get, how much network bandwidth do we get? How much of, like objects to a brand that we get in here? W s. And we have tuned heat for that. That's the second point And the third thing is my secret autopilot, which provides machine learning based automation. So what it does is that has the users workload is running. It learns from it, it improves, uh, various premieres in the system. So the system keeps getting better as you learn more and more questions. And this is the third thing, uh, as a result of which we get a significant edge over the competition. >>Interesting. I mean, look, any I SV can go on any cloud and take advantage of it. And that's, uh I love it. We live in a new world. How about machine learning workloads? What? What did you see there in terms of performance and benchmarks? >>Right. So machine learning. We offer three capabilities training, which is fully automated, running in France and explanations. So one of the things which many of our customers told us coming from the enterprise is that explanations are very important to them because, uh, customers want to know that. Why did the the system, uh, choose a certain prediction? So we offer explanations for all models which have been derailed by. That's the first thing. Now, one of the interesting things about training is that training is usually the most expensive phase of machine learning. So we have spent a lot of time improving the performance of training. So we have a bunch of techniques which we have developed inside of Oracle to improve the training process. For instance, we have, uh, metal and proxy models, which really give us an advantage. We use adaptive sampling. We have, uh, invented in techniques for paralysing the hyper parameter search. So as a result of a lot of this work, our training is about 25 times faster than that ship them health and all the data is, uh, inside the database. All this processing is being done inside the database, so it's much faster. It is inside the database. And I want to point out that there is no additional charge for the history of customers because we're using the same cluster. You're not working in your service. So all of these machine learning capabilities are being offered at no additional charge inside the database and as a performance, which is significantly faster than that, >>are you taking advantage of or is there any, uh, need not need, but any advantage that you can get if two by exploiting things like gravity. John, we've talked about that a little bit in the past. Or trainee. Um, you just mentioned training so custom silicon that AWS is doing, you're taking advantage of that. Do you need to? Can you give us some insight >>there? So there are two things, right? We're always evaluating What are the choices we have from hybrid perspective? Obviously, for us to leverage is right and like all the things you mention about like we have considered them. But there are two things to consider. One is he is a memory system. So he favours a big is the dominant cost. The processor is a person of the cost, but memory is the dominant cost. So what we have evaluated and found is that the current shape which we are using is going to provide our customers with the best price performance. That's the first thing. The second thing is that there are opportunities at times when we can use a specialised processor for vaccinating the world for a bit. But then it becomes a matter of the cost of the customer. Advantage of our current architecture is on the same hardware. Customers are getting very good performance. Very good, energetic performance in a very good machine learning performance. If you will go with the specialised processor, it may. Actually, it's a machine learning, but then it's an additional cost with the customers we need to pay. So we are very sensitive to the customer's request, which is usually to provide very good performance at a very low cost. And we feel is that the current design we have as providing customers very good performance and very good price performance. >>So part of that is architectural. The memory intensive nature of of heat wave. The other is A W s pricing. If AWS pricing were to flip, it might make more sense for you to take advantage of something like like cranium. Okay, great. Thank you. And welcome back to the benchmarks benchmarks. Sometimes they're artificial right there. A car can go from 0 to 60 in two seconds. But I might not be able to experience that level of performance. Do you? Do you have any real world numbers from customers that have used my sequel Heatwave on A W s. And how they look at performance? >>Yes, absolutely so the my Secret service on the AWS. This has been in Vera for, like, since November, right? So we have a lot of customers who have tried the service. And what actually we have found is that many of these customers, um, planning to migrate from Aurora to my secret heat rape. And what they find is that the performance difference is actually much more pronounced than what I was talking about. Because with Aurora, the performance is actually much poorer compared to uh, like what I've talked about. So in some of these cases, the customers found improvement from 60 times, 240 times, right? So he travels 100 for 240 times faster. It was much less expensive. And the third thing, which is you know, a noteworthy is that customers don't need to change their applications. So if you ask the top three reasons why customers are migrating, it's because of this. No change to the application much faster, and it is cheaper. So in some cases, like Johnny Bites, what they found is that the performance of their applications for the complex storeys was about 60 to 90 times faster. Then we had 60 technologies. What they found is that the performance of heat we have compared to Aurora was 100 and 39 times faster. So, yes, we do have many such examples from real workloads from customers who have tried it. And all across what we find is if it offers better performance, lower cost and a single database such that it is compatible with all existing by sequel based applications and workloads. >>Really impressive. The analysts I talked to, they're all gaga over heatwave, and I can see why. Okay, last question. Maybe maybe two and one. Uh, what's next? In terms of new capabilities that customers are going to be able to leverage and any other clouds that you're thinking about? We talked about that upfront, but >>so in terms of the capabilities you have seen, like they have been, you know, non stop attending to the feedback from the customers in reacting to it. And also, we have been in a wedding like organically. So that's something which is gonna continue. So, yes, you can fully expect that people not dressed and continue to in a way and with respect to the other clouds. Yes, we are planning to support my sequel. He tripped on a show, and this is something that will be announced in the near future. Great. >>All right, Thank you. Really appreciate the the overview. Congratulations on the work. Really exciting news that you're moving my sequel Heatwave into other clouds. It's something that we've been expecting for some time. So it's great to see you guys, uh, making that move, and as always, great to have you on the Cube. >>Thank you for the opportunity. >>All right. And thank you for watching this special cube conversation. I'm Dave Volonte, and we'll see you next time.

>> Okay, up next in the Lightning Talk Session is Brian Galligan; Mgr, Security and Operations at Brookfield Properties. Brian, great to see you. Thanks for coming on. >> Thanks for having me, John. >> So unified visibility across extended asset surface area is key these days. You can't secure what you can't see. So tell me more about how you were able to centralize your view of network assets with Armis and what impact that had on your business. >> Yeah, that's been a really key component of ours where we've actually owned multiple companies with them and are always acquiring companies from time to time. So it's always a question. What is actually out there and what do we need to be worried about. So from an inventory perspective it's definitely something that we've been looking into. Armis was a great partner in being able to get us the visibility into a lot of the IoT that we have out in the environment. And then also trying to find what we have and what's actually installed on those devices. What's running, who's talking to who. So that's definitely been a key component with our partnership with Armis. >> You know, we interview a lot of practitioners and companies and one things we found is vulnerability Management programs. There's a lot of gaps. You know, vulnerability management comes across more sometimes just IT devices, but not all assets. How has Armis Vulnerability Management made things better for your business? And what can you see now that you couldn't see before? >> Yeah, again, because we own multiple companies and they actually use different tools for vulnerability management. It's been a challenge to be able to compare apples to apples on when we have vulnerability. When we have risk out there, how do you put a single number to it? How do you prioritize different initiatives across those sectors? And being able to use Armis and have that one score, have that one visibility and also that one platform that you can query across all of those different companies, has been huge because we just haven't had the ability to say are we vulnerable to X, Y and Z across the board in these different companies? >> You know, it's interesting when you have a lot of different assets and companies, as you mentioned. It kind of increases the complexity and yeah we love the enterprise. You solve complexity by more complexity but that's not the playbook anymore. We want simplicity. We want to have a better solution. So when you take into account, the criticality of these businesses as you're integrating in, in real time and the assets within those business operations you got to keep focused on the right solutions. What has Armis done for you that's been correct and right for you guys? >> Yeah, so being able to see the different like be able to actually drill down into the nitty gritty on what devices are connecting to what. Being able to enforce policies that way, I think has been a huge win that we've been able to see from Armis. It's one of those things where we were able to see north-south traffic. No problem with our typical SIM tools, firewall tools and different logging sources but we haven't been able to see anything east-west and that's where we're going to be most vulnerable. That's where we've been actually found. We found some gaps in our coverage from a pen test perspective where we've found that where we don't have that visibility. Armis has allowed us to get into that communication to better fine tune the rules that we have across devices across sectors, across the data center to properties. Properties of the data center and then also to the cloud. >> Yeah, visibility into the assets is huge. But as you're in operations you got to operationalize these tools. I mean, some people sound like they've got a great sales pitch and all sounds like, "Wait a minute, I got to re-configure my entire operations." At the end of the day, you want to have an easy to use, but effective capability. So you're not taxed either personnel or operations. How easy has it been with Armis to implement from an ease of use, simplicity, plug and play? In other words, how quickly did you get to the time to value? Can you share your thoughts? >> This honestly is the biggest value that we've seen in Armis. I think a, a big kudos goes to the professional services group for getting us stood up being able to explain the tool, be able to dig into it and then get us to that time to value. Honestly, we've only scratched the surface on what Armis can give us which is great because they've given us so much already. So definitely taking that model of let's crawl, walk, run with what we're able to do. But the professional services team has given us so much assistance in getting from one collector to now many collectors. And we're in that deployment phase where we're able to gather more data and find those anomalies that are out there. I again, big props to the, the professional services team. >> Yeah, you know one of we'd add an old expression when you know when the whole democratization happened on the web here comes all the people, you know social media and whatnot now with IoT here comes all the devices. Here comes all the things- >> Yeah. >> Things >> More things are being attached to the network. So Armis has this global asset knowledge base that crowd-sources the asset intelligence. How has that been a game changer for you? And were you shocked when you discovered how many assets they were able to discover and what impact did that have for you? >> We have a large wifi footprint for guests, vendors, contractors that are working on site along with our corporate side, which has a lot of devices on it as well. And being able to see what devices are using what services on there and then be able to fingerprint them easily has been huge. I would say one of the best stories that I can tell is actually with a pen test that we ran recently. We were able to determine what the pen test device was and how it was acting anomalous and then fingerprint that device within five minutes opposed to getting on the phone with probably four or five different groups to figure out what is this device? It's not one of our normal devices. It's not one of our normal builds or anything. We were able to find that device within probably three to five minutes with Armis and the fingerprinting capability. >> Yeah, nothing's going to get by you with these port scans or any kind of activity, so to speak, jumping on the wifi. Great stuff. Anything else you'd like to share about Armis while I got you here? >> Yeah, I would say that something recently, we actually have an open position on our team currently. And one of the most exciting things is being able to share our journey that we've had with Armis over the last year, year and a half, and their eyes light up when they hear the capabilities of what Armis can do, what Armis can offer. And you see a little bit of jealousy of, you know, "Hey I really wish my current organization had that." And it's one of those selling tools that you're able to give to security engineers, security analysts saying, "Here's what you're going to have on the team to be able to do your job, right." So that you don't have to worry about necessarily the normal mundane things. You get to actually go do the cool hunting stuff, which Armis allows you to do. >> Well. Brian, thanks for the time here on this Lightning Talk, appreciate your insight. I'm John Furrier with theCUBE the leader in enterprise tech coverage. Up next in the Lightning Talk Session is Alex Schuchman. He's the CISO of Colgate-Palmolive Thanks for watching.

>> Okay, up next in the Lightning Talk Session is Brian Galligan; Mgr, Security and Operations at Brookfield Properties. Brian, great to see you. Thanks for coming on. >> Thanks for having me, John. >> So unified visibility across extended asset surface area is key these days. You can't secure what you can't see. So tell me more about how you were able to centralize your view of network assets with Armis and what impact that had on your business. >> Yeah, that's been a really key component of ours where we've actually owned multiple companies with them and are always acquiring companies from time to time. So it's always a question. What is actually out there and what do we need to be worried about. So from an inventory perspective it's definitely something that we've been looking into. Armis was a great partner in being able to get us the visibility into a lot of the IoT that we have out in the environment. And then also trying to find what we have and what's actually installed on those devices. What's running, who's talking to who. So that's definitely been a key component with our partnership with Armis. >> You know, we interview a lot of practitioners and companies and one things we found is vulnerability Management programs. There's a lot of gaps. You know, vulnerability management comes across more sometimes just IT devices, but not all assets. How has Armis Vulnerability Management made things better for your business? And what can you see now that you couldn't see before? >> Yeah, again, because we own multiple companies and they actually use different tools for vulnerability management. It's been a challenge to be able to compare apples to apples on when we have vulnerability. When we have risk out there, how do you put a single number to it? How do you prioritize different initiatives across those sectors? And being able to use Armis and have that one score, have that one visibility and also that one platform that you can query across all of those different companies, has been huge because we just haven't had the ability to say are we vulnerable to X, Y and Z across the board in these different companies? >> You know, it's interesting when you have a lot of different assets and companies, as you mentioned. It kind of increases the complexity and yeah we love the enterprise. You solve complexity by more complexity but that's not the playbook anymore. We want simplicity. We want to have a better solution. So when you take into account, the criticality of these businesses as you're integrating in, in real time and the assets within those business operations you got to keep focused on the right solutions. What has Armis done for you that's been correct and right for you guys? >> Yeah, so being able to see the different like be able to actually drill down into the nitty gritty on what devices are connecting to what. Being able to enforce policies that way, I think has been a huge win that we've been able to see from Armis. It's one of those things where we were able to see north-south traffic. No problem with our typical SIM tools, firewall tools and different logging sources but we haven't been able to see anything east-west and that's where we're going to be most vulnerable. That's where we've been actually found. We found some gaps in our coverage from a pen test perspective where we've found that where we don't have that visibility. Armis has allowed us to get into that communication to better fine tune the rules that we have across devices across sectors, across the data center to properties. Properties of the data center and then also to the cloud. >> Yeah, visibility into the assets is huge. But as you're in operations you got to operationalize these tools. I mean, some people sound like they've got a great sales pitch and all sounds like, "Wait a minute, I got to re-configure my entire operations." At the end of the day, you want to have an easy to use, but effective capability. So you're not taxed either personnel or operations. How easy has it been with Armis to implement from an ease of use, simplicity, plug and play? In other words, how quickly did you get to the time to value? Can you share your thoughts? >> This honestly is the biggest value that we've seen in Armis. I think a, a big kudos goes to the professional services group for getting us stood up being able to explain the tool, be able to dig into it and then get us to that time to value. Honestly, we've only scratched the surface on what Armis can give us which is great because they've given us so much already. So definitely taking that model of let's crawl, walk, run with what we're able to do. But the professional services team has given us so much assistance in getting from one collector to now many collectors. And we're in that deployment phase where we're able to gather more data and find those anomalies that are out there. I again, big props to the, the professional services team. >> Yeah, you know one of we'd add an old expression when you know when the whole democratization happened on the web here comes all the people, you know social media and whatnot now with IoT here comes all the devices. Here comes all the things- >> Yeah. >> Things >> More things are being attached to the network. So Armis has this global asset knowledge base that crowd-sources the asset intelligence. How has that been a game changer for you? And were you shocked when you discovered how many assets they were able to discover and what impact did that have for you? >> We have a large wifi footprint for guests, vendors, contractors that are working on site along with our corporate side, which has a lot of devices on it as well. And being able to see what devices are using what services on there and then be able to fingerprint them easily has been huge. I would say one of the best stories that I can tell is actually with a pen test that we ran recently. We were able to determine what the pen test device was and how it was acting anomalous and then fingerprint that device within five minutes opposed to getting on the phone with probably four or five different groups to figure out what is this device? It's not one of our normal devices. It's not one of our normal builds or anything. We were able to find that device within probably three to five minutes with Armis and the fingerprinting capability. >> Yeah, nothing's going to get by you with these port scans or any kind of activity, so to speak, jumping on the wifi. Great stuff. Anything else you'd like to share about Armis while I got you here? >> Yeah, I would say that something recently, we actually have an open position on our team currently. And one of the most exciting things is being able to share our journey that we've had with Armis over the last year, year and a half, and their eyes light up when they hear the capabilities of what Armis can do, what Armis can offer. And you see a little bit of jealousy of, you know, "Hey I really wish my current organization had that." And it's one of those selling tools that you're able to give to security engineers, security analysts saying, "Here's what you're going to have on the team to be able to do your job, right." So that you don't have to worry about necessarily the normal mundane things. You get to actually go do the cool hunting stuff, which Armis allows you to do. >> Well. Brian, thanks for the time here on this Lightning Talk, appreciate your insight. I'm John Furrier with theCUBE the leader in enterprise tech coverage. Up next in the Lightning Talk Session is Alex Schuchman. He's the CISO of Colgate-Palmolive Thanks for watching.

>> From theCUBE Studios in Palo Alto and Boston, bringing you data-driven insights from theCUBE and ETR, this is Breaking Analysis with Dave Vellante. >> Despite a mixed bag of earnings reports from tech companies, negative GDP growth this past quarter, and rising inflation, the cloud continues its relentless expandtion on the IT landscape. AWS, Microsoft, and Alphabet of all reported earnings, and when you include Alibaba Cloud in the mix, the Big 4 hyperscalers are on track to generate 167 billion in revenue this year based on our projections. But as we said many times on theCUBE, the definition of cloud is expanding and hybrid environments are becoming the norm at major organizations. We're seeing the largest enterprise tech companies focus on solving for hybrid, and every public cloud company now has a strategy to bring their environments closer to where customers workloads live, at data centers, and at the edge. Hello, and welcome to this week's Wikibon CUBE Insights powered by ETR. In this Breaking Analysis will update you on our latest cloud projections and outlook. We'll share some fresh ETR data and commentary on what's happening in the hybrid zone of cloud. Let's start with the market data for the Big 4 hyperscalers. In this chart, we share our Big 4 cloud share for IaaS and PaaS for 2020, 2021, and the first quarter of 2022, and our estimate for 2022 full year and growth. Remember, only AWS and Alibaba report relatively clean IaaS and PaaS figures, whereas Microsoft and Google, they bundled their cloud infrastructure in with their SaaS numbers. We both firms, however, they do give guidance and we use survey data and other tidbits to create an apples to apples comparison, and that's what we show here. For the quarter, the Big 4 approach to 37 billion in revenue as a group. Azure's growth rate is reported by Microsoft but the absolute revenue is not. Azure growth accelerated sequentially by 49% to just over 13 billion in the quarter by our estimates while AWS's growth moderated, sequentially, but revenue still hit 18.4 billion. Azure, by our estimates, now is more than 2/3 the size of AWS's cloud business. Google and Alibaba are fighting for the bronze medal, but well behind the two leaders. Microsoft's Azure acceleration is quite remarkable for such a large revenue base, but it's not unprecedented as we've seen this pattern before with AWS. Nonetheless, the fact that Azure is growing at the same rate as GCP is quite impressive. Now, a couple of other tidbits of information. Amazon, its stock is getting hammered today because of inflation and slowing growth rates at the top line. But AWS continues to beat Wall Street's expectations. A look at Amazon's operating income this quarter tells the story. Amazon overall had operating income of -3.66 billion and AWS's operating income with 6.5 billion. AWS's operating margin grew sequentially from nearly 30% last quarter to 35.3%. That's an astoundingly profitable figure. This is comparable to insanely profitable companies like Oracle and Microsoft. These are software companies with software marginal economics. Is that level of sustainable? Probably not for AWS, but it's eye opening, nonetheless. ETR survey data shows why these companies are doing so well with customers. This chart shows the net score granularity for the Big 4 cloud players. Net score, remember, measures spending momentum by asking customers, are you adopting new? That's the lime green. Increasing spend by 6% or more, that's the forest green. Flats spend is the gray. Spending dropping by 6% or worse is the light pink. And the red is decommissioning the platform. Subtract the reds from the greens and you get a net score which is shown on the right. Anything, by the way, over 40% we consider highly elevated. Now some key points here. Microsoft includes its entire business in this chart, we are including, ETR is including Microsoft's entire business, not just its cloud. Its Azure-only net score is 67%, higher than even AWS's, and that's huge. Google Cloud, on the other hand, while still elevated is well behind the two leaders. Alibaba's data sample in the ETR survey is small and China has had its foot on the neck of Big Tech for a while so we can't read too much into a net score of 26. But notice the replacements in red across the boards single digits for all and low single digits for the two giants, 1% for Amazon and Azure. Very impressive. Now the other really telling reality check is CapEx spending on cloud. CapEx spend tends to be a pretty good indicator of scale. And Charles Fitzgerald who runs the Platformonomics blog spends a fair amount of his time on this topic and we borrowed this chart from a recent post he did, and then we put in some estimates of our own. It shows CapEx spend over time for five cloud companies, the Big 3 US firms that we just talked about, plus IBM and Oracle. And it's always astounding to me to go back to the pre-cloud era and look at IBM. They were in a great position prior to 2006 to really dominate this notion of as a service and the transition to what is now known as cloud. But they really couldn't get their head out of professional services and their outsourcing business. There was some conflicts there as well. And so, you know, IBM you see is that dark blue or black line and spent significantly more than the others way back when, not anymore. Charles is kind of a snark. He loves to make fun of our super cloud concept even though I'm confident it's evolving and is real. But his point above in this chart is right on, the Big 3 US players spend far more on CapEx than IBM and Oracle. He states that Oracle's uptick in CapEx spend puts them past IBM, but the two of them are battling to distance themselves and differentiate from the X-axis. Funny guy, Charles. In its recent earnings report, Amazon stated that around 40% of its CapEx goes to infrastructure and most of that goes to AWS. It expects CapEx to grow this year and around 50% will go toward infrastructure. So we've superimposed our rough estimate of where AWS lands when you subtract out all of Amazon's warehouses for retail. And once again, Microsoft is notable because unlike Amazon, it doesn't have a zillion warehouses to ship products to consumers. And while Google spending is massive, it's mostly on servers to power its ad network. But there's no question that GCP can leverage that infrastructure and the tech behind it, and it does. And by the way, so can everyone else, by the way, leverage all this CapEx spend. We're going to come back to that and talk about super cloud in a moment. Okay, let's close by looking at the ever-expanding cloud landscape. This chart shows a two-dimensional view of the ETR data for cloud computing. On the vertical-axis is net score or spending momentum, and in the horizontal-axis is pervasiveness in the data set. It's like market share within the survey, if you will. The chart insert shows the data for how the dots are plotted on each axis. The red dotted line at 40%, remember, indicates a highly elevated position with net score and significant spending momentum. And the green arrows show the movement for some companies relative to three months ago. Okay, so Microsoft and AWS, they're kind of circled way up in the right-hand corner, very impressive. Just to reduce the clutter, we're not showing AWS Lambda here and some other highly elevated services which would push up, ticked up AWS's net score but it's still really, really good. As is azure, they're both moving solidly to the right relative to last quarters survey. So gaining presence in the data set and presumably in the market as well. Google is, as we've said, well behind and has much work to do. It was announced this past week that the head of sales at Google Cloud, Rob Enslin, is leaving to join UiPath, so some interesting news there. We've highlighted the hybrid zone. Now to the theme of this Breaking Analysis, the ever-expanding cloud, AWS announced that it's completed the launch of 16 local zones in the US and there are 32 more coming across 26 countries. Local zones basically bring cloud infrastructure to regions where there's a lot of IT that isn't going to move. And for proximity and latency reasons, they have to move closer, move the cloud closer, the cloud operating model if you will, closer to the customers. And there's that CapEx build out showing its head again. Now the reason this hybrid zone becomes interesting is you're seeing the large enterprise players finally go after the hybrid cloud in Earnest. It's almost like the AWS outposts announcement in 2018 was a wake up call to infrastructure players like Dell, HPE, and IBM. It took a while, but Oracle is kind of skipping to its own tune, but they're in that hybrid zone as well. IBM had a really good quarter and the Red Hat acquisition seems to be working to support its hybrid cloud strategy. Now VMware several years ago clean up its fuzzy cloud strategy and partnered up with AWS and everyone else. And you see VMware Cloud on AWS doing well as is VMware Cloud, its on-prem offering. Even though it's somewhat lower on the X-axis, based on that green arrow was showing relative to last quarter. It's moving to the right with a greater presence in the data set so that we see that as a positive sign. Now, Dell and HP are interesting. Both companies are going hard after as a service with APEX and GreenLake, respectively. HPE, based on the survey data from ETR, seems to have a lead in spending momentum while Dell has a larger presence in the market, naturally, as a much bigger company. HPE is climbing up on the X-axis, as is Dell, although, not as quickly. And the point we come back to often is the definition of cloud is in the eye of the customer. AWS can say, "No, no that's not cloud." And the on-prem crowd can say, "Ooh, we have cloud too." It really doesn't matter. What matters is what the customer thinks and which platforms they choose to invest. And I'll close by circling back to the idea of super cloud. You are seeing it evolve and you're going to hear more and more about it. Yeah, maybe not the term, many don't like it. We're going to continue to use it as a metaphor for a layer that leverages the CapEx build, the gift that the hyperscalers are providing the industry. This is a real opportunity for the likes of Dell, HPE, IBM, Cisco, and dozens of other companies providing compute and storage infrastructure, networking, security, database, and other parts of the stack. By hiding the underlying complexity of the cloud, dealing with all the API and primitive muck, creating singular experience across on-prem, across clouds, and out to the edge is a definite need from customers. This is a new battle that's shaping up and it's going to be expensive to build and it require an ecosystem cooperating across this API economy, as some like to call it. It's going to have to do that to make it a reality. Now there's a definite, as I say, customer need for this common experience, and in our view, we're seeing it manifest in pockets today and in strategies and in R&D projects, both within startups and established players. Okay, that's it for today. Thanks to Stephanie Chan who helps research Breaking Analysis topics. Alex Myerson is on production and he also manages the Breaking Analysis podcast. Kristen and Martin and Cheryl Knight get the word out on social. Thanks to all, including Rob Hof, our editor in chief at SiliconANGLE. Remember these episodes are all available as podcast wherever you listen. All you got to do is search Breaking Analysis podcast. Check out ETR website at etr.ai. We publish a full report every week on wikibon.com and siliconangle.com. You can email me directly at david.vellante@siliconangle.com, or DM me @dvellante or comment on our LinkedIn posts. This is Dave Vellante for theCUBE Insights powered by ETR. Have a great week, stay safe, be well and we'll see you next time. (upbeat music)

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 vellante you know we've often said that the next 10 years in cloud computing won't be like the last ten cloud has firmly planted its footprint on the other side of the chasm with the momentum of the entire multi-trillion dollar tech business behind it both sellers and buyers are leaning in by adopting cloud technologies and many are building their own value layers on top of cloud in the coming years we expect innovation will continue to coalesce around the three big u.s clouds plus alibaba in apac with the ecosystem building value on top of the hardware saw tooling provided by the hyperscalers now importantly we don't see this as a race to the bottom rather our expectation is that the large public cloud players will continue to take cost out of their platforms through innovation automation and integration while other cloud providers and the ecosystem including traditional companies that buy it mine opportunities in their respective markets as matt baker of dell is fond of saying this is not a zero sum game welcome to this week's wikibon cube insights powered by etr in this breaking analysis we'll update you on our latest projections in the cloud market we'll share some new etr survey data with some surprising nuggets and drill into this the important cloud database landscape first we want to take a look at what people are talking about in cloud and what's been in the recent news with the exception of alibaba all the large cloud players have reported earnings google continues to focus on growth at the expense of its profitability google reported that it's cloud business which includes applications like google workspace grew 45 percent to five and a half billion dollars but it had an operating loss of 890 billion now since thomas curion joined google to run its cloud business google has increased head count in its cloud business from 25 000 25 000 people now it's up to 40 000 in an effort to catch up to the two leaders but playing catch up is expensive now to put this into perspective let's go back to aws's revenue in q1 2018 when the company did 5.4 billion so almost exactly the same size as google's current total cloud business and aws is growing faster at the time at 49 don't forget google includes in its cloud numbers a big chunk of high margin software aws at the time had an operating profit of 1.4 billion that quarter around 26 of its revenues so it was a highly profitable business about as profitable as cisco's overall business which again is a great business this is what happens when you're number three and didn't get your head out of your ads fast enough now in fairness google still gets high marks on the quality of its technology according to corey quinn of the duck bill group amazon and google cloud are what he called neck and neck with regard to reliability with microsoft azure trailing because of significant disruptions in the past these comments were made last week in a bloomberg article despite some recent high-profile outages on aws not surprisingly a microsoft spokesperson said that the company's cloud offers industry-leading reliability and that gives customers payment credits after some outages thank you turning to microsoft and cloud news microsoft's overall cloud business surpassed 22 billion in the december quarter up 32 percent year on year like google microsoft includes application software and sas offerings in its cloud numbers and gives little nuggets of guidance on its azure infrastructure as a service business by the way we estimate that azure comprises about 45 percent of microsoft's overall cloud business which we think hit a 40 billion run rate last quarter microsoft guided in its earning call that recent declines in the azure growth rates will reverse in q1 and that implies sequential growth for azure and finally it was announced that the ftc not the doj will review microsoft's announced 75 billion acquisition of activision blizzard it appears ftc chair lena khan wants to take this one on herself she of course has been very outspoken about the power of big tech companies and in recent a recent cnbc interview suggested that the u.s government's actions were a meaningful contributor back then to curbing microsoft's power in the 90s i personally found that dubious just ask netscape wordperfect novell lotus and spc the maker of harvard presentation graphics how effective the government was in curbing microsoft power generally my take is that the u s government has had a dismal record regulating tech companies most notably ibm and microsoft and it was market forces company hubris complacency and self-inflicted wounds not government intervention these were far more effective than the government now of course if companies are breaking the law they should be punished but the u.s government hasn't been very productive in its actions and the unintended consequences of regulation could be detrimental to the u.s competitiveness in the race with china but i digress lastly in the news amazon announced earnings thursday and the company's value increased by 191 billion dollars on friday that's a record valuation gain for u.s stocks aws amazon's profit engine grew 40 percent year on year for the quarter it closed the year at 62 billion dollars in revenue and at a 71 billion dollar revenue run rate aws is now larger than ibm which without kindrel is at a 67 billion dollar run rate just for context ibm's revenue in 2011 was 107 billion dollars now there's a conversation going on in the media and social that in order to continue this growth and compete with microsoft that aws has to get into the sas business and offer applications we don't think that's the right strategy for amp from for amazon in the near future rather we see them enabling developers to compete in that business finally amazon disclosed that 48 of its top 50 customers are using graviton 2 instances why is this important because aws is well ahead of the competition in custom silicon chips is and is on a price performance curve that is far better than alternatives especially those based on x86 this is one of the reasons why we think this business is not a race to the bottom aws is being followed by google microsoft and alibaba in terms of developing custom silicon and will continue to drive down their internal cost structures and deliver price performance equal to or better than the historical moore's law curves so that's the recent news for the big u.s cloud providers let's now take a look at how the year ended for the big four hyperscalers and look ahead to next year here's a table we've shown this view before it shows the revenue estimates for worldwide is and paths generated by aws microsoft alibaba and google now remember amazon and alibaba they share clean eye ass figures whereas microsoft and alphabet only give us these nuggets that we have to interpret and we correlate those tidbits with other data that we gather we're one of the few outlets that actually attempts to make these apples to apples comparisons there's a company called synergy research there's another firm that does this but i really can't map to their numbers their gcp figures look far too high and azure appears somewhat overestimated and they do include other stuff like hosted private cloud services but it's another data point that you can use okay back to the table we've slightly adjusted our gcp figures down based on interpreting some of alphabet's statements and other survey data only alibaba has yet to announce earnings so we'll stick to a 2021 market size of about 120 billion dollars that's a 41 growth rate relative to 2020 and we expect that figure to increase by 38 percent to 166 billion in 2022 now we'll discuss this a bit later but these four companies have created an opportunity for the ecosystem to build what we're calling super clouds on top of this infrastructure and we're seeing it happen it was increasingly obvious at aws re invent last year and we feel it will pick up momentum in the coming months and years a little bit more on that later now here's a graphical view of the quarterly revenue shares for these four companies notice that aws has reversed its share erosion and is trending up slightly aws has accelerated its growth rate four quarters in a row now it accounted for 52 percent of the big four hyperscaler revenue last year and that figure was nearly 54 in the fourth quarter azure finished the year with 32 percent of the hyper scale revenue in 2021 which dropped to 30 percent in q4 and you can see gcp and alibaba they're neck and neck fighting for the bronze medal by the way in our recent 2022 predictions post we said google cloud platform would surpass alibaba this year but given the recent trimming of our numbers google's got some work to do for that prediction to be correct okay just to put a bow on the wikibon market data let's look at the quarterly growth rates and you'll see the compression trends there this data tracks quarterly revenue growth rates back to 20 q1 2019 and you can see the steady downward trajectory and the reversal that aws experienced in q1 of last year now remember microsoft guided for sequential growth and azure so that orange line should trend back up and given gcp's much smaller and big go to market investments that we talked about we'd like to see an acceleration there as well the thing about aws is just remarkable that it's able to accelerate growth at a 71 billion run rate business and alibaba you know is a bit more opaque and likely still reeling from the crackdown of the chinese government we're admittedly not as close to the china market but we'll continue to watch from afar as that steep decline in growth rate is somewhat of a concern okay let's get into the survey data from etr and to do so we're going to take some time series views on some of the select cloud platforms that are showing spending momentum in the etr data set you know etr uses a metric we talked about this a lot called net score to measure that spending velocity of products and services netscore basically asks customers are you spending more less or the same on a platform and a vendor and then it subtracts the lesses from the moors and that yields a net score this chart shows net score for five cloud platforms going back to january 2020. note in the table that the table we've inserted inside that chart shows the net score and shared n the latter metric indicates the number of mentions in the data set and all the platforms we've listed here show strong presence in the survey that red dotted line at 40 percent that indicates spending is at an elevated level and you can see azure and aws and vmware cloud on aws as well as gcp are all nicely elevated and bounding off their october figures indicating continued cloud momentum overall but the big surprise in these figures is the steady climb and the steep bounce up from oracle which came in just under the 40 mark now one quarter is not necessarily a trend but going back to january 2020 the oracle peaks keep getting higher and higher so we definitely want to keep watching this now here's a look at some of the other cloud platforms in the etr survey the chart here shows the same time series and we've now brought in some of the big hybrid players notably vmware cloud which is vcf and other on-prem solutions red hat openstack which as we've reported in the past is still popular in telcos who want to build their own cloud we're also starting to see hpe with green lake and dell with apex show up more and ibm which years ago acquired soft layer which was really essentially a bare metal hosting company and over the years ibm cobbled together its own public cloud ibm is now racing after hybrid cloud using red hat openshift as the linchpin to that strategy now what this data tells us first of all these platforms they don't have the same presence in the data set as do the previous players vmware is the one possible exception but other than vmware these players don't have the spending velocity shown in the previous chart and most are below the red line hpe and dell are interesting and notable in that they're transitioning their early private cloud businesses to dell gr sorry hpe green lake and dell apex respectively and finally after years of kind of staring at their respective navels in in cloud and milking their legacy on-prem models they're finally building out cloud-like infrastructure for their customers they're leaning into cloud and marketing it in a more sensible and attractive fashion for customers so we would expect these figures are going to bounce around for a little while for those two as they settle into a groove and we'll watch that closely now ibm is in the process of a complete do-over arvin krishna inherited three generations of leadership with a professional services mindset now in the post gerschner gerstner era both sam palmisano and ginny rometty held on far too long to ibm's service heritage and protected the past from the future they missed the cloud opportunity and they forced the acquisition of red hat to position the company for the hybrid cloud remedy tried to shrink to grow but never got there krishna is moving faster and with the kindred spin is promising mid-single-digit growth which would be a welcome change ibm is a lot of work to do and we would expect its net score figures as well to bounce around as customers transition to the future all right let's take a look at all these different players in context these are all the clouds that we just talked about in a two-dimensional view the vertical axis is net score or spending momentum and the horizontal axis is market share or presence or pervasiveness in the data set a couple of call-outs that we'd like to make here first the data confirms what we've been saying what everybody's been saying aws and microsoft stand alone with a huge presence many tens of billions of dollars in revenue yet they are both well above the 40 line and show spending momentum and they're well ahead of gcp on both dimensions second vmware while much smaller is showing legitimate momentum which correlates to its public statements alibaba the alibaba in this survey really doesn't have enough sample to make hardcore conclusions um you can see hpe and dell and ibm you know similarly they got a little bit more presence in the data set but they clearly have some work to do what you're seeing there is their transitioning their legacy install bases oracle's the big surprise look what oracle was in the january survey and how they've shot up recently now we'll see if this this holds up let's posit some possibilities as to why it really starts with the fact that oracle is the king of mission critical apps now if you haven't seen video on twitter you have to check it out it's it's hilarious we're not going to run the video here but the link will be in our post but i'll give you the short version some really creative person they overlaid a data migration narrative on top of this one tooth guy who speaks in spanish gibberish but the setup is he's a pm he's a he's a a project manager at a bank and aws came into the bank this of course all hypothetical and said we can move all your apps to the cloud in 12 months and the guy says but wait we're running mission critical apps on exadata and aws says there's nothing special about exadata and he starts howling and slapping his knee and laughing and giggling and talking about the 23 year old senior engineer who says we're going to do this with microservices and he could tell he was he was 23 because he was wearing expensive sneakers and what a nightmare they encountered migrating their environment very very very funny video and anyone who's ever gone through a major migration of mission critical systems this is gonna hit home it's funny not funny the point is it's really painful to move off of oracle and oracle for all its haters and its faults is really the best environment for mission critical systems and customers know it so what's happening is oracle's building out the best cloud for oracle database and it has a lot of really profitable customers running on-prem that the company is migrating to oracle cloud infrastructure oci it's a safer bet than ripping it and putting it into somebody else's cloud that doesn't have all the specialized hardware and oracle knowledge because you can get the same integrated exadata hardware and software to run your database in the oracle cloud it's frankly an easier and much more logical migration path for a lot of customers and that's possibly what's happening here not to mention oracle jacks up the license price nearly doubles the license price if you run on other clouds so not only is oracle investing to optimize its cloud infrastructure it spends money on r d we've always talked about that really focused on mission critical applications but it's making it more cost effective by penalizing customers that run oracle elsewhere so this possibly explains why when the gartner magic quadrant for cloud databases comes out it's got oracle so well positioned you can see it there for yourself oracle's position is right there with aws and microsoft and ahead of google on the right-hand side is gartner's critical capabilities ratings for dbms and oracle leads in virtually all of the categories gartner track this is for operational dvms so it's kind of a narrow view it's like the red stack sweet spot now this graph it shows traditional transactions but gartner has oracle ahead of all vendors in stream processing operational intelligence real-time augmented transactions now you know gartner they're like old name framers and i say that lovingly so maybe they're a bit biased and they might be missing some of the emerging opportunities that for example like snowflake is pioneering but it's hard to deny that oracle for its business is making the right moves in cloud by optimizing for the red stack there's little question in our view when it comes to mission critical we think gartner's analysis is correct however there's this other really exciting landscape emerging in cloud data and we don't want it to be a blind spot snowflake calls it the data cloud jamactagani calls it data mesh others are using the term data fabric databricks calls it data lake house so so does oracle by the way and look the terminology is going to evolve and most of the action action that's happening is in the cloud quite frankly and this chart shows a select group of database and data warehouse companies and we've filtered the data for aws azure and gcp customers accounts so how are these accounts or companies that were showing how these vendors were showing doing in aws azure and gcp accounts and to make the cut you had to have a minimum of 50 mentions in the etr survey so unfortunately data bricks didn't make it just not enough presence in the data set quite quite yet but just to give you a sense snowflake is represented in this cut with 131 accounts aws 240 google 108 microsoft 407 huge [ __ ] 117 cloudera 52 just made the cut ibm 92 and oracle 208. again these are shared accounts filtered by customers running aws azure or gcp the chart shows a net score lime green is new ads forest green is spending more gray is flat spending the pink is spending less and the bright red is defection again you subtract the red from the green and you get net score and you can see that snowflake as we reported last week is tops in the data set with a net score in the 80s and virtually no red and even by the way single digit flat spend aws google and microsoft are all prominent in the data set as is [ __ ] and snowflake as i just mentioned and they're all elevated over the 40 mark cloudera yeah what can we say once they were a high flyer they're really not in the news anymore with anything compelling other than they just you know took the company private so maybe they can re-emerge at some point with a stronger story i hope so because as you can see they actually have some new additions and spending momentum in the green just a lot of customers holding steady and a bit too much red but they're in the positive territory at least with uh plus 17 percent unlike ibm and oracle and this is the flip side of the coin ibm they're knee-deep really chest deep in the middle of a major transformation we've said before arvind krishna's strategy and vision is at least achievable prune the portfolio i.e spin out kindrel sell watson health hold serve with the mainframe and deal with those product cycles shift the mix to software and use red hat to win the day in hybrid red hat is working for ibm's growing well into the double digits unfortunately it's not showing up in this chart with little database momentum in aws azure and gcp accounts zero new ads not enough acceleration and spending a big gray middle in nearly a quarter of the base in the red ibm's data and ai business only grew three percent this last quarter and the word database wasn't even mentioned once on ibm's earnings call this has to be a concern as you can see how important database is to aws microsoft google and the momentum it's giving companies like snowflake and [ __ ] and others which brings us to oracle with a net score of minus 12. so how do you square the momentum in oracle cloud spending and the strong ratings and databases from gartner with this picture good question and i would say the following first look at the profile people aren't adding oracle new a large portion of the base 25 is reducing spend by 6 or worse and there's a decent percentage of the base migrating off oracle with a big fat middle that's flat and this accounts for the poor net score overall but what etr doesn't track is how much is being spent rather it's an account based model and oracle is heavily weighted toward big spenders running mission critical applications and databases oracle's non-gaap operating margins are comparable to ibm's gross margins on a percentage basis so a very profitable company with a big license and maintenance in stall basin oracle has focused its r d investments into cloud erp database automation they've got vertical sas and they've got this integrated hardware and software story and this drives differentiation for the company but as you can see in this chart it has a legacy install base that is constantly trying to minimize its license costs okay here's a little bit of different view on the same data we expand the picture with the two dimensions of net score on the y-axis and market share or pervasiveness on the horizontal axis and the table insert is how the data gets plotted y and x respectively not much to add here other than to say the picture continues to look strong for those companies above the 40 line that are focused and their focus and have figured out a clear cloud strategy and aren't necessarily dealing with a big install base the exception of course is is microsoft and the ones below the line definitely have parts of their portfolio which have solid momentum but they're fighting the inertia of a large install base that moves very slowly again microsoft had the advantage of really azure and migrating those customers very quickly okay so let's wrap it up starting with the big three cloud players aws is accelerating and innovating great example is custom silicon with nitro and graviton and other chips that will help the company address concerns related to the race to the bottom it's not a race to zero aws we believe will let its developers go after the sas business and for the most part aws will offer solutions that address large vertical markets think call centers the edge remains a wild card for aws and all the cloud players really aws believes that in the fullness of time all workloads will run in the public cloud now it's hard for us to imagine the tesla autonomous vehicles running in the public cloud but maybe aws will redefine what it means by its cloud microsoft well they're everywhere and they're expanding further now into gaming and the metaverse when he became ceo in 2014 many people said that satya should ditch xbox just as an aside the joke among many oracle employees at the time was that safra katz would buy her kids and her nieces and her nephews and her kids friends everybody xbox game consoles for the holidays because microsoft lost money for everyone that they shipped well nadella has stuck with it and he sees an opportunity to expand through online gaming communities one of his first deals as ceo was minecraft now the acquisition of activision will make microsoft the world's number three gaming company by revenue behind only 10 cent and sony all this will be powered by azure and drive more compute storage ai and tooling now google for its part is battling to stay relevant in the conversation luckily it can afford the massive losses it endures in cloud because the company's advertising business is so profitable don't expect as many have speculated that google is going to bail on cloud that would be a huge mistake as the market is more than large enough for three players which brings us to the rest of the pack cloud ecosystems generally and aws specifically are exploding the idea of super cloud that is a layer of value that spans multiple clouds hides the underlying complexity and brings new value that the cloud players aren't delivering that's starting to bubble to the top and legacy players are staying close to their customers and fighting to keep them spending and it's working dell hpe cisco and smaller predominantly on-plan prem players like pure storage they continue to do pretty well they're just not as sexy as the big cloud players the real interesting activity it's really happening in the ecosystem of companies and firms within industries that are transforming to create their own digital businesses virtually all of them are running a portion of their offerings on the public cloud but often connecting to on-premises workloads and data think goldman sachs making that work and creating a great experience across all environments is a big opportunity and we're seeing it form right before our eyes don't miss it okay that's it for now thanks to my colleague stephanie chan who helped research this week's topics remember these episodes are all available as podcasts wherever you listen just search breaking analysis podcast check out etr's website at etr dot ai and also we publish a full report every week on wikibon.com and siliconangle.com you can get in touch with me email me at david.velante siliconangle.com you can dm me at divalante or comment on my linkedin post this is dave vellante for the cube insights powered by etr have a great week stay safe be well and we'll see you next time [Music] you

>>Welcome to this cube conversation. I'm Dave Nicholson, and this is part of the AWS startup showcase season two. I'm very happy to have with me Webb brown CEO of Qube cost web. Welcome to the program. How are you? I'm doing >>Great. It's great to be here, Dave. Thank you so much for having me really excited for the discussion. >>Good to see you. I guess we saw each other last down in Los Angeles for, for coop con, >>Right? Exactly. Right. Still feeling the energy from that event. Hoping we can be back together in person. Not, not too long from now. >>Yeah. Well I'll second that, well, let, let's get straight to it. Tell us, tell us about Q cost. What do you guys do? And I think just central to that question is what gives you guys the right to exist? What problem are you solving? >>Yeah, I love the question. So first and foremost coupe costs, we provide cost monitoring and cost management solutions for teams running Kubernetes or cloud native workloads. Everything we do is, is built on open source. Our founding team was working on infrastructure monitoring solutions at Google before this. And, and what we saw was as we had several teammates join the Kubernetes effort very early days at Google, we saw teams really struggling even just to, to monitor and understand Kubernetes costs, right? There's lots of complexity with the Kubernetes scheduler and being able to answer the question of what is the cost of an application or what is the cost of, you know, a team department, et cetera. And the workloads that they're deploying was really hard for most teams. If you look at CNCF study from late last year, still today, about two thirds of teams, can't answer where they are spending money. And what we saw when digging in there is that when you can't answer that question, it's really hard to be efficient. And by be efficient, we, we mean get the right balance between cost and performance and reliability. So we help teams in, in these areas and more where, you know, now have thousands of teams using our product. You know, we feel where we're just getting started on our mission as well. >>So when people hear it, when people think of coop costs, they w they naturally associate that with Kubernetes. And they think, well, Kubernetes is open-source wait, isn't that free? So what, so what costs are you tracking? Exactly. >>Yeah. Great question. We would track costs in any environment where you can run Kubernetes. So if that's on-prem, you can bring a custom pricing sheet to monitor, say the cost of your underlying CPU course, you know, GPU's memory, et cetera. If you're running in a cloud environment, we have integrations with Azure, GCP and AWS, where we would be able to reflect all the complexity of, you know, whatever deployment you have, whether you're using a spot and multiple regions where you have complex enterprise discounts are eyes savings plans, you name it, we'd be reflecting it. So it's really about, you know, not just generic prices, it's about getting the right price for your organization. >>So the infrastructure that goes into this calculation can be on premises or off premises in the form of cloud. I heard that, right? >>Yeah, that's exactly right. So all of those environments, we'd give you a visibility into all the resources that your Kubernetes clusters are consuming. Again, that's, you know, nodes, load balancers, every resource that it's directly touching also have the ability for you to pull in external costs, right? So if you have Kubernetes tenants that are using S3 or cloud sequel, or, you know, another external cloud service, we would make that connection for you. And then lastly, if you have shared costs, sometimes even like the cost of a dev ops team, we'd give you the ability to kind of allocate that back to your core infrastructure, which may be used for showback or even charged back across your, your, >>So who are the folks in an organization that are tapping into this, are these, you know, our, our, our, our developers being encouraged to be cognizant of these costs throughout the process, or is this just sort of a CFO on down visibility tool? >>Yeah, it's a great, it's a great question. And what we see is a major transformation here where, you know, kind of shift left from a cost perspective where more and more engineering teams are interested in just being aware or having transparency. So they can build a culture of accountability with costs, right, with the amazing ability to rapidly push to production and iterate, you know, with microservices and Kubernetes, it's hard to have this kind of, you know, just wait for say the finance team to review this at the end of the month or the end of the quarter. We see this increasingly be being viewed in real time by infrastructure teams, by engineering teams. Now finance is still a very important stakeholder and, you know, absolutely has a very important like seat at the table in these conversations. But increasingly these are, again, real time or near real time engineering decisions that are really moving the needle on cost and cost efficiency, overtime and performance as well. >>Now, can you use this to model what costs might be, or is this, or is this, you know, you, you mentioned monitoring in real time, is this only for pulling information as it exists, or could you do, could you use some of the aspects of, of, of your toolset to make a decision, whether something makes more sense to run on your existing infrastructure on premises versus moving into, you know, working in a cloud? Is that something that is designed for or not? >>Great question. So we do have the ability to predict cost cost going forward, based on everything we've learned about your environment, whether you're in multi-cloud hybrid cloud, et cetera. So some really interesting functionality there and a lot more coming later this year, because we do see more and more teams wanting to model the state of the future, right? As you deploy really complex technologies, like say the cluster auto scale or, or HPA in different environments, it can really challenging to do an apples to apples comparison, and we help teams do exactly that. And again, gonna have a lot more interesting announcements here later this year. >>So later that later this year, meaning not in the next few minutes while we're together, >>Nothing new to announce on that front today, but I would say, you know, expect later this quarter for us to have more. >>Okay, that sounds good. Now, now you touched on this a little bit, but I want to hone in on why this is particularly relevant now and moving into the future. You know, we've always tracking costs has always been important, you know, even before the Dawn of cloud, but why is it increasingly important? And, and, you know, there are, there are alternatives for cost tracking legacy alternatives that are out there. So talk about why it's particularly relevant now and tell us what your super power is. You know, what's the, all right. All right. >>Secrets, >>Secret sauce is something you can't share super power. You can talk about >>Absolutely >>NDA. So yes, >>Your superpower. Yeah. Great questions. So for support, just to, to, to touch on, what's fundamentally changing to make a company like ours, you know, impactful or relevant. There's really three things here first and foremost is the new abstractions or complexities that come with Kubernetes, right. Super powerful, but from a cost standpoint, make it considerably harder to accurately track costs. And the big transformation here is, you know, with Kubernetes, you can, at any given moment have 50 applications running on a single node or a single VM, you can fast forward five minutes and there could be 50 entirely new applications, right? So just assigning that VM or, you know, tagging that VM back to an application or team or department really is not relevant in those places. So just the new complexity related to costs makes this problem harder for teams. Second is what we touch on. >>Just again, the power of Cooney. Kubernetes is the ability to allow distributed engineering teams to work on many microservices concurrently. So you're no longer in a lot of ways managing this problem where they centralized kind of single point of decision-making. Oftentimes these decisions are distributed across not only your infrastructure team, but your engineering team. So just the way these decisions and, you know, innovation is happening is changing how you manage these. And lastly, it's just scale, right? The, the cloud and, you know, Kubernetes continue to be incredibly successful. You know, where as goop costs now managing billions of dollars as these numbers get bigger and bigger just becomes more of a business focus and business critical issue. So those are the, you know, the three kind of underlying themes that are changing. When I talk about what we do, that makes us special. It's really this like foundational layer of visibility that we build. >>And what we can do is in real time with a very high degree of accuracy at the largest Kubernetes clusters in the world, give you visibility at any dimension. And so from there, you can do things like have real-time monitoring. You can have real-time insights, you can allow automation to make decisions on these, you know, inputs or data feeds. You can set alerts, you can set recurring reports. All of these things are made possible because of, you know, the, the, I would say really hard work that we've done to, again, give this real-time visibility with a high degree of accuracy at, at crazy scale. >>So if we were to play little make-believe for a moment, pretend like I'm a skeptical sitting on the fence. Not sure if I want to go down this path kind of person. And I say, you know what, web, I think I have a really good handle on all of my costs so far. What would you hit me with as, as, as an example of something that people really didn't expect until they, until they were running coup costs and they had actually had that visibility, what are some of the things that people are surprised by? >>Yeah. Great question. There'd be a number, number one. I'd have, you know, one data point I want to get from you, which is, you know, for your organization or for all of your clusters, what is your cost efficiency? Can you answer that with a high degree of accuracy and by cost efficiency? >>And the answer is now. So tell me, tell me, tell me how to sign up for coupons. >>Yeah. And so the answer, the answer there is you can go get our community version, you know, you can be up and running in minutes, you don't have to share any data, right? Like it is, you know, simply a helmet install, but cost efficiency is this notion of, of every dollar that you are spending on provision resources. What percentage of those dollars are you actually utilizing? And we have, you know, we, we now have, you know, thousands of teams using our product and we've worked with, you know, hundreds of them really closely, you know, this is, you know, that's not the entire market, but in our large sample sizes, we regularly see teams start in the low 20% cost efficiency, meaning that approximately 80% is quote waste time and time. Again, we see teams just be shocked by this number. And again, most of it is not because they were measuring it and accurately or anything like that. Most teams again today still just don't have that visibility until they start working with this. >>So is that, is that sort of the, I in my house household, certain members seem to only believe that there is one position for a light switch, and that would be the on position. Is there, is this a bit of a parallel where, where folks are, are spinning up resources and then just out of sight, out of mind, maybe not spinning them down when not needed. Yeah. >>Yeah. It's, it's, that's definitely one class of the challenges I would say, you know, so today, if you look at our product, we have 14 different insights across like different dimensions of your infrastructure one, or, or I would say several of those relate to exactly what you just described, which is you spin up a VM, you spend a bit load balancer, you spin up an external IP address. You're using it. You're not paying for it. Another class is this notion of, again, I don't have an understanding of what my resources cost. I also don't have a great sense for how much my microservice or application will need. So I'm just going to turn on all the lights, which is, or I'm going to drastically over provision again, I don't know the cost, so I'm just going to kind of set it and forget it. And if my application is performing, you know, then you know, we're doing well here. Again, with this visibility, you can get much more specific, much more accurate, much more actionable with making that trade off, you know, again, down to the individual pod workload, you know, deployment, et cetera. >>So we've, we've touched on this a bit peripherally, but give me an example. You know, you, you run into someone who happens to be a happy user of coop cost. What's the dream story that you love to hear from them about what life was before was before coop costs and what life was like after? >>Yeah, there's a lot, a lot of different dimensions there. You know, one, one is, you know, working with an infrastructure team that, that used to get asked these questions a lot about, you know, why does this cost so much, or why are we spending this and Kubernetes or, or wire expenses growing the rate that they are, you know, like when this, when this works, you know, engineering teams or infrastructure teams, aren't getting asked those questions, right? The tool could cost itself is getting asked that and answering that. So I think one is infrastructure teams, not fielding those types of questions as much. Secondly, is just, you know, more and more teams rolling this out throughout their organization. And ultimately just getting, building a culture of awareness, like ownership, accountability. And then, you know, we just increasingly are seeing teams, you know, find this right balance between cost and performance again. So, you know, in certain cases, improving performance, when are resource bottlenecks in places and other places, you know, reducing costs, you know, by 10 plus million dollars, ultimately at the end of the day, we like to see just teams being more comfortable running their workloads in Kubernetes, right? That is the ultimate sign of success is just an organization, feels comfortable with how they're deploying, how they're managing, how they're spending in Kubernetes. Again, whether that be, you know, on-prem or transitioning from on-prem to a cloud in multiple clouds, et cetera. >>So we're talking to you today as part of the second season of the AWS startup showcase. What's, what's the relationship there with, with AWS? >>So it is the, the largest platform for coop costs being run today. So I believe, you know, at this point, at least a thousand different organizations running our product on AWS hosted clusters, whether they're, you know, ETS or, or self-managed, but you know, a growing number of those on, on EKS. And, you know, we've just, you know, absolutely loved working with the team across, I think at this point, you know, six or seven different groups from marketplace to their containers team, you know, obviously, you know, ETS and others, and just very much see them continuing to push the boundaries on what's possible from a scale and, you know, ease of use and, you know, just breadth of, of offering to this market. >>Well, we really look forward to having you back and hearing about some of these announcements, things that are, that are coming down the line. So we'll definitely have to touch base in the future, but just one, one final, more general question for you, where do you see Kubernetes in general going in 2022? Is it sort of a linear growth? Is there some, is there an inflection point that we see, you know, a good percentage of software that's running enterprises right now is already in that open source category, but what are your thoughts on Kubernetes in 2022? >>Yeah, I think, you know, the one word is everywhere is where I see Kubernetes in 2022, like very deep in the like large and really complex enterprises. Right. So I think you'll see just, you know, major bets there. And I think you'll continue to see more engineers adopted. And I think you'll also continue to see, you know, more and more flavors of it, right? So, you know, some teams find that running Kubernetes anymore serverless fashion is, is right for them. Others find that, you know, having full control, you know, at every part of the stack, including running their own autoscaler for example is really powerful. So I think just, you know, you'll see more and more options. And again, I think teams increasingly adopting the right, you know, abstraction level on top of Kubernetes that works for their workloads and their organizations >>Sounds good. We'll we'll, we'll come back in 2023 and we'll check and see how that, how that all panned out. Well, it's been great talking to you today as part of the startup showcase. Really appreciate it. Great to see you again. It's right about the time where I can still tell you happy new year, because we're still, we're still in January here. Hope you have a great 2022 with that from me, Dave Nicholson, part of the cube part of AWS startup showcase season two, I'd like to thank everyone for joining and stay with us for the best in hybrid tech coverage.

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 vellante last week's aws re invent brought into focus the degree to which cloud computing generally and aws specifically have impacted the technology landscape from making infrastructure orders of magnitude simpler to deploy to accelerating the pace of innovation to the formation of the world's most active and vibrant infrastructure ecosystem it's clear that aws has been the number one force for change in the technology industry in the last decade now going forward we see three high-level contributors from aws that will drive the next 10 years of innovation including one the degree to which data will play a defining role in determining winners and losers two the knowledge assimilation effect of aws's cultural processes such as two pizza teams customer obsession and working backwards and three the rise of super clouds that is clouds that run on top of hyperscale infrastructure that focus not only on i.t transformation but deeper business integration and digital transformation of entire industries hello everyone and welcome to this week's wikibon cube insights powered by etr in this breaking analysis we'll review some of the takeaways from the 10th annual aws re invent conference and focus on how we see the rise of super clouds impacting the future of virtually all industries one of the most poignant moments for me was a conversation with steve mullaney at aw aws re invent he's the ceo of networking company aviatrix now just before we went on the cube nick sterile one of aviatrix's vcs looked up at steve and said it's happening now before i explain what that means this was the most important hybrid event of the year you know no one really knew what the crowd would be like but well over twenty 000 people came to reinvent and i'd say at least 25 to 26 000 people attended the expo and probably another 10 000 or more came without badges to have meetings and side meetings and do networking off the expo floor so let's call it somewhere between thirty to forty thousand people physically attended the reinvent and another two hundred thousand or more online so huge event now what nick sterile meant by its happening was the next era of cloud innovation is upon us and it's happening in earnest the cloud is expanding out to the edge aws is bringing its operating model its apis its primitives and services to more and more locations yes data and machine learning are critical we talk about that all the time but the ecosystem flywheel was so evident at this year's re invent more so than any other re invent partners were charged up you know there wasn't nearly as much chatter about aws competing with them rather there was much more excitement around the value that partners are creating on top of aws's massive platform now despite aggressive marketing from competitive hyperscalers other cloud providers and as a service or on-prem slash hybrid offerings aws lead appears to be accelerating a notable example is aws's efforts around custom silicon far more companies especially isvs are tapping into aws's silicon advancements we saw the announcement of graviton 3 and new chips for training and inference and as we've reported extensively aws is now on a curve a silicon curve that will outpace x86 vis-a-vis performance price performance cost power consumption and speed of innovation and its nitro platform is giving aws and its partners the greatest degree of optionality in the industry from cpus gpus intel amd and nvidia and very importantly arm-based custom silicon springing from aws's acquisition of annapurna aws started its custom silicon journey in 2008 and is and it has invested massive resources into this effort other hyperscalers notably microsoft google and alibaba which have the scale economics to justify such custom silicon efforts are just recently announcing initiatives in this regard others who don't have the scale will be relying on third-party silicon providers a perfectly reasonable strategy but because aws has control of the entire stack we believe it has a strategic advantage in this respect silicon especially is a domain where to quote andy jassy there is no compression algorithm for experience b on the curve matters a lot and the biggest story in my view this past week was the rise of the super clouds in his 2020 book with steve hamm frank slootman laid out the case for the rise of data cloud a title which i've conveniently stolen for this breaking analysis rise of the super cloud thank you frank in his book slootman made a case for companies to put data at the center of their organizations rather than organizing just around people for example the idea is to create data networks while people of course are critical organizing around data and enabling people to access and share data will lead to the democracy democratization of data and network effects will kick in this was essentially metcalfe's law for data bob metcalf was the inventor of ethernet ethernet he put forth that premise when we we both worked or the premise when we both worked for pat mcgovern at idg that the value of a network is proportional to the square of the number of its users or nodes on the network thought of another way the first connection isn't so valuable but the billionth connection is really valuable slootman's law if i may says the more people that have access to the data governed of course and the more data connections that can be shared or create sharing the more value will be realized from that data exponential value in fact okay but what is a super cloud super cloud is an architecture that taps the underlying services and primitives of hyperscale clouds to deliver incremental value above and beyond what's available from the public cloud provider a super cloud delivers capabilities through software consumed as services and can run on a single hyperscale cloud or span multiple clouds in fact to the degree that a super cloud can span multiple clouds and even on-premises workloads and hide the underlying complexity of the infrastructure supporting this work the more adoption and the more value will be realized now we've listed some examples of what we consider to be super clouds in the making snowflake is an example we use frequently frequently building a data cloud that spans multiple clouds and supports distributed data but governs that data centrally somewhat consistent with the data mesh approach that we've been talking about for quite some time goldman sachs announced at re invent this year a new data management cloud the goldman sachs financial cloud for data with amazon web services we're going to come back to that later nasdaq ceo adina friedman spoke at the day one keynote with adam silipsky of course the new ceo of aws and talked about the super cloud they're building they didn't use that term that's our term dish networks is building a super cloud to power 5g wireless networks united airlines is really in my view they're porting applications to aws as part of its digital transformation but eventually it will start building out a super cloud travel platform what was most significant about the united effort is the best practices they're borrowing from aws like small teams and moving fast but many others that we've listed here are on a super cloud journey just some of the folks we talked to at reinvent that are building clouds on top of clouds that are shown here cohesity building out a data management cloud focused on data protection and governance hashicorp announced its ipo at a 13 billion valuation building an it automation super cloud data bricks chaos search z-scaler z-scaler is building a security super cloud and many others that we spoke with at the event now we want to take a moment to talk about castles in the cloud it's a premise put forth by jerry chen and the team at greylock it's a really important piece of work that is building out a data set and categorizing the various cloud services to better understand where the cloud giants are investing where startups can participate and how companies can play in the castles that are being built that have been built by the hyperscalers and how they can cross the moats that have been dug and where innovation opportunities exist for other companies now frequently i'm challenged about our statements that there really are only four hyperscalers that exist in the world today aws microsoft google and alibaba while we recognize that companies like oracle have done a really excellent job of improving their clouds we don't consider companies like oracle ibm and other managed service providers as hyperscalers and one of the main data points that we use to defend our thinking is capex investment this was a point that was made in castles in the cloud there are many others that we look at elder kpi size of ecosystem partner acceleration enablement for partners feature sets etc but capex is a big one here's a chart from platform nomics a firm that is obsessed with cl with capex showing annual capex spend for five cloud companies amazon google microsoft ibm and oracle this data goes through 2019 it's annual spend and we've superimposed the direction for each of these companies amazon spent more than 40 billion dollars on capex in 2020 and will spend more than 50 billion this year sure there are some warehouses for the amazon retail business in there and there's other capital expenses in these numbers but the vast majority spent on building out its cloud infrastructure same with google and microsoft now oracle is at least increasing its cap x it's going to spend about 4 billion but it's de minimis compared to the cloud giants and ibm is headed in the other direction it's choosing to invest for instance 34 billion dollars in acquiring red hat instead of putting its capital into a cloud infrastructure look that's a very reasonable strategy but it underscores the gap okay another metric we look at is i as revenue here's an updated chart that we showed last month in our cloud update which at the time excluded alibaba's most recent quarter results so we've updated that very slight change it wasn't really material so you see the four hyperscalers and by the way they invested more than a hundred billion dollars in capex last year it's gonna be larger this year they'll collectively generate more than 120 billion dollars in revenue this year and they're growing at 41 collectively that is remarkable for such a large base of revenue and for aws the rate of revenue growth is accelerating it's the only hyperscaler that can say that that's unreal at their size i mean they're going to do more than 60 billion dollars in revenue this year okay so that's why we say there are only four hyperscalers but so what there are so many opportunities to build on top of the infrastructure that the three u.s giants especially are building as folks are really cautious about china at the moment so let's take a look at what some of the companies that we've been following are doing in the super cloud arena if you will this chart shows some etr data plotting net score or spending momentum on the vertical axis and market share or presence in the etr data set on the horizontal axis most every name on the chart is building some type of super cloud but let me start as we often do calling out aws and azure i guess they're already super clouds but they're not building necessarily on top of of of other people's clouds and there are a little bit you know microsoft does some of that certainly google's doing some of that amazon really bringing its cloud to the edge at this point it's not participating in multi-cloud actively anyway aws and azure they stand alone as the cloud leaders and you can debate what's included in azure in our previous chart on revenue attempts to strip out the microsoft sas business but this is a customer view they see microsoft as a cloud leader which it is so that's why its presence on the horizontal axis and its momentum is is you know very large and very strong stronger than even in aws in this view even though it's is revenue that we showed earlier microsoft is significantly smaller but they both have strong momentum on the vertical axis as shown by that red horizontal line anything above that remember is considered considered elevated that 40 percent or above now google cloud it's well behind these two to we kind of put a red dotted line around it but look at snowflake that blue circle i mean i realize we repeat ourselves often but snowflake continues to hold a net score in the mid to high 70s it held 80 percent for a long time it's getting much much bigger it's so hard to hold that and in 165 mentions in the survey which you can see in the inserted table it continues to expand its market's presence on the horizontal axis now all the technology companies that we track of all of them we feel snowflake's vision and execution on its data cloud and that strategy is most is the most prominent example of a super cloud truly every tech company every company should be paying attention to snowflakes moves and carving out unique value propositions for their customers by standing on the shoulders of cloud giants as ceo ed walsh likes to say now on the left hand side of the chart you can see a number of companies that we spoke with that are in various stages of building out their super clouds data bricks dot spot data robots z z scalar mentioned hashi you see elastic confluent they're all above the forty percent line and somewhat below that line but still respectable we see vmware with tanzu cohesity rubric and veeam and many others that we didn't necessarily speak with directly at reinvent and or they don't show up in the etr dataset now we've also called out cisco dell hpe and ibm we didn't plot them because there's so much other data in there that's not apples to apple but we want to call them up because they all have different points of view and are two varying degrees building super clouds but to be honest these large companies are first protecting their respective on-prem turf you can't blame them those are very large install basis now they're all adding as a service offerings which is cloud-like i mean they're behind way behind trying to figure out you know things like billing and they don't nearly have the ecosystem but they're going to fight rightly they're going to fight hard and compete with their respective portfolios with their channels and their vastly improved simplicity but when you speak to customers at re invent and these are not just startups we're talking to we're talking about customers of these enterprise tech companies these customers want to build on aws they look at aws as cloud and that is the cloud that they want to write to now they want to connect they're on-prem but they're still largely different worlds when you when you talk to these customers now they'll fully admit they can't or won't move everything out of their data centers but the vast vast majority of the customers i spoke with last week at reinvent have much more momentum around moving towards aws they're not repatriating as everybody's talking about or not everybody but many are talking about and yeah there's some recency bias because we just got back but the numbers that we shared earlier don't lie the trend is very clear now these large firms that we mentioned these incumbents in the tech industry these big enterprise tech giants they're starting to move in the super cloud direction and they will have much more credibility around multi-cloud than the hyperscalers but my honest view is that aws's lead is actually accelerating the gap in my opinion is not closing now i want to come back and dig into super cloud a little bit more around 2010 and 2011 we collaborated with two individuals who really shaped our thinking in the big data space peter goldmaker was a cell side analyst at common at the time and abi abhishek meta was with bank of america and b of a was transforming its data operations and avi was was leading that now peter was you know an analyst sharp and less at the time he said you know it's going to be the buyers of big data technology and those that apply big data to their operations who would create the most value he used an example of sap he said look you you couldn't have chosen that sap was going to lead an erp but if you could have figured out who which companies were going to apply erp to their business you would have made a lot of money investing so that was kind of one of his investment theses now he posited that the companies that would apply the big data technology the buyers if you will would create far more value than the cloud errors or the hortonworks or a collection of other number of big data players and clearly he was right in that regard now abi mehta was an example of that and he posited that ecosystems would evolve within vertical industries around data kind of going back to frank slootman's premise that in putting data at the core and that would power the next generation of value creation via data machine learning and business transformation and he was right and that's what we're seeing with the rise of super cloud now after the after the first reinvent we published a post seen on the right hand side of this chart on wikibon about the making of a new gorilla aws and we said the way to compete would be to take an industry focus or one way to compete with take an industry focus and become best to breed within that industry and we aligned really with abbey meta's point of view that industry ecosystems would evolve around data and offer opportunities for non-hyperscalers to compete now what we didn't predict at the time but are now seeing clearly emerge is that these super clouds are going to be built on top of aws and other hyperscale clouds makes sense goldman's financial cloud for data is taking a page out of aws it's pointing its proprietary data algorithms tools and processes at its clients just like amazon did with its technology and it's making these assets available as a service on top of the aws cloud a super cloud for financial services if you will they are relying on aws for infrastructure compute storage networking security and other services like sagemaker to power that super cloud but they're bringing their own ip to the table nasdaq and dish similarly bringing forth their unique value and as i said as i said earlier united airlines will in our view eventually evolve from migrating its apps portfolio to the cloud to building out a super cloud for travel what about your logo what's your super cloud strategy i'm sure you've been thinking about it or perhaps you're already well down the road i'd love to hear how you're doing it and if you see the trends the same or differently as we do okay that's it for now don't forget these episodes are all available as podcasts wherever you listen all you do is search breaking analysis podcast you definitely want to check out etr's website at etr.plus for all the survey data remember we publish a full report every week on wikibon.com and siliconangle.com you can email me if you want to get in touch with david.velante at siliconangle.com you can dm me at devolante on twitter you can comment on our linkedin posts this is dave vellante for the cube insights powered by etr have a great week stay safe be well and we'll see you next time [Music] you

(upbeat music) >> Welcome back, everyone, to theCUBE's live coverage, day one wrap-up. I'm John Furrier, with Dave Vellante. We have Jerry Chen, special guest who's been with us every year on theCUBE since inception. Certainly every AWS re:Invent, nine years straight. Jerry Chen, great to see you for our guest analyst's wrap up VC general partner, Greylock partners, good to see you. >> John, Dave, it's great to see you guys. Thanks for having me again. It wouldn't be re:Invent without the three of us sitting here and we missed last year, right, because of COVID. So we have to make up for lost time. >> John: We did a virtual one- >> Dave: we did virtual stuff= >> John: wasn't the same as in-person. >> Dave: Definitely not the same. >> Jerry: Not the same thing. So, it's good to see you guys again in person, and less than 6 feet apart. >> Cheers, yeah. >> And 7,000 people here, showing that the event's still relevant. >> Jerry: Yeah. >> Some people would kill for those numbers, it's a bad year for Amazon, down from 60,000. >> Jerry: Yeah. >> So, ecosystem's booming. Okay, let's get to it. Day one in the books, new CEO, new sheriff in town, his name's Adam Selipsky. Your take? >> Well, Adam's new, but he's old, right? Something, you know, like something new, something old, something blue, right? It's so, Adam was early Amazon, so he had that founding DNA. Left, you know, CEO of Tableau, acquired by Salesforce, came back few months ago. So I think it was a great move, because one, he's got the history and culture under Jassy, so he's definitely the Bezos Jassy tree of leadership, but yet he's been outside the bubble. Right? So he actually knows what it means to run a company not on the Amazon platform. So, I think Adam's a great choice to lead AWS for what we call it, like maybe act two, right? Act one, the first X years with Jassy, and maybe this is the second act under Adam. >> Yeah. And he's got- and he was very technical, hung around all the techies, James Hamilton, DeSantis, all the engineers, built that core primitives. Now, as they say, this cloud next gen's here, act two, it's about applications. >> Jerry: Yeah. >> Infrastructure as code is in place. Interesting area. Where's the growth come from? So, look, you know, the ecosystem has got to build these super clouds, or as you say, Castles on the Cloud, which you coined, but you brought this up years ago, that the moats and the value has to be in there somewhere. Do you want to revise that prediction now that you see what's coming from Selipsky? >> Okay, well, so let's refresh. Greylock.com/castles has worked out, like we did, but a lot of thought leadership and the two of you, have informed my thinking at Castles in the Cloud, how to compete against Amazon in the cloud. So you'd argue act one, the startup phase, the first, you know, X years at Amazon was from 2008 to, you know, 2021, the first X years, building the platform, digging the moats. Right? So what did you have? You have castle the platform business, economies of scale, which means decreasing marginal costs and natural network effects. So once the moat's in place and you had huge market share, what do you for act two, right? Now the moats are in place, you can start exploring the moats for I think, Adam talked about in your article, horizontal and verticals, right? Horizontal solutions up the stack, like Amazon Connect, CRM solutions, right? Horizontal apps, maybe the app layer, and verticals, industrials, financials, healthcare, et cetera. So, I think Jassy did a foundation of the castle and now we're seeing, you know, what Adam and his generation would do for act two. >> So he's, so there's almost like an act one A, because if you take the four hyperscalers, they're about, maybe do 120 billion this year, out of, I don't know, pick a number, it's many hundreds of billions, at least in infrastructure. >> Jerry: Correct. >> And those four hyperscalers growing at 35% collectively, right? So there's some growth there, but I feel like there's got to be deeper business integration, right? It's not just about IT transformation, it's about deeper- So that's maybe where this Connect like stuff comes, but are there enough of those? You know, I didn't, I haven't, I didn't hear a lot of that this morning. I heard a little bit, ML- >> Jerry: Sure. >> AI into Connect, but where's the next Connect, right? They've got to do dozens of those in order to go deeper. >> Either, Dave, dozens of those Connects or more of those premise, so the ML announcement was today. So you look at what Twilio did by buying Segment, right? Deconstruct a CRM to compete against Adam Selipsky's old acquire of Salesforce.com. They bought Segment, so Twilio now has communicates, like texting, messaging, email, but all the data come from Segment. >> Dave: With consumption-based pricing. >> With consumption-based pricing. So, right? So that's an example of kind of what the second act of cloud looks like. It may not look like full SaaS apps like Salesforce.com, but these primitives, both horizontally vertically, because again, what does Amazon have as an asset that other guys don't? Install based developers. Developers aren't going to necessarily build or consume SaaS apps, but they're going to consume things like these API's and primitives. And so you look around, what's cloud act two look like? It may not be VM's or containers. It may be API's like Stripe and Billing, Twilio messaging, right? Concepts like that. So, we'll see what the next act at cloud looks like. And they announced a bunch of stuff today, serverless for the data analytics, right? So serverless is this move towards not consuming raw compute and storage, but APIs. >> What about competition? Microsoft is nipping at the heels of AWS. >> Dave: John put them out of business earlier today. [John and Dave Laugh] >> No, I said, quote, I'll just- let me rephrase. I said, if Amazon goes unchecked- >> Jerry: Sure. >> They'll annihilate Microsoft's ecosystem. Because if you're an ISV, why wouldn't you want to run on the best platform? >> Jerry: Sure. >> Speeds and feeds matter when you have these shifts of software development. >> Jerry: You want them both. >> So, you know, I mean, you thought about the 80's, if you were at database, you wanted the best processor. So I think this Annapurna vertical integrated stacks are interesting because if my app runs better and I have a platform, prefabricated or purpose-built platform, to be there for me, I'm going to build a great SaaS app. If it runs faster and it cost less, I'm going to flop to Amazon. That's just, that's my prediction. >> So I think better changes, right? And so I think if you're Amazon, you say cheaper, better, faster, and they're investing in chips, proprietary silicon to run better, faster, their machine learning training chips, but if you're Azure or Google, you got to redefine what better is. And as a startup investor, we're always trying to do category definition, right? Like here's a category by spin. So now, if you're Azure or Google, there are things you can say that are better, and Google argued their chips, their TensorFlow, are better. Azure say our regions, our security, our enterprise readiness is better. And so all of a sudden, the criteria "what's better" changes. So from faster and cheaper to maybe better compliance, better visibility, better manageability, different colors, I don't know, right? You have to change the game , because if you play the same game on Amazon's turf, to your point, John, it- it's game over because they have economies of scale. But I think Azure and Google and other clouds, the superclouds, or subclouds are changing the game, what it means to compete. And so I think what's going on, just two more seconds, from decentralized cloud, being Web 3 and crypto, that's a whole 'nother can of worms, to Edge compute, what Cloudflare are doing with R2 and storage, they're trying to change the name of the game. >> Well, that's right. If you go frontal against Amazon, you're got to get decimated. You got to move the goalposts for better. And I think that's a good way to look at it, Dave. What does better mean? So that's the question that's on the table. What does that look like? And I think that's an unknown, that's coming. Okay, back to the start-ups. Category definition. That's an awesome term. That to me is a key thing. How do you look at what a category is on your sub- on your Castles of the Cloud, you brought up how many categories of- >> Jerry: 33 markets and a bunch of submarkets, yeah. >> Yeah. Explain that concept. >> So, we did Castle in the Clouds where my team looked at all the services offered at Azure, Google, and Amazon. We downloaded the services and recategorized them to like, 30 plus markets and a bunch of submarkets. Because, the reason why is apples to apples, you know, Amazon, Google, Azure all have databases, but they might call them different things. And so I think first things first is, let's give developers and customers kind of apples to apples comparisons. So I think those are known markets. The key in investing in the cloud, or investing in general, is you're either investing in budget replacement, replacing a known market, cheaper, better database, to your point, or a net new market, right? Which is always tricky. So I think the biggest threat to a lot of the startups and incumbents, the biggest threat by startups and incumbents, is either one, do something cheaper, better in a current market, or find a net new market that they haven't thought about yet. And if you can win that net new market before the rest, then that's unbelievable. We call it the, you know, the blue ocean strategy, >> Dave: Is that essentially what Snowflake has done, started with cheaper, better, and now they're building the data cloud? >> Jerry: I think there's- it's evolution, correct. So they said cheaper, better. And the Castle in the Cloud, we talked about, they actually built deep IP. So they went a known category, data warehouses, right? You had Teradata, Redshift, Snowflake cheaper, better, faster. And now let's say, okay, once you have the customers, let's change the name of the game and create a data cloud. And it's TBD whether or not Snowflake can win data cloud. Like we talked about Rockset, one of my investments that's actually move the goalpost saying, oh, data cloud is nice, but real time data is where it's at, and Snowflake and those guys can't play in real time. >> Dave: No, they're not in a position to play in real time data. >> Jerry: Right. >> Dave: I mean, that's right. >> So again, so that's an example of a startup moving the goalpost on what previously was a startup that moved the goalpost on an incumbent. >> Dave: And when you think about Edge, it's going to be real-time AI inferencing at the Edge, and you're right, Snowflake's not set up well at all for that. >> John: So competition wise, how do the people compete? Because this is what Databricks did the same exact thing. I have Ali on the record going back years, "Well, we love Amazon. We're only on Amazon." Now he's talking multicloud. >> So, you know, once you get there, you kind of change your tune cause you've got some scale, but then you got new potential entrants coming in, like Rockset. >> Jerry: Correct. >> So. >> Dave: But then, and if you add up the market caps of just those two companies, Databricks and Snowflake, it's much larger than the database market. So this, we're defining new markets now. >> Jerry: I think there's market cap, especially Snowflake that's in the public market, Databricks is still private, is optimism that there's a second or third act in the database space left to be unlocked. And you look at what's going on in that space, these real-time analytics or real-time apps, for sure there's optimism there. But, but to John's point, you're right, like you earn the right to play the next act, but it's tricky because startups disrupt incumbents and become incumbents, and they're also victims their own success, right? So you're- there's technical debt, there's also business model debt. So you're victims of your own business model, victims of your own success. And so what got you here may not get you to the next phase. And so I think for Amazon, that's a question. For Databricks and Snowflake, that's a question, is what got them here? Can they play to the next act? And look, Apple did it, multiple acts. >> John: Well, I mean, I think I- [Crosstalk] >> John: I think it's whether you take shortcuts or not, if you have debt, you make it a little bit of a shortcut bet. >> Jerry: Yeah. >> Okay. That's cool. But ultimately what you're getting at here is beachhead thinking. Get a beachhead- >> Jerry: Correct. >> Get in the market, and then sequence to a different position. Classic competitive strategy, 101. That's hard to do because you want to win the beachhead- >> I know. >> John: And take a little technical debt and business model debt, cheat a little bit, and then, is it not fortified yet? So beachhead to expansion is the question. >> Jerry: That's every board meeting, John and Dave, that we're in, right? It's called you need a narrow enough wedge to land. And it is like, I don't want the tip of the spear, I want the poison on the tip of a spear, right? [Dave and John Laugh] >> You want, especially in this cloud market, a super focused wedge to land. And the problem is, as a founder, as investor, you're always thinking about the global max, right? Like the ultimate platform winner, but you don't get the right to play the early- the late innings if you don't make it out of the early innings. And so narrow beachhead, sharp wedge, but you got to land in a space, a place of real estate with adjacent tan, adjacent markets, right? Like Uber, black cars, taxi's, food, whatever, right? Snowflake, data warehouse, data cloud. And so I think the key with all startups is you'll hit some ceiling of market size. Is there a second ramp? >> Dave: So it's- the art is when to scale and how fast to scale. >> Right. Picking when, how fast, in which- which best place, it was tough. And so, the best companies are always thinking about their second or third act while the first act's still going. >> John: Yeah. And leveraging cloud to refactor, I think that's the key to Snowflake, was they had the wedge with data warehouse, they saw the position, but refactored and in the cloud with services that they knew Teradata wouldn't use. >> Jerry: Correct. >> And they're in. From there, it's just competitive IP, crank, go to market. >> And then you have the other unnatural things. You have channel, you have installed base of customers, right? And then you start selling more stuff to the same channel, to the same customers. That's what Amazon's doing. All the incumbent's do that. Amazon's got, you know, 300 services now, launching more this week, so now they have channel distribution, right? Every credit card for all the developers, and they have installed base of customers. And so they will just launch new things and serve the customers. So the startups had to disrupt them somehow. >> Well, it's always great to chat with Jerry. Every year we discover and we riff and we identify, in real time, new stuff. We were talking about this whole vertical, horizontal scale and kind of castles early on, years ago. And now it's happened. You were right. Congratulations. That's a great thesis. There's real advantages to build on a cloud. You can get the- you can build a business there. >> Jerry: Right. >> John: That's your thesis. And by the way, these markets are changing. So if you're smart, you can actually compete. >> Jerry: I think you beat, and to Dave's earlier point, you have to adapt, right? And so what's the Darwin thing, it's not the strongest, but the most adaptable. So both- Amazon's adapt and the startups who are the most adaptable will win. >> Dave: Where are you, you guys might've talked about this, where do you stand on the cost of goods sold issue? >> Jerry: Oh, I think everything's true, right? I think you can save money at some scale to repatriate your cloud, but again, Wall Street rewards growth versus COGS, right? So I think you've got a choice between a dollar of growth versus a dollar reducing COGS, people choose growth right now. That may not always be the case, but at some point, if you're a company at some scale and the dollars of growth is slowing down, you definitely have to reduce the dollars in cost. And so you start optimizing cloud costs, and that could be going to Amazon, Azure, or Google, reducing COGS. >> Dave: Negotiate, yeah. >> John: Or, you have no visibility on new net new opportunities. So growth is about new opportunities. >> Correct. >> If you repatriating things, there's no growth. >> Jerry: It's not either, or- >> That's my opinion. >> Jerry: COGS or growth, right? But they're both valid, definitely, so you can do both. And so I don't think- it's what's your priorities, you can't do everything at once. So if I'm a founder or CEO or in this case investor, and I said, "Hey, Dave, and John, if you said I can either save you 25 basis points in gross margin, or I can increase another 10% top line this year", I'm going to say increase the top line, we'll deal with the gross margin later. Not that it's not important, but right now the early phase- >> Priorities. >> Jerry: It's growth. >> Yeah. All right, Jerry Chen, great to see you. Great to have you on, great CUBE alumni, great guest analyst. Thanks for breaking it down. CUBE coverage here in Las Vegas for re:Invent, back in person. Of course, it's a virtual event, we've got a hybrid event for Amazon, as well as theCUBE. I'm John Furrier, you're watching the leader in worldwide tech coverage. Thanks for watching. (Gentle music)

>>Hello and welcome today's cube presentation of eight of us startup showcase. I'm john for your host highlighting the hottest companies and devops data analytics and cloud management lisa martin and David want are here to kick it off. We've got a great program for you again. This is our, our new community event model where we're doing every quarter, we have every new episode, this is quarter three this year or episode three, season one of the hottest cloud startups and we're gonna be featured. Then we're gonna do a keynote package and then 15 countries will present their story, Go check them out and then have a closing keynote with a practitioner and we've got some great lineups, lisa Dave, great to see you. Thanks for joining me. >>Hey guys, >>great to be here. So David got to ask you, you know, back in events last night we're at the 14 it's event where they had the golf PGA championship with the cube Now we got the hybrid model, This is the new normal. We're in, we got these great companies were showcasing them. What's your take? >>Well, you're right. I mean, I think there's a combination of things. We're seeing some live shows. We saw what we did with at mobile world Congress. We did the show with AWS storage day where it was, we were at the spheres, there was no, there was a live audience, but they weren't there physically. It was just virtual and yeah, so, and I just got pained about reinvent. Hey Dave, you gotta make your flights. So I'm making my flights >>were gonna be at the amazon web services, public sector summit next week. At least a lot, a lot of cloud convergence going on here. We got many companies being featured here that we spoke with the Ceo and their top people cloud management, devops data, nelson security. Really cutting edge companies, >>yes, cutting edge companies who are all focused on acceleration. We've talked about the acceleration of digital transformation the last 18 months and we've seen a tremendous amount of acceleration in innovation with what these startups are doing. We've talked to like you said, there's, there's C suite, we've also talked to their customers about how they are innovating so quickly with this hybrid environment, this remote work and we've talked a lot about security in the last week or so. You mentioned that we were at Fortinet cybersecurity skills gap. What some of these companies are doing with automation for example, to help shorten that gap, which is a big opportunity >>for the job market. Great stuff. Dave so the format of this event, you're going to have a fireside chat with the practitioner, we'd like to end these programs with a great experienced practitioner cutting edge in data february. The beginning lisa are gonna be kicking off with of course Jeff bar to give us the update on what's going on AWS and then a special presentation from Emily Freeman who is the author of devops for dummies, she's introducing new content. The revolution in devops devops two point oh and of course jerry Chen from Greylock cube alumni is going to come on and talk about his new thesis castles in the cloud creating moats at cloud scale. We've got a great lineup of people and so the front ends can be great. Dave give us a little preview of what people can expect at the end of the fireside chat. >>Well at the highest level john I've always said we're entering that sort of third great wave of cloud. First wave was experimentation. The second big wave was migration. The third wave of integration, Deep business integration and what you're >>going to hear from >>Hello Fresh today is how they like many companies that started early last decade. They started with an on prem Hadoop system and then of course we all know what happened is S three essentially took the knees out from, from the on prem Hadoop market lowered costs, brought things into the cloud and what Hello Fresh is doing is they're transforming from that legacy Hadoop system into its running on AWS but into a data mess, you know, it's a passionate topic of mine. Hello Fresh was scaling they realized that they couldn't keep up so they had to rethink their entire data architecture and they built it around data mesh Clements key and christoph Soewandi gonna explain how they actually did that are on a journey or decentralized data >>measure it and your posts have been awesome on data measure. We get a lot of traction. Certainly you're breaking analysis for the folks watching check out David Landes, Breaking analysis every week, highlighting the cutting edge trends in tech Dave. We're gonna see you later, lisa and I are gonna be here in the morning talking about with Emily. We got Jeff Barr teed up. Dave. Thanks for coming on. Looking forward to fireside chat lisa. We'll see you when Emily comes back on. But we're gonna go to Jeff bar right now for Dave and I are gonna interview Jeff. Mm >>Hey Jeff, >>here he is. Hey, how are you? How's it going really well. So I gotta ask you, the reinvent is on, everyone wants to know that's happening right. We're good with Reinvent. >>Reinvent is happening. I've got my hotel and actually listening today, if I just remembered, I still need to actually book my flights. I've got my to do list on my desk and I do need to get my >>flights. Uh, >>really looking forward >>to it. I can't wait to see the all the announcements and blog posts. We're gonna, we're gonna hear from jerry Chen later. I love the after on our next event. Get your reaction to this castle and castles in the cloud where competitive advantages can be built in the cloud. We're seeing examples of that. But first I gotta ask you give us an update of what's going on. The ap and ecosystem has been an incredible uh, celebration these past couple weeks, >>so, so a lot of different things happening and the interesting thing to me is that as part of my job, I often think that I'm effectively living in the future because I get to see all this really cool stuff that we're building just a little bit before our customers get to, and so I'm always thinking okay, here I am now, and what's the world going to be like in a couple of weeks to a month or two when these launches? I'm working on actually get out the door and that, that's always really, really fun, just kind of getting that, that little edge into where we're going, but this year was a little interesting because we had to really significant birthdays, we had the 15 year anniversary of both EC two and S three and we're so focused on innovating and moving forward, that it's actually pretty rare for us at Aws to look back and say, wow, we've actually done all these amazing things in in the last 15 years, >>you know, it's kind of cool Jeff, if I may is is, you know, of course in the early days everybody said, well, a place for startup is a W. S and now the great thing about the startup showcases, we're seeing the startups that >>are >>very near, or some of them have even reached escape velocity, so they're not, they're not tiny little companies anymore, they're in their transforming their respective industries, >>they really are and I think that as they start ups grow, they really start to lean into the power of the cloud. They as they start to think, okay, we've we've got our basic infrastructure in place, we've got, we were serving data, we're serving up a few customers, everything is actually working pretty well for us. We've got our fundamental model proven out now, we can invest in publicity and marketing and scaling and but they don't have to think about what's happening behind the scenes. They just if they've got their auto scaling or if they're survivalists, the infrastructure simply grows to meet their demand and it's it's just a lot less things that they have to worry about. They can focus on the fun part of their business which is actually listening to customers and building up an awesome business >>Jeff as you guys are putting together all the big pre reinvented, knows a lot of stuff that goes on prior as well and they say all the big good stuff to reinvent. But you start to see some themes emerged this year. One of them is modernization of applications, the speed of application development in the cloud with the cloud scale devops personas, whatever persona you want to talk about but basically speed the speed of of the app developers where other departments have been slowing things down, I won't say name names, but security group and I t I mean I shouldn't have said that but only kidding but no but seriously people want in minutes and seconds now not days or weeks. You know whether it's policy. What are some of the trends that you're seeing around this this year as we get into some of the new stuff coming out >>So Dave customers really do want speed and for we've actually encapsulate this for a long time in amazon in what we call the bias for action leadership principle >>where >>we just need to jump in and move forward and and make things happen. A lot of customers look at that and they say yes this is great. We need to have the same bias fraction. Some do. Some are still trying to figure out exactly how to put it into play. And they absolutely for sure need to pay attention to security. They need to respect the past and make sure that whatever they're doing is in line with I. T. But they do want to move forward. And the interesting thing that I see time and time again is it's not simply about let's adopt a new technology. It's how do we >>how do we keep our workforce >>engaged? How do we make sure that they've got the right training? How do we bring our our I. T. Team along for this. Hopefully new and fun and exciting journey where they get to learn some interesting new technologies they've got all this very much accumulated business knowledge they still want to put to use, maybe they're a little bit apprehensive about something brand new and they hear about the cloud, but there by and large, they really want to move forward. They just need a little bit of >>help to make it happen >>real good guys. One of the things you're gonna hear today, we're talking about speed traditionally going fast. Oftentimes you meant you have to sacrifice some things on quality and what you're going to hear from some of the startups today is how they're addressing that to automation and modern devoPS technologies and sort of rethinking that whole application development approach. That's something I'm really excited to see organization is beginning to adopt so they don't have to make that tradeoff anymore. >>Yeah, I would >>never want to see someone >>sacrifice quality, >>but I do think that iterating very quickly and using the best of devoPS principles to be able to iterate incredibly quickly and get that first launch out there and then listen with both ears just >>as much >>as you can, Everything. You hear iterate really quickly to meet those needs in, in hours and days, not months, quarters or years. >>Great stuff. Chef and a lot of the companies were featuring here in the startup showcase represent that new kind of thinking, um, systems thinking as well as you know, the cloud scale and again and it's finally here, the revolution of deVOps is going to the next generation and uh, we're excited to have Emily Freeman who's going to come on and give a little preview for her new talk on this revolution. So Jeff, thank you for coming on, appreciate you sharing the update here on the cube. Happy >>to be. I'm actually really looking forward to hearing from Emily. >>Yeah, it's great. Great. Looking forward to the talk. Brand new Premier, Okay, uh, lisa martin, Emily Freeman is here. She's ready to come in and we're going to preview her lightning talk Emily. Um, thanks for coming on, we really appreciate you coming on really, this is about to talk around deVOPS next gen and I think lisa this is one of those things we've been, we've been discussing with all the companies. It's a new kind of thinking it's a revolution, it's a systems mindset, you're starting to see the connections there she is. Emily, Thanks for coming. I appreciate it. >>Thank you for having me. So your teaser video >>was amazing. Um, you know, that little secret radical idea, something completely different. Um, you gotta talk coming up, what's the premise behind this revolution, you know, these tying together architecture, development, automation deployment, operating altogether. >>Yes, well, we have traditionally always used the sclc, which is the software delivery life cycle. Um, and it is a straight linear process that has actually been around since the sixties, which is wild to me um, and really originated in manufacturing. Um, and as much as I love the Toyota production system and how much it has shown up in devops as a sort of inspiration on how to run things better. We are not making cars, we are making software and I think we have to use different approaches and create a sort of model that better reflects our modern software development process. >>It's a bold idea and looking forward to the talk and as motivation. I went into my basement and dusted off all my books from college in the 80s and the sea estimates it was waterfall. It was software development life cycle. They trained us to think this way and it came from the mainframe people. It was like, it's old school, like really, really old and it really hasn't been updated. Where's the motivation? I actually cloud is kind of converging everything together. We see that, but you kind of hit on this persona thing. Where did that come from this persona? Because you know, people want to put people in buckets release engineer. I mean, where's that motivation coming from? >>Yes, you're absolutely right that it came from the mainframes. I think, you know, waterfall is necessary when you're using a punch card or mag tape to load things onto a mainframe, but we don't exist in that world anymore. Thank goodness. And um, yes, so we, we use personas all the time in tech, you know, even to register, well not actually to register for this event, but a lot events. A lot of events, you have to click that drop down. Right. Are you a developer? Are you a manager, whatever? And the thing is personas are immutable in my opinion. I was a developer. I will always identify as a developer despite playing a lot of different roles and doing a lot of different jobs. Uh, and this can vary throughout the day. Right. You might have someone who has a title of software architect who ends up helping someone pair program or develop or test or deploy. Um, and so we wear a lot of hats day to day and I think our discussions around roles would be a better, um, certainly a better approach than personas >>lease. And I've been discussing with many of these companies around the roles and we're hearing from them directly and they're finding out that people have, they're mixing and matching on teams. So you're, you're an S R E on one team and you're doing something on another team where the workflows and the workloads defined the team formation. So this is a cultural discussion. >>It absolutely is. Yes. I think it is a cultural discussion and it really comes to the heart of devops, right? It's people process. And then tools deVOps has always been about culture and making sure that developers have all the tools they need to be productive and honestly happy. What good is all of this? If developing software isn't a joyful experience. Well, >>I got to ask you, I got you here obviously with server list and functions just starting to see this kind of this next gen. And we're gonna hear from jerry Chen, who's a Greylock VC who's going to talk about castles in the clouds, where he's discussing the moats that could be created with a competitive advantage in cloud scale. And I think he points to the snowflakes of the world. You're starting to see this new thing happening. This is devops 2.0, this is the revolution. Is this kind of where you see the same vision of your talk? >>Yes, so DeVOps created 2000 and 8, 2000 and nine, totally different ecosystem in the world we were living in, you know, we didn't have things like surveillance and containers, we didn't have this sort of default distributed nature, certainly not the cloud. Uh and so I'm very excited for jerry's talk. I'm curious to hear more about these moz. I think it's fascinating. Um but yeah, you're seeing different companies use different tools and processes to accelerate their delivery and that is the competitive advantage. How can we figure out how to utilize these tools in the most efficient way possible. >>Thank you for coming and giving us a preview. Let's now go to your lightning keynote talk. Fresh content. Premier of this revolution in Devops and the Freemans Talk, we'll go there now. >>Hi, I'm Emily Freeman, I'm the author of devops for dummies and the curator of 97 things every cloud engineer should know. I am thrilled to be here with you all today. I am really excited to share with you a kind of a wild idea, a complete re imagining of the S DLC and I want to be clear, I need your feedback. I want to know what you think of this. You can always find me on twitter at editing. Emily, most of my work centers around deVOps and I really can't overstate what an impact the concept of deVOPS has had on this industry in many ways it built on the foundation of Agile to become a default a standard we all reach for in our everyday work. When devops surfaced as an idea in 2008, the tech industry was in a vastly different space. AWS was an infancy offering only a handful of services. Azure and G C P didn't exist yet. The majority's majority of companies maintained their own infrastructure. Developers wrote code and relied on sys admins to deploy new code at scheduled intervals. Sometimes months apart, container technology hadn't been invented applications adhered to a monolithic architecture, databases were almost exclusively relational and serverless wasn't even a concept. Everything from the application to the engineers was centralized. Our current ecosystem couldn't be more different. Software is still hard, don't get me wrong, but we continue to find novel solutions to consistently difficult, persistent problems. Now, some of these end up being a sort of rebranding of old ideas, but others are a unique and clever take to abstracting complexity or automating toil or perhaps most important, rethinking challenging the very premises we have accepted as Cannon for years, if not decades. In the years since deVOps attempted to answer the critical conflict between developers and operations, engineers, deVOps has become a catch all term and there have been a number of derivative works. Devops has come to mean 5000 different things to 5000 different people. For some, it can be distilled to continuous integration and continuous delivery or C I C D. For others, it's simply deploying code more frequently, perhaps adding a smattering of tests for others. Still, its organizational, they've added a platform team, perhaps even a questionably named DEVOPS team or have created an engineering structure that focuses on a separation of concerns. Leaving feature teams to manage the development, deployment, security and maintenance of their siloed services, say, whatever the interpretation, what's important is that there isn't a universally accepted standard. Well, what deVOPS is or what it looks like an execution, it's a philosophy more than anything else. A framework people can utilize to configure and customize their specific circumstances to modern development practices. The characteristic of deVOPS that I think we can all agree on though, is that an attempted to capture the challenges of the entire software development process. It's that broad umbrella, that holistic view that I think we need to breathe life into again, The challenge we face is that DeVOps isn't increasingly outmoded solution to a previous problem developers now face. Cultural and technical challenge is far greater than how to more quickly deploy a monolithic application. Cloud native is the future the next collection of default development decisions and one the deVOPS story can't absorb in its current form. I believe the era of deVOPS is waning and in this moment as the sun sets on deVOPS, we have a unique opportunity to rethink rebuild free platform. Even now, I don't have a crystal ball. That would be very handy. I'm not completely certain with the next decade of tech looks like and I can't write this story alone. I need you but I have some ideas that can get the conversation started, I believe to build on what was we have to throw away assumptions that we've taken for granted all this time in order to move forward. We must first step back. Mhm. The software or systems development life cycle, what we call the S. D. L. C. has been in use since the 1960s and it's remained more or less the same since before color television and the touch tone phone. Over the last 60 or so odd years we've made tweaks, slight adjustments, massaged it. The stages or steps are always a little different with agile and deVOps we sort of looped it into a circle and then an infinity loop we've added pretty colors. But the sclc is more or less the same and it has become an assumption. We don't even think about it anymore, universally adopted constructs like the sclc have an unspoken permanence. They feel as if they have always been and always will be. I think the impact of that is even more potent. If you were born after a construct was popularized. Nearly everything around us is a construct, a model, an artifact of a human idea. The chair you're sitting in the desk, you work at the mug from which you drink coffee or sometimes wine, buildings, toilets, plumbing, roads, cars, art, computers, everything. The sclc is a remnant an artifact of a previous era and I think we should throw it away or perhaps more accurately replace it, replace it with something that better reflects the actual nature of our work. A linear, single threaded model designed for the manufacturer of material goods cannot possibly capture the distributed complexity of modern socio technical systems. It just can't. Mhm. And these two ideas aren't mutually exclusive that the sclc was industry changing, valuable and extraordinarily impactful and that it's time for something new. I believe we are strong enough to hold these two ideas at the same time, showing respect for the past while envisioning the future. Now, I don't know about you, I've never had a software project goes smoothly in one go. No matter how small. Even if I'm the only person working on it and committing directly to master software development is chaos. It's a study and entropy and it is not getting any more simple. The model with which we think and talk about software development must capture the multithreaded, non sequential nature of our work. It should embody the roles engineers take on and the considerations they make along the way. It should build on the foundations of agile and devops and represent the iterative nature of continuous innovation. Now, when I was thinking about this, I was inspired by ideas like extreme programming and the spiral model. I I wanted something that would have layers, threads, even a way of visually representing multiple processes happening in parallel. And what I settled on is the revolution model. I believe the visualization of revolution is capable of capturing the pivotal moments of any software scenario. And I'm going to dive into all the discrete elements. But I want to give you a moment to have a first impression, to absorb my idea. I call it revolution because well for one it revolves, it's circular shape reflects the continuous and iterative nature of our work, but also because it is revolutionary. I am challenging a 60 year old model that is embedded into our daily language. I don't expect Gartner to build a magic quadrant around this tomorrow, but that would be super cool. And you should call me my mission with. This is to challenge the status quo to create a model that I think more accurately reflects the complexity of modern cloud native software development. The revolution model is constructed of five concentric circles describing the critical roles of software development architect. Ng development, automating, deploying and operating intersecting each loop are six spokes that describe the production considerations every engineer has to consider throughout any engineering work and that's test, ability, secure ability, reliability, observe ability, flexibility and scalability. The considerations listed are not all encompassing. There are of course things not explicitly included. I figured if I put 20 spokes, some of us, including myself, might feel a little overwhelmed. So let's dive into each element in this model. We have long used personas as the default way to do divide audiences and tailor messages to group people. Every company in the world right now is repeating the mantra of developers, developers, developers but personas have always bugged me a bit because this approach typically either oversimplifies someone's career are needlessly complicated. Few people fit cleanly and completely into persona based buckets like developers and operations anymore. The lines have gotten fuzzy on the other hand, I don't think we need to specifically tailor messages as to call out the difference between a devops engineer and a release engineer or a security administrator versus a security engineer but perhaps most critically, I believe personas are immutable. A persona is wholly dependent on how someone identifies themselves. It's intrinsic not extrinsic. Their titles may change their jobs may differ, but they're probably still selecting the same persona on that ubiquitous drop down. We all have to choose from when registering for an event. Probably this one too. I I was a developer and I will always identify as a developer despite doing a ton of work in areas like devops and Ai Ops and Deverell in my heart. I'm a developer I think about problems from that perspective. First it influences my thinking and my approach roles are very different. Roles are temporary, inconsistent, constantly fluctuating. If I were an actress, the parts I would play would be lengthy and varied, but the persona I would identify as would remain an actress and artist lesbian. Your work isn't confined to a single set of skills. It may have been a decade ago, but it is not today in any given week or sprint, you may play the role of an architect. Thinking about how to design a feature or service, developer building out code or fixing a bug and on automation engineer, looking at how to improve manual processes. We often refer to as soil release engineer, deploying code to different environments or releasing it to customers or in operations. Engineer ensuring an application functions inconsistent expected ways and no matter what role we play. We have to consider a number of issues. The first is test ability. All software systems require testing to assure architects that designs work developers, the code works operators, that infrastructure is running as expected and engineers of all disciplines that code changes won't bring down the whole system testing in its many forms is what enables systems to be durable and have longevity. It's what reassures engineers that changes won't impact current functionality. A system without tests is a disaster waiting to happen, which is why test ability is first among equals at this particular roundtable. Security is everyone's responsibility. But if you understand how to design and execute secure systems, I struggle with this security incidents for the most part are high impact, low probability events. The really big disasters, the one that the ones that end up on the news and get us all free credit reporting for a year. They don't happen super frequently and then goodness because you know that there are endless small vulnerabilities lurking in our systems. Security is something we all know we should dedicate time to but often don't make time for. And let's be honest, it's hard and complicated and a little scary def sec apps. The first derivative of deVOPS asked engineers to move security left this approach. Mint security was a consideration early in the process, not something that would block release at the last moment. This is also the consideration under which I'm putting compliance and governance well not perfectly aligned. I figure all the things you have to call lawyers for should just live together. I'm kidding. But in all seriousness, these three concepts are really about risk management, identity, data, authorization. It doesn't really matter what specific issue you're speaking about, the question is who has access to what win and how and that is everyone's responsibility at every stage site reliability engineering or sorry, is a discipline job and approach for good reason. It is absolutely critical that applications and services work as expected. Most of the time. That said, availability is often mistakenly treated as a synonym for reliability. Instead, it's a single aspect of the concept if a system is available but customer data is inaccurate or out of sync. The system is not reliable, reliability has five key components, availability, latency, throughput. Fidelity and durability, reliability is the end result. But resiliency for me is the journey the action engineers can take to improve reliability, observe ability is the ability to have insight into an application or system. It's the combination of telemetry and monitoring and alerting available to engineers and leadership. There's an aspect of observe ability that overlaps with reliability, but the purpose of observe ability isn't just to maintain a reliable system though, that is of course important. It is the capacity for engineers working on a system to have visibility into the inner workings of that system. The concept of observe ability actually originates and linear dynamic systems. It's defined as how well internal states of a system can be understood based on information about its external outputs. If it is critical when companies move systems to the cloud or utilize managed services that they don't lose visibility and confidence in their systems. The shared responsibility model of cloud storage compute and managed services require that engineering teams be able to quickly be alerted to identify and remediate issues as they arise. Flexible systems are capable of adapting to meet the ever changing needs of the customer and the market segment, flexible code bases absorb new code smoothly. Embody a clean separation of concerns. Are partitioned into small components or classes and architected to enable the now as well as the next inflexible systems. Change dependencies are reduced or eliminated. Database schemas accommodate change well components, communicate via a standardized and well documented A. P. I. The only thing constant in our industry is change and every role we play, creating flexibility and solutions that can be flexible that will grow as the applications grow is absolutely critical. Finally, scalability scalability refers to more than a system's ability to scale for additional load. It implies growth scalability and the revolution model carries the continuous innovation of a team and the byproducts of that growth within a system. For me, scalability is the most human of the considerations. It requires each of us in our various roles to consider everyone around us, our customers who use the system or rely on its services, our colleagues current and future with whom we collaborate and even our future selves. Mhm. Software development isn't a straight line, nor is it a perfect loop. It is an ever changing complex dance. There are twirls and pivots and difficult spins forward and backward. Engineers move in parallel, creating truly magnificent pieces of art. We need a modern model for this modern era and I believe this is just the revolution to get us started. Thank you so much for having me. >>Hey, we're back here. Live in the keynote studio. I'm john for your host here with lisa martin. David lot is getting ready for the fireside chat ending keynote with the practitioner. Hello! Fresh without data mesh lisa Emily is amazing. The funky artwork there. She's amazing with the talk. I was mesmerized. It was impressive. >>The revolution of devops and the creative element was a really nice surprise there. But I love what she's doing. She's challenging the status quo. If we've learned nothing in the last year and a half, We need to challenge the status quo. A model from the 1960s that is no longer linear. What she's doing is revolutionary. >>And we hear this all the time. All the cube interviews we do is that you're seeing the leaders, the SVP's of engineering or these departments where there's new new people coming in that are engineering or developers, they're playing multiple roles. It's almost a multidisciplinary aspect where you know, it's like going into in and out burger in the fryer later and then you're doing the grill, you're doing the cashier, people are changing roles or an architect, their test release all in one no longer departmental, slow siloed groups. >>She brought up a great point about persona is that we no longer fit into these buckets. That the changing roles. It's really the driver of how we should be looking at this. >>I think I'm really impressed, really bold idea, no brainer as far as I'm concerned, I think one of the things and then the comments were off the charts in a lot of young people come from discord servers. We had a good traction over there but they're all like learning. Then you have the experience, people saying this is definitely has happened and happening. The dominoes are falling and they're falling in the direction of modernization. That's the key trend speed. >>Absolutely with speed. But the way that Emily is presenting it is not in a brash bold, but it's in a way that makes great sense. The way that she creatively visually lined out what she was talking about Is amenable to the folks that have been doing this for since the 60s and the new folks now to really look at this from a different >>lens and I think she's a great setup on that lightning top of the 15 companies we got because you think about sis dig harness. I white sourced flamingo hacker one send out, I oh, okay. Thought spot rock set Sarah Ops ramp and Ops Monte cloud apps, sani all are doing modern stuff and we talked to them and they're all on this new wave, this monster wave coming. What's your observation when you talk to these companies? >>They are, it was great. I got to talk with eight of the 15 and the amount of acceleration of innovation that they've done in the last 18 months is phenomenal obviously with the power and the fuel and the brand reputation of aws but really what they're all facilitating cultural shift when we think of devoPS and the security folks. Um, there's a lot of work going on with ai to an automation to really kind of enabled to develop the develops folks to be in control of the process and not have to be security experts but ensuring that the security is baked in shifting >>left. We saw that the chat room was really active on the security side and one of the things I noticed was not just shift left but the other groups, the security groups and the theme of cultural, I won't say war but collision cultural shift that's happening between the groups is interesting because you have this new devops persona has been around Emily put it out for a while. But now it's going to the next level. There's new revolutions about a mindset, a systems mindset. It's a thinking and you start to see the new young companies coming out being funded by the gray locks of the world who are now like not going to be given the we lost the top three clouds one, everything. there's new business models and new technical architecture in the cloud and that's gonna be jerry Chen talk coming up next is going to be castles in the clouds because jerry chant always talked about moats, competitive advantage and how moats are key to success to guard the castle. And then we always joke, there's no more moz because the cloud has killed all the boats. But now the motor in the cloud, the castles are in the cloud, not on the ground. So very interesting thought provoking. But he's got data and if you look at the successful companies like the snowflakes of the world, you're starting to see these new formations of this new layer of innovation where companies are growing rapidly, 98 unicorns now in the cloud. Unbelievable, >>wow, that's a lot. One of the things you mentioned, there's competitive advantage and these startups are all fueled by that they know that there are other companies in the rear view mirror right behind them. If they're not able to work as quickly and as flexibly as a competitor, they have to have that speed that time to market that time to value. It was absolutely critical. And that's one of the things I think thematically that I saw along the eighth sort of that I talked to is that time to value is absolutely table stakes. >>Well, I'm looking forward to talking to jerry chan because we've talked on the queue before about this whole idea of What happens when winner takes most would mean the top 3, 4 cloud players. What happens? And we were talking about that and saying, if you have a model where an ecosystem can develop, what does that look like and back in 2013, 2014, 2015, no one really had an answer. Jerry was the only BC. He really nailed it with this castles in the cloud. He nailed the idea that this is going to happen. And so I think, you know, we'll look back at the tape or the videos from the cube, we'll find those cuts. But we were talking about this then we were pontificating and riffing on the fact that there's going to be new winners and they're gonna look different as Andy Jassy always says in the cube you have to be misunderstood if you're really going to make something happen. Most of the most successful companies are misunderstood. Not anymore. The cloud scales there. And that's what's exciting about all this. >>It is exciting that the scale is there, the appetite is there the appetite to challenge the status quo, which is right now in this economic and dynamic market that we're living in is there's nothing better. >>One of the things that's come up and and that's just real quick before we bring jerry in is automation has been insecurity, absolutely security's been in every conversation, but automation is now so hot in the sense of it's real and it's becoming part of all the design decisions. How can we automate can we automate faster where the keys to automation? Is that having the right data, What data is available? So I think the idea of automation and Ai are driving all the change and that's to me is what these new companies represent this modern error where AI is built into the outcome and the apps and all that infrastructure. So it's super exciting. Um, let's check in, we got jerry Chen line at least a great. We're gonna come back after jerry and then kick off the day. Let's bring in jerry Chen from Greylock is he here? Let's bring him in there. He is. >>Hey john good to see you. >>Hey, congratulations on an amazing talk and thesis on the castles on the cloud. Thanks for coming on. >>All right, Well thanks for reading it. Um, always were being put a piece of workout out either. Not sure what the responses, but it seemed to resonate with a bunch of developers, founders, investors and folks like yourself. So smart people seem to gravitate to us. So thank you very much. >>Well, one of the benefits of doing the Cube for 11 years, Jerry's we have videotape of many, many people talking about what the future will hold. You kind of are on this early, it wasn't called castles in the cloud, but you were all I was, we had many conversations were kind of connecting the dots in real time. But you've been on this for a while. It's great to see the work. I really think you nailed this. I think you're absolutely on point here. So let's get into it. What is castles in the cloud? New research to come out from Greylock that you spearheaded? It's collaborative effort, but you've got data behind it. Give a quick overview of what is castle the cloud, the new modes of competitive advantage for companies. >>Yeah, it's as a group project that our team put together but basically john the question is, how do you win in the cloud? Remember the conversation we had eight years ago when amazon re event was holy cow, Like can you compete with them? Like is it a winner? Take all? Winner take most And if it is winner take most, where are the white spaces for Some starts to to emerge and clearly the past eight years in the cloud this journey, we've seen big companies, data breaks, snowflakes, elastic Mongo data robot. And so um they spotted the question is, you know, why are the castles in the cloud? The big three cloud providers, Amazon google and Azure winning. You know, what advantage do they have? And then given their modes of scale network effects, how can you as a startup win? And so look, there are 500 plus services between all three cloud vendors, but there are like 500 plus um startups competing gets a cloud vendors and there's like almost 100 unicorn of private companies competing successfully against the cloud vendors, including public companies. So like Alaska, Mongo Snowflake. No data breaks. Not public yet. Hashtag or not public yet. These are some examples of the names that I think are winning and watch this space because you see more of these guys storm the castle if you will. >>Yeah. And you know one of the things that's a funny metaphor because it has many different implications. One, as we talk about security, the perimeter of the gates, the moats being on land. But now you're in the cloud, you have also different security paradigm. You have a different um, new kinds of services that are coming on board faster than ever before. Not just from the cloud players but From companies contributing into the ecosystem. So the combination of the big three making the market the main markets you, I think you call 31 markets that we know of that probably maybe more. And then you have this notion of a sub market, which means that there's like we used to call it white space back in the day, remember how many whites? Where's the white space? I mean if you're in the cloud, there's like a zillion white spaces. So talk about this sub market dynamic between markets and that are being enabled by the cloud players and how these sub markets play into it. >>Sure. So first, the first problem was what we did. We downloaded all the services for the big three clowns. Right? And you know what as recalls a database or database service like a document DB and amazon is like Cosmo dB and Azure. So first thing first is we had to like look at all three cloud providers and you? Re categorize all the services almost 500 Apples, Apples, Apples # one number two is you look at all these markets or sub markets and said, okay, how can we cluster these services into things that you know you and I can rock right. That's what amazon Azure and google think about. It is very different and the beauty of the cloud is this kind of fat long tail of services for developers. So instead of like oracle is a single database for all your needs. They're like 20 or 30 different databases from time series um analytics, databases. We're talking rocks at later today. Right. Um uh, document databases like Mongo search database like elastic. And so what happens is there's not one giant market like databases, there's a database market And 30, 40 sub markets that serve the needs developers. So the Great News is cloud has reduced the cost and create something that new for developers. Um also the good news is for a start up you can find plenty of white speeds solving a pain point, very specific to a different type of problem >>and you can sequence up to power law to this. I love the power of a metaphor, you know, used to be a very thin neck note no torso and then a long tail. But now as you're pointing out this expansion of the fat tail of services, but also there's big tam's and markets available at the top of the power law where you see coming like snowflake essentially take on the data warehousing market by basically sitting on amazon re factoring with new services and then getting a flywheel completely changing the economic unit economics completely changing the consumption model completely changing the value proposition >>literally you >>get Snowflake has created like a storm, create a hole, that mode or that castle wall against red shift. Then companies like rock set do your real time analytics is Russian right behind snowflakes saying, hey snowflake is great for data warehouse but it's not fast enough for real time analytics. Let me give you something new to your, to your parallel argument. Even the big optic snowflake have created kind of a wake behind them that created even more white space for Gaza rock set. So that's exciting for guys like me and >>you. And then also as we were talking about our last episode two or quarter two of our showcase. Um, from a VC came on, it's like the old shelf where you didn't know if a company's successful until they had to return the inventory now with cloud you if you're not successful, you know it right away. It's like there's no debate. Like, I mean you're either winning or not. This is like that's so instrumented so a company can have a good better mousetrap and win and fill the white space and then move up. >>It goes both ways. The cloud vendor, the big three amazon google and Azure for sure. They instrument their own class. They know john which ecosystem partners doing well in which ecosystems doing poorly and they hear from the customers exactly what they want. So it goes both ways they can weaponize that. And just as well as you started to weaponize that info >>and that's the big argument of do that snowflake still pays the amazon bills. They're still there. So again, repatriation comes back, That's a big conversation that's come up. What's your quick take on that? Because if you're gonna have a castle in the cloud, then you're gonna bring it back to land. I mean, what's that dynamic? Where do you see that compete? Because on one hand is innovation. The other ones maybe cost efficiency. Is that a growth indicator slow down? What's your view on the movement from and to the cloud? >>I think there's probably three forces you're finding here. One is the cost advantage in the scale advantage of cloud so that I think has been going for the past eight years, there's a repatriation movement for a certain subset of customers, I think for cost purposes makes sense. I think that's a tiny handful that believe they can actually run things better than a cloud. The third thing we're seeing around repatriation is not necessary against cloud, but you're gonna see more decentralized clouds and things pushed to the edge. Right? So you look at companies like Cloudflare Fastly or a company that we're investing in Cato networks. All ideas focus on secure access at the edge. And so I think that's not the repatriation of my own data center, which is kind of a disaggregated of cloud from one giant monolithic cloud, like AWS east or like a google region in europe to multiple smaller clouds for governance purposes, security purposes or legacy purposes. >>So I'm looking at my notes here, looking down on the screen here for this to read this because it's uh to cut and paste from your thesis on the cloud. The excellent cloud. The of the $38 billion invested this quarter. Um Ai and ml number one, um analytics. Number two, security number three. Actually, security number one. But you can see the bubbles here. So all those are data problems I need to ask you. I see data is hot data as intellectual property. How do you look at that? Because we've been reporting on this and we just started the cube conversation around workflows as intellectual property. If you have scale and your motives in the cloud. You could argue that data and the workflows around those data streams is intellectual property. It's a protocol >>I believe both are. And they just kind of go hand in hand like peanut butter and jelly. Right? So data for sure. I. P. So if you know people talk about days in the oil, the new resource. That's largely true because of powers a bunch. But the workflow to your point john is sticky because every company is a unique snowflake right? Like the process used to run the cube and your business different how we run our business. So if you can build a workflow that leverages the data, that's super sticky. So in terms of switching costs, if my work is very bespoke to your business, then I think that's competitive advantage. >>Well certainly your workflow is a lot different than the cube. You guys just a lot of billions of dollars in capital. We're talking to all the people out here jerry. Great to have you on final thought on your thesis. Where does it go from here? What's been the reaction? Uh No, you put it out there. Great love the restart. Think you're on point on this one. Where did we go from here? >>We have to follow pieces um in the near term one around, you know, deep diver on open source. So look out for that pretty soon and how that's been a powerful strategy a second. Is this kind of just aggregation of the cloud be a Blockchain and you know, decentralized apps, be edge applications. So that's in the near term two more pieces of, of deep dive we're doing. And then the goal here is to update this on a quarterly and annual basis. So we're getting submissions from founders that wanted to say, hey, you missed us or he screwed up here. We got the big cloud vendors saying, Hey jerry, we just lost his new things. So our goal here is to update this every single year and then probably do look back saying, okay, uh, where were we wrong? We're right. And then let's say the castle clouds 2022. We'll see the difference were the more unicorns were there more services were the IPO's happening. So look for some short term work from us on analytics, like around open source and clouds. And then next year we hope that all of this forward saying, Hey, you have two year, what's happening? What's changing? >>Great stuff and, and congratulations on the southern news. You guys put another half a billion dollars into early, early stage, which is your roots. Are you still doing a lot of great investments in a lot of unicorns. Congratulations that. Great luck on the team. Thanks for coming on and congratulations you nailed this one. I think I'm gonna look back and say that this is a pretty seminal piece of work here. Thanks for sharing. >>Thanks john thanks for having us. >>Okay. Okay. This is the cube here and 81 startup showcase. We're about to get going in on all the hot companies closing out the kino lisa uh, see jerry Chen cube alumni. He was right from day one. We've been riffing on this, but he nails it here. I think Greylock is lucky to have him as a general partner. He's done great deals, but I think he's hitting the next wave big. This is, this is huge. >>I was listening to you guys talking thinking if if you had a crystal ball back in 2013, some of the things Jerry saying now his narrative now, what did he have a crystal >>ball? He did. I mean he could be a cuBA host and I could be a venture capital. We were both right. I think so. We could have been, you know, doing that together now and all serious now. He was right. I mean, we talked off camera about who's the next amazon who's going to challenge amazon and Andy Jassy was quoted many times in the queue by saying, you know, he was surprised that it took so long for people to figure out what they were doing. Okay, jerry was that VM where he had visibility into the cloud. He saw amazon right away like we did like this is a winning formula and so he was really out front on this one. >>Well in the investments that they're making in these unicorns is exciting. They have this, this lens that they're able to see the opportunities there almost before anybody else can. And finding more white space where we didn't even know there was any. >>Yeah. And what's interesting about the report I'm gonna dig into and I want to get to him while he's on camera because it's a great report, but He says it's like 500 services I think Amazon has 5000. So how you define services as an interesting thing and a lot of amazon services that they have as your doesn't have and vice versa, they do call that out. So I find the report interesting. It's gonna be a feature game in the future between clouds the big three. They're gonna say we do this, you're starting to see the formation, Google's much more developer oriented. Amazon is much more stronger in the governance area with data obviously as he pointed out, they have such experience Microsoft, not so much their developer cloud and more office, not so much on the government's side. So that that's an indicator of my, my opinion of kind of where they rank. So including the number one is still amazon web services as your long second place, way behind google, right behind Azure. So we'll see how the horses come in, >>right. And it's also kind of speaks to the hybrid world in which we're living the hybrid multi cloud world in which many companies are living as companies to not just survive in the last year and a half, but to thrive and really have to become data companies and leverage that data as a competitive advantage to be able to unlock the value of it. And a lot of these startups that we talked to in the showcase are talking about how they're helping organizations unlock that data value. As jerry said, it is the new oil, it's the new gold. Not unless you can unlock that value faster than your competition. >>Yeah, well, I'm just super excited. We got a great day ahead of us with with all the cots startups. And then at the end day, Volonte is gonna interview, hello, fresh practitioners, We're gonna close it out every episode now, we're going to do with the closing practitioner. We try to get jpmorgan chase data measures. The hottest area right now in the enterprise data is new competitive advantage. We know that data workflows are now intellectual property. You're starting to see data really factoring into these applications now as a key aspect of the competitive advantage and the value creation. So companies that are smart are investing heavily in that and the ones that are kind of slow on the uptake are lagging the market and just trying to figure it out. So you start to see that transition and you're starting to see people fall away now from the fact that they're not gonna make it right, You're starting to, you know, you can look at look at any happens saying how much ai is really in there. Real ai what's their data strategy and you almost squint through that and go, okay, that's gonna be losing application. >>Well the winners are making it a board level conversation >>And security isn't built in. Great to have you on this morning kicking it off. Thanks John Okay, we're going to go into the next set of the program at 10:00 we're going to move into the breakouts. Check out the companies is three tracks in there. We have an awesome track on devops pure devops. We've got the data and analytics and we got the cloud management and just to run down real quick check out the sis dig harness. Io system is doing great, securing devops harness. IO modern software delivery platform, White Source. They're preventing and remediating the rest of the internet for them for the company's that's a really interesting and lumbago, effortless acres land and monitoring functions, server list super hot. And of course hacker one is always great doing a lot of great missions and and bounties you see those success continue to send i O there in Palo alto changing the game on data engineering and data pipe lining. Okay. Data driven another new platform, horizontally scalable and of course thought spot ai driven kind of a search paradigm and of course rock set jerry Chen's companies here and press are all doing great in the analytics and then the cloud management cost side 80 operations day to operate. Ops ramps and ops multi cloud are all there and sunny, all all going to present. So check them out. This is the Cubes Adria's startup showcase episode three.

>>let's bring in jerry Chen from Greylock is he here? Let's bring him in there? He is. >>Hey john good to see you. >>Hey congratulations on an amazing talk and thesis on the castles on the cloud. Thanks for coming on. >>All right, well thanks for reading it. Um, always were being put a piece of work out out of the ether, not sure what the responses, but it seemed to resonate with a bunch of developers, founders, investors and folks like yourself. So smart people seem to gravitate to us. So thank you very much. >>Well, one of the benefits of doing the Cube for 11 years, Jerry's, we have videotape of many, many people talking about what the future will hold. You kind of are on this early, it wasn't called castles in the cloud, but you were all, I was, we had many conversations were kind of connecting the dots in real time, but you've been on this for a while it's great to see the work. I really think you nailed this. I think you're absolutely on point here. So let's get into it. What is castles in the cloud? New research come out from Greylock that you spearheaded? It's collaborative effort, but you've got data behind it. Give a quick overview of what is castle the cloud, The new modes of competitive advantage for companies. >>Yeah, it's as a group project that our team put together but basically john the question is how do you win in the cloud? Remember the conversation we had eight years ago when amazon re event was holy cow like can you compete with them? Like is it a winner? Take all, Winner take most. And if it is winner take most. Where are the white spaces for some starts to to emerge clearly the past eight years in the cloud this journey we've seen big companies data breaks, snowflakes, elastic mongo data robot. And so um they spotted the question is you know, why are the castles in the cloud? The big three cloud providers amazon google and as you're winning, you know, what advantage do they have? And then given their modes of scale network effects, how can you as a startup win? And so look, there are 500 plus services between all three cloud vendors but there are like 500 plus um startups, competing gets a cloud vendors and there's like almost 100 unicorn of private companies competing successfully against the cloud vendors, including public companies. So like Alaska Mongo snowflake, No data breaks. Not public yet. Hashtag or not public yet. These are some examples of the names that I think are winning and watch this space because you see more of these guys storm the castle if you will. >>Yeah. And you know one of the things that's a funny metaphor because it has many different implications. One, as we talk about security, the perimeter of the gates, the most being on land, but now you're in the cloud, you have also different security paradigm. You have a different um new kinds of services that are coming on board faster than ever before, not just from the cloud players, but from companies contributing into the ecosystem. So the combination of the big three making the market the main markets, you, I think you call it 31 markets that we know of that probably maybe more. And then you have this notion of sub market, which means that there's like, we used to call it white space back in the day. Remember how many whites? Where's the white space? I mean if you're in the cloud there's like a zillion white spaces. So talk about this sub market dynamic between markets and that are being enabled by the cloud players and how these sub markets play into it. >>Sure. So first, the first problem was what we did, we downloaded all the services for the big three clowns. Right. And you know what as recalls a database or database service, like a document dB and amazon is like Cosmo, dB and Azure. So first thing first is we had to like look at all three cloud providers and you? Re categorize all the services almost 500 Apples, Apples, Apples, # one. Number two, is you look at all these markets or sub markets and said, okay, how can we cluster these services into things that you know, you and I can rock. Right, That's what amazon as well. And google think about it is very different. And the beauty of the cloud is this kind of fat long tail of services for developers. So instead of like oracle as a single database for all your needs, they're like 20 or 30 different databases from time series um, analytics, databases we're talking rocks at later today, right? Um uh, document databases like mongo search database like elastic and so what happens is there's not one giant market like databases, there's a database market and 30 40 sub markets that serve the needs developers. So the Great News is cloud has reduced the cost and create something that new for developers. Um also the good uses for a start up, you can find plenty of white speech solving a pain point very specific to a different type of problem >>and you can sequence up the power law to this. I love the power of a metaphor, you know, used to be a very thin neck note no torso and then a long tail. But now as you're pointing out this expansion of the fat tail of services but also this big tam's and markets available at the top of the power law where you see coming like snowflake essentially take on the data warehousing market by basically sitting on amazon and re factoring with new services and then getting a flywheel completely changing the economic unit economics completely changing the consumption model completely changing the value proposition literally >>you snowflake has created like storm create a hole that mode or that castle wall against red shift. Then companies like rock set real time analytics, It's Russian right behind snowflakes saying, hey snowflake is great for data warehouse, but it's not fast enough for real time analytics. Let me give you something new to your, your parallel argument. Even the big optics snowflake have created kind of a wake behind them that created even more white space for Gaza rock set. So that's exciting for guys like media. >>And then also as we were talking about our last episode two or quarter two of our showcase, um, from a VC came on, it's like the old shelf where you didn't know if a company's successful until they had to return the inventory now with cloud. If you're not successful, you know it right away. It's like, it's like there's no debate. Like, I mean you're either winning or not. This is like that's so instrumented. So a company can have a good better mousetrap and win and fill the white space and then move up. >>It goes both ways. The cloud vendor, the big three amazon google and Azure for sure. They instrument their own class. They know john which ecosystem partners doing well in which ecosystems doing poorly and they hear from the customers exactly what they want. So it goes both ways they can weaponize that just as well as you started to weaponize that info >>and that's the big argument of do that snowflake still pays the amazon bills, they're still there. So again, repatriation comes back. That's a big conversation that's come up. Um, what's your quick take on that? Because if you're gonna have a castle in the cloud, then you're gonna bring it back to land. I mean, what's that dynamic? Where do you see that compete? Because on one hand is innovation, the other ones maybe cost efficiency. Is that a growth indicator? Slow down? What's your view on the movement from and to the cloud? >>I think there's probably three forces you're finding here. One is the cost advantage in the scale advantage of cloud. So that I think has been going for the past eight years. There's a repatriation movement for a certain subset of customers, I think for cost purposes makes sense. I think that's a tiny handful that believe they can actually run things better than a cloud. The third thing we're seeing around repatriation is not necessary against cloud, but you're gonna see more decentralized clouds and things pushed to the edge. Right? So you look at companies like Cloudflare Fastly or a company that we're investing in Cato networks. All ideas focus on secure access at the edge. And so I think that's not repatriation of my own data center, but it's kind of a disaggregated of cloud from one giant monolithic cloud, like AWS East or like a google region in europe to multiple smaller clouds for governance purposes, security purposes or legacy purposes. >>So I'm looking at my notes here, looking down on the screen here for this to read this because it's uh to cut and paste from your thesis on the cloud, the cloud. The of the $38 billion invested uh this quarter. Um uh Ai and ml number one um analytics number two, security number three. Actually security number one. But you can see the bubbles here. So all those are data problems I need to ask you. I see data is hot data as intellectual property. How do you look at that? Because we've been reporting on this and we just started the cube conversation around workflows as intellectual property. If you have scale and your motives in the cloud, you could argue that data and the workflows around those data streams is intellectual property, it's a protocol. >>I believe both are. And they just kind of go hand in hand like peanut butter and jelly. Right? So data for sure. I p So if you know people talk about days in the oil, the new resource. That's largely true because the powers a bunch. But the workflow to your point john is sticky because every company is a unique snowflake, right? Like the process used to run the cube and your business different how we run our business. So if you can build a workflow that leverages the data that's super sticky. So in terms of switching costs, if my work is very bespoke to your business then I think that's competitive advantage. >>Well certainly your workflow is a lot different than the cube. You guys. Just a lot of billions of dollars in capital. Uh, we're talking to all the people out here jerry. Great to have you on final thought on your thesis. Where does it go from here? What's been the reaction? Uh, no, you put it out there. Great, love the research. I think you're on point on this one. Where did, where's it go from here? >>We have to follow pieces. Um, in the near term one around, you know, deep diver on open source. So look out for that pretty soon. And how that's been a powerful strategy a second is this kind of disaggregated of the cloud be a Blockchain and you know, decentralized apps, be edge applications. So that's in the near term two more pieces of, of deep dive we're doing. And then the goal here is to update this on a quarterly and annual basis. So we're getting submissions from founders that wanted to say, hey, you missed us Or he screwed up here. We got the big cloud vendors saying, Hey jerry, we just lost his new things. So our goal here is to update this every single year and then probably do look back saying, okay, uh, were we wrong? We're right. And then let's say the castle clouds 2022 we'll see the difference were the more unicorns, were there more services were the IPO's happening. So look for some short term work from us on analytics, like around open source and clouds. And then next year we hope that all this forward saying, Hey, you have two year, what's happening? What's changing? >>Great stuff And, and congratulations on the Southern news. You guys put another half a billion dollars into early, early stage, which is your roots. Are you still doing a lot of great investments in a lot of unicorns? Congratulations that great luck on the team. Thanks for coming on And congratulations. You nailed this one. I think I'm gonna look back and say that this is a pretty seminal piece of work here. Thanks for for sharing. >>Thanks john, Thanks for having me as >>always.

>> From theCUBE studios in Palo Alto in Boston, bringing you data-driven insights from theCUBE and ETR. This is braking analysis with Dave Vellante. >> Techniques to protect sensitive data have evolved over thousands of years, literally. The pace of modern data protection is rapidly accelerating and presents both opportunities and threats for organizations. In particular, the amount of data stored in the cloud combined with hybrid work models, the clear and present threat of cyber crime, regulatory edicts, and the ever expanding edge and associated use cases should put CXOs on notice that the time is now to rethink your data protection strategies. Hello, and welcome to this week's Wikibon Cube Insights powered by ETR. In this breaking analysis, we're going to explore the evolving world of data protection and share some information on how we see the market changing in the competitive landscape for some of the top players. Steve Kenniston, AKA the Storage Alchemist, shared a story with me, and it was pretty clever. Way back in 4000 BC, the Sumerians invented the first system of writing. Now, they used clay tokens to represent transactions at that time. Now, to prevent messing with these tokens, they sealed them in clay jars to ensure that the tokens, i.e the data, would remain secure with an accurate record that was, let's call it quasi, immutable, and lived in a clay vault. And since that time, we've seen quite an evolution of data protection. Tape, of course, was the main means of protecting data and backing data up during most of the mainframe era. And that carried into client server computing, which really accentuated and underscored the issues around backup windows and challenges with RTO, recovery time objective and RPO recovery point objective. And just overall recovery nightmares. Then in the 2000's data reduction made disk-based backup more popular and pushed tape into an archive last resort media. Data Domain, then EMC, now Dell still sell many purpose-built backup appliances as do others as a primary backup target disc-based. The rise of virtualization brought more changes in backup and recovery strategies, as a reduction in physical resources squeezed the one application that wasn't under utilizing compute, i.e, backup. And we saw the rise of Veem, the cleverly-named company that became synonymous with data protection for virtual machines. Now, the cloud has created new challenges related to data sovereignty, governance, latency, copy creep, expense, et cetera. But more recently, cyber threats have elevated data protection to become a critical adjacency to information security. Cyber resilience to specifically protect against attacks is the new trend being pushed by the vendor community as organizations are urgently looking for help with this insidious threat. Okay, so there are two major disruptors that we're going to talk about today, the cloud and cyber crime, especially around ransoming your data. Every customer is using the cloud in some way, shape, or form. Around 76% are using multiple clouds, that's according to a recent study by Hashi Corp. We've talked extensively about skill shortages on theCUBE, and data protection and security concerns are really key challenges to address, given that skill shortage is a real talent gap in terms of being able to throw people at solving this problem. So what customers are doing, they're either building out or they're buying really mostly building abstraction layers to hide the underlying cloud complexity. So what this does... The good news is it's simplifies provisioning and management, but it creates problems around opacity. In other words, you can't see sometimes what's going on with the data. These challenges fundamentally become data problems, in our view. Things like fast, accurate, and complete backup recovery, compliance, data sovereignty, data sharing. I mentioned copy creep, cyber resiliency, privacy protections. These are all challenges brought to fore by the cloud, the advantages, the pros, and the cons. Now, remote workers are especially vulnerable. And as clouds span rapidly, data protection technologies are struggling to keep pace. So let's talk briefly about the rapidly-expanding public cloud. This chart shows worldwide revenue for the big four hyperscalers. As you can see, we projected that they're going to surpass $115 billion in revenue in 2021. That's up from 86 billion last year. So it's a huge market, it's growing in the 35% range. The interesting thing is last year, 80-plus billion dollars in revenue, but 100 billion dollars was spent last year by these firms in cap ex. So they're building out infrastructure for the industry. This is a gift to the balance of the industry. Now to date, legacy vendors and the surrounding community have been pretty defensive around the cloud. Oh, not everything's going to move to the cloud. It's not a zero sum game we hear. And while that's all true, the narrative was really kind of a defensive posture, and that's starting to change as large tech companies like Dell, IBM, Cisco, HPE, and others see opportunities to build on top of this infrastructure. You certainly see that with Arvind Krishna comments at IBM, Cisco obviously leaning in from a networking and security perspective, HPE using language that is very much cloud-like with its GreenLake strategy. And of course, Dell is all over this. Let's listen to how Michael Dell is thinking about this opportunity when he was questioned on the queue by John Furrier about the cloud. Play the clip. So in my view, Michael nailed it. The cloud is everywhere. You have to make it easy. And you have to admire the scope of his comments. We know this guy, he thinks big. He said, "Enables everything." He's basically saying is that technology is at the point where it has the potential to touch virtually every industry, every person, every problem, everything. So let's talk about how this informs the changing world of data protection. Now, we all know, we've seen with the pandemic, there's an acceleration in toward digital, and that has caused an escalation, if you will, in the data protection mandate. So essentially what we're talking about here is the application of Michael Dell's cloud everywhere comments. You've got on-prem, private clouds, hybrid clouds. You've got public clouds across AWS, Azure, Google, Alibaba. Really those are the big four hyperscalers. You got many clouds that are popping up all their place. But multi-cloud, to that Hashi Corp data point, 75, 70 6%. And then you now see the cloud expanding out to the edge, programmable infrastructure heading out to the edge. So the opportunity here to build the data protection cloud is to have the same experiences across all these estates with automation and orchestration in that cloud, that data protection cloud, if you will. So think of it as an abstraction layer that hides that underlying complexity, you log into that data protection cloud, it's the same experience. So you've got backup, you've got recovery, you can handle bare metal. You can do virtualized backups and recoveries, any cloud, any OS, out to the edge, Kubernetes and container use cases, which is an emerging data protection requirement. And you've got analytics, perhaps you've got PII, personally identifiable information protection in there. So the attributes of this data protection cloud, again, abstracts the underlying cloud primitives, takes care of that. It also explodes cloud native technologies. In other words, it takes advantage of whether it's machine learning, which all the big cloud players have expertise in, new processor models, things like graviton, and other services that are in the cloud natively. It doesn't just wrap it's on-prem stack in a container and shove it into the cloud, no. It actually re architects or architects around those cloud native services. And it's got distributed metadata to track files and volumes and any organizational data irrespective of location. And it enables sets of services to intelligently govern in a federated governance manner while ensuring data integrity. And all this is automated and an orchestrated to help with the skills gap. Now, as it relates to cyber recovery, air-gap solutions must be part of the portfolio, but managed outside of that data protection cloud that we just briefly described. The orchestration and the management must also be gaped, if you will. Otherwise, (laughs) you don't have an air gap. So all of this is really a cohort to cyber security or your cybersecurity strategy and posture, but you have to be careful here because your data protection strategy could get lost in this mess. So you want to think about the data protection cloud as again, an adjacency or maybe an overlay to your cybersecurity approach. Not a bolt on, it's got to be fundamentally architectured from the bottom up. And yes, this is going to maybe create some overheads and some integration challenges, but this is the way in which we think you should think about it. So you'll likely need a partner to do this. Again, we come back to the skill skills gap if we're seeing the rise of MSPs, managed service providers and specialist service providers. Not public cloud providers. People are concerned about lock-in, and that's really not their role. They're not high-touch services company. Probably not your technology arms dealer, (clear throat) excuse me, they're selling technology to these MSPs. So the MSPs, they have intimate relationships with their customers. They understand their business and specialize in architecting solutions to handle these difficult challenges. So let's take a look at some of the risk factors here, dig a little bit into the cyber threat that organizations face. This is a slide that, again, the Storage Alchemists, Steve Kenniston, shared with me. It's based on a study that IBM funds with the Panmore Institute, which is a firm that studies these things like cost of breaches and has for many, many, many years. The slide shows the total cost of a typical breach within each dot and on the Y axis and the frequency in percentage terms on the horizontal axis. Now, it's interesting. The top two compromise credentials and phishing, which once again proves that bad user behavior trumps good security every time. But the point here is that the adversary's attack vectors are many. And specific companies often specialize in solving these problems often with point products, which is why the slide that we showed from Optiv earlier, that messy slide, looks so cluttered. So there's a huge challenge for companies. And that's why we've seen the emergence of cyber recovery solutions from virtually all the major players. Ransomware and the solar winds hack have made trust the number one issue for CIOs and CISOs and boards of directors. Shifting CISO spending patterns are clear. They're shifting largely because they're catalyzed by the work from home. But outside of the moat to endpoint security, identity and access management, cloud security, the horizontal network security. So security priorities and spending are changing. And that's why you see the emergence of disruptors like we've covered extensively, Okta, CrowdStrike, Zscaler. And cyber resilience is top of mind, and robust solutions are required. And that's why companies are building cyber recovery solutions that are most often focused on the backup corpus because that's a target for the bad guys. So there is an opportunity, however, to expand from just the backup corpus to all data and protect this kind of 3, 2, 1, or maybe it's 3, 2, 1, 1, three copies, two backups, a backup in the cloud and one that's air gaped. So this can be extended to primary storage, copies, snaps, containers, data in motion, et cetera, to have a comprehensive data protection strategy. And customers, as I said earlier, are increasingly looking to manage service providers and specialists because of that skills gap. And that's a big reason why automation is so important in orchestration. And automation and orchestration, I'll emphasize, on the air gap solutions should be separated physically and logically. All right, now let's take a look at some of the ETR data and some of the players. This is a chart that we like to show often. It's a X-Y axis. And the Y axis is net score, which is a measure of spending momentum. And the horizontal axis is market share. Now, market share is an indicator of pervasiveness in the survey. It's not spending market share, it's not market share of the overall market, it's a term that ETR uses. It's essentially market share of the responses within the survey set. Think of it as mind share. Okay, you've got the pure plays here on this slide, in the storage category. There is no data protection or backup category. So what we've done is we've isolated the pure plays or close to pure plays in backup and data protection. Now notice that red line, that red is kind of our subjective view of anything that's over that 40% line is elevated. And you can see only Rubrik, and the July survey is over that 40% line. I'll show you the ends in a moment. Smaller ends, but still, Rubrik is the only one. Now, look at Cohesity and Rubrik in the January 2020. So last year, pre-pandemic, Cohesity and Rubrik, they've come well off their peak for net score. Look at Veeam. Veeam, having studied this data for the last say 24 hours months, Veeam has been steady Eddy. It is really always in the mid to high 30s, always shows a large shared end, so it's coming up in the survey. Customers are mentioning Veeam. And it's got a very solid net score. It's not above that 40% line, but it's hovering just below consistently. That's very impressive. Commvault has steadily been moving up. Sanjay Mirchandani has made some acquisitions. He did the Hedvig acquisition. They launched Metallic, that's driving cloud affinity within Commvault's large customer base. So it's good example of a legacy player pivoting and evolving and transforming itself. Veritas, it continues to under perform in the ETR surveys relative to the other players. Now, for context, let's add IBM and Dell to the chart. Now just note, this is IBM and Dell's full storage portfolio. The category in the taxonomy at ETR is all storage. Just previous slide, I isolated on the pure plays. But this now adds in IBM and Dell. It probably representative of where they would be. Probably Dell larger on the horizontal axis than IBM, of course. And you could see the spending momentum accordingly. So you can see that in the data chart that we've inserted. So some smaller ends for Rubrik and Cohesity. But still enough to pay attention, it's not like one or two. When you're 20-plus, 15-plus 25-plus, you can start to pay attention to trends. Veeam, again, is very impressive. It's net score is solid, it's got a consistent presence in the dataset, it's clear leader here. SimpliVity is small, but it's improving relative to last several surveys. And we talked about Convolt. Now, I want to emphasize something that we've been hitting on for quite some time now. And that's the Renaissance that's coming in compute. Now, we all know about Moore's Law, the doubling of transistor density every two years, 18 to 24 months. And that leads to a doubling of performance in that timeframe. X86, that x86 curve is in the blue. And if you do the math, this is expressed in trillions of operations per second. The orange line is representative of Apples A series, culminating in the A15, most recently. The A series is what Apple is now... Well, it's the technology basis for what's inside M1, the new Apple laptops, which is replacing Intel. That's that that orange line there, we'll come back to that. So go back to the blue line for a minute. If you do the math on doubling performance every 24 months, it comes out to roughly 40% annual improvement in processing power per year. That's now moderated. So Moore's Law is waning in one sense, so we wrote a piece Moore's Law is not dead. So I'm sort of contradicting myself there. But the traditional Moore's Law curve on x86 is waning. It's probably now down to around 30%, low 30s. But look at the orange line. Again, using the A series as an indicator, if you combine then the CPU, the NPU, which neuro processing unit, XPU, pick whatever PU you want, the accelerators, the DSPs, that line is growing at 100% plus per year. It's probably more accurately around 110% a year. So there's a new industry curve occurring, and it's being led by the Arm ecosystem. The other key factor there, and you're seeing this in a lot of use cases, a lot of consumer use cases, Apple is an example, but you're also seeing it in things like Tesla, Amazon with AWS graviton, the Annapurna acquisition, building out graviton and nitro, that's based on Arm. You can get from design to tape out in less than two years. Whereas the Intel cycles, we know, they've been running it four to five years now. Maybe Pat Gelsinger is compressing those. But Intel is behind. So organizations that are on that orange curve are going to see faster acceleration, lower cost, lower power, et cetera. All right, so what's the tie to data protection. I'm going to leave you with this chart. Arm has introduced it's confidential, compute architecture and is ushering in a new era of security and data protection. Zero trust is the new mandate. And what Arm has it's done with what they call realms is create physical separation of the vulnerable components by creating essentially physical buckets to put code in and to put data in, separate from the OS. Remember, the OS is the most valuable entry point for hackers or one of them because it contains privileged access, and it's a weak link because of things like memory leakages and vulnerabilities. And malicious code can be placed by bad guys within data in the OS and appear benign, even though it's anything but. So in this, all the OS does is create API calls to the realm controller. That's the only interaction. So it makes it much harder for bad actors to get access to the code and the data. And importantly, very importantly, it's an end-to-end architecture. So there's protection throughout. If you're pulling data from the edge and bringing it back to the on-prem or the cloud, you've got that end to end architecture and protection throughout. So the link to data protection is that backup software vendors need to be the most trusted of applications. Backup software needs to be the most trusted of applications because it's one of the most targeted areas in a cyber attack. Realms provide an end-to-end separation of data and code from the OS and it's a better architectural construct to support zero trust and confidential computing and critical use cases like data protection/backup and other digital business apps. So our call to action is backup software vendors, you can lead the charge. Arm is several years ahead at the moment, ahead of Intel, in our view. So you've got to pay attention to that, research that. We're not saying over rotate, but go investigate that. And use your relationships with Intel to accelerate its version of this architecture. Or ideally, the industry should agree on common standards and solve this problem together. Pat Gelsinger told us in theCUBE that if it's the last thing he's going to do in his industry life, he's going to solve this security problem. That's when he was at VMware. Well, Pat, you're even in a better place to do it now. You don't have to solve it yourself, you can't, and you know that. So while you're going about your business saving Intel, look to partner with Arm. I know it sounds crazy to use these published APIs and push to collaborate on an open source architecture that addresses the cyber problem. If anyone can do it, you can. Okay, that's it for today. Remember, these episodes are all available as podcasts. All you got to do is search Braking Analysis Podcast. I publish weekly on wikibond.com and siliconangle.com. Or you can reach me @dvellante on Twitter, email me at david.vellante@siliconangle.com. And don't forget to check out etr.plus for all the survey and data action. This is Dave Vellante for theCUBE Insights, powered by ETR. Thanks for watching, everybody. Be well, and we'll see you next time. (gentle music)

(upbeat music) >> There are many constants in the storage business, relentlessly declining costs per bit. Innovations that perpetually battle the laws of physics, a seemingly endless flow of venture capital, very intense competition. And there's one other constant in the storage industry, Eric Herzog. And he joins us today in this CUBE video exclusive to talk about IBM's recent storage announcements. Eric, welcome back to theCUBE. Great to see you, my friend. >> Great Dave, thank you very much. Of course, IBM always loves to participate with theCUBE and everything you guys do. Thank you very much for inviting us to come today. >> Really our pleasure. So we're going to cover a lot of ground. IBM Storage made a number of announcements this month around data resilience. You've got a new as a service model. You've got performance enhancements. Eric, can you give us, give us the top line summary of the hard news? >> Yeah. Top line. IBM is enhancing data and cyber resiliency across all non mainframe platforms. We already have it on the mainframe of course, and we're changing CapEx to OpEx with our storage as a service. Those are the key takeaways and the hot ticket items from an end user perspective. >> So maybe we could start with sort of the cyber piece. I mean, wow. I mean the last 18 months have been incredible and you're just seeing, you know, new levels of threats. The work from home pivot has created greater exposure. Organizations are kind of rethinking hybrid. You're seeing the ascendancy of some of the sort of hot cyber startups, but, but you're also seeing the, not only of the attack vectors winded, but the, the techniques are different. You know, threat hunting has become much more important. Your responses to threats. You have to be really careful the whole ransomware thing. So what are some of the big trends that you guys are seeing that are kind of informing how you approach the market? >> Well, first of all, it's gotten a lot worse. In fact, Fortune magazine just released the Fortune 500 a couple of weeks ago, and they had a survey that's public of CEOs, and they said, "What's the number one threat to your business? With no list just what's the number one threat?" Cyber security was number one 66% of the Fortune 500 Chief Executive Officers. Not CIOs not CTOs, but literally the CEOs of the biggest companies in the world. However, it's not just big companies. It hits the mid size, the small companies, everyone is open now to cyber threats and cyber attacks. >> Yeah. So for sure. And it's (chuckles) across the board. Let's talk about your solution, the announcement that you made here. Safeguard Copy, I think is what the branding is. >> Yeah. So what we've done is we've got a number of different technologies within our storage portfolio. For example, with our Spectrum Protect product, we can see anomalous pattern detection and backup data sets. Why would that matter? If I am going to hold theCUBE for ransom, if I don't get control of your secondary storage, snaps, replicas, and backups, you can just essentially say, I'm not paying you. You could just do a recovery, right? So we have anomalous protection there. We see encryption, we encrypt at rest with no performance penalty with our FlashSystem's family. We do air gapping. And in case of safeguarded copy, it's a form of air gapping. So we see physical air gapping with tape. logical air gapping, but to a remote location with snaps or replicas to your Cloud provider, and then local logical on-prem, which is what safeguarded copy does. We've had this technology for many years now on the mainframe platform. And we brought it down to the non mainframe environments, Linux, UNIX, and the Windows Server world by putting safeguarded copy on our FlashSystem's portfolio. >> So, okay. So part of the strategy is air gapping. So you're taking a copy, your air gapping it. You probably, you probably take those snaps, you know, at different intervals, you mix that up, et cetera. How do you manage the copies? How do you ensure if I have to do a recovery that you've got kind of a consistent data set? >> Yeah. So a couple things, first of all, we can create on a single FlashSystem array the full array up to 15,000 immutable copies, essentially they're weren't, you can't delete them, you can't change them. On a per volume basis, you can have 255. This is all managed with our storage copy manager, which can automate the entire process. Creation, deletion, frequency, and even recovery mode. So for example, I could have volume one and volume one perhaps I need to make immutable copies every four hours, while at 255 divided by four a day, I can go for many months and still be making those immutable copies. But with our Copy Services Manager, you can set up to be only 30 days, 60 days, you can set the frequency and once you set it up, it's all automated. And you can even integrate with IBM's QRadar, which is a threat detection and breach software from the security division of IBM. And when certain threats hit, it can actually automatically kick off a safeguarded copy. So what we do is make sure you've got that incredibly rapid recovery. And in fact, you can get air gapping, remotely. We have this on the main frame and a number of large global Fortune 500's actually do double air gapping, local logical, right? So they can do recovery in just a couple hours if they have an attack. And then they take that local logical and either go remote logical. Okay. Which gives them a second level of protection, or they'll go out to tape. So you can use this in a myriad of ways. You can have multiple protection. We even, by the way Dave, have three separate different admin levels. So you can have three different types of admins. One admin can't delete, one admin can. So that way you're also safe from what I'll call industrial espionage. So you can never know if someone's going to be stealing stuff from inside with multiple administrative capabilities, it makes it more difficult for someone to steal your data and then sell it to somebody. >> So, okay. Yeah, right. Because immutable is sort of, well, you're saying that you can set it up so that only one admin has control over that, is that right? If you want it... >> There's three, there's three admins with different levels of control. >> Right. >> And the whole point of having a three admins with different levels of control, is you have that extra security from an internal IT perspective versus one person, again, think of the old war movies, you know, nuclear war movies. Thank God it's never happened. Where two guys turn the key. So you've got some protection, we've got multiple admin level to do that as well. So it's a great solution with the air gapping. It's rapid recovery because it's local, but it is fully logically air gapped separated from the host. It's immutable, it's WORM, Write Once, Read Many can't delete can't change. Can't do anything. And you can automate all the management with our Copy Services Manager software that will work with safeguard copy. >> You, you talked about earlier, you could detect anomalous behavior. So, so presumably this can help with, with detecting threats, is that? >> Well, that's what our spectrum protect product does. My key point was we have all levels of data resiliency across the whole portfolio, whether it be encrypting data at rest, with our VTLs, we can encrypt in-flight. We have safeguarded copy on the mainframe, safeguarded copy on FlashSystems, any type of storage, including our competitor storage. You could air gap it to tape, right? With our spectrum virtualized software in our SAN Volume Controller, you could actually air gap out to a Cloud for 500 arrays that aren't even ours. So what we've done is put in a huge set of data and cyber resiliency across the portfolio. One thing that I've noticed, Dave, that's really strange. Storage is intrinsic to every data center, whether you're big, medium, or small. And when most people think about a cybersecurity strategy from a corporate perspective, they usually don't even think about storage. I've been shocked, but I've been in meetings with CEOs and VPs and they said, "oh, you're right, storage is, is a risk." I don't know why they don't think of it. And clearly many of the security channel partners, right? You have channel that are very focused on security and security consultants, they often don't think about the storage gaps. So we're trying to make sure, A, we've got broad coverage, primary storage, secondary storage, backup, you know, all kinds of things that we can do. And we make sure that we're talking to the end users, as well as the channel to realize that if you don't have data resilience storage, you do not have a corporate cybersecurity strategy because you just left out the storage part. >> Right on. Eric, are you seeing any use case patterns emerge in the customer base? >> Well, the main use case is prioritizing workloads. Obviously, as you do the immutable copies, you chew up capacity. Right now there's a good reason to do that. So you've got these immutable copies, but what they're doing is prioritizing workloads. What are the workloads? I absolutely have to have up and going rapidly. What are other workloads that are super important, but I could do maybe remote logical air gapping? What ones can I put out to tape? Where I have a logical, where I have a true physical air gap. But of course tape can take a long recovery time. So they're prioritizing their applications, workloads and use case to figure out what they need to have a safeguarded copy with what they could do. And by the way, they're trying to do that as well. You know, with our FlashSystem products, we could encrypt data at rest with no performance penalty. So if you were getting, you know, 30,000 database records and they were taken, you know, 10 seconds for sake of argument, when you encrypt, normally you slow that down. Well, guess what, when you encrypt with our FlashSystem product. So in fact, you know, it's interesting Dave, we have a comprehensive and free cyber resiliency assessment, no charge to the end-user, no charge to a business partner if they want to engage with us. And we will look at based on the NIST framework, any gaps. So for example, if theCUBE said, these five databases are most critical databases, then part of our cyber resilience assess and say, "ah, well, we noticed that you're not encrypting those. Why are you not encrypting those?" And by the way, that cyber resilience assessment works not only for IBM storage, but any storage estate they've got. So if they're homogenous, we can evaluate that if they're heterogeneous in their storage estate would evaluate that, and it is vendor agnostic and conforms to the NIST framework, which of course is adopted all over the world. And it's a great thing for people to get free, no obligation. You don't have to buy a single thing from IBM. It's just a free assessment of their storage and what cyber security exposure they have in their storage estate. And that's a free thing that we offer that includes safeguarded copy, encryption, air gapping, all the various functionality. And we'll say, "why are you not encrypting? Why are you not air gapping?" That if it's that important, "what, why are you leaving these things exposed?" So that's what our free cyber resilience assessment does. >> Got to love those freebies take advantage of those for sure. A lot of, a lot of organizations will charge big bucks for those. You know, maybe not ridiculously huge bucks, but you're talking tens of thousands. Sometimes you'll get up to hundreds of thousands of dollars for that type of type of assessment. So that's, you've got to take advantage of that if you're a customer out there. You know, I, I wanted to ask you about just kind of shift topics here and get into the, as a service piece of it. So you guys announced your, your as a service for storage, a lot of people have also done that. What do we need to know about the IBM Solution? And what's different from the others, maybe two part question, but what's the first part. What do we need to know? >> A couple of thing is, from an overall strategy perspective, you don't buy storage. It's a full OpEx model. IBM retains legal title. We own it. We'll do the software upgrades as needed. We may even go ahead and swap the physical system out. You buy an SLA, a tier if you will. You buy capacity, performance, we own it. So let's take an easy one. Our tier two, we give you our worst case performance at 2,250 IOPS per terabyte. Our competitors by the way, when you look at their contracts and look what they're putting out there, they will give you their best case number. So if they're two is 2,250, that's the best case. With us it's our worst case, which means if your applications or workloads get 4,000 IOPS per terabyte, it's free. We don't charge you for that. We give you the worst case scenario and our numbers are higher than our competition. So we make sure that we're differentiated true OpEx model. It's not a modified Lease model. So it's truly converts CapEx into operational expense. We have a base as everybody does, but we have a variable. And guess what? There's the base price and the variable price are the same. So if you don't use the variable, we don't charge you. We bill you for 1/4 in arrears, every feature function that's on our FlashSystem technology such as safeguarded copy, which we just talked about. AI based tiering, data at rest encryption with no performance penalty, data in compression with no performance, all those features you get, all of them, all we're doing is giving you an option. We still let you buy CapEx. We will let you lease with IBM Global Financial Services. And guess what? You could do a full OpEx model. The technology though, our flash core modules, our spectrum virtualized software is all the same. So it's all the same feature function. It's not some sort of stripped down model. We even offer Dave, 100% availability option. We give Six Nines of availability as a default, several of the competitor, which is only five minutes and 26 seconds of downtime, several of our competitors, guess what they give? Fournines. If you want five or six, you got to pay for it. We just give you six as a default differentiator, but then we're the only vendor to offer 100% availability guarantee. Now that is an option. It's the one option. But since we're already at Six Nines, when our competitors are at Four or Five Nines, we already have better availability with our storage as a service than the competition does. >> So let me just make this, make sure I'm clear on this. So you got Six Nines as part of the service. That's >> Absolutely >> Fundamental. And I get, I can pay up for 100% availability option. And, >> Yes you can. >> So what does that, what does that mean? Practically? You're putting in redundancies and, >> Right, right. So we have a technology known as HyperSwap. We have several public references by the way, at ibm.com. We've been shipping HyperSwap on both the mainframe, probably eight or nine years now. We brought it to our FlashSystem product probably five years ago. As I mentioned, we've got public references. You don't pay for the software by the way, you do have to have a dual node cluster. And HyperSwap allows you to do that. But you can do that as a service. You can buy it. You can do as CapEx, right? When you need the additional FlashSystem to go with it again, the software is free. So you're not to pay for the software. You just have to pay for the additional system level componentry, but you can do that as a service and have it completely be an OpEx model as well. We even assign a technical account manager to every account. Every account gets a technical account manager. If you will, concierge service comes with every OpEx version of our storage as a service. >> So what does that mean? What does that concierge do? Just paying attention to (indistinct) >> Concierge service will do a quarterly, a quarterly review with you. So let's say theCUBE bought 10,000 other analyst firms in the industry. You're now the behemoth. And you at theCUBE are using IBM storage as a service. You call up your technical account manager to say, "Guess what? We just bought these companies. We're going to convert them all to storage as a service, A, we need a higher tier, you could upgrade the tier B, we have a one-year contract, but you know what we'd like to extend it to two, C, we think we need more capacity." You tell your technical account manager, they'll take care of all of that for you, as well as giving you best practices. For example, if you decide you want to do safeguarded copy, which you can do, because it's built into our spectrum virtualized software, which is part of our storage as a service, we can give you best practices on that he would tell you, or she would tell you about our integration with our security visions, QRadar. So those are various best practices. So the technical account manager makes sure the software is always up to date, right? All the little things that you would have to do yourself if you own it, we take care of, because we legally own it, which is allow you to buy it as a service. So it is a true OpEx model from a financial perspective. >> In the term of the contracts are what? One, two and three years. >> One to five. >> Yeah. Okay. >> If you don't renew and you don't cancel, we'll automatically re up you at the exact tier you're at, at the exact same price. Several of our competitors, by the way, if you do that, they actually charge you a premium until you sign a contract. We do not. So if you have a contract based on tier two, right? We go buy SLA tier one, tier two, tier three. So if I have a tier two contract at theCUBE, and you forgot to get the contract done at the end of two years, but you still want it, you can go for the next 2/4. I mean, well our business partner as I should say, "Dave, don't you want to sign a contract, you said you like it." Obviously you would, but we will let you stay. You just say, now I want to keep it without a contract. And we don't charge your premium. Our competitors if you don't have a contract, they charge your premium. If you keep it installed without putting a contract in place. So little things like that clearly differentiate what we do. We don't charge a premium. If you go above the base. One of the competitors, in fact, when you go into the variable space, okay? And by the way, we provide 50% extra capacity. We over-provision. The other competitors usually do 25%. We do 50%. No charge, is just part of the service. So the other vendors, if you go into the variable space, they raised the price. So if it's $5, you know, for X capacity and you go into the, which is your base, and then you go above that, they charge you $7 and 50 cents. We don't. It's $5 at the base and $5 at the variable. Now obviously your variable can be very big or very small, but whatever the variable is, we charge you. But we do not charge you an a bigger price. Couple of competitors when you go into the variable world, they charge you more. Guess what it gets you to do, raise your base capacity. (Eric laughs) >> Yeah. I mean, that's, that should, the math should be the opposite of that, in my view. If you make a commitment to a vendor, say, okay, I'm going to commit to X. You have a nice chart on this, actually in your, in your deck. If I'm going to commit to X, and then I'm going to add on, I would think the add on price per bit should be at the same or lower. It shouldn't be higher. Right? And I get, I get what you're saying there. They're forcing you to jack up the base, but then you're taking all the risk. That's not a shared risk model. I get... >> And that's why we made sure that we don't do that. In fact, Dave, you can, you know, the fact that we don't charge you a premium if you go beyond your contract period and say, "I still wanted to do it, but I haven't done the contract yet." The other guys charge you a premium, if you go beyond your contract period. We don't do that either. So we try to be end-user friendly, customer friendly, and we've also factored in our business partners can participate in this program. At least one of our competitors came out with a program and guess what? Partners could not participate. It was all direct. And that company by happens to have about 80% of their business through the channel and their partners were basically cut out of the model, which by the way, is what a lot of Cloud providers had done in the past as well. So it was not a channel friendly model, we're channel friendly, we're end user-friendly, it's all about ease of use. In fact, when you need more capacity, it takes about 10 minutes to get the new capacity up and going, that's it? >> How long does it take to set up? How long does it take to set up initially? And how long does it take to get new capacity? >> So, first of all, we deploy either in a Colo facility that you've contracted with, including Equinix, Equinix, is part of our press release, or we install on your site. So the technical account managers is assigned, he would call up theCUBE and say, "When is it okay for us to come install the storage?" We install it. You don't install anything. You just say, here's your space. Go ahead and install. We do the installation. You then of course do the normal rationing of the capacity to this goes to this Oracle, this goes to SAP. This goes to Mongo or Cassandra, right? You do that part, but we install it. We get it up and going. We get it turned on. We hook it up to your switching infrastructure. If you've got switching infrastructure, we do all of that. And then when you need more capacity, we use our storage insights pro which automatically monitors capacity, performance, and potential tech support problems. So we give you 50% extra, right? If you drop that to 25%, so you now don't have 50% extra anymore, you only have 25% extra, we'll, the technical account manager would call you and say, "Dave, do you know that we'd like to come install extra capacity at no charge to get you back up to that 50% margin?" So we always call because it's on your site or in your Colo facility, right? We own the asset, but we set it up and you know, it takes a week or two, whatever it takes to ship to whatever location. Now by the way, our storage as a service for 2021 will be in North America and Europe only, we are really expanding our storage as a service outside into Asia and into Latin America, et cetera, but not until 2022. So we'll start out with North America and Europe first. >> So I presume part of that is figuring out just the compensation models right? And so how, how did you solve that? I mean, you can't, you know, you don't seem to be struggling with that. Like some do. I think there's some people dipping their toes in the water. Was that because, you know, IBM's got experience with like SAS pricing or how were you thinking about that and how did you deal with kind of the internal (indistinct) >> Sure. So, first of all, we've had for several years, our storage utility model. >> Right? >> Our storage utility model has been sort of a hybrid part CapEx and part OpEx. So first of all, we were already halfway there to an OpEx model with our storage utility model that's item, number one. It also gave us the experience of the billing. So for example, we bill you for a full quarter. We don't send you a monthly bill. We send you a quarterly bill. And guess what, we always bill you in arrears. So for example, since theCUBE is going to be a customer this quarter, we will send you a bill for this quarter in October for the October quarter, we'll send you a bill for that quarter in January. Okay. And if it goes up, it goes up. If it goes down, it goes down. And if you don't use any variable, there's no bill. Because what we do is the base you pay for once a year, the variable you pay for by on a quarterly basis. So if you, if you are within the base, we don't send you a bill at all because there's no bill. You didn't go into the variable capacity area at all. >> I love that. >> When you have a variable It can go up and down. >> Is that unique to some, do some competitors try to charge you up front? Like if it's a one-year term. (Dave laughs) >> Everbody charges, everybody builds yearly on the base capacity. Pretty much everyone does that. >> Okay, so upfront you pay for the base? Okay. >> Right. And the variable can be zero. If you really only use the base, then there is no variable. We only bill for it's a pay for what you use model. So if you don't use any of the variable, we never charge you for variable. Now, you know, because you guys have written about it, storage grows exponentially. So the odds of them ending up needing some of the variable is moderately high. The other thing we've done is we didn't just look at what we've done with our storage utility model, but we actually looked at Cloud providers. And in fact, not only IBM storage, but almost every of our competitors does a comparison to Cloud pricing. And when you do apples to apples, Cloud vendors are more expensive than storage as a services, not just from us, but pretty much for a moment. So let's take an example. We're Six Nines by default. Okay. So as you know, most Cloud providers provide three or Fournines as the default. They'll let you get five or Six Nines, but guess what? They charge you extra. So item number one. Second thing, performance, as you know, the performance of Cloud storage is usually very weak, but you can make it faster if you want to. They charge extra for that. We're sitting at 2,250 terabytes per IOPS, excuse me, per terabytes. That's incredible performance If you've got 100 terabytes, okay. And if your applications and workloads and that's the worst case, by the way, which differentiates from our competitors who usually quote the best case, we quote you the worst case and our worst case by the way, is almost always higher than their best cases in each of the tiers. So at their middle tier, our worst case is usually better than their best case. But the point is, if you get 4,000 IOPS per terabyte and you're on a tier two contract, it's a two-tier contract. And in fact, let's say that theCUBE has a five-year deal. And we base this on our FlashSystem technology. And so let's say for tier two, for sake of argument, FlashSystem, 7,200. We come out two years after theCUBE has it installed with the FlashSystem, 7,400. And let's say the FlashSystem, 7,400, won't deliver a 2,250 IOPS per terabyte, but 5,000, if we choose to replace it, 'cause remember it's our physical property. We own it. If we choose to replace that 7,200 with a 7,400, and now you get 5,000 IOPS per terabyte, it's free. You signed a tier two contract for five years. So two years later, if we decide to put a different physical system there and it's faster, or has four more software features, we don't charge you for any of that. You signed an SLA for tier two. >> You haven't Paid for capacity, right? All right. >> You are paying for the capacity (indistinct) performance, you don't pay for that. If we swap it out and the, the array is physically faster, and has got five new software features. You pay nothing, you pay what your original contract was based on the capacity. >> What I'm saying is you're learning from the Cloud providers 'cause you are a Cloud provider. But you know, a lot of the Cloud providers always sort of talk about how they lower prices. They lower prices, but you know, well, you worked at storage companies your whole life and they, they lower prices on a regular basis because they 'cause the cost of the curve. And so. >> Right. The cost of storage to Cloud, I mean, the average price decline in the storage industry is between 15 and 25%, depending on the year, every single year. >> Right. >> As, you know, you used to be with one of those analysts firms that used to track it by the numbers. So you've seen the numbers. >> For sure. Absolutely. >> On average it drops 15 to 25% every year. >> So, what's driving this then? If it's, it's not necessarily, is it the shift from, from CapEx to OPEX? Is it just a more convenient model than on a Cloud like model? How do you see that? >> So what's happened in IT overall is of course it started with people like salesforce.com. Well, over 10 years ago, and of course it's swept the software industry software as a service. So once that happened, then you now see infrastructure as a service, servers, switches, storage, and an IBM with our storage as a service, we're providing that storage capability. So that as a service model, getting off of the traditional licensing in the software world, which still is out there, but it's mostly now is mostly software as a service has now moved into the infrastructure space. From our perspective, we are giving our business partners and our customers, the choice. You still want to buy it. No problem. You want to lease it? No problem. You want a full OpEx model. No problem. So for us, we're able to offer any of the three options. The, as a service model that started in software has moved now into the systems world. So people want to change often that CapEx into OpEx, we can even see Global Fortune 500s where one division is doing something and a different division might do something else, or they might do it different by geography. In a certain geography, they buy our FlashSystem products and other geographies they lease them. And in other geographies it's, as a service. We are delivering the same feature, function, benefit from a performance availability software function. We just give them a different way to procure. Do you want CapEx you want leasing or OpEx you pick what you want, we'll deliver the right solution for you. >> So, you got the optionality. And that's great. You've thought that out, but, but the reason I'm asking Eric, is I'm trying to figure out this is not just for you for everybody. Is this a check-off item or is this going to be the prevailing way in which storage is consumed? So if you had, if you had a guess, let's go far out. So we're not making any near-term forecast, but end of the decade, is this going to be the dominant model or is it going to be, you know, one of the few. >> It will be one of a few, but it'll be a big few. It'll be the big, one of the biggest. So for sake of argument, there we'll still be CapEx, they'll still be OpEx they'll still be, or there will be OpEx and they're still be leasing, but I will bet you, you know, at the end of this decade, it'll be 40 to 50% will be on the OpEx model. And the other two will have the other 50%. I don't think it's going to move to everything 'cause remember, it's a little easier during the software world. In the system world, you've got to put the storage, the servers, or the networking on the prem, right? Otherwise you're not truly, you know, you got to make it a true OpEx model. There's legal restrictions. You have to make it OpEx, if not, then, you know, based on the a country's practice, depending on the country, you're in, they could say, "Well, no, you really bought that. It's not really a service model." So there's legal constraints that the software worldwise easier to get through and easier to get to bypass. Right? So, and remember, now everything is software as a service, but go back when salesforce.com was started, everyone in the enterprise was doing ELAs and all the small companies were buying some sort of contract, right, or buying by the (indistinct) basis. It took a while for that to change. Now, obviously the predominant model is software as a service, but I would argue given when salesforce.com started, which was, you know, 2007 or so, it took a good 10 years for software as a service to become the dominant level. So I think A, it won't take 10 full years because the software world has blazed a trail now for the systems world. But I do think you'll see, right. We're sitting here know halfway through 2021, that you're going to have a huge percentage. Like I said, the dominant percentage will be OpEx, but the other two will still be there as well. >> Right. >> By the way, you know in software, almost, no one's doing ELAs these days, right? A few people still do, but it's very rare, right? It's all software as a service. So we see that over time doing the same thing in the, in the infrastructure side, but we do think it will be slower. And we'll, we'll offer all three as, as long as customers want it. >> I think you're right. I think it's going to be mixed. Like, do I care more about my income statement or my balance sheet and the different companies or individual different divisions are going to have different requirements. Eric, you got to leave it there. Thanks much for your time and taking us through this announcement. Always great to see you. >> Great. Thank you very much. We really appreciate our time with theCUBE. >> All right. Thank you for watching this CUBE conversation. This is Dave Vellante and we'll see you next time. (upbeat music)

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 vellante despite all the chatter about cloud repatriation and the exorbitant cost of cloud computing customer spending momentum continues to accelerate in the post-isolation economy if the pandemic was good for the cloud it seems that the benefits of cloud migration remain lasting in the late stages of covid and beyond and we believe this stickiness is going to continue for quite some time we expect i asked revenue for the big four hyperscalers to surpass 115 billion dollars in 2021 moreover the strength of aws specifically as well as microsoft azure remain notable such large organizations showing elevated spending momentum as shown in the etr survey results is perhaps unprecedented in the technology sector hello everyone and welcome to this week's wikibon cube insights powered by etr in this breaking analysis we'll share some some fresh july survey data that indicates accelerating momentum for the largest cloud computing firms importantly not only is the momentum broad-based but it's also notable in key strategic sectors namely ai and database there seems to be no stopping the cloud momentum there's certainly plenty of buzz about the cloud tax so-called cloud tax but other than wildly assumptive valuation models and some pockets of anecdotal evidence you don't really see the supposed backlash impacting cloud momentum our forecast calls for the big four hyperscalers aws azure alibaba and gcp to surpass 115 billion as we said in is revenue this year the latest etr survey results show that aws lambda has retaken the lead among all major cloud services tracked in the data set as measured in spending momentum this is the service with the most elevated scores azure overall azure functions vmware cloud on aws and aws overall also demonstrate very highly elevated performance all above that of gcp now impressively aws momentum in the all-important fortune 500 where it has always showed strength is also accelerating one concern in the most recent survey data is that the on-prem clouds and so-called hybrid platforms which we had previously reported as showing an upward spending trajectory seem to have cooled off a bit but the data is mixed and it's a little bit too early to draw firm conclusions nonetheless while hyperscalers are holding steady the spending data appears to be somewhat tepid for the on-prem players you know particularly for their cloud we'll study that further after etr drops its full results on july 23rd now turning our attention back to aws the aws cloud is showing strength across its entire portfolio and we're going to show you that shortly in particular we see notable strength relative to others in analytics ai and the all-important database category aurora and redshift are particularly strong but several other aws database services are showing elevated spending velocity which we'll quantify in a moment all that said snowflake continues to lead all database suppliers in spending momentum by a wide margin which again will quantify in this episode but before we dig into the survey let's take a look at our latest projections for the big four hyperscalers in is as you know we track quarterly revenues for the hyperscalers remember aws and alibaba ias data is pretty clean and reported in their respective earnings reports azure and gcp we have to extrapolate and strip out all a lot of the the apps and other certain revenue to make an apples-to-apples comparison with aws and alibaba and as you can see we have the 2021 market exceeding 115 billion dollars worldwide that's a torrid 35 growth rate on top of 41 in 2020 relative to 2019. aggressive yes but the data continues to point us in this direction until we see some clearer headwinds for the cloud players this is the call we're making aws is perhaps losing a sharepoint or so but it's also is so large that its annual incremental revenue is comparable to alibaba's and google's respective cloud business in total is business in total the big three u.s cloud companies all report at the end of july while alibaba is mid mid-august so we'll update these figures at that time okay let's move on and dig into the survey data we don't have the data yet on alibaba and we're limited as to what we can share until etr drops its research update on on the 23rd but here's a look at the net score timeline in the fortune 500 specifically so we filter the fortune 500 for cloud computing you got azure and the yellow aws and the black and gcp in blue so two points here stand out first is that aws and microsoft are converging and remember the customers who respond to the survey they probably include a fair amount of application software spending in their cloud answers so it favors microsoft in that respect and gcp second point is showing notable deceleration relative to the two leaders and the green call out is because this cut is from an aws point of view so in other words gcp declines are a positive for aws so that's how it should be interpreted now let's take a moment to better understand the idea of net score this is one of the fundamental metrics of the etr methodology here's the data for aws so we use that as a as a reference point net score is calculated by asking customers if they're adding a platform new that's the lime green bar that you see here in the current survey they're asking are you spending six percent or more in the second half relative to the first half of the year that's the forest green they're also asking is spending flat that's the gray or are you spending less that's the pink or are you replacing the platform i.e repatriating so not much spending going on in replacements now in fairness one percent of aws is half a billion dollars so i can see where some folks would get excited about that but in the grand scheme of things it's a sliver so again we don't see repatriation in the numbers okay back to net score subtract the reds from the greens and you get net score which in the case of aws is 61 now just for reference my personal subjective elevated net score level is 40 so anything above that is really impressive based on my experience and to have a company of this size be so elevated is meaningful same for microsoft by the way which is consistently well above the 50 mark in net score in the etr surveys so that's you can think about it that's even more impressive perhaps than aws because it's triple the revenue okay let's stay with aws and take a look at the portfolio and the strength across the board this chart shows net score for the past three surveys serverless is on fire by the way not just aws but azure and gcp functions as well but look at the aws portfolio every category is well above the 40 percent elevated red line the only exception is chime and even chime is showing an uptick and chime is meh if you've ever used chime every other category is well above 50 percent next net score very very strong for aws now as we've frequently reported ai is one of the four biggest focus areas from a spending standpoint along with cloud containers and rpa so it stands to reason that the company with the best ai and ml and the greatest momentum in that space has an advantage because ai is being embedded into apps data processes machines everywhere this chart compares the ai players on two dimensions net score on the vertical axis and market share or presence in the data set on the horizontal axis for companies with more than 15 citations in the survey aws has the highest net score and what's notable is the presence on the horizontal axis databricks is a company where high on also shows elevated scores above both google and microsoft who are showing strength in their own right and then you can see data iq data robot anaconda and salesforce with einstein all above that 40 percent mark and then below you can see the position of sap with leonardo ibm watson and oracle which is well below the 40 line all right let's look at at the all-important database category for a moment and we'll first take a look at the aws database portfolio this chart shows the database services in aws's arsenal and breaks down the net score components with the total net score superimposed on top of the bars point one is aurora is highly elevated with a net score above 70 percent that's due to heavy new adoptions redshift is also very strong as are virtually all aws database offerings with the exception of neptune which is the graph database rds dynamodb elastic document db time stream and quantum ledger database all show momentum above that all important 40 line so while a lot of people criticize the fragmentation of the aws data portfolio and their right tool for the right job approach the spending spending metrics tell a story and that that the strategy is working now let's take a look at the microsoft database portfolio there's a story here similar similar to that of aws azure sql and cosmos db microsoft's nosql distributed database are both very highly elevated as are azure database for mysql and mariadb azure cash for redis and azure for cassandra also microsoft is giving look at microsoft's giving customers a lot of options which is kind of interesting you know we've often said that oracle's strategy because we think about oracle they're building the oracle database cloud we've said oracle strategy should be to not just be the cloud for oracle databases but be the cloud for all databases i mean oracle's got a lot of specialty capability there but it looks like microsoft is beating oracle to that punch not that oracle is necessarily going there but we think it should to expand the appeal of its cloud okay last data chart that we'll show and then and then this one looks at database disruption the chart shows how the cloud database companies are doing in ibm oracle teradata in cloudera accounts the bars show the net score granularity as we described earlier and the etr callouts are interesting so first remember this is an aws this is in an aws context so with 47 responses etr rightly indicates that aws is very well positioned in these accounts with the 68 net score but look at snowflake it has an 81 percent net score which is just incredible and you can see google database is also very strong and the high 50 percent range while microsoft even though it's above the 40 percent mark is noticeably lower than the others as is mongodb with presumably atlas which is surprisingly low frankly but back to snowflake so the etr callout stresses that snowflake doesn't have a strong as strong a presence in the legacy database vendor accounts yet now i'm not sure i would put cloudair in the legacy database category but okay whatever cloudera they're positioning cdp is a hybrid platform as are all the on-prem players with their respective products and platforms but it's going to be interesting to see because snowflake has flat out said it's not straddling the cloud and on-prem rather it's all in on cloud but there is a big opportunity to connect on-prem to the cloud and across clouds which snowflake is pursuing that that ladder the cross-cloud the multi-cloud and snowflake is betting on incremental use cases that involve data sharing and federated governance while traditional players they're protecting their turf at the same time trying to compete in cloud native and of course across cloud i think there's room for both but clearly as we've shown cloud has the spending velocity and a tailwind at its back and aws along with microsoft seem to be getting stronger especially in the all-important categories related to machine intelligence ai and database now to be an essential infrastructure technology player in the data era it would seem obvious that you have to have database and or data management intellectual property in your portfolio or you're going to be less valuable to customers and investors okay we're going to leave it there for today remember these episodes they're all available as podcasts wherever you listen all you do is search breaking analysis podcast and please subscribe to the series check out etr's website at etr dot plus plus etr plus we also publish a full report every week on wikibon.com and siliconangle.com you can get in touch with me david.velante at siliconangle.com you can dm me at d vallante or you can hit hit me up on our linkedin post this is dave vellante for the cube insights powered by etr have a great week stay safe be well and we'll see you next time you

>>Welcome back everyone to Dell Technologies World 2021 the virtual version. You're watching the cubes continuing coverage of the event and we're gonna talk about the Edge, the transformation of telco in the future of our expanding tech universe. With me is Aaron Jason, who's the vice president? Edge and Telkom marketing at Dell Technologies erin great to see you. I love this topic. >>Absolutely. It's it's pretty popular these days. I'm glad to be here with you. Thanks. >>It is popular, you know, cloud was kind of the shiny new toy last decade and it's still growing at double digits but it's kind of mainstream and now the Edge is all the rage. What's the best way to think about? What is the Edge? How do you define that? >>Yeah, you know, that's probably one of the most common questions I get is we start really doubling down on what we're doing it in the Edge world today. Um you know, I tried to basically not overcomplicated too much, you know, last year we really tried to to talk about it as being where you're the physical world, in the virtual world, connect. Um but you know, really it's more about what customers are looking to do with that technology. And so what we're really thinking about it today is the edges really where customers data is being used near point of generation to really define and build the essential value for that customer and that essential value is gonna be different in each vertical in each industry. Right? So in manufacturing, that essential value is created in the factory and retail, it's going to be, you know, at point of sale, whether that's in a store or on your device, in a virtual interaction, um in health care, it's going to be the point of care, Right? So it's gonna be the ambulance or the emergency room or the radiology lab. and of course in farming that essential values created in the field itself. So um, you know, for for many customers, it's really trying to figure out, you know, how do they take technology closer to the point of that value creation to be able to drive new new capabilities for the business, whether it's for what they're trying to accomplish or what they're trying to do in helping their customers. So really that's how we're thinking about the edge today. It's where that value generation occurs for a company. And how do we take technology to that point of generation to deliver value for them? >>Yeah, I like that. I mean to me the edge, I know what it's not, I know the edges, not a mega data center, but but everything else could be the edge. I mean, it's it's to me it's the place that's the most logical, the most logical place to process the data. So as you say, it could be a factory, it could be a hospital, it could be a retail store, it could be, could be a race track, it could be a farm, I mean virtually anything. So the edges, it's always been here, but it's changing. I mean most of the edge data has historically been analog. Everything now is getting instrumented. What are the factors that you think will make this, this industry's vision of the edge real in your opinion? >>Yeah. You know, it's it's really bringing together a handful of technologies that have really started to mature after over the last decade or so. Um the ones that have been around for a little bit, things like IOT have been emerging in the last several years. Um even Ai and machine learning many of those algorithms have been around for decades, but we've only recently been able to bring the compute power required to do that in edge environments in the last decade or so. Um it's so really the two key sort of killer technologies that have matured in the last couple of years is really the mic realization of computing. So being able to put compute almost anywhere on the planet and then the emergence of five G networking, giving us the ability to provide very high performance, low latency and high bandwidth environments to connect all those things together and get the data to those analytics environments. From that computer perspective. I mean, I still like to talk about moore's law as an example of that that ever marched that's been going on for, you know, half a century or more now is continuing to push forward um at a rate that is that that that that just really hasn't slowed down for the most part, you know, the example that I use with people, as, you know, you know, I still remember when I got my first calculator watch as a kid, you know, that Casio calculator watch that so many of us had, And my dad told me the story when he gave it to me, he's like, Hey, look, this has the same amount of compute power as the landing module on the moon, and I didn't know it at the time, but that was my first sort of entry and education around what Moore's law provided. And it's not so much speed. I mean, people think about that as it doubles in speed every 18 months, but it's really more about the density of compute that happens that moore's law drought, pushes along, so I can now squish more and more compute power into a smudge smaller location and I can now take that performance out to the edge in a way that I haven't been able to do before. I mean I think about my history, I joined E M C, that was acquired by Dell Technologies a couple years back. I joined that back in the late nineties when the biggest baddest storage array on the planet was one whole terabyte in size. And now I can fit that in the palm of my hand. In fact, when I walk around, you know, when I used to walk around with my, with my back, my laptop and go into offices, um you know, if I had my laptop and my tablet and my my my smartwatch, I had 12 to 16 cores on me and a couple of terabytes of capacity all connected with the equivalent of tens of T ones. Right? So what was once a small or or a mid sized data center just in the last decade or so? We now all walk around a small data centers and the power that that compute now brings to the edge allows us to take analytics that was really once done in data centers. I may have captured it at the edge, but I had to move it into a data lake. I had to stage it and analyze it. It was more of a historical way of looking at data. Now I can put compute right next to the point of data generation and give insight instantaneously as data is being generated. And that's opening up whole new ways that industries can drive new value for them and for their customers. And that's really what's exciting about it is this combination of these technologies that are all sort of maturing and coming together at the same time. Um, and there's just so much doing, it happened that space and devils really, really excited to be part of bringing that into these environments for our customers. >>I'm gonna give you a stat that a lot of people, I don't, I don't think realize, uh, you talked about moore's law and you're absolutely right. It's really, you know, technically moore's law is about the density, right? But the outcome of being able to do that is performance. And if you do the math, you know, moore's law doubling performance every two years, roughly, The math on that is that means 44 improvement per year in performance. Everybody talks about how moore's laws is dead. It's not, it's just changing. Here's the, here's the stat. If you take a system on a chip, take like for instance apples a 14 and go back five years from 2015 to 2021. If you add up the performance of the CPU the combinatorial factors of the CPU gpu and in the N. P. U. The neural processing unit, just those three, The growth rate has been 118 a year vs 44%. So it's actually accelerating and that doesn't include the accelerators and the DSPS and all the other alternative processors. So, and to your point and by the way that a 14 shipping cost Apple 50 bucks. So and and that fits in the palm of your hand to the point that you were just making So imagine that processing power at the edge most of of of of of ai today is modeling, let's say in the cloud, the vast majority is going to be a i influencing at the edge. So you are right on on that point. >>Yeah, there's no question about it. So, to your point, I mean, moore's law is just of course CPU itself. All right. And it comes out to roughly, on average, it's about 10 x every five years. 100 X every 10 years, 1000 X every 15 years. I mean, it's incredible how much power you can put in a small footprint today. And then if you factor in the accelerators and everything else um, it's actually if anything that innovation is going faster and faster and to your point, um you know, the while the modeling is still going to typically happen in data centers as you pull together lots of different data sets to be able to analyze and create new models. But those models are getting pushed right out to the edge on these compute devices literally feet away at times from the point of data generation to be able to give us really real time analytics and influencing. The other cool thing about this too is you know we're going from sort of more looking backwards and making business analytics based on what has already happened in the past to being able to do that in the very near past. And of course now with modern analytics and models that are being created for ai we're able to do more predictive analytics so we can actually identify errors, identify challenges before they even occur based on pattern matching that they're saying. Um So it's really opening up new doors and new areas that we've never been able to see before that's really all powered by by these capabilities. >>It's insane the amount of data that is coming. We think data is overwhelming today. You ain't seen nothing yet. Um Now erin you cover the edge and the telecom business up. I was beside it when I when I when I found that out because the telecom businesses is ripe for transformation. Um So what do you how is Dell thinking about that? Why are you sort of putting those together? What are the synergies that you see in in the commonalities in those 22 sectors? >>Yeah. I mean at the end of the day it's really all about serving the enterprise customers in the in the organizations of all kinds um that the industry is trying to bring these edge technologies too and that's no different with the telecommunications industry. Right? So you know when when the when the four G world changed about 10 years ago um you know the telecom industry was able to bring the plumbing the network piping out to all the endpoints but they really didn't capture the over the top revenue opportunities that Four G technologies opened up right. That really went to the hyper scholars. It went to you know, a lot of the companies that we all know and love like uh you know, Uber and Airbnb and netflix and others um and that really when the four Gr that was really more about opening up consumer opportunities as we move to five G. And as we move these ultra low latency and high bandwidth capabilities out to the enterprise edge, it's really the B two B opportunities that are opening up and so on the telecom side we're partnering with the telecommunication companies to modernize their network, enroll five G. L. Quickly. But one of the more important things is that we're partnering with them to be able to build services over the top of that that they can then sell into their customer base and their business customer base. So whether that's mech, whether that's private mobility, um delivering data services over the top of those networks, there's a tremendous opportunity for the telecoms to be able to go and capture um Ed revenue opportunities and we're here to help them to partner with them to be able to do that. Now if you put yourself in the shoes of the customer, the enterprise business, a manufacturer or retail, who's looking to be able to leverage these technologies, there's a variety of ways in which they're going to be able to to to consume these technologies. In some cases they'll be getting it direct from vendors direct from Dell Technologies and others. They might be using solutions integrators to be able to combine these technologies together for a particular solution. They may get some of those technologies from their telecom provider and even others, they might get it from the cloud provider. So um Dell wants to make sure that we're being able to help our customers across a variety of ways in which they want to consume those technologies and we have to businesses focused on that. We've got one business focused on edge solutions where we partner with oT vendors closely as well as cloud providers to be able to provide a technology and infrastructure based on which we can consolidate edge workloads To be able to allow customers that want to be able to run those um those services on prem and by those from a direct vendor. Um there's other customers that want to get those through the telecoms. And so we work closely with the telecommunication providers to provide them that modern cloud native disaggregated network that they're looking to build to support 5G. And then help them build those services on the top that they can sell either way whether the customer wants to get that from a vendor like Dell or from a service provider like like uh like an A T and T and Verizon or others. Um Dell looks to partner with them and be a way to provide that underlying infrastructure that connects all of that together for them. >>Well, I mean the beauty of the telco networks is their hardened. But the problem for the telco networks is they're they're hardened and so you've got the over over the top vendors bow guarding their network. The cost per bit is coming down, data is going through the roof and the telcos can't, they can't participate in that over the top and get to those subscribers. But with Five G. And the technologies that you're talking about bringing to the telecoms world, they're they're gonna transform and many are going to start competing directly and this is just a whole new world out there. I wonder Aaron if you could talk about um what you're specifically talking about at Del Tech World this year as it relates to Edge. >>Sure. So the both of the businesses hedge in telecom have a couple announcements this year. This this year, Deltek World, um starting with Edge um as you may recall back in uh in in the fall of last year when we had our last technologies world, we announced our intent to launch an edge business. Um so that that was formulated and stood up over the last couple of months and and we're really focusing on a couple of different areas. How do we look at our overall Dell technologies portfolio and be able to bring particular products and solutions that exist already and be able to apply those uh to edge use cases. We're looking at building a platform which would allow us to be able to consolidate a variety of workloads. And of course we're working on partnerships specifically in the ot space to be able to vertical eyes these offers to help particular uh particular industries. Right now we're focusing on manufacturing and retail but we'll expand that over time. So at Del Tech World this year we're launching our first set of of solutions family which is going to be the Dell Technologies manufacturing edge solutions, the first one that's gonna be launching as a reference architecture with PTC um thing works on top of what we're also proud to be announcing this week, which is our apex private cloud offering. So this is the first example of of of a partnership with an O. T. Provider on top of apex private cloud so that we can bring in as a service platform offering to the Enterprise edge uh for manufacturers. And combined with one of the industry's leading oT software vendors of thing works. So that's one of the solutions were doing um we're also looking to launch a product which is we're taking our existing um streaming data platform from our unified storage team and taking that, which was once running in the data center out to edge these cases as well. And that allows us to be able to capture click stream data in manufacturing and other environments, buffer and cash that in a in an appliance and then be able to move that off to a data like for longer term analytics. While it's in that buffered state though we open provide a P. I. S. So that you can actually do real time influencing against those click stream data as it's flowing through the appliance on its way to the data lake for longer term analytics. So those are two key areas that we're gonna be focusing on from an edge perspective on the telecom side. Um we're really this is going to be a big year from us as we move towards creating a common end end five G platform from quarter Iran and then also start focusing on partnerships and ecosystems on top of that platform. Uh last week at Red hat summit we actually announced a reference architecture for red hat. Open shift on top of Dell technologies infrastructure servers and networking. And here at Dell technologies world. This week we're announcing a reference architecture with VM ware. So running VM ware telecom cloud platform. Also on top of Dell technologies. Power edge servers and power such as um so this allows us to create that foundation that open cloud native. These are container and virtual layers on top of our hard work to give that that cloud native disaggregated uh, network claim to be able to now run and build core edge and ran solutions on top of and you'll be hearing more about what we're doing in this space in the coming months. >>Nice. That's great. The open ran stuff is really exciting now, last question. So mobile world Congress, the biggest telco show is coming up in late june Yeah, still on. According to the G S M, a lot of people have tapped out um, and but the cube is planning to be there with a hybrid presence, both virtual and physical. We'll see um I wonder if there's anything you want to talk about just in terms of what's happening in telco telco transformation, you guys got any get any events coming up, what can you tell us? >>Yeah, so we took a close look at mobile world congress and and uh this has been a challenging year for everybody. Um you know, Dell as well as many other vendors made the decision this year that we would actually not participate, but we look forward to participating uh with full gusto next year when it's back in a physical environment. Um So what we've decided to do is we are going to be having our own virtual launch event on june 9th. Um And in that event, the theme of that is going to be the modern ecosystem in the neighboring leveraging the power of open. Um So we'll be talking a little bit more about what we're doing from that open cloud, native network infrastructure and then also talk a little bit more about what Dell technologies looking to do to bring a broad ecosystem of technology vendors together and deliver that ecosystem platform for the telecom industry. So registration actually opens this week at Dell Technologies World. So if you go to Dell technologies dot com can register for the event. Um we're really excited to be talking to the telecom providers and also other hardware and software vendors that are in that space to see how we can work together to really drive this next generation of five G. >>That's awesome. I'll be looking for that and and look forward to collaborating with you on that, bringing your thought leadership and the cube community we would really love to to partner on that. Aaron, thanks so much for coming to the cube. Really exciting area and best of luck to you. >>Right. Thank you. I appreciate the time. >>All right. And thank you for watching everybody says Dave Volonte for the Cubes, continuous coverage of Del Tech World 2021. The virtual version will be right back right after this short break.