(upbeat music) >> Hey, everyone. Welcome back to theCUBE's day one coverage of Cloud Native SecurityCon 2023. This has been a great conversation that we've been able to be a part of today. Lisa Martin with John Furrier and Dave Vellante. Dave and John, I want to get your take on the conversations that we had today, starting with the keynote that we were able to see. What are your thoughts? We talked a lot about technology. We also talked a lot about people and culture. John, starting with you, what's the story here with this inaugural event? >> Well, first of all, there's two major threads. One is the breakout of a new event from CloudNativeCon/KubeCon, which is a very successful community and events that they do international and in North America. And that's not stopping. So that's going to be continuing to go great. This event is a breakout with an extreme focus on security and all things security around that ecosystem. And with extensions into the Linux Foundation. We heard Brian Behlendorf was on there from the Linux Foundation. So he was involved in Hyperledger. So not just Cloud Native, all things containers, Kubernetes, all things Linux Foundation as an open source. So, little bit more of a focus. So I like that piece of it. The other big thread on this story is what Dave and Yves were talking about on our panel we had earlier, which was the business model of security is real and that is absolutely happening. It's impacting business today. So you got this, let's build as fast as possible, let's retool, let's replatform, refactor and then the reality of the business imperative. To me, those are the two big high-order bits that are going on and that's the reality of this current situation. >> Dave, what are your top takeaways from today's day one inaugural coverage? >> Yeah, I would add a third leg of the stool to what John said and that's what we were talking about several times today about the security is a do-over. The Pat Gelsinger quote, from what was that, John, 2011, 2012? And that's right around the time that the cloud was hitting this steep part of the S-curve and do-over really has meant in looking back, leveraging cloud native tooling, and cloud native technologies, which are different than traditional security approaches because it has to take into account the unique characteristics of the cloud whether that's dynamic resource allocation, unlimited resources, microservices, containers. And while that has helped solve some problems it also brings new challenges. All these cloud native tools, securing this decentralized infrastructure that people are dealing with and really trying to relearn the security culture. And that's kind of where we are today. >> I think the other thing too that I had Dave is that was we get other guests on with a diverse opinion around foundational models with AI and machine learning. You're going to see a lot more things come in to accelerate the scale and automation piece of it. It is one thing that CloudNativeCon and KubeCon has shown us what the growth of cloud computing is is that containers Kubernetes and these new services are powering scale. And scale you're going to need to have automation and machine learning and AI will be a big part of that. So you start to see the new formation of stacks emerging. So foundational stacks is the machine learning and data apps are coming out. It's going to start to see more apps coming. So I think there's going to be so many new applications and services are going to emerge, and if you don't get your act together on the infrastructure side those apps will not be fully baked. >> And obviously that's a huge risk. Sorry, Dave, go ahead. >> No, that's okay. So there has to be hardware somewhere. You can't get away with no hardware. But increasingly the security architecture like everything else is, is software-defined and makes it a lot more flexible. And to the extent that practitioners and organizations can consolidate this myriad of tools that they have, that means they're going to have less trouble learning new skills, they're going to be able to spend more time focused and become more proficient on the tooling that is being applied. And you're seeing the same thing on the vendor side. You're seeing some of these large vendors, Palo Alto, certainly CrowdStrike and fundamental to their strategy is to pick off more and more and more of these areas in security and begin to consolidate them. And right now, that's a big theme amongst organizations. We know from the survey data that consolidating redundant vendors is the number one cost saving priority today. Along with, at a distant second, optimizing cloud costs, but consolidating redundant vendors there's nowhere where that's more prominent than in security. >> Dave, talk a little bit about that, you mentioned the practitioners and obviously this event bottoms up focused on the practitioners. It seems like they're really in the driver's seat now. With this being the inaugural Cloud Native SecurityCon, first time it's been pulled out of an elevated out of KubeCon as a focus, do you think this is about time that the practitioners are in the driver's seat? >> Well, they're certainly, I mean, we hear about all the tech layoffs. You're not laying off your top security pros and if you are, they're getting picked up very quickly. So I think from that standpoint, anybody who has deep security expertise is in the driver's seat. The problem is that driver's seat is pretty hairy and you got to have the stomach for it. I mean, these are technical heroes, if you will, on the front lines, literally saving the world from criminals and nation-states. And so yes, I think Lisa they have been in the driver's seat for a while, but it it takes a unique person to drive at those speeds. >> I mean, the thing too is that the cloud native world that we are living in comes from cloud computing. And if you look at this, what is a practitioner? There's multiple stakeholders that are being impacted and are vulnerable in the security front at many levels. You have application developers, you got IT market, you got security, infrastructure, and network and whatever. So all that old to new is happening. So if you look at IT, that market is massive. That's still not transformed yet to cloud. So you have companies out there literally fully exposed to ransomware. IT teams that are having practices that are antiquated and outdated. So security patching, I mean the blocking and tackling of the old securities, it's hard to even support that old environment. So in this transition from IT to cloud is changing everything. And so practitioners are impacted from the devs and the ones that get there faster and adopt the ways to make their business better, whether you call it modern technology and architectures, will be alive and hopefully thriving. So that's the challenge. And I think this security focus hits at the heart of the reality of business because like I said, they're under threats. >> I wanted to pick up too on, I thought Brian Behlendorf, he did a forward looking what could become the next problem that we really haven't addressed. He talked about generative AI, automating spearphishing and he flat out said the (indistinct) is not fixed. And so identity access management, again, a lot of different toolings. There's Microsoft, there's Okta, there's dozens of companies with different identity platforms that practitioners have to deal with. And then what he called free riders. So these are folks that go into the repos. They're open source repos, and they find vulnerabilities that developers aren't hopping on quickly. It's like, you remember Patch Tuesday. We still have Patch Tuesday. That meant Hacker Wednesday. It's kind of the same theme there going into these repos and finding areas where the practitioners, the developers aren't responding quickly enough. They just don't necessarily have the resources. And then regulations, public policy being out of alignment with what's really needed, saying, "Oh, you can't ship that fix outside of Germany." Or I'm just making this up, but outside of this region because of a law. And you could be as a developer personally liable for it. So again, while these practitioners are in the driver's seat, it's a hairy place to be. >> Dave, we didn't get the word supercloud in much on this event, did we? >> Well, I'm glad you brought that up because I think security is the big single, biggest challenge for supercloud, securing the supercloud with all the diversity of tooling across clouds and I think you brought something up in the first supercloud, John. You said, "Look, ultimately the cloud, the hyperscalers have to lean in. They are going to be the enablers of supercloud. They already are from an infrastructure standpoint, but they can solve this problem by working together. And I think there needs to be more industry collaboration. >> And I think the point there is that with security the trend will be, in my opinion, you'll see security being reborn in the cloud, around zero trust as structure, and move from an on-premise paradigm to fully cloud native. And you're seeing that in the network side, Dave, where people are going to each cloud and building stacks inside the clouds, hyperscaler clouds that are completely compatible end-to-end with on-premises. Not trying to force the cloud to be working with on-prem. They're completely refactoring as cloud native first. And again, that's developer first, that's data first, that's security first. So to me that's the tell sign. To me is if when you see that, that's good. >> And Lisa, I think the cultural conversation that you've brought into these discussions is super important because I've said many times, bad user behavior is going to trump good security every time. So that idea that the entire organization is responsible for security. You hear that all the time. Well, what does that mean? It doesn't mean I have to be a security expert, it just means I have to be smart. How many people actually use a VPN? >> So I think one of the things that I'm seeing with the cultural change is face-to-face problem solving is one, having remote teams is another. The skillset is big. And I think the culture of having these teams, Dave mentioned something about intramural sports, having the best people on the teams, from putting captains on the jersey of security folks is going to happen. I think you're going to see a lot more of that going on because there's so many areas to work on. You're going to start to see security embedded in all processes. >> Well, it needs to be and that level of shared responsibility is not trivial. That's across the organization. But they're also begs the question of the people problem. People are one of the biggest challenges with respect to security. Everyone has to be on board with this. It has to be coming from the top down, but also the bottom up at the same time. It's challenging to coordinate. >> Well, the training thing I think is going to solve itself in good time. And I think in the fullness of time, if I had to predict, you're going to see managed services being a big driver on the front end, and then as companies realize where their IP will be you'll see those managed service either be a core competency of their business and then still leverage. So I'm a big believer in managed services. So you're seeing Kubernetes, for instance, a lot of managed services. You'll start to see more, get the ball going, get that rolling, then build. So Dave mentioned bottoms up, middle out, that's how transformation happens. So I think managed services will win from here, but ultimately the business model stuff is so critical. >> I'm glad you brought up managed services and I want to add to that managed security service providers, because I saw a stat last year, 50% of organizations in the US don't even have a security operations team. So managed security service providers MSSPs are going to fill the gap, especially for small and midsize companies and for those larger companies that just need to augment and compliment their existing staff. And so those practitioners that we've been talking about, those really hardcore pros, they're going to go into these companies, some large, the big four, all have them. Smaller companies like Arctic Wolf are going to, I think, really play a key role in this decade. >> I want to get your opinion Dave on what you're hoping to see from this event as we've talked about the first inaugural standalone big focus here on security as a standalone. Obviously, it's a huge challenge. What are you hoping for this event to get groundswell from the community? What are you hoping to hear and see as we wrap up day one and go into day two? >> I always say events like this they're about educating, aspiring to action. And so the practitioners that are at this event I think, I used to say they're the technical heroes. So we know there's going to be another Log4j or a another SolarWinds. It's coming. And my hope is that when that happens, it's not an if, it's a when, that the industry, these practitioners are able to respond in a way that's safe and fast and agile and they're able to keep us protected, number one and number two, that they can actually figure out what happened in the long tail of still trying to clean it up is compressed. That's my hope or maybe it's a dream. >> I think day two tomorrow you're going to hear more supply chain, security. You're going to start to see them focus on sessions that target areas if within the CNCF KubeCon + CloudNativeCon area that need support around containers, clusters, around Kubernetes cluster. You're going to start to see them laser focus on cleaning up the house, if you will, if you can call it cleaning up or fixing what needs to get fixed or solved what needs to get solved on the cloud native front. That's going to be urgent. And again, supply chain software as Dave mentioned, free riders too, just using open source. So I think you'll see open source continue to grow, but there'll be an emphasis on verification and certification. And Docker has done a great job with that. You've seen what they've done with their business model over hundreds of millions of dollars in revenue from a pivot. Catch a few years earlier because they verify. So I think we're going to be in this verification blue check mark of code era, of code and software. Super important bill of materials. They call SBOMs, software bill of materials. People want to know what's in their software and that's going to be, again, another opportunity for machine learning and other things. So I'm optimistic that this is going to be a good focus. >> Good. I like that. I think that's one of the things thematically that we've heard today is optimism about what this community can generate in terms of today's point. The next Log4j is coming. We know it's not if, it's when, and all organizations need to be ready to Dave's point to act quickly with agility to dial down and not become the next headline. Nobody wants to be that. Guys, it's been fun working with you on this day one event. Looking forward to day two. Lisa Martin for Dave Vellante and John Furrier. You're watching theCUBE's day one coverage of Cloud Native SecurityCon '23. We'll see you tomorrow. (upbeat music)

(upbeat music) >> Live from Las Vegas, it's theCUBE covering AWS re:Invent 2018. Brought to you by Amazon Web Services, Intel, and their ecosystem partners. >> Okay, welcome back everyone. Live coverage here in Las Vegas for Amazon re:Invent 2018. Day three, we're winding down over 150 videos. We'll have over 500 clips. Losing the voice. Dave Vellante, my co-host. Suzi analyst tech that we're going to extract theCUBE insights, James Kobielus. David Floyer from Wikibon. Jim you've been prolific on the blogs, Siliconangle.com, great stories. David you've got some research. What's your take? Jim, you're all over what's going on in the news. What's the impact? >> Well I think what this years re:Invent shows is that AWS is doubling down on A.I. If you look at the sheer range of innovative A.I. capabilities they've introduced into their portfolio, in terms of their announcements, it's really significant. A. They have optimized tense or flow for their cloud. B. They now have an automated labeling, called Ground Truth, labeling capability that leverages mechanical turf, which has been an Amazon capability for a while. They've also got now the industries first, what's called reinforcement learning plug-in to their data science tool chain, in this case Sage Maker, reinforcement learning is becoming so important for robotics, and gaming, and lots of other applications of A.I., and I'm just scratching the surface. So they've announced a lot of things, and David can discuss other things, but I'm seeing the depth of A.I. Their investment in it shows that they've really got their fingers on what enterprises are doing, and will be doing to differentiate themselves with this technology over the next five to ten years. >> What's an area that you see that people are getting? Clearly A.I. What areas are people missing that's compelling that you've observed here? >> When you say people are missing, you mean the general...? >> Journalists. >> Oh. >> Audience. There's so much news. >> Yeah. Yeah. >> Where are the nuggets that are hidden in the news? (laughing) What are you seeing that people might not see that's different? >> Getting back to the point I was raising, which is that robotics is becoming a predominant application realm for A.I. Robotics, outside the laboratory, or outside of the industrial I.O.T., robots are coming into everything, and there's a special type of A.I. you build into robots, re-enforcement learning is a big part of it. So I think the general, if you look at the journalists, they've missed the fact that I've seen in the past couple of years, robotics and re-enforcement learning are almost on the verge of being mainstream in the space, and AWS gets it. Just the depth of their investments. Like Deep Racer, that cute little autonomous vehicle that they rolled out here at this event, that just shows that they totally get it. That will be a huge growth sector. >> David Floyer, outpost is their on premises cloud. You've been calling this for I don't know how many years, >> (laughing) Three years. >> Three years? >> Yeah. What's the impact? >> And people said, no way Foyer's wrong (laughing). >> So you get vindication but... >> And people, in particular in AWS. (laughing) >> So you're right. So you're right, but is it going to be out in a year? >> Yeah, next in 2019. >> Will this thing actually make it to the market? And if it does what is the impact? Who wins and who loses? >> Well let's start with will it get to the market? Absolutely. It is outposts, AWS Outposts, is the name. It is taking AWS in the cloud and putting it on premise. The same API's. The same services. It'll be eventually identical between the two. And that has enormous increase in the range, and the reach that AWS and the time that AWS can go after. It is a major, major impact on the marketplace, puts pressure on a whole number of people, the traditional vendors who are supplying that marketplace of the moment, and in my opinion it's going to be wildly successful. People have been waiting that, wanting that, particularly in the enterprise market. They reasons for it are simple. Latency, low latency, you've got to have the data and the compute very close together. Moving data is very, very expensive over long distances, and the third one is many people want, or need to have the data in certain places. So the combination is meeting the requirements, they've taken a long time to get there. I think it's going to be, however wildly successful. It's going to be coming out in 2019. They'll have their alpha, their betas in the beginning of it. They'll have some announcements, probably about mid 2019. >> Who's threatened by this? Everybody? Cisco? HP? Dell? >> The integration of everything, storage, networking, compute, all in the same box is obviously a threat to all suppliers within that. And their going to have to adapt to that pretty strongly. It's going to be a declining market. Declining markets are good if you adapt properly. A lot of people make a lot of money from, like IBM, from mainframe. >> It's a huge threat to IBM. >> You're playing it safe. You're not naming names. (laughing) Okay, I'll rephrase. What's your prediction? >> What's my prediction on? >> Of the landscape after this is wildly successful. >> The landscape is that the alternatives is going to be a much, much smaller pie, and only those that have volume, and only those that can adapt to that environment are going to survive. >> Well, and let's name names. So who's threatened by this? Clearly Dell, EMC, is threatened by this. >> HP. >> HP, New Tanix, the VX rat guys, Lenovo is in there. Are they wiped out? No, but they have to respond. How do they respond? >> They have to respond, yeah. They have to have self service. They have to have utility pricing. They have to connect to the cloud. So either they go hard after AWS, connecting AWS, or they belly up to Microsoft >> With Azure Stack, >> Microsoft Azure. that's clearly going to be their fallback place, so in a way, Microsoft with Azure Stack is also threatened by this, but in a way it's goodness for them because the ecosystem is going to evolve to that. So listen, these guys don't just give up. >> No, no I know. >> They're hard competitors, they're fighters. It's also to me a confirmation of Oracle's same same strategy. On paper Oracle's got that down, they're executing on that, even though it's in a narrow Oracle world. So I think it does sort of indicate that that iPhone for the enterprise strategy is actually quite viable. If I may jump in here, four things stood out to me. The satellite as a service, was to me amazing. What's next? Amazon with scale, there's just so many opportunities for them. The Edge, if we have time. >> I was going to talk about the Edge. >> Love to talk about the Edge. The hybrid evolution, and Open Source. Amazon use to make it easy for the enterprise players to complete. They had limited sales and service capabilities, they had no Open Source give back, they were hybrid deniers. Everything's going to go into the public cloud. That's all changed. They're making it much, much more difficult, for what they call the old guard, to compete. >> So that same way the objection? >> Yeah, they're removing those barriers, those objections. >> Awesome. Edge. >> Yeah, and to comment on one of the things you were talking about, which is the Edge, they have completely changed their approach to the Edge. They have put in Neo as part of Sage Maker, which allows them to push out inference code, and they themselves are pointing out that inference code is 90% of all the compute, into... >> Not the training. >> Not the training, but the inference code after that, that's 90% of the compute. They're pushing that into the devices at the Edge, all sorts of architectures. That's a major shift in mindset about that. >> Yeah, and in fact I was really impressed by Elastic Inference for the same reasons, because it very much is a validation of a trend I've been seeing in the A.I. space for the last several years, which is, you can increasingly build A.I. in your preferred visual, declarative environment with Python code, and then the abstraction layers of the A.I. Ecosystem have developed to a point where, the ecosystem increasingly will auto-compile to TensorFlow, or MXNet, or PyTorch, and then from there further auto-compile your deployed trained model to the most efficient format for the Edge device, for the GP, or whatever. Where ever it's going to be executed, that's already a well established trend. The fact that AWS has productized that, with this Elastic Inference in their cloud, shows that not only do they get that trend, they're just going to push really hard. I'm making sure that AWS, it becomes in many ways, the hub of efficient inferencing for everybody. >> One more quick point on the Edge, if I may. What's going on on the Edge reminds me of the days when Microsoft was trying to take Windows and stick it on mobile. Right, the windows phone. Top down, I.T. guys coming at it, >> Oh that's right. >> and that's what a lot of people are doing today in IT. It's not going to work. What Amazon is doing see, we're going to build an environment that you can build applications on, that are secure, you can manage them from a bottoms up approach. >> Yeah. Absolutely. >> Identifying what the operations technology developers want. Giving them the tools to do that. That's a winning strategy. >> And focusing on them producing the devices, not themselves. >> Right. >> And not declaring where the boundaries are. >> Spot on. >> Very very important. >> Yep. >> And they're obviously inferencing, you get most value out of the data if you put that inferencing as close as you possibly can to that data, within a camera, is in the camera itself. >> And I eluded to it earlier, another key announcement from AWS here is, first of all the investment in Sage Maker itself is super impressive. In the year since they've introduced it, look at they've already added, they have that slide with all the feature enhancements, and new modules. Sage Maker Ground Truth, really important, the fully managed service for automating labeling of training datasets, using Mechanical Turk . The vast majority of the costs in a lot of A.I. initiatives involves human annotators of training data, and without human annotated training data you can't do supervised learning, which is the magic on a lot of A.I, AWS gets the fact that their customers want to automate that to the nth degree. Now they got that. >> We sound like Fam boys (laughing). >> That's going to be wildly popular. >> As we say, clean data makes good M.L., and good M.L. makes great A.I. >> Yeah. (laughing) >> So you don't want any dirty data out there. Cube, more coverage here. Cube insights panel, here in theCUBE at re:Invent. Stay with us for more after this short break. (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. >> The world's leading telcos are trying to shed the stigma of being monopolies lacking innovation. Telcos have been great at operational efficiency and connectivity and living off of transmission, and the costs and expenses or revenue associated with that transmission. But in a world beyond telephone poles and basic wireless and mobile services, how will telcos modernize and become more agile and monetize new opportunities brought about by 5G and private wireless and a spate of new innovations and infrastructure, cloud data and apps? Hello, and welcome to this week's Wikibon CUBE Insights powered by ETR. In this breaking analysis and ahead of Mobile World Congress or now, MWC23, we explore the evolution of the telco business and how the industry is in many ways, mimicking transformations that took place decades ago in enterprise IT. We'll model some of the traditional enterprise vendors using ETR data and investigate how they're faring in the telecommunications sector, and we'll pose some of the key issues facing the industry this decade. First, let's take a look at what the GSMA has in store for MWC23. GSMA is the host of what used to be called Mobile World Congress. They've set the theme for this year's event as "Velocity" and they've rebranded MWC to reflect the fact that mobile technology is only one part of the story. MWC has become one of the world's premier events highlighting innovations not only in Telco, mobile and 5G, but the collision between cloud, infrastructure, apps, private networks, smart industries, machine intelligence, and AI, and more. MWC comprises an enormous ecosystem of service providers, technology companies, and firms from virtually every industry including sports and entertainment. And as well, GSMA, along with its venue partner at the Fira Barcelona, have placed a major emphasis on sustainability and public and private partnerships. Virtually every industry will be represented at the event because every industry is impacted by the trends and opportunities in this space. GSMA has said it expects 80,000 attendees at MWC this year, not quite back to 2019 levels, but trending in that direction. Of course, attendance from Chinese participants has historically been very high at the show, and obviously the continued travel issues from that region are affecting the overall attendance, but still very strong. And despite these concerns, Huawei, the giant Chinese technology company. has the largest physical presence of any exhibitor at the show. And finally, GSMA estimates that more than $300 million in economic benefit will result from the event which takes place at the end of February and early March. And The Cube will be back at MWC this year with a major presence thanks to our anchor sponsor, Dell Technologies and other supporters of our content program, including Enterprise Web, ArcaOS, VMware, Snowflake, Cisco, AWS, and others. And one of the areas we're interested in exploring is the evolution of the telco stack. It's a topic that's often talked about and one that we've observed taking place in the 1990s when the vertically integrated IBM mainframe monopoly gave way to a disintegrated and horizontal industry structure. And in many ways, the same thing is happening today in telecommunications, which is shown on the left-hand side of this diagram. Historically, telcos have relied on a hardened, integrated, and incredibly reliable, and secure set of hardware and software services that have been fully vetted and tested, and certified, and relied upon for decades. And at the top of that stack on the left are the crown jewels of the telco stack, the operational support systems and the business support systems. For the OSS, we're talking about things like network management, network operations, service delivery, quality of service, fulfillment assurance, and things like that. For the BSS systems, these refer to customer-facing elements of the stack, like revenue, order management, what products they sell, billing, and customer service. And what we're seeing is telcos have been really good at operational efficiency and making money off of transport and connectivity, but they've lacked the innovation in services and applications. They own the pipes and that works well, but others, be the over-the-top content companies, or private network providers and increasingly, cloud providers have been able to bypass the telcos, reach around them, if you will, and drive innovation. And so, the right-most diagram speaks to the need to disaggregate pieces of the stack. And while the similarities to the 1990s in enterprise IT are greater than the differences, there are things that are different. For example, the granularity of hardware infrastructure will not likely be as high where competition occurred back in the 90s at every layer of the value chain with very little infrastructure integration. That of course changed in the 2010s with converged infrastructure and hyper-converged and also software defined. So, that's one difference. And the advent of cloud, containers, microservices, and AI, none of that was really a major factor in the disintegration of legacy IT. And that probably means that disruptors can move even faster than did the likes of Intel and Microsoft, Oracle, Cisco, and the Seagates of the 1990s. As well, while many of the products and services will come from traditional enterprise IT names like Dell, HPE, Cisco, Red Hat, VMware, AWS, Microsoft, Google, et cetera, many of the names are going to be different and come from traditional network equipment providers. These are names like Ericsson and Huawei, and Nokia, and other names, like Wind River, and Rakuten, and Dish Networks. And there are enormous opportunities in data to help telecom companies and their competitors go beyond telemetry data into more advanced analytics and data monetization. There's also going to be an entirely new set of apps based on the workloads and use cases ranging from hospitals, sports arenas, race tracks, shipping ports, you name it. Virtually every vertical will participate in this transformation as the industry evolves its focus toward innovation, agility, and open ecosystems. Now remember, this is not a binary state. There are going to be greenfield companies disrupting the apple cart, but the incumbent telcos are going to have to continue to ensure newer systems work with their legacy infrastructure, in their OSS and BSS existing systems. And as we know, this is not going to be an overnight task. Integration is a difficult thing, transformations, migrations. So that's what makes this all so interesting because others can come in with Greenfield and potentially disrupt. There'll be interesting partnerships and ecosystems will form and coalitions will also form. Now, we mentioned that several traditional enterprise companies are or will be playing in this space. Now, ETR doesn't have a ton of data on specific telecom equipment and software providers, but it does have some interesting data that we cut for this breaking analysis. What we're showing here in this graphic is some of the names that we've followed over the years and how they're faring. Specifically, we did the cut within the telco sector. So the Y-axis here shows net score or spending velocity. And the horizontal axis, that shows the presence or pervasiveness in the data set. And that table insert in the upper left, that informs as to how the dots are plotted. You know, the two columns there, net score and the ends. And that red-dotted line, that horizontal line at 40%, that is an indicator of a highly elevated level. Anything above that, we consider quite outstanding. And what we'll do now is we'll comment on some of the cohorts and share with you how they're doing in telecommunications, and that sector, that vertical relative to their position overall in the data set. Let's start with the public cloud players. They're prominent in every industry. Telcos, telecommunications is no exception and it's quite an interesting cohort here. On the one hand, they can help telecommunication firms modernize and become more agile by eliminating the heavy lifting and you know, all the cloud, you know, value prop, data center costs, and the cloud benefits. At the same time, public cloud players are bringing their services to the edge, building out their own global networks and are a disruptive force to traditional telcos. All right, let's talk about Azure first. Their net score is basically identical to telco relative to its overall average. AWS's net score is higher in telco by just a few percentage points. Google Cloud platform is eight percentage points higher in telco with a 53% net score. So all three hyperscalers have an equal or stronger presence in telco than their average overall. Okay, let's look at the traditional enterprise hardware and software infrastructure cohort. Dell, Cisco, HPE, Red Hat, VMware, and Oracle. We've highlighted in this chart just as sort of indicators or proxies. Dell's net score's 10 percentage points higher in telco than its overall average. Interesting. Cisco's is a bit higher. HPE's is actually lower by about nine percentage points in the ETR survey, and VMware's is lower by about four percentage points. Now, Red Hat is really interesting. OpenStack, as we've previously reported is popular with telcos who want to build out their own private cloud. And the data shows that Red Hat OpenStack's net score is 15 percentage points higher in the telco sector than its overall average. OpenShift, on the other hand, has a net score that's four percentage points lower in telco than its overall average. So this to us talks to the pace of adoption of microservices and containers. You know, it's going to happen, but it's going to happen more slowly. Finally, Oracle's spending momentum is somewhat lower in the sector than its average, despite the firm having a decent telco business. IBM and Accenture, heavy services companies are both lower in this sector than their average. And real quickly, snowflake's net score is much lower by about 12 percentage points relative to its very high average net score of 62%. But we look for them to be a player in this space as telcos need to modernize their analytics stack and share data in a governed manner. Databricks' net score is also much lower than its average by about 13 points. And same, I would expect them to be a player as open architectures and cloud gains steam in telco. All right, let's close out now on what we're going to be talking about at MWC23 and some of the key issues that we'll be unpacking. We've talked about stack disaggregation in this breaking analysis, but the key here will be the pace at which it will reach the operational efficiency and reliability of closed stacks. Telcos, you know, in a large part, they're engineering heavy firms and much of their work takes place, kind of in the basement, in the dark. It's not really a big public hype machine, and they tend to move slowly and cautiously. While they understand the importance of agility, they're going to be careful because, you know, it's in their DNA. And so at the same time, if they don't move fast enough, they're going to get hurt and disrupted by competitors. So that's going to be a topic of conversation, and we'll be looking for proof points. And the other comment I'll make is around integration. Telcos because of their conservatism will benefit from better testing and those firms that can innovate on the testing front and have labs and certifications and innovate at that level, with an ecosystem are going to be in a better position. Because open sometimes means wild west. So the more players like Dell, HPE, Cisco, Red Hat, et cetera, that do that and align with their ecosystems and provide those resources, the faster adoption is going to go. So we'll be looking for, you know, who's actually doing that, Open RAN or Radio Access Networks. That fits in this discussion because O-RAN is an emerging network architecture. It essentially enables the use of open technologies from an ecosystem and over time, look at O-RAN is going to be open, but the questions, you know, a lot of questions remain as to when it will be able to deliver the operational efficiency of traditional RAN. Got some interesting dynamics going on. Rakuten is a company that's working hard on this problem, really focusing on operational efficiency. Then you got Dish Networks. They're also embracing O-RAN. They're coming at it more from service innovation. So that's something that we'll be monitoring and unpacking. We're going to look at cloud as a disruptor. On the one hand, cloud can help drive agility, as we said earlier and optionality, and innovation for incumbent telcos. But the flip side is going to also do the same for startups trying to disrupt and cloud attracts startups. While some of the telcos are actually embracing the cloud, many are being cautious. So that's going to be an interesting topic of discussion. And there's private wireless networks and 5G, and hyperlocal private networks, they're being deployed, you know, at the edge. This idea of open edge is also a really hot topic and this trend is going to accelerate. You know, the importance here is that the use cases are going to be widely varied. The needs of a hospital are going to be different than those of a sports venue are different from a remote drilling location, and energy or a concert venue. Things like real-time AI inference and data flows are going to bring new services and monetization opportunities. And many firms are going to be bypassing traditional telecommunications networks to build these out. Satellites as well, we're going to see, you know, in this decade, you're going to have, you're going to look down at Google Earth and you're going to see real-time. You know, today you see snapshots and so, lots of innovations going in that space. So how is this going to disrupt industries and traditional industry structures? Now, as always, we'll be looking at data angles, right? 'Cause it's in The Cube's DNA to follow the data and what opportunities and risks data brings. The Cube is going to be on location at MWC23 at the end of the month. We got a great set. We're in the walkway between halls four and five, right in Congress Square, it's booths CS60. So we'll have a full, they're called Stan CS60. We have a full schedule. I'm going to be there with Lisa Martin, Dave Nicholson and the entire Cube crew, so don't forget to stop by. All right, that's a wrap. I want to thank Alex Myerson, who's on production and manages the podcast, Ken Schiffman as well. Kristin Martin and Cheryl Knight help get the word out on social media and in our newsletters. And Rob Hof is our editor-in-chief over at Silicon Angle, does some great stuff for us. Thank you all. Remember, all these episodes are available as podcasts. Wherever you listen, just search "Breaking Analysis" podcasts I publish each week on wikibon.com and silicon angle.com. And all the video content is available on demand at thecube.net. You can email me directly at david.vellante@silicon angle.com. You can DM me at dvellante or comment on my LinkedIn post. Please do check out etr.ai for the best survey data in the enterprise tech business. This is Dave Vellante for The Cube Insights powered by ETR. Thanks for watching and we'll see you at Mobile World Congress, and/or at next time on "Breaking Analysis." (bright music) (bright music fades)

(gentle synth music) (music ends) >> Welcome back to Supercloud 2, an open industry collaboration between technologists, consultants, analysts, and of course practitioners to help shape the future of cloud. At this event, one of the key areas we're exploring is the intersection of cloud and data. And how building value on top of hyperscale clouds and across clouds is evolving, a concept of course we call "Supercloud". And we're pleased to welcome our friends from Enterprise Technology research, Erik Bradley and Darren Brabham. Guys, thanks for joining us, great to see you. we love to bring the data into these conversations. >> Thank you for having us, Dave, I appreciate it. >> Yeah, thanks. >> You bet. And so, let me do the setup on what is Supercloud. It's a concept that we've floated, Before re:Invent 2021, based on the idea that cloud infrastructure is becoming ubiquitous, incredibly powerful, but there's a lack of standards across the big three clouds. That creates friction. So we defined over the period of time, you know, better part of a year, a set of essential elements, deployment models for so-called supercloud, which create this common experience for specific cloud services that, of course, again, span multiple clouds and even on-premise data. So Erik, with that as background, I wonder if you could add your general thoughts on the term supercloud, maybe play proxy for the CIO community, 'cause you do these round tables, you talk to these guys all the time, you gather a lot of amazing information from senior IT DMs that compliment your survey. So what are your thoughts on the term and the concept? >> Yeah, sure. I'll even go back to last year when you and I did our predictions panel, right? And we threw it out there. And to your point, you know, there's some haters. Anytime you throw out a new term, "Is it marketing buzz? Is it worth it? Why are you even doing it?" But you know, from my own perspective, and then also speaking to the IT DMs that we interview on a regular basis, this is just a natural evolution. It's something that's inevitable in enterprise tech, right? The internet was not built for what it has become. It was never intended to be the underlying infrastructure of our daily lives and work. The cloud also was not built to be what it's become. But where we're at now is, we have to figure out what the cloud is and what it needs to be to be scalable, resilient, secure, and have the governance wrapped around it. And to me that's what supercloud is. It's a way to define operantly, what the next generation, the continued iteration and evolution of the cloud and what its needs to be. And that's what the supercloud means to me. And what depends, if you want to call it metacloud, supercloud, it doesn't matter. The point is that we're trying to define the next layer, the next future of work, which is inevitable in enterprise tech. Now, from the IT DM perspective, I have two interesting call outs. One is from basically a senior developer IT architecture and DevSecOps who says he uses the term all the time. And the reason he uses the term, is that because multi-cloud has a stigma attached to it, when he is talking to his business executives. (David chuckles) the stigma is because it's complex and it's expensive. So he switched to supercloud to better explain to his business executives and his CFO and his CIO what he's trying to do. And we can get into more later about what it means to him. But the inverse of that, of course, is a good CSO friend of mine for a very large enterprise says the concern with Supercloud is the reduction of complexity. And I'll explain, he believes anything that takes the requirement of specific expertise out of the equation, even a little bit, as a CSO worries him. So as you said, David, always two sides to the coin, but I do believe supercloud is a relevant term, and it is necessary because the cloud is continuing to be defined. >> You know, that's really interesting too, 'cause you know, Darren, we use Snowflake a lot as an example, sort of early supercloud, and you think from a security standpoint, we've always pushed Amazon and, "Are you ever going to kind of abstract the complexity away from all these primitives?" and their position has always been, "Look, if we produce these primitives, and offer these primitives, we we can move as the market moves. When you abstract, then it becomes harder to peel the layers." But Darren, from a data standpoint, like I say, we use Snowflake a lot. I think of like Tim Burners-Lee when Web 2.0 came out, he said, "Well this is what the internet was always supposed to be." So in a way, you know, supercloud is maybe what multi-cloud was supposed to be. But I mean, you think about data sharing, Darren, across clouds, it's always been a challenge. Snowflake always, you know, obviously trying to solve that problem, as are others. But what are your thoughts on the concept? >> Yeah, I think the concept fits, right? It is reflective of, it's a paradigm shift, right? Things, as a pendulum have swung back and forth between needing to piece together a bunch of different tools that have specific unique use cases and they're best in breed in what they do. And then focusing on the duct tape that holds 'em all together and all the engineering complexity and skill, it shifted from that end of the pendulum all the way back to, "Let's streamline this, let's simplify it. Maybe we have budget crunches and we need to consolidate tools or eliminate tools." And so then you kind of see this back and forth over time. And with data and analytics for instance, a lot of organizations were trying to bring the data closer to the business. That's where we saw self-service analytics coming in. And tools like Snowflake, what they did was they helped point to different databases, they helped unify data, and organize it in a single place that was, you know, in a sense neutral, away from a single cloud vendor or a single database, and allowed the business to kind of be more flexible in how it brought stuff together and provided it out to the business units. So Snowflake was an example of one of those times where we pulled back from the granular, multiple points of the spear, back to a simple way to do things. And I think Snowflake has continued to kind of keep that mantle to a degree, and we see other tools trying to do that, but that's all it is. It's a paradigm shift back to this kind of meta abstraction layer that kind of simplifies what is the reality, that you need a complex multi-use case, multi-region way of doing business. And it sort of reflects the reality of that. >> And you know, to me it's a spectrum. As part of Supercloud 2, we're talking to a number of of practitioners, Ionis Pharmaceuticals, US West, we got Walmart. And it's a spectrum, right? In some cases the practitioner's saying, "You know, the way I solve multi-cloud complexity is mono-cloud, I just do one cloud." (laughs) Others like Walmart are saying, "Hey, you know, we actually are building an abstraction layer ourselves, take advantage of it." So my general question to both of you is, is this a concept, is the lack of standards across clouds, you know, really a problem, you know, or is supercloud a solution looking for a problem? Or do you hear from practitioners that "No, this is really an issue, we have to bring together a set of standards to sort of unify our cloud estates." >> Allow me to answer that at a higher level, and then we're going to hand it over to Dr. Brabham because he is a little bit more detailed on the realtime streaming analytics use cases, which I think is where we're going to get to. But to answer that question, it really depends on the size and the complexity of your business. At the very large enterprise, Dave, Yes, a hundred percent. This needs to happen. There is complexity, there is not only complexity in the compute and actually deploying the applications, but the governance and the security around them. But for lower end or, you know, business use cases, and for smaller businesses, it's a little less necessary. You certainly don't need to have all of these. Some of the things that come into mind from the interviews that Darren and I have done are, you know, financial services, if you're doing real-time trading, anything that has real-time data metrics involved in your transactions, is going to be necessary. And another use case that we hear about is in online travel agencies. So I think it is very relevant, the complexity does need to be solved, and I'll allow Darren to explain a little bit more about how that's used from an analytics perspective. >> Yeah, go for it. >> Yeah, exactly. I mean, I think any modern, you know, multinational company that's going to have a footprint in the US and Europe, in China, or works in different areas like manufacturing, where you're probably going to have on-prem instances that will stay on-prem forever, for various performance reasons. You have these complicated governance and security and regulatory issues. So inherently, I think, large multinational companies and or companies that are in certain areas like finance or in, you know, online e-commerce, or things that need real-time data, they inherently are going to have a very complex environment that's going to need to be managed in some kind of cleaner way. You know, they're looking for one door to open, one pane of glass to look at, one thing to do to manage these multi points. And, streaming's a good example of that. I mean, not every organization has a real-time streaming use case, and may not ever, but a lot of organizations do, a lot of industries do. And so there's this need to use, you know, they want to use open-source tools, they want to use Apache Kafka for instance. They want to use different megacloud vendors offerings, like Google Pub/Sub or you know, Amazon Kinesis Firehose. They have all these different pieces they want to use for different use cases at different stages of maturity or proof of concept, you name it. They're going to have to have this complexity. And I think that's why we're seeing this need, to have sort of this supercloud concept, to juggle all this, to wrangle all of it. 'Cause the reality is, it's complex and you have to simplify it somehow. >> Great, thanks you guys. All right, let's bring up the graphic, and take a look. Anybody who follows the breaking analysis, which is co-branded with ETR Cube Insights powered by ETR, knows we like to bring data to the table. ETR does amazing survey work every quarter, 1200 plus 1500 practitioners that that answer a number of questions. The vertical axis here is net score, which is ETR's proprietary methodology, which is a measure of spending momentum, spending velocity. And the horizontal axis here is overlap, but it's the presence pervasiveness, and the dataset, the ends, that table insert on the bottom right shows you how the dots are plotted, the net score and then the ends in the survey. And what we've done is we've plotted a bunch of the so-called supercloud suspects, let's start in the upper right, the cloud platforms. Without these hyperscale clouds, you can't have a supercloud. And as always, Azure and AWS, up and to the right, it's amazing we're talking about, you know, 80 plus billion dollar company in AWS. Azure's business is, if you just look at the IaaS is in the 50 billion range, I mean it's just amazing to me the net scores here. Anything above 40% we consider highly elevated. And you got Azure and you got Snowflake, Databricks, HashiCorp, we'll get to them. And you got AWS, you know, right up there at that size, it's quite amazing. With really big ends as well, you know, 700 plus ends in the survey. So, you know, kind of half the survey actually has these platforms. So my question to you guys is, what are you seeing in terms of cloud adoption within the big three cloud players? I wonder if you could could comment, maybe Erik, you could start. >> Yeah, sure. Now we're talking data, now I'm happy. So yeah, we'll get into some of it. Right now, the January, 2023 TSIS is approaching 1500 survey respondents. One caveat, it's not closed yet, it will close on Friday, but with an end that big we are over statistically significant. We also recently did a cloud survey, and there's a couple of key points on that I want to get into before we get into individual vendors. What we're seeing here, is that annual spend on cloud infrastructure is expected to grow at almost a 70% CAGR over the next three years. The percentage of those workloads for cloud infrastructure are expected to grow over 70% as three years as well. And as you mentioned, Azure and AWS are still dominant. However, we're seeing some share shift spreading around a little bit. Now to get into the individual vendors you mentioned about, yes, Azure is still number one, AWS is number two. What we're seeing, which is incredibly interesting, CloudFlare is number three. It's actually beating GCP. That's the first time we've seen it. What I do want to state, is this is on net score only, which is our measure of spending intentions. When you talk about actual pervasion in the enterprise, it's not even close. But from a spending velocity intention point of view, CloudFlare is now number three above GCP, and even Salesforce is creeping up to be at GCPs level. So what we're seeing here, is a continued domination by Azure and AWS, but some of these other players that maybe might fit into your moniker. And I definitely want to talk about CloudFlare more in a bit, but I'm going to stop there. But what we're seeing is some of these other players that fit into your Supercloud moniker, are starting to creep up, Dave. >> Yeah, I just want to clarify. So as you also know, we track IaaS and PaaS revenue and we try to extract, so AWS reports in its quarterly earnings, you know, they're just IaaS and PaaS, they don't have a SaaS play, a little bit maybe, whereas Microsoft and Google include their applications and so we extract those out and if you do that, AWS is bigger, but in the surveys, you know, customers, they see cloud, SaaS to them as cloud. So that's one of the reasons why you see, you know, Microsoft as larger in pervasion. If you bring up that survey again, Alex, the survey results, you see them further to the right and they have higher spending momentum, which is consistent with what you see in the earnings calls. Now, interesting about CloudFlare because the CEO of CloudFlare actually, and CloudFlare itself uses the term supercloud basically saying, "Hey, we're building a new type of internet." So what are your thoughts? Do you have additional information on CloudFlare, Erik that you want to share? I mean, you've seen them pop up. I mean this is a really interesting company that is pretty forward thinking and vocal about how it's disrupting the industry. >> Sure, we've been tracking 'em for a long time, and even from the disruption of just a traditional CDN where they took down Akamai and what they're doing. But for me, the definition of a true supercloud provider can't just be one instance. You have to have multiple. So it's not just the cloud, it's networking aspect on top of it, it's also security. And to me, CloudFlare is the only one that has all of it. That they actually have the ability to offer all of those things. Whereas you look at some of the other names, they're still piggybacking on the infrastructure or platform as a service of the hyperscalers. CloudFlare does not need to, they actually have the cloud, the networking, and the security all themselves. So to me that lends credibility to their own internal usage of that moniker Supercloud. And also, again, just what we're seeing right here that their net score is now creeping above AGCP really does state it. And then just one real last thing, one of the other things we do in our surveys is we track adoption and replacement reasoning. And when you look at Cloudflare's adoption rate, which is extremely high, it's based on technical capabilities, the breadth of their feature set, it's also based on what we call the ability to avoid stack alignment. So those are again, really supporting reasons that makes CloudFlare a top candidate for your moniker of supercloud. >> And they've also announced an object store (chuckles) and a database. So, you know, that's going to be, it takes a while as you well know, to get database adoption going, but you know, they're ambitious and going for it. All right, let's bring the chart back up, and I want to focus Darren in on the ecosystem now, and really, we've identified Snowflake and Databricks, it's always fun to talk about those guys, and there are a number of other, you know, data platforms out there, but we use those too as really proxies for leaders. We got a bunch of the backup guys, the data protection folks, Rubric, Cohesity, and Veeam. They're sort of in a cluster, although Rubric, you know, ahead of those guys in terms of spending momentum. And then VMware, Tanzu and Red Hat as sort of the cross cloud platform. But I want to focus, Darren, on the data piece of it. We're seeing a lot of activity around data sharing, governed data sharing. Databricks is using Delta Sharing as their sort of place, Snowflakes is sort of this walled garden like the app store. What are your thoughts on, you know, in the context of Supercloud, cross cloud capabilities for the data platforms? >> Yeah, good question. You know, I think Databricks is an interesting player because they sort of have made some interesting moves, with their Data Lakehouse technology. So they're trying to kind of complicate, or not complicate, they're trying to take away the complications of, you know, the downsides of data warehousing and data lakes, and trying to find that middle ground, where you have the benefits of a managed, governed, you know, data warehouse environment, but you have sort of the lower cost, you know, capability of a data lake. And so, you know, Databricks has become really attractive, especially by data scientists, right? We've been tracking them in the AI machine learning sector for quite some time here at ETR, attractive for a data scientist because it looks and acts like a lake, but can have some managed capabilities like a warehouse. So it's kind of the best of both worlds. So in some ways I think you've seen sort of a data science driver for the adoption of Databricks that has now become a little bit more mainstream across the business. Snowflake, maybe the other direction, you know, it's a cloud data warehouse that you know, is starting to expand its capabilities and add on new things like Streamlit is a good example in the analytics space, with apps. So you see these tools starting to branch and creep out a bit, but they offer that sort of neutrality, right? We heard one IT decision maker we recently interviewed that referred to Snowflake and Databricks as the quote unquote Switzerland of what they do. And so there's this desirability from an organization to find these tools that can solve the complex multi-headed use-case of data and analytics, which every business unit needs in different ways. And figure out a way to do that, an elegant way that's governed and centrally managed, that federated kind of best of both worlds that you get by bringing the data close to the business while having a central governed instance. So these tools are incredibly powerful and I think there's only going to be room for growth, for those two especially. I think they're going to expand and do different things and maybe, you know, join forces with others and a lot of the power of what they do well is trying to define these connections and find these partnerships with other vendors, and try to be seen as the nice add-on to your existing environment that plays nicely with everyone. So I think that's where those two tools are going, but they certainly fit this sort of label of, you know, trying to be that supercloud neutral, you know, layer that unites everything. >> Yeah, and if you bring the graphic back up, please, there's obviously big data plays in each of the cloud platforms, you know, Microsoft, big database player, AWS is, you know, 11, 12, 15, data stores. And of course, you know, BigQuery and other, you know, data platforms within Google. But you know, I'm not sure the big cloud guys are going to go hard after so-called supercloud, cross-cloud services. Although, we see Oracle getting in bed with Microsoft and Azure, with a database service that is cross-cloud, certainly Google with Anthos and you know, you never say never with with AWS. I guess what I would say guys, and I'll I'll leave you with this is that, you know, just like all players today are cloud players, I feel like anybody in the business or most companies are going to be so-called supercloud players. In other words, they're going to have a cross-cloud strategy, they're going to try to build connections if they're coming from on-prem like a Dell or an HPE, you know, or Pure or you know, many of these other companies, Cohesity is another one. They're going to try to connect to their on-premise states, of course, and create a consistent experience. It's natural that they're going to have sort of some consistency across clouds. You know, the big question is, what's that spectrum look like? I think on the one hand you're going to have some, you know, maybe some rudimentary, you know, instances of supercloud or maybe they just run on the individual clouds versus where Snowflake and others and even beyond that are trying to go with a single global instance, basically building out what I would think of as their own cloud, and importantly their own ecosystem. I'll give you guys the last thought. Maybe you could each give us, you know, closing thoughts. Maybe Darren, you could start and Erik, you could bring us home on just this entire topic, the future of cloud and data. >> Yeah, I mean I think, you know, two points to make on that is, this question of these, I guess what we'll call legacy on-prem players. These, mega vendors that have been around a long time, have big on-prem footprints and a lot of people have them for that reason. I think it's foolish to assume that a company, especially a large, mature, multinational company that's been around a long time, it's foolish to think that they can just uproot and leave on-premises entirely full scale. There will almost always be an on-prem footprint from any company that was not, you know, natively born in the cloud after 2010, right? I just don't think that's reasonable anytime soon. I think there's some industries that need on-prem, things like, you know, industrial manufacturing and so on. So I don't think on-prem is going away, and I think vendors that are going to, you know, go very cloud forward, very big on the cloud, if they neglect having at least decent connectors to on-prem legacy vendors, they're going to miss out. So I think that's something that these players need to keep in mind is that they continue to reach back to some of these players that have big footprints on-prem, and make sure that those integrations are seamless and work well, or else their customers will always have a multi-cloud or hybrid experience. And then I think a second point here about the future is, you know, we talk about the three big, you know, cloud providers, the Google, Microsoft, AWS as sort of the opposite of, or different from this new supercloud paradigm that's emerging. But I want to kind of point out that, they will always try to make a play to become that and I think, you know, we'll certainly see someone like Microsoft trying to expand their licensing and expand how they play in order to become that super cloud provider for folks. So also don't want to downplay them. I think you're going to see those three big players continue to move, and take over what players like CloudFlare are doing and try to, you know, cut them off before they get too big. So, keep an eye on them as well. >> Great points, I mean, I think you're right, the first point, if you're Dell, HPE, Cisco, IBM, your strategy should be to make your on-premise state as cloud-like as possible and you know, make those differences as minimal as possible. And you know, if you're a customer, then the business case is going to be low for you to move off of that. And I think you're right. I think the cloud guys, if this is a real problem, the cloud guys are going to play in there, and they're going to make some money at it. Erik, bring us home please. >> Yeah, I'm going to revert back to our data and this on the macro side. So to kind of support this concept of a supercloud right now, you know Dave, you and I know, we check overall spending and what we're seeing right now is total year spent is expected to only be 4.6%. We ended 2022 at 5% even though it began at almost eight and a half. So this is clearly declining and in that environment, we're seeing the top two strategies to reduce spend are actually vendor consolidation with 36% of our respondents saying they're actively seeking a way to reduce their number of vendors, and consolidate into one. That's obviously supporting a supercloud type of play. Number two is reducing excess cloud resources. So when I look at both of those combined, with a drop in the overall spending reduction, I think you're on the right thread here, Dave. You know, the overall macro view that we're seeing in the data supports this happening. And if I can real quick, couple of names we did not touch on that I do think deserve to be in this conversation, one is HashiCorp. HashiCorp is the number one player in our infrastructure sector, with a 56% net score. It does multiple things within infrastructure and it is completely agnostic to your environment. And if we're also speaking about something that's just a singular feature, we would look at Rubric for data, backup, storage, recovery. They're not going to offer you your full cloud or your networking of course, but if you are looking for your backup, recovery, and storage Rubric, also number one in that sector with a 53% net score. Two other names that deserve to be in this conversation as we watch it move and evolve. >> Great, thank you for bringing that up. Yeah, we had both of those guys in the chart and I failed to focus in on HashiCorp. And clearly a Supercloud enabler. All right guys, we got to go. Thank you so much for joining us, appreciate it. Let's keep this conversation going. >> Always enjoy talking to you Dave, thanks. >> Yeah, thanks for having us. >> All right, keep it right there for more content from Supercloud 2. This is Dave Valente for John Ferg and the entire Cube team. We'll be right back. (gentle synth music) (music fades)

>> 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. >> The unraveling of market enthusiasm continued in Q4 of 2022 with the earnings reports from the US hyperscalers, the big three now all in. As we said earlier this year, even the cloud is an immune from the macro headwinds and the cracks in the armor that we saw from the data that we shared last summer, they're playing out into 2023. For the most part actuals are disappointing beyond expectations including our own. It turns out that our estimates for the big three hyperscaler's revenue missed by 1.2 billion or 2.7% lower than we had forecast from even our most recent November estimates. And we expect continued decelerating growth rates for the hyperscalers through the summer of 2023 and we don't think that's going to abate until comparisons get easier. Hello and welcome to this week's Wikibon Cube Insights powered by ETR. In this Breaking Analysis, we share our view of what's happening in cloud markets not just for the hyperscalers but other firms that have hitched a ride on the cloud. And we'll share new ETR data that shows why these trends are playing out tactics that customers are employing to deal with their cost challenges and how long the pain is likely to last. You know, riding the cloud wave, it's a two-edged sword. Let's look at the players that have gone all in on or are exposed to both the positive and negative trends of cloud. Look the cloud has been a huge tailwind for so many companies like Snowflake and Databricks, Workday, Salesforce, Mongo's move with Atlas, Red Hats Cloud strategy with OpenShift and so forth. And you know, the flip side is because cloud is elastic what comes up can also go down very easily. Here's an XY graphic from ETR that shows spending momentum or net score on the vertical axis and market presence in the dataset on the horizontal axis provision or called overlap. This is data from the January 2023 survey and that the red dotted lines show the positions of several companies that we've highlighted going back to January 2021. So let's unpack this for a bit starting with the big three hyperscalers. The first point is AWS and Azure continue to solidify their moat relative to Google Cloud platform. And we're going to get into this in a moment, but Azure and AWS revenues are five to six times that of GCP for IaaS. And at those deltas, Google should be gaining ground much faster than the big two. The second point on Google is notice the red line on GCP relative to its starting point. While it appears to be gaining ground on the horizontal axis, its net score is now below that of AWS and Azure in the survey. So despite its significantly smaller size it's just not keeping pace with the leaders in terms of market momentum. Now looking at AWS and Microsoft, what we see is basically AWS is holding serve. As we know both Google and Microsoft benefit from including SaaS in their cloud numbers. So the fact that AWS hasn't seen a huge downward momentum relative to a January 2021 position is one positive in the data. And both companies are well above that magic 40% line on the Y-axis, anything above 40% we consider to be highly elevated. But the fact remains that they're down as are most of the names on this chart. So let's take a closer look. I want to start with Snowflake and Databricks. Snowflake, as we reported from several quarters back came down to Earth, it was up in the 80% range in the Y-axis here. And it's still highly elevated in the 60% range and it continues to move to the right, which is positive but as we'll address in a moment it's customers can dial down consumption just as in any cloud. Now, Databricks is really interesting. It's not a public company, it never made it to IPO during the sort of tech bubble. So we don't have the same level of transparency that we do with other companies that did make it through. But look at how much more prominent it is on the X-axis relative to January 2021. And it's net score is basically held up over that period of time. So that's a real positive for Databricks. Next, look at Workday and Salesforce. They've held up relatively well, both inching to the right and generally holding their net scores. Same from Mongo, which is the brown dot above its name that says Elastic, it says a little gets a little crowded which Elastic's actually the blue dot above it. But generally, SaaS is harder to dial down, Workday, Salesforce, Oracles, SaaS and others. So it's harder to dial down because commitments have been made in advance, they're kind of locked in. Now, one of the discussions from last summer was as Mongo, less discretionary than analytics i.e. Snowflake. And it's an interesting debate but maybe Snowflake customers, you know, they're also generally committed to a dollar amount. So over time the spending is going to be there. But in the short term, yeah maybe Snowflake customers can dial down. Now that highlighted dotted red line, that bolded one is Datadog and you can see it's made major strides on the X-axis but its net score has decelerated quite dramatically. Openshift's momentum in the survey has dropped although IBM just announced that OpenShift has a a billion dollar ARR and I suspect what's happening there is IBM consulting is bundling OpenShift into its modernization projects. It's got a, that sort of captive base if you will. And as such it's probably not as top of mind to the respondents but I'll bet you the developers are certainly aware of it. Now the other really notable call out here is CloudFlare, We've reported on them earlier. Cloudflare's net score has held up really well since January of 2021. It really hasn't seen the downdraft of some of these others, but it's making major major moves to the right gaining market presence. We really like how CloudFlare is performing. And the last comment is on Oracle which as you can see, despite its much, much lower net score continues to gain ground in the market and thrive from a profitability standpoint. But the data pretty clearly shows that there's a downdraft in the market. Okay, so what's happening here? Let's dig deeper into this data. Here's a graphic from the most recent ETR drill down asking customers that said they were going to cut spending what technique they're using to do so. Now, as we've previously reported, consolidating redundant vendors is by far the most cited approach but there's two key points we want to make here. One is reducing excess cloud resources. As you can see in the bars is the second most cited technique and it's up from the previous polling period. The second we're not showing, you know directly but we've got some red call outs there. Reducing cloud costs jumps to 29% and 28% respectively in financial services and tech telco. And it's much closer to second. It's basically neck and neck with consolidating redundant vendors in those two industries. So they're being really aggressive about optimizing cloud cost. Okay, so as we said, cloud is great 'cause you can dial it up but it's just as easy to dial down. We've identified six factors that customers tell us are affecting their cloud consumption and there are probably more, if you got more we'd love to hear them but these are the ones that are fairly prominent that have hit our radar. First, rising mortgage rates mean banks are processing fewer loans means less cloud. The crypto crash means less trading activity and that means less cloud resources. Third lower ad spend has led companies to reduce not only you know, their ad buying but also their frequency of running their analytics and their calculations. And they're also often using less data, maybe compressing the timeframe of the corpus down to a shorter time period. Also very prominent is down to the bottom left, using lower cost compute instances. For example, Graviton from AWS or AMD chips and tiering storage to cheaper S3 or deep archived tiers. And finally, optimizing based on better pricing plans. So customers are moving from, you know, smaller companies in particular moving maybe from on demand or other larger companies that are experimenting using on demand or they're moving to spot pricing or reserved instances or optimized savings plans. That all lowers cost and that means less cloud resource consumption and less cloud revenue. Now in the days when everything was on prem CFOs, what would they do? They would freeze CapEx and IT Pros would have to try to do more with less and often that meant a lot of manual tasks. With the cloud it's much easier to move things around. It still takes some thinking and some effort but it's dramatically simpler to do so. So you can get those savings a lot faster. Now of course the other huge factor is you can cut or you can freeze. And this graphic shows data from a recent ETR survey with 159 respondents and you can see the meaningful uptick in hiring freezes, freezing new IT deployments and layoffs. And as we've been reporting, this has been trending up since earlier last year. And note the call out, this is especially prominent in retail sectors, all three of these techniques jump up in retail and that's a bit of a concern because oftentimes consumer spending helps the economy make a softer landing out of a pullback. But this is a potential canary in the coal mine. If retail firms are pulling back it's because consumers aren't spending as much. And so we're keeping a close eye on that. So let's boil this down to the market data and what this all means. So in this graphic we show our estimates for Q4 IaaS revenues compared to the "actual" IaaS revenues. And we say quote because AWS is the only one that reports, you know clean revenue and IaaS, Azure and GCP don't report actuals. Why would they? Because it would make them look even, you know smaller relative to AWS. Rather, they bury the figures in overall cloud which includes their, you know G-Suite for Google and all the Microsoft SaaS. And then they give us little tidbits about in Microsoft's case, Azure, they give growth rates. Google gives kind of relative growth of GCP. So, and we use survey data and you know, other data to try to really pinpoint and we've been covering this for, I don't know, five or six years ever since the cloud really became a thing. But looking at the data, we had AWS growing at 25% this quarter and it came in at 20%. So a significant decline relative to our expectations. AWS announced that it exited December, actually, sorry it's January data showed about a 15% mid-teens growth rate. So that's, you know, something we're watching. Azure was two points off our forecast coming in at 38% growth. It said it exited December in the 35% growth range and it said that it's expecting five points of deceleration off of that. So think 30% for Azure. GCP came in three points off our expectation coming in 35% and Alibaba has yet to report but we've shaved a bid off that forecast based on some survey data and you know what maybe 9% is even still not enough. Now for the year, the big four hyperscalers generated almost 160 billion of revenue, but that was 7 billion lower than what what we expected coming into 2022. For 2023, we're expecting 21% growth for a total of 193.3 billion. And while it's, you know, lower, you know, significantly lower than historical expectations it's still four to five times the overall spending forecast that we just shared with you in our predictions post of between 4 and 5% for the overall market. We think AWS is going to come in in around 93 billion this year with Azure closing in at over 71 billion. This is, again, we're talking IaaS here. Now, despite Amazon focusing investors on the fact that AWS's absolute dollar growth is still larger than its competitors. By our estimates Azure will come in at more than 75% of AWS's forecasted revenue. That's a significant milestone. AWS is operating margins by the way declined significantly this past quarter, dropping from 30% of revenue to 24%, 30% the year earlier to 24%. Now that's still extremely healthy and we've seen wild fluctuations like this before so I don't get too freaked out about that. But I'll say this, Microsoft has a marginal cost advantage relative to AWS because one, it has a captive cloud on which to run its massive software estate. So it can just throw software at its own cloud and two software marginal costs. Marginal economics despite AWS's awesomeness in high degrees of automation, software is just a better business. Now the upshot for AWS is the ecosystem. AWS is essentially in our view positioning very smartly as a platform for data partners like Snowflake and Databricks, security partners like CrowdStrike and Okta and Palo Alto and many others and SaaS companies. You know, Microsoft is more competitive even though AWS does have competitive products. Now of course Amazon's competitive to retail companies so that's another factor but generally speaking for tech players, Amazon is a really thriving ecosystem that is a secret weapon in our view. AWS happy to spin the meter with its partners even though it sells competitive products, you know, more so in our view than other cloud players. Microsoft, of course is, don't forget is hyping now, we're hearing a lot OpenAI and ChatGPT we reported last week in our predictions post. How OpenAI is shot up in terms of market sentiment in ETR's emerging technology company surveys and people are moving to Azure to get OpenAI and get ChatGPT that is a an interesting lever. Amazon in our view has to have a response. They have lots of AI and they're going to have to make some moves there. Meanwhile, Google is emphasizing itself as an AI first company. In fact, Google spent at least five minutes of continuous dialogue, nonstop on its AI chops during its latest earnings call. So that's an area that we're watching very closely as the buzz around large language models continues. All right, let's wrap up with some assumptions for 2023. We think SaaS players are going to continue to be sticky. They're going to be somewhat insulated from all these downdrafts because they're so tied in and customers, you know they make the commitment up front, you've got the lock in. Now having said that, we do expect some backlash over time on the onerous and generally customer unfriendly pricing models of most large SaaS companies. But that's going to play out over a longer period of time. Now for cloud generally and the hyperscalers specifically we do expect accelerating growth rates into Q3 but the amplitude of the demand swings from this rubber band economy, we expect to continue to compress and become more predictable throughout the year. Estimates are coming down, CEOs we think are going to be more cautious when the market snaps back more cautious about hiring and spending and as such a perhaps we expect a more orderly return to growth which we think will slightly accelerate in Q4 as comps get easier. Now of course the big risk to these scenarios is of course the economy, the FED, consumer spending, inflation, supply chain, energy prices, wars, geopolitics, China relations, you know, all the usual stuff. But as always with our partners at ETR and the Cube community, we're here for you. We have the data and we'll be the first to report when we see a change at the margin. Okay, that's a wrap for today. I want to thank Alex Morrison who's on production and manages the podcast, Ken Schiffman as well out of our Boston studio getting this up on LinkedIn Live. Thank you for that. Kristen Martin also and Cheryl Knight help get the word out on social media and in our newsletters. And Rob Hof is our Editor-in-Chief over at siliconangle.com. He does some great editing for us. Thank you all. Remember all these episodes are available as podcast. Wherever you listen, just search Breaking Analysis podcast. I publish each week on wikibon.com, at siliconangle.com where you can see all the data and you want to get in touch. Just all you can do is email me david.vellante@siliconangle.com or DM me @dvellante if you if you got something interesting, I'll respond. If you don't, it's either 'cause I'm swamped or it's just not tickling me. You can comment on our LinkedIn post as well. And please check out ETR.ai for the best survey data in the enterprise tech business. This is Dave Vellante for the Cube Insights powered by ETR. Thanks for watching and we'll see you next time on Breaking Analysis. (gentle upbeat music)

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

>> 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. >> A better than expected earnings report in late August got people excited about Snowflake again, but the negative sentiment in the market is weighed heavily on virtually all growth tech stocks and Snowflake is no exception. As we've stressed many times the company's management is on a long term mission to dramatically simplify the way organizations use data. Snowflake is tapping into a multi hundred billion dollar total available market and continues to grow at a rapid pace. In our view, Snowflake is embarking on its third major wave of innovation data apps, while its first and second waves are still bearing significant fruit. Now for short term traders focused on the next 90 or 180 days, that probably doesn't matter. But those taking a longer view are asking, "Should we still be optimistic about the future of this high flyer or is it just another over hyped tech play?" Hello and welcome to this week's Wiki Bond Cube Insights powered by ETR. Snowflake's Quarter just ended. And in this breaking analysis we take a look at the most recent survey data from ETR to see what clues and nuggets we can extract to predict the near term future in the long term outlook for Snowflake which is going to announce its earnings at the end of this month. Okay, so you know the story. If you've been investor in Snowflake this year, it's been painful. We said at IPO, "If you really want to own this stock on day one, just hold your nose and buy it." But like most IPOs we said there will be likely a better entry point in the future, and not surprisingly that's been the case. Snowflake IPOed a price of 120, which you couldn't touch on day one unless you got into a friends and family Delio. And if you did, you're still up 5% or so. So congratulations. But at one point last year you were up well over 200%. That's been the nature of this volatile stock, and I certainly can't help you with the timing of the market. But longer term Snowflake is targeting 10 billion in revenue for fiscal year 2028. A big number. Is it achievable? Is it big enough? Tell you what, let's come back to that. Now shorter term, our expert trader and breaking analysis contributor Chip Simonton said he got out of the stock a while ago after having taken a shot at what turned out to be a bear market rally. He pointed out that the stock had been bouncing around the 150 level for the last few months and broke that to the downside last Friday. So he'd expect 150 is where the stock is going to find resistance on the way back up, but there's no sign of support right now. He said maybe at 120, which was the July low and of course the IPO price that we just talked about. Now, perhaps earnings will be a catalyst, when Snowflake announces on November 30th, but until the mentality toward growth tech changes, nothing's likely to change dramatically according to Simonton. So now that we have that out of the way, let's take a look at the spending data for Snowflake in the ETR survey. Here's a chart that shows the time series breakdown of snowflake's net score going back to the October, 2021 survey. Now at that time, Snowflake's net score stood at a robust 77%. And remember, net score is a measure of spending velocity. It's a proprietary network, and ETR derives it from a quarterly survey of IT buyers and asks the respondents, "Are you adopting the platform new? Are you spending 6% or more? Is you're spending flat? Is you're spending down 6% or worse? Or are you leaving the platform decommissioning?" You subtract the percent of customers that are spending less or churning from those that are spending more and adopting or adopting and you get a net score. And that's expressed as a percentage of customers responding. In this chart we show Snowflake's in out of the total survey which ranges... The total survey ranges between 1,200 and 1,400 each quarter. And the very last column... Oh sorry, very last row, we show the number of Snowflake respondents that are coming in the survey from the Fortune 500 and the Global 2000. Those are two very important Snowflake constituencies. Now what this data tells us is that Snowflake exited 2021 with very strong momentum in a net score of 82%, which is off the charts and it was actually accelerating from the previous survey. Now by April that sentiment had flipped and Snowflake came down to earth with a 68% net score. Still highly elevated relative to its peers, but meaningfully down. Why was that? Because we saw a drop in new ads and an increase in flat spend. Then into the July and most recent October surveys, you saw a significant drop in the percentage of customers that were spending more. Now, notably, the percentage of customers who are contemplating adding the platform is actually staying pretty strong, but it is off a bit this past survey. And combined with a slight uptick in planned churn, net score is now down to 60%. That uptick from 0% and 1% and then 3%, it's still small, but that net score at 60% is still 20 percentage points higher than our highly elevated benchmark of 40% as you recall from listening to earlier breaking analysis. That 40% range is we consider a milestone. Anything above that is actually quite strong. But again, Snowflake is down and coming back to churn, while 3% churn is very low, in previous quarters we've seen Snowflake 0% or 1% decommissions. Now the last thing to note in this chart is the meaningful uptick in survey respondents that are citing, they're using the Snowflake platform. That's up to 212 in the survey. So look, it's hard to imagine that Snowflake doesn't feel the softening in the market like everyone else. Snowflake is guiding for around 60% growth in product revenue against the tough compare from a year ago with a 2% operating margin. So like every company, the reaction of the street is going to come down to how accurate or conservative the guide is from their CFO. Now, earlier this year, Snowflake acquired a company called Streamlit for around $800 million. Streamlit is an open source Python library and it makes it easier to build data apps with machine learning, obviously a huge trend. And like Snowflake, generally its focus is on simplifying the complex, in this case making data science easier to integrate into data apps that business people can use. So we were excited this summer in the July ETR survey to see that they added some nice data and pick on Streamlit, which we're showing here in comparison to Snowflake's core business on the left hand side. That's the data warehousing, the Streamlit pieces on the right hand side. And we show again net score over time from the previous survey for Snowflake's core database and data warehouse offering again on the left as compared to a Streamlit on the right. Snowflake's core product had 194 responses in the October, 22 survey, Streamlit had an end of 73, which is up from 52 in the July survey. So significant uptick of people responding that they're doing business in adopting Streamlit. That was pretty impressive to us. And it's hard to see, but the net scores stayed pretty constant for Streamlit at 51%. It was 52% I think in the previous quarter, well over that magic 40% mark. But when you blend it with Snowflake, it does sort of bring things down a little bit. Now there are two key points here. One is that the acquisition seems to have gained exposure right out of the gate as evidenced by the large number of responses. And two, the spending momentum. Again while it's lower than Snowflake overall, and when you blend it with Snowflake it does pull it down, it's very healthy and steady. Now let's do a little pure comparison with some of our favorite names in this space. This chart shows net score or spending velocity in the Y-axis, an overlap or presence, pervasiveness if you will, in the data set on the X-axis. That red dotted line again is that 40% highly elevated net score that we like to talk about. And that table inserted informs us as to how the companies are plotted, where the dots set up, the net score, the ins. And we're comparing a number of database players, although just a caution, Oracle includes all of Oracle including its apps. But we just put it in there for reference because it is the leader in database. Right off the bat, Snowflake jumps out with a net score of 64%. The 60% from the earlier chart, again included Streamlit. So you can see its core database, data warehouse business actually is higher than the total company average that we showed you before 'cause the Streamlit is blended in. So when you separate it out, Streamlit is right on top of data bricks. Isn't that ironic? Only Snowflake and Databricks in this selection of names are above the 40% level. You see Mongo and Couchbase, they know they're solid and Teradata cloud actually showing pretty well compared to some of the earlier survey results. Now let's isolate on the database data platform sector and see how that shapes up. And for this analysis, same XY dimensions, we've added the big giants, AWS and Microsoft and Google. And notice that those three plus Snowflake are just at or above the 40% line. Snowflake continues to lead by a significant margin in spending momentum and it keeps creeping to the right. That's that end that we talked about earlier. Now here's an interesting tidbit. Snowflake is often asked, and I've asked them myself many times, "How are you faring relative to AWS, Microsoft and Google, these big whales with Redshift and Synapse and Big Query?" And Snowflake has been telling folks that 80% of its business comes from AWS. And when Microsoft heard that, they said, "Whoa, wait a minute, Snowflake, let's partner up." 'Cause Microsoft is smart, and they understand that the market is enormous. And if they could do better with Snowflake, one, they may steal some business from AWS. And two, even if Snowflake is winning against some of the Microsoft database products, if it wins on Azure, Microsoft is going to sell more compute and more storage, more AI tools, more other stuff to these customers. Now AWS is really aggressive from a partnering standpoint with Snowflake. They're openly negotiating, not openly, but they're negotiating better prices. They're realizing that when it comes to data, the cheaper that you make the offering, the more people are going to consume. At scale economies and operating leverage are really powerful things at volume that kick in. Now Microsoft, they're coming along, they obviously get it, but Google is seemingly resistant to that type of go to market partnership. Rather than lean into Snowflake as a great partner Google's field force is kind of fighting fashion. Google itself at Cloud next heavily messaged what they call the open data cloud, which is a direct rip off of Snowflake. So what can we say about Google? They continue to be kind of behind the curve when it comes to go to market. Now just a brief aside on the competitive posture. I've seen Slootman, Frank Slootman, CEO of Snowflake in action with his prior companies and how he depositioned the competition. At Data Domain, he eviscerated a company called Avamar with their, what he called their expensive and slow post process architecture. I think he actually called it garbage, if I recall at one conference I heard him speak at. And that sort of destroyed BMC when he was at ServiceNow, kind of positioning them as the equivalent of the department of motor vehicles. And so it's interesting to hear how Snowflake openly talks about the data platforms of AWS, Microsoft, Google, and data bricks. I'll give you this sort of short bumper sticker. Redshift is just an on-prem database that AWS morphed to the cloud, which by the way is kind of true. They actually did a brilliant job of it, but it's basically a fact. Microsoft Excel, a collection of legacy databases, which also kind of morphed to run in the cloud. And even Big Query, which is considered cloud native by many if not most, is being positioned by Snowflake as originally an on-prem database to support Google's ad business, maybe. And data bricks is for those people smart enough to get it to Berkeley that love complexity. And now Snowflake doesn't, they don't mention Berkeley as far as I know. That's my addition. But you get the point. And the interesting thing about Databricks and Snowflake is a while ago in the cube I said that there was a new workload type emerging around data where you have AWS cloud, Snowflake obviously for the cloud database and Databricks data for the data science and EML, you bring those things together and there's this new workload emerging that's going to be very powerful in the future. And it's interesting to see now the aspirations of all three of these platforms are colliding. That's quite a dynamic, especially when you see both Snowflake and Databricks putting venture money and getting their hooks into the loyalties of the same companies like DBT labs and Calibra. Anyway, Snowflake's posture is that we are the pioneer in cloud native data warehouse, data sharing and now data apps. And our platform is designed for business people that want simplicity. The other guys, yes, they're formidable, but we Snowflake have an architectural lead and of course we run in multiple clouds. So it's pretty strong positioning or depositioning, you have to admit. Now I'm not sure I agree with the big query knockoffs completely. I think that's a bit of a stretch, but snowflake, as we see in the ETR survey data is winning. So in thinking about the longer term future, let's talk about what's different with Snowflake, where it's headed and what the opportunities are for the company. Snowflake put itself on the map by focusing on simplifying data analytics. What's interesting about that is the company's founders are as you probably know from Oracle. And rather than focusing on transactional data, which is Oracle's sweet spot, the stuff they worked on when they were at Oracle, the founder said, "We're going to go somewhere else. We're going to attack the data warehousing problem and the data analytics problem." And they completely re-imagined the database and how it could be applied to solve those challenges and reimagine what was possible if you had virtually unlimited compute and storage capacity. And of course Snowflake became famous for separating the compute from storage and being able to completely shut down compute so you didn't have to pay for it when you're not using it. And the ability to have multiple clusters hit the same data without making endless copies and a consumption/cloud pricing model. And then of course everyone on the planet realized, "Wow, that's a pretty good idea." Every venture capitalist in Silicon Valley has been funding companies to copy that move. And that today has pretty much become mainstream in table stakes. But I would argue that Snowflake not only had the lead, but when you look at how others are approaching this problem, it's not necessarily as clean and as elegant. Some of the startups, the early startups I think get it and maybe had an advantage of starting later, which can be a disadvantage too. But AWS is a good example of what I'm saying here. Is its version of separating compute from storage was an afterthought and it's good, it's... Given what they had it was actually quite clever and customers like it, but it's more of a, "Okay, we're going to tier to storage to lower cost, we're going to sort of dial down the compute not completely, we're not going to shut it off, we're going to minimize the compute required." It's really not true as separation is like for instance Snowflake has. But having said that, we're talking about competitors with lots of resources and cohort offerings. And so I don't want to make this necessarily all about the product, but all things being equal architecture matters, okay? So that's the cloud S-curve, the first one we're showing. Snowflake's still on that S-curve, and in and of itself it's got legs, but it's not what's going to power the company to 10 billion. The next S-curve we denote is the multi-cloud in the middle. And now while 80% of Snowflake's revenue is AWS, Microsoft is ramping up and Google, well, we'll see. But the interesting part of that curve is data sharing, and this idea of data clean rooms. I mean it really should be called the data sharing curve, but I have my reasons for calling it multi-cloud. And this is all about network effects and data gravity, and you're seeing this play out today, especially in industries like financial services and healthcare and government that are highly regulated verticals where folks are super paranoid about compliance. There not going to share data if they're going to get sued for it, if they're going to be in the front page of the Wall Street Journal for some kind of privacy breach. And what Snowflake has done is said, "Put all the data in our cloud." Now, of course now that triggers a lot of people because it's a walled garden, okay? It is. That's the trade off. It's not the Wild West, it's not Windows, it's Mac, it's more controlled. But the idea is that as different parts of the organization or even partners begin to share data that they need, it's got to be governed, it's got to be secure, it's got to be compliant, it's got to be trusted. So Snowflake introduced the idea of, they call these things stable edges. I think that's the term that they use. And they track a metric around stable edges. And so a stable edge, or think of it as a persistent edge is an ongoing relationship between two parties that last for some period of time, more than a month. It's not just a one shot deal, one a done type of, "Oh guys shared it for a day, done." It sent you an FTP, it's done. No, it's got to have trajectory over time. Four weeks or six weeks or some period of time that's meaningful. And that metric is growing. Now I think sort of a different metric that they track. I think around 20% of Snowflake customers are actively sharing data today and then they track the number of those edge relationships that exist. So that's something that's unique. Because again, most data sharing is all about making copies of data. That's great for storage companies, it's bad for auditors, and it's bad for compliance officers. And that trend is just starting out, that middle S-curve, it's going to kind of hit the base of that steep part of the S-curve and it's going to have legs through this decade we think. And then finally the third wave that we show here is what we call super cloud. That's why I called it multi-cloud before, so it could invoke super cloud. The idea that you've built a PAS layer that is purpose built for a specific objective, and in this case it's building data apps that are cloud native, shareable and governed. And is a long-term trend that's going to take some time to develop. I mean, application development platforms can take five to 10 years to mature and gain significant adoption, but this one's unique. This is a critical play for Snowflake. If it's going to compete with the big cloud players, it has to have an app development framework like Snowpark. It has to accommodate new data types like transactional data. That's why it announced this thing called UniStore last June, Snowflake a summit. And the pattern that's forming here is Snowflake is building layer upon layer with its architecture at the core. It's not currently anyway, it's not going out and saying, "All right, we're going to buy a company that's got to another billion dollars in revenue and that's how we're going to get to 10 billion." So it's not buying its way into new markets through revenue. It's actually buying smaller companies that can complement Snowflake and that it can turn into revenue for growth that fit in to the data cloud. Now as to the 10 billion by fiscal year 28, is that achievable? That's the question. Yeah, I think so. Would the momentum resources go to market product and management prowess that Snowflake has? Yes, it's definitely achievable. And one could argue to $10 billion is too conservative. Indeed, Snowflake CFO, Mike Scarpelli will fully admit his forecaster built on existing offerings. He's not including revenue as I understand it from all the new stuff that's in the pipeline because he doesn't know what it's going to look like. He doesn't know what the adoption is going to look like. He doesn't have data on that adoption, not just yet anyway. And now of course things can change quite dramatically. It's possible that is forecast for existing businesses don't materialize or competition picks them off or a company like Databricks actually is able in the longer term replicate the functionality of Snowflake with open source technologies, which would be a very competitive source of innovation. But in our view, there's plenty of room for growth, the market is enormous and the real key is, can and will Snowflake deliver on the promises of simplifying data? Of course we've heard this before from data warehouse, the data mars and data legs and master data management and ETLs and data movers and data copiers and Hadoop and a raft of technologies that have not lived up to expectations. And we've also, by the way, seen some tremendous successes in the software business with the likes of ServiceNow and Salesforce. So will Snowflake be the next great software name and hit that 10 billion magic mark? I think so. Let's reconnect in 2028 and see. Okay, we'll leave it there today. I want to thank Chip Simonton for his input to today's episode. Thanks to Alex Myerson who's on production and manages the podcast. Ken Schiffman as well. Kristin Martin and Cheryl Knight help get the word out on social media and in our newsletters. And Rob Hove is our Editor in Chief over at Silicon Angle. He does some great editing for us. Check it out for all the news. Remember all these episodes are available as podcasts. Wherever you listen, just search Breaking Analysis podcast. I publish each week on wikibon.com and siliconangle.com. Or you can email me to get in touch David.vallante@siliconangle.com. DM me @dvellante or comment on our LinkedIn post. And please do check out etr.ai, they've got the best survey data in the enterprise tech business. This is Dave Vellante for the CUBE Insights, powered by ETR. Thanks for watching, thanks for listening and we'll see you next time on breaking analysis. (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 Ante. >>Have you ever been driving on the highway and traffic suddenly slows way down and then after a little while it picks up again and you're cruising along and you're thinking, Okay, hey, that was weird. But it's clear sailing now. Off we go, only to find out in a bit that the traffic is building up ahead again, forcing you to pump the brakes as the traffic pattern ebbs and flows well. Welcome to the Seesaw economy. The fed induced fire that prompted an unprecedented rally in tech is being purposefully extinguished now by that same fed. And virtually every sector of the tech industry is having to reset its expectations, including the cloud segment. Hello and welcome to this week's Wikibon Cube Insights powered by etr. In this breaking analysis will review the implications of the earnings announcements from the big three cloud players, Amazon, Microsoft, and Google who announced this week. >>And we'll update you on our quarterly IAS forecast and share the latest from ETR with a focus on cloud computing. Now, before we get into the new data, we wanna review something we shared with you on October 14th, just a couple weeks back, this is sort of a, we told you it was coming slide. It's an XY graph that shows ET R'S proprietary net score methodology on the vertical axis. That's a measure of spending momentum, spending velocity, and an overlap or presence in the dataset that's on the X axis. That's really a measure of pervasiveness. In the survey, the table, you see that table insert there that shows Wiki Bond's Q2 estimates of IAS revenue for the big four hyperscalers with their year on year growth rates. Now we told you at the time, this is data from the July TW 22 ETR survey and the ETR hadn't released its October survey results at that time. >>This was just a couple weeks ago. And while we couldn't share the specific data from the October survey, we were able to get a glimpse and we depicted the slowdown that we saw in the October data with those dotted arrows kind of down into the right, we said at the time that we were seeing and across the board slowdown even for the big three cloud vendors. Now, fast forward to this past week and we saw earnings releases from Alphabet, Microsoft, and just last night Amazon. Now you may be thinking, okay, big deal. The ETR survey data didn't really tell us anything we didn't already know. But judging from the negative reaction in the stock market to these earnings announcements, the degree of softness surprised a lot of investors. Now, at the time we didn't update our forecast, it doesn't make sense for us to do that when we're that close to earning season. >>And now that all the big three ha with all the big four with the exception of Alibaba have announced we've, we've updated. And so here's that data. This chart lays out our view of the IS and PAs worldwide revenue. Basically it's cloud infrastructure with an attempt to exclude any SaaS revenue so we can make an apples to apples comparison across all the clouds. Now the reason that actual is in quotes is because Microsoft and Google don't report IAS revenue, but they do give us clues and kind of directional commentary, which we then triangulate with other data that we have from the channel and ETR surveys and just our own intelligence. Now the second column there after the vendor name shows our previous estimates for q3, and then next to that we show our actuals. Same with the growth rates. And then we round out the chart with that lighter blue color highlights, the full year estimates for revenue and growth. >>So the key takeaways are that we shaved about $4 billion in revenue and roughly 300 basis points of growth off of our full year estimates. AWS had a strong July but exited Q3 in the mid 20% growth rate year over year. So we're using that guidance, you know, for our Q4 estimates. Azure came in below our earlier estimates, but Google actually exceeded our expectations. Now the compression in the numbers is in our view of function of the macro demand climate, we've made every attempt to adjust for constant currency. So FX should not be a factor in this data, but it's sure you know that that ma the the, the currency effects are weighing on those companies income statements. And so look, this is the fundamental dynamic of a cloud model where you can dial down consumption when you need to and dial it up when you need to. >>Now you may be thinking that many big cloud customers have a committed level of spending in order to get better discounts. And that's true. But what's happening we think is they'll reallocate that spend toward, let's say for example, lower cost storage tiers or they may take advantage of better price performance processors like Graviton for example. That is a clear trend that we're seeing and smaller companies that were perhaps paying by the drink just on demand, they're moving to reserve instance models to lower their monthly bill. So instead of taking the easy way out and just spending more companies are reallocating their reserve capacity toward lower cost. So those sort of lower cost services, so they're spending time and effort optimizing to get more for, for less whereas, or get more for the same is really how we should, should, should phrase it. Whereas during the pandemic, many companies were, you know, they perhaps were not as focused on doing that because business was booming and they had a response. >>So they just, you know, spend more dial it up. So in general, as they say, customers are are doing more with, with the same. Now let's look at the growth dynamic and spend some time on that. I think this is important. This data shows worldwide quarterly revenue growth rates back to Q1 2019 for the big four. So a couple of interesting things. The data tells us during the pandemic, you saw both AWS and Azure, but the law of large numbers and actually accelerate growth. AWS especially saw progressively increasing growth rates throughout 2021 for each quarter. Now that trend, as you can see is reversed in 2022 for aws. Now we saw Azure come down a bit, but it's still in the low forties in terms of percentage growth. While Google actually saw an uptick in growth this last quarter for GCP by our estimates as GCP is becoming an increasingly large portion of Google's overall cloud business. >>Now, unfortunately Google Cloud continues to lose north of 850 million per quarter, whereas AWS and Azure are profitable cloud businesses even though Alibaba is suffering its woes from China. And we'll see how they come in when they report in mid-November. The overall hyperscale market grew at 32% in Q3 in terms of worldwide revenue. So the slowdown isn't due to the repatriation or competition from on-prem vendors in our view, it's a macro related trend. And cloud will continue to significantly outperform other sectors despite its massive size. You know, on the repatriation point, it just still doesn't show up in the data. The A 16 Z article from Sarah Wong and Martin Martin Kasa claiming that repatriation was inevitable as a means to lower cost of good sold for SaaS companies. You know, while that was thought provoking, it hasn't shown up in the numbers. And if you read the financial statements of both AWS and its partners like Snowflake and you dig into the, to the, to the quarterly reports, you'll see little notes and comments with their ongoing negotiations to lower cloud costs for customers. >>AWS and no doubt execs at Azure and GCP understand that the lifetime value of a customer is worth much more than near term gross margin. And you can expect the cloud vendors to strike a balance between profitability, near term profitability anyway and customer attention. Now, even though Google Cloud platform saw accelerated growth, we need to put that in context for you. So GCP, by our estimate, has now crossed over the $3 billion for quarter market actually did so last quarter, but its growth rate accelerated to 42% this quarter. And so that's a good sign in our view. But let's do a quick little comparison with when AWS and Azure crossed the $3 billion mark and compare their growth rates at the time. So if you go back to to Q2 2016, as we're showing in this chart, that's around the time that AWS hit 3 billion per quarter and at the same time was growing at 58%. >>Azure by our estimates crossed that mark in Q4 2018 and at that time was growing at 67%. Again, compare that to Google's 42%. So one would expect Google's growth rate would be higher than its competitors at this point in the MO in the maturity of its cloud, which it's, you know, it's really not when you compared to to Azure. I mean they're kind of con, you know, comparable now but today, but, but you'll go back, you know, to that $3 billion mark. But more so looking at history, you'd like to see its growth rate at this point of a maturity model at least over 50%, which we don't believe it is. And one other point on this topic, you know, my business friend Matt Baker from Dell often says it's not a zero sum game, meaning there's plenty of opportunity exists to build value on top of hyperscalers. >>And I would totally agree it's not a dollar for dollar swap if you can continue to innovate. But history will show that the first company in makes the most money. Number two can do really well and number three tends to break even. Now maybe cloud is different because you have Microsoft software estate and the power behind that and that's driving its IAS business and Google ads are funding technology buildouts for, for for Google and gcp. So you know, we'll see how that plays out. But right now by this one measurement, Google is four years behind Microsoft in six years behind aws. Now to the point that cloud will continue to outpace other markets, let's, let's break this down a bit in spending terms and see why this claim holds water. This is data from ET r's latest October survey that shows the granularity of its net score or spending velocity metric. >>The lime green is new adoptions, so they're adding the platform, the forest green is spending more 6% or more. The gray bars spending is flat plus or minus, you know, 5%. The pinkish colors represent spending less down 6% or worse. And the bright red shows defections or churn of the platform. You subtract the reds from the greens and you get what's called net score, which is that blue dot that you can see on each of the bars. So what you see in the table insert is that all three have net scores above 40%, which is a highly elevated measure. Microsoft's net scores above 60% AWS well into the fifties and GCP in the mid forties. So all good. Now what's happening with all three is more customers are keep keeping their spending flat. So a higher percentage of customers are saying, our spending is now flat than it was in previous quarters and that's what's accounting for the compression. >>But the churn of all three, even gcp, which we reported, you know, last quarter from last quarter survey was was five x. The other two is actually very low in the single digits. So that might have been an anomaly. So that's a very good sign in our view. You know, again, customers aren't repatriating in droves, it's just not a trend that we would bet on, maybe makes for a FUD or you know, good marketing head, but it's just not a big deal. And you can't help but be impressed with both Microsoft and AWS's performance in the survey. And as we mentioned before, these companies aren't going to give up customers to try and preserve a little bit of gross margin. They'll do what it takes to keep people on their platforms cuz they'll make up for it over time with added services and improved offerings. >>Now, once these companies acquire a customer, they'll be very aggressive about keeping them. So customers take note, you have negotiating leverage, so use it. Okay, let's look at another cut at the cloud market from the ETR data set. Here's the two dimensional view, again, it's back, it's one of our favorites. Net score or spending momentum plotted against presence. And the data set, that's the x axis net score on the, on the vertical axis, this is a view of et r's cloud computing sector sector. You can see we put that magic 40% dotted red line in the table showing and, and then that the table inserts shows how the data are plotted with net score against presence. I e n in the survey, notably only the big three are above the 40% line of the names that we're showing here. The oth there, there are others. >>I mean if you put Snowflake on there, it'd be higher than any of these names, but we'll dig into that name in a later breaking analysis episode. Now this is just another way of quantifying the dominance of AWS and Azure, not only relative to Google, but the other cloud platforms out there. So we've, we've taken the opportunity here to plot IBM and Oracle, which both own a public cloud. Their performance is largely a reflection of them migrating their install bases to their respective public clouds and or hybrid clouds. And you know, that's fine, they're in the game. That's a point that we've made, you know, a number of times they're able to make it through the cloud, not whole and they at least have one, but they simply don't have the business momentum of AWS and Azure, which is actually quite impressive because AWS and Azure are now as large or larger than IBM and Oracle. >>And to show this type of continued growth that that that Azure and AWS show at their size is quite remarkable and customers are starting to recognize the viability of on-prem hi, you know, hybrid clouds like HPE GreenLake and Dell's apex. You know, you may say, well that's not cloud, but if the customer thinks it is and it was reporting in the survey that it is, we're gonna continue to report this view. You know, I don't know what's happening with H P E, They had a big down tick this quarter and I, and I don't read too much into that because their end is still pretty small at 53. So big fluctuations are not uncommon with those types of smaller ends, but it's over 50. So, you know, we did notice a a a negative within a giant public and private sector, which is often a, a bellwether giant public private is big public companies and large private companies like, like a Mars for example. >>So it, you know, it looks like for HPE it could be an outlier. We saw within the Fortune 1000 HPE E'S cloud looked actually really good and it had good spending momentum in that sector. When you di dig into the industry data within ETR dataset, obviously we're not showing that here, but we'll continue to monitor that. Okay, so where's this Leave us. Well look, this is really a tactical story of currency and macro headwinds as you can see. You know, we've laid out some of the points on this slide. The action in the stock market today, which is Friday after some of the soft earnings reports is really robust. You know, we'll see how it ends up in the day. So maybe this is a sign that the worst is over, but we don't think so. The visibility from tech companies is murky right now as most are guiding down, which indicates that their conservative outlook last quarter was still too optimistic. >>But as it relates to cloud, that platform is not going anywhere anytime soon. Sure, there are potential disruptors on the horizon, especially at the edge, but we're still a long ways off from, from the possibility that a new economic model emerges from the edge to disrupt the cloud and the opportunities in the cloud remain strong. I mean, what other path is there? Really private cloud. It was kind of a bandaid until the on-prem guys could get their a as a service models rolled out, which is just now happening. The hybrid thing is real, but it's, you know, defensive for the incumbents until they can get their super cloud investments going. Super cloud implying, capturing value above the hyperscaler CapEx, you know, call it what you want multi what multi-cloud should have been, the metacloud, the Uber cloud, whatever you like. But there are opportunities to play offense and that's clearly happening in the cloud ecosystem with the likes of Snowflake, Mongo, Hashi Corp. >>Hammer Spaces is a startup in this area. Aviatrix, CrowdStrike, Zeke Scaler, Okta, many, many more. And even the projects we see coming out of enterprise players like Dell, like with Project Alpine and what Pure Storage is doing along with a number of other of the backup vendors. So Q4 should be really interesting, but the real story is the investments that that companies are making now to leverage the cloud for digital transformations will be paying off down the road. This is not 1999. We had, you know, May might have had some good ideas and admittedly at a lot of bad ones too, but you didn't have the infrastructure to service customers at a low enough cost like you do today. The cloud is that infrastructure and so far it's been transformative, but it's likely the best is yet to come. Okay, let's call this a rap. >>Many thanks to Alex Morrison who does production and manages the podcast. Also Can Schiffman is our newest edition to the Boston Studio. Kristin Martin and Cheryl Knight helped get the word out on social media and in our newsletters. And Rob Ho is our editor in chief over@siliconangle.com, who does some wonderful editing for us. Thank you. Remember, all these episodes are available as podcasts. Wherever you listen, just search breaking analysis podcast. I publish each week on wiki bond.com at silicon angle.com. And you can email me at David dot valante@siliconangle.com or DM me at Dante or comment on my LinkedIn posts. And please do checkout etr.ai. They got the best survey data in the enterprise tech business. This is Dave Valante for the Cube Insights powered by etr. Thanks for watching and we'll see you next time on breaking analysis.

>> From theCUBE Studios in Palo Alto and Boston, bringing you data-driven insights from theCUBE and ETR, this is Breaking Analysis with Dave Vellante. >> This past week we saw two of the Big 3 cloud providers present the latest update on their respective cloud visions, their business progress, their announcements and innovations. The content at these events had many overlapping themes, including modern cloud infrastructure at global scale, applying advanced machine intelligence, AKA AI, end-to-end data platforms, collaboration software. They talked a lot about the future of work automation. And they gave us a little taste, each company of the Metaverse Web 3.0 and much more. Despite these striking similarities, the differences between these two cloud platforms and that of AWS remains significant. With Microsoft leveraging its massive application software footprint to dominate virtually all markets and Google doing everything in its power to keep up with the frenetic pace of today's cloud innovation, which was set into motion a decade and a half ago by AWS. Hello and welcome to this week's Wikibon CUBE Insights, powered by ETR. In this Breaking Analysis, we unpack the immense amount of content presented by the CEOs of Microsoft and Google Cloud at Microsoft Ignite and Google Cloud Next. We'll also quantify with ETR survey data the relative position of these two cloud giants in four key sectors: cloud IaaS, BI analytics, data platforms and collaboration software. Now one thing was clear this past week, hybrid events are the thing. Google Cloud Next took place live over a 24-hour period in six cities around the world, with the main gathering in New York City. Microsoft Ignite, which normally is attended by 30,000 people, had a smaller event in Seattle, in person with a virtual audience around the world. AWS re:Invent, of course, is much different. Yes, there's a virtual component at re:Invent, but it's all about a big live audience gathering the week after Thanksgiving, in the first week of December in Las Vegas. Regardless, Satya Nadella keynote address was prerecorded. It was highly produced and substantive. It was visionary, energetic with a strong message that Azure was a platform to allow customers to build their digital businesses. Doing more with less, which was a key theme of his. Nadella covered a lot of ground, starting with infrastructure from the compute, highlighting a collaboration with Arm-based, Ampere processors. New block storage, 60 regions, 175,000 miles of fiber cables around the world. He presented a meaningful multi-cloud message with Azure Arc to support on-prem and edge workloads, as well as of course the public cloud. And talked about confidential computing at the infrastructure level, a theme we hear from all cloud vendors. He then went deeper into the end-to-end data platform that Microsoft is building from the core data stores to analytics, to governance and the myriad tooling Microsoft offers. AI was next with a big focus on automation, AI, training models. He showed demos of machines coding and fixing code and machines automatically creating designs for creative workers and how Power Automate, Microsoft's RPA tooling, would combine with Microsoft Syntex to understand documents and provide standard ways for organizations to communicate with those documents. There was of course a big focus on Azure as developer cloud platform with GitHub Copilot as a linchpin using AI to assist coders in low-code and no-code innovations that are coming down the pipe. And another giant theme was a workforce transformation and how Microsoft is using its heritage and collaboration and productivity software to move beyond what Nadella called productivity paranoia, i.e., are remote workers doing their jobs? In a world where collaboration is built into intelligent workflows, and he even showed a glimpse of the future with AI-powered avatars and partnerships with Meta and Cisco with Teams of all firms. And finally, security with a bevy of tools from identity, endpoint, governance, et cetera, stressing a suite of tools from a single provider, i.e., Microsoft. So a couple points here. One, Microsoft is following in the footsteps of AWS with silicon advancements and didn't really emphasize that trend much except for the Ampere announcement. But it's building out cloud infrastructure at a massive scale, there is no debate about that. Its plan on data is to try and provide a somewhat more abstracted and simplified solutions, which differs a little bit from AWS's approach of the right database tool, for example, for the right job. Microsoft's automation play appears to provide simple individual productivity tools, kind of a ground up approach and make it really easy for users to drive these bottoms up initiatives. We heard from UiPath that forward five last month, a little bit of a different approach of horizontal automation, end-to-end across platforms. So quite a different play there. Microsoft's angle on workforce transformation is visionary and will continue to solidify in our view its dominant position with Teams and Microsoft 365, and it will drive cloud infrastructure consumption by default. On security as well as a cloud player, it has to have world-class security, and Azure does. There's not a lot of debate about that, but the knock on Microsoft is Patch Tuesday becomes Hack Wednesday because Microsoft releases so many patches, it's got so much Swiss cheese in its legacy estate and patching frequently, it becomes a roadmap and a trigger for hackers. Hey, patch Tuesday, these are all the exploits that you can go after so you can act before the patches are implemented. And so it's really become a problem for users. As well Microsoft is competing with many of the best-of-breed platforms like CrowdStrike and Okta, which have market momentum and appear to be more attractive horizontal plays for customers outside of just the Microsoft cloud. But again, it's Microsoft. They make it easy and very inexpensive to adopt. Now, despite the outstanding presentation by Satya Nadella, there are a couple of statements that should raise eyebrows. Here are two of them. First, as he said, Azure is the only cloud that supports all organizations and all workloads from enterprises to startups, to highly regulated industries. I had a conversation with Sarbjeet Johal about this, to make sure I wasn't just missing something and we were both surprised, somewhat, by this claim. I mean most certainly AWS supports more certifications for example, and we would think it has a reasonable case to dispute that claim. And the other statement, Nadella made, Azure is the only cloud provider enabling highly regulated industries to bring their most sensitive applications to the cloud. Now, reasonable people can debate whether AWS is there yet, but very clearly Oracle and IBM would have something to say about that statement. Now maybe it's not just, would say, "Oh, they're not real clouds, you know, they're just going to hosting in the cloud if you will." But still, when it comes to mission-critical applications, you would think Oracle is really the the leader there. Oh, and Satya also mentioned the claim that the Edge browser, the Microsoft Edge browser, no questions asked, he said, is the best browser for business. And we could see some people having some questions about that. Like isn't Edge based on Chrome? Anyway, so we just had to question these statements and challenge Microsoft to defend them because to us it's a little bit of BS and makes one wonder what else in such as awesome keynote and it was awesome, it was hyperbole. Okay, moving on to Google Cloud Next. The keynote started with Sundar Pichai doing a virtual session, he was remote, stressing the importance of Google Cloud. He mentioned that Google Cloud from its Q2 earnings was on a $25-billion annual run rate. What he didn't mention is that it's also on a 3.6 billion annual operating loss run rate based on its first half performance. Just saying. And we'll dig into that issue a little bit more later in this episode. He also stressed that the investments that Google has made to support its core business and search, like its global network of 22 subsea cables to support things like, YouTube video, great performance obviously that we all rely on, those innovations there. Innovations in BigQuery to support its search business and its threat analysis that it's always had and its AI, it's always been an AI-first company, he's stressed, that they're all leveraged by the Google Cloud Platform, GCP. This is all true by the way. Google has absolutely awesome tech and the talk, as well as his talk, Pichai, but also Kurian's was forward thinking and laid out a vision of the future. But it didn't address in our view, and I talked to Sarbjeet Johal about this as well, today's challenges to the degree that Microsoft did and we expect AWS will at re:Invent this year, it was more out there, more forward thinking, what's possible in the future, somewhat less about today's problem, so I think it's resonates less with today's enterprise players. Thomas Kurian then took over from Sundar Pichai and did a really good job of highlighting customers, and I think he has to, right? He has to say, "Look, we are in this game. We have customers, 9 out of the top 10 media firms use Google Cloud. 8 out of the top 10 manufacturers. 9 out of the top 10 retailers. Same for telecom, same for healthcare. 8 out of the top 10 retail banks." He and Sundar specifically referenced a number of companies, customers, including Avery Dennison, Groupe Renault, H&M, John Hopkins, Prudential, Minna Bank out of Japan, ANZ bank and many, many others during the session. So you know, they had some proof points and you got to give 'em props for that. Now like Microsoft, Google talked about infrastructure, they referenced training processors and regions and compute optionality and storage and how new workloads were emerging, particularly data-driven workloads in AI that required new infrastructure. He explicitly highlighted partnerships within Nvidia and Intel. I didn't see anything on Arm, which somewhat surprised me 'cause I believe Google's working on that or at least has come following in AWS's suit if you will, but maybe that's why they're not mentioning it or maybe I got to do more research there, but let's park that for a minute. But again, as we've extensively discussed in Breaking Analysis in our view when it comes to compute, AWS via its Annapurna acquisition is well ahead of the pack in this area. Arm is making its way into the enterprise, but all three companies are heavily investing in infrastructure, which is great news for customers and the ecosystem. We'll come back to that. Data and AI go hand in hand, and there was no shortage of data talk. Google didn't mention Snowflake or Databricks specifically, but it did mention, by the way, it mentioned Mongo a couple of times, but it did mention Google's, quote, Open Data cloud. Now maybe Google has used that term before, but Snowflake has been marketing the data cloud concept for a couple of years now. So that struck as a shot across the bow to one of its partners and obviously competitor, Snowflake. At BigQuery is a main centerpiece of Google's data strategy. Kurian talked about how they can take any data from any source in any format from any cloud provider with BigQuery Omni and aggregate and understand it. And with the support of Apache Iceberg and Delta and Hudi coming in the future and its open Data Cloud Alliance, they talked a lot about that. So without specifically mentioning Snowflake or Databricks, Kurian co-opted a lot of messaging from these two players, such as life and tech. Kurian also talked about Google Workspace and how it's now at 8 million users up from 6 million just two years ago. There's a lot of discussion on developer optionality and several details on tools supported and the open mantra of Google. And finally on security, Google brought out Kevin Mandian, he's a CUBE alum, extremely impressive individual who's CEO of Mandiant, a leading security service provider and consultancy that Google recently acquired for around 5.3 billion. They talked about moving from a shared responsibility model to a shared fate model, which is again, it's kind of a shot across AWS's bow, kind of shared responsibility model. It's unclear that Google will pay the same penalty if a customer doesn't live up to its portion of the shared responsibility, but we can probably assume that the customer is still going to bear the brunt of the pain, nonetheless. Mandiant is really interesting because it's a services play and Google has stated that it is not a services company, it's going to give partners in the channel plenty of room to play. So we'll see what it does with Mandiant. But Mandiant is a very strong enterprise capability and in the single most important area security. So interesting acquisition by Google. Now as well, unlike Microsoft, Google is not competing with security leaders like Okta and CrowdStrike. Rather, it's partnering aggressively with those firms and prominently putting them forth. All right. Let's get into the ETR survey data and see how Microsoft and Google are positioned in four key markets that we've mentioned before, IaaS, BI analytics, database data platforms and collaboration software. First, let's look at the IaaS cloud. ETR is just about to release its October survey, so I cannot share the that data yet. I can only show July data, but we're going to give you some directional hints throughout this conversation. This chart shows net score or spending momentum on the vertical axis and overlap or presence in the data, i.e., how pervasive the platform is. That's on the horizontal axis. And we've inserted the Wikibon estimates of IaaS revenue for the companies, the Big 3. Actually the Big 4, we included Alibaba. So a couple of points in this somewhat busy data chart. First, Microsoft and AWS as always are dominant on both axes. The red dotted line there at 40% on the vertical axis. That represents a highly elevated spending velocity and all of the Big 3 are above the line. Now at the same time, GCP is well behind the two leaders on the horizontal axis and you can see that in the table insert as well in our revenue estimates. Now why is Azure bigger in the ETR survey when AWS is larger according to the Wikibon revenue estimates? And the answer is because Microsoft with products like 365 and Teams will often be considered by respondents in the survey as cloud by customers, so they fit into that ETR category. But in the insert data we're stripping out applications and SaaS from Microsoft and Google and we're only isolating on IaaS. The other point is when you take a look at the early October returns, you see downward pressure as signified by those dotted arrows on every name. The only exception was Dell, or Dell and IBM, which showing slightly improved momentum. So the survey data generally confirms what we know that AWS and Azure have a massive lead and strong momentum in the marketplace. But the real story is below the line. Unlike Google Cloud, which is on pace to lose well over 3 billion on an operating basis this year, AWS's operating profit is around $20 billion annually. Microsoft's Intelligent Cloud generated more than $30 billion in operating income last fiscal year. Let that sink in for a moment. Now again, that's not to say Google doesn't have traction, it does and Kurian gave some nice proof points and customer examples in his keynote presentation, but the data underscores the lead that Microsoft and AWS have on Google in cloud. And here's a breakdown of ETR's proprietary net score methodology, that vertical axis that we showed you in the previous chart. It asks customers, are you adopting the platform new? That's that lime green. Are you spending 6% or more? That's the forest green. Is you're spending flat? That's the gray. Is you're spending down 6% or worse? That's the pinkest color. Or are you replacing the platform, defecting? That's the bright red. You subtract the reds from the greens and you get a net score. Now one caveat here, which actually is really favorable from Microsoft, the Microsoft data that we're showing here is across the entire Microsoft portfolio. The other point is, this is July data, we'll have an update for you once ETR releases its October results. But we're talking about meaningful samples here, the ends. 620 for AWS over a thousand from Microsoft in more than 450 respondents in the survey for Google. So the real tell is replacements, that bright red. There is virtually no churn for AWS and Microsoft, but Google's churn is 5x, those two in the survey. Now 5% churn is not high, but you'd like to see three things for Google given it's smaller size. One is less churn, two is much, much higher adoption rates in the lime green. Three is a higher percentage of those spending more, the forest green. And four is a lower percentage of those spending less. And none of these conditions really applies here for Google. GCP is still not growing fast enough in our opinion, and doesn't have nearly the traction of the two leaders and that shows up in the survey data. All right, let's look at the next sector, BI analytics. Here we have that same XY dimension. Again, Microsoft dominating the picture. AWS very strong also in both axes. Tableau, very popular and respectable of course acquired by Salesforce on the vertical axis, still looking pretty good there. And again on the horizontal axis, big presence there for Tableau. And Google with Looker and its other platforms is also respectable, but it again, has some work to do. Now notice Streamlit, that's a recent Snowflake acquisition. It's strong in the vertical axis and because of Snowflake's go-to-market (indistinct), it's likely going to move to the right overtime. Grafana is also prominent in the Y axis, but a glimpse at the most recent survey data shows them slightly declining while Looker actually improves a bit. As does Cloudera, which we'll move up slightly. Again, Microsoft just blows you away, doesn't it? All right, now let's get into database and data platform. Same X Y dimensions, but now database and data warehouse. Snowflake as usual takes the top spot on the vertical axis and it is actually keeps moving to the right as well with again, Microsoft and AWS is dominant in the market, as is Oracle on the X axis, albeit it's got less spending velocity, but of course it's the database king. Google is well behind on the X axis but solidly above the 40% line on the vertical axis. Note that virtually all platforms will see pressure in the next survey due to the macro environment. Microsoft might even dip below the 40% line for the first time in a while. Lastly, let's look at the collaboration and productivity software market. This is such an important area for both Microsoft and Google. And just look at Microsoft with 365 and Teams up into the right. I mean just so impressive in ubiquitous. And we've highlighted Google. It's in the pack. It certainly is a nice base with 174 N, which I can tell you that N will rise in the next survey, which is an indication that more people are adopting. But given the investment and the tech behind it and all the AI and Google's resources, you'd really like to see Google in this space above the 40% line, given the importance of this market, of this collaboration area to Google's success and the degree to which they emphasize it in their pitch. And look, this brings up something that we've talked about before on Breaking Analysis. Google doesn't have a tech problem. This is a go-to-market and marketing challenge that Google faces and it's up against two go-to-market champs and Microsoft and AWS. And Google doesn't have the enterprise sales culture. It's trying, it's making progress, but it's like that racehorse that has all the potential in the world, but it's just missing some kind of key ingredient to put it over at the top. It's always coming in third, (chuckles) but we're watching and Google's obviously, making some investments as we shared with earlier. All right. Some final thoughts on what we learned this week and in this research: customers and partners should be thrilled that both Microsoft and Google along with AWS are spending so much money on innovation and building out global platforms. This is a gift to the industry and we should be thankful frankly because it's good for business, it's good for competitiveness and future innovation as a platform that can be built upon. Now we didn't talk much about multi-cloud, we haven't even mentioned supercloud, but both Microsoft and Google have a story that resonates with customers in cross cloud capabilities, unlike AWS at this time. But we never say never when it comes to AWS. They sometimes and oftentimes surprise you. One of the other things that Sarbjeet Johal and John Furrier and I have discussed is that each of the Big 3 is positioning to their respective strengths. AWS is the best IaaS. Microsoft is building out the kind of, quote, we-make-it-easy-for-you cloud, and Google is trying to be the open data cloud with its open-source chops and excellent tech. And that puts added pressure on Snowflake, doesn't it? You know, Thomas Kurian made some comments according to CRN, something to the effect that, we are the only company that can do the data cloud thing across clouds, which again, if I'm being honest is not really accurate. Now I haven't clarified these statements with Google and often things get misquoted, but there's little question that, as AWS has done in the past with Redshift, Google is taking a page out of Snowflake, Databricks as well. A big difference in the Big 3 is that AWS doesn't have this big emphasis on the up-the-stack collaboration software that both Microsoft and Google have, and that for Microsoft and Google will drive captive IaaS consumption. AWS obviously does some of that in database, a lot of that in database, but ISVs that compete with Microsoft and Google should have a greater affinity, one would think, to AWS for competitive reasons. and the same thing could be said in security, we would think because, as I mentioned before, Microsoft competes very directly with CrowdStrike and Okta and others. One of the big thing that Sarbjeet mentioned that I want to call out here, I'd love to have your opinion. AWS specifically, but also Microsoft with Azure have successfully created what Sarbjeet calls brand distance. AWS from the Amazon Retail, and even though AWS all the time talks about Amazon X and Amazon Y is in their product portfolio, but you don't really consider it part of the retail organization 'cause it's not. Azure, same thing, has created its own identity. And it seems that Google still struggles to do that. It's still very highly linked to the sort of core of Google. Now, maybe that's by design, but for enterprise customers, there's still some potential confusion with Google, what's its intentions? How long will they continue to lose money and invest? Are they going to pull the plug like they do on so many other tools? So you know, maybe some rethinking of the marketing there and the positioning. Now we didn't talk much about ecosystem, but it's vital for any cloud player, and Google again has some work to do relative to the leaders. Which brings us to supercloud. The ecosystem and end customers are now in a position this decade to digitally transform. And we're talking here about building out their own clouds, not by putting in and building data centers and installing racks of servers and storage devices, no. Rather to build value on top of the hyperscaler gift that has been presented. And that is a mega trend that we're watching closely in theCUBE community. While there's debate about the supercloud name and so forth, there little question in our minds that the next decade of cloud will not be like the last. All right, we're going to leave it there today. Many thanks to Sarbjeet Johal, and my business partner, John Furrier, for their input to today's episode. Thanks to Alex Myerson who's on production and manages the podcast and Ken Schiffman as well. Kristen Martin and Cheryl Knight helped get the word out on social media and in our newsletters. And Rob Hof is our editor in chief over at SiliconANGLE, who does some wonderful editing. And check out SiliconANGLE, a lot of coverage on Google Cloud Next and Microsoft Ignite. Remember, all these episodes are available as podcast wherever you listen. Just search Breaking Analysis podcast. I publish each week on wikibon.com and siliconangle.com. And you can always get in touch with me via email, david.vellante@siliconangle.com or you can DM me at dvellante or comment on my LinkedIn posts. And please do check out etr.ai, the best survey data in the enterprise tech business. This is Dave Vellante for the CUBE Insights, powered by ETR. Thanks for watching and we'll see you next time on Breaking Analysis. (gentle music)

>> From The Cube Studios in Palo Alto and Boston, bringing you data driven insights from The Cube at ETR. This is "Breaking Analysis" with Dave Vellante. >> The reverse momentum in tech stocks caused by rising interest rates, less attractive discounted cash flow models, and more tepid forward guidance, can be easily measured by public market valuations. And while there's lots of discussion about the impact on private companies and cash runway and 409A valuations, measuring the performance of non-public companies isn't as easy. IPOs have dried up and public statements by private companies, of course, they accentuate the good and they kind of hide the bad. Real data, unless you're an insider, is hard to find. Hello and welcome to this week's "Wikibon Cube Insights" powered by ETR. In this "Breaking Analysis", we unlock some of the secrets that non-public, emerging tech companies may or may not be sharing. And we do this by introducing you to a capability from ETR that we've not exposed you to over the past couple of years, it's called the Emerging Technologies Survey, and it is packed with sentiment data and performance data based on surveys of more than a thousand CIOs and IT buyers covering more than 400 companies. And we've invited back our colleague, Erik Bradley of ETR to help explain the survey and the data that we're going to cover today. Erik, this survey is something that I've not personally spent much time on, but I'm blown away at the data. It's really unique and detailed. First of all, welcome. Good to see you again. >> Great to see you too, Dave, and I'm really happy to be talking about the ETS or the Emerging Technology Survey. Even our own clients of constituents probably don't spend as much time in here as they should. >> Yeah, because there's so much in the mainstream, but let's pull up a slide to bring out the survey composition. Tell us about the study. How often do you run it? What's the background and the methodology? >> Yeah, you were just spot on the way you were talking about the private tech companies out there. So what we did is we decided to take all the vendors that we track that are not yet public and move 'em over to the ETS. And there isn't a lot of information out there. If you're not in Silicon (indistinct), you're not going to get this stuff. So PitchBook and Tech Crunch are two out there that gives some data on these guys. But what we really wanted to do was go out to our community. We have 6,000, ITDMs in our community. We wanted to ask them, "Are you aware of these companies? And if so, are you allocating any resources to them? Are you planning to evaluate them," and really just kind of figure out what we can do. So this particular survey, as you can see, 1000 plus responses, over 450 vendors that we track. And essentially what we're trying to do here is talk about your evaluation and awareness of these companies and also your utilization. And also if you're not utilizing 'em, then we can also figure out your sales conversion or churn. So this is interesting, not only for the ITDMs themselves to figure out what their peers are evaluating and what they should put in POCs against the big guys when contracts come up. But it's also really interesting for the tech vendors themselves to see how they're performing. >> And you can see 2/3 of the respondents are director level of above. You got 28% is C-suite. There is of course a North America bias, 70, 75% is North America. But these smaller companies, you know, that's when they start doing business. So, okay. We're going to do a couple of things here today. First, we're going to give you the big picture across the sectors that ETR covers within the ETS survey. And then we're going to look at the high and low sentiment for the larger private companies. And then we're going to do the same for the smaller private companies, the ones that don't have as much mindshare. And then I'm going to put those two groups together and we're going to look at two dimensions, actually three dimensions, which companies are being evaluated the most. Second, companies are getting the most usage and adoption of their offerings. And then third, which companies are seeing the highest churn rates, which of course is a silent killer of companies. And then finally, we're going to look at the sentiment and mindshare for two key areas that we like to cover often here on "Breaking Analysis", security and data. And data comprises database, including data warehousing, and then big data analytics is the second part of data. And then machine learning and AI is the third section within data that we're going to look at. Now, one other thing before we get into it, ETR very often will include open source offerings in the mix, even though they're not companies like TensorFlow or Kubernetes, for example. And we'll call that out during this discussion. The reason this is done is for context, because everyone is using open source. It is the heart of innovation and many business models are super glued to an open source offering, like take MariaDB, for example. There's the foundation and then there's with the open source code and then there, of course, the company that sells services around the offering. Okay, so let's first look at the highest and lowest sentiment among these private firms, the ones that have the highest mindshare. So they're naturally going to be somewhat larger. And we do this on two dimensions, sentiment on the vertical axis and mindshare on the horizontal axis and note the open source tool, see Kubernetes, Postgres, Kafka, TensorFlow, Jenkins, Grafana, et cetera. So Erik, please explain what we're looking at here, how it's derived and what the data tells us. >> Certainly, so there is a lot here, so we're going to break it down first of all by explaining just what mindshare and net sentiment is. You explain the axis. We have so many evaluation metrics, but we need to aggregate them into one so that way we can rank against each other. Net sentiment is really the aggregation of all the positive and subtracting out the negative. So the net sentiment is a very quick way of looking at where these companies stand versus their peers in their sectors and sub sectors. Mindshare is basically the awareness of them, which is good for very early stage companies. And you'll see some names on here that are obviously been around for a very long time. And they're clearly be the bigger on the axis on the outside. Kubernetes, for instance, as you mentioned, is open source. This de facto standard for all container orchestration, and it should be that far up into the right, because that's what everyone's using. In fact, the open source leaders are so prevalent in the emerging technology survey that we break them out later in our analysis, 'cause it's really not fair to include them and compare them to the actual companies that are providing the support and the security around that open source technology. But no survey, no analysis, no research would be complete without including these open source tech. So what we're looking at here, if I can just get away from the open source names, we see other things like Databricks and OneTrust . They're repeating as top net sentiment performers here. And then also the design vendors. People don't spend a lot of time on 'em, but Miro and Figma. This is their third survey in a row where they're just dominating that sentiment overall. And Adobe should probably take note of that because they're really coming after them. But Databricks, we all know probably would've been a public company by now if the market hadn't turned, but you can see just how dominant they are in a survey of nothing but private companies. And we'll see that again when we talk about the database later. >> And I'll just add, so you see automation anywhere on there, the big UiPath competitor company that was not able to get to the public markets. They've been trying. Snyk, Peter McKay's company, they've raised a bunch of money, big security player. They're doing some really interesting things in developer security, helping developers secure the data flow, H2O.ai, Dataiku AI company. We saw them at the Snowflake Summit. Redis Labs, Netskope and security. So a lot of names that we know that ultimately we think are probably going to be hitting the public market. Okay, here's the same view for private companies with less mindshare, Erik. Take us through this one. >> On the previous slide too real quickly, I wanted to pull that security scorecard and we'll get back into it. But this is a newcomer, that I couldn't believe how strong their data was, but we'll bring that up in a second. Now, when we go to the ones of lower mindshare, it's interesting to talk about open source, right? Kubernetes was all the way on the top right. Everyone uses containers. Here we see Istio up there. Not everyone is using service mesh as much. And that's why Istio is in the smaller breakout. But still when you talk about net sentiment, it's about the leader, it's the highest one there is. So really interesting to point out. Then we see other names like Collibra in the data side really performing well. And again, as always security, very well represented here. We have Aqua, Wiz, Armis, which is a standout in this survey this time around. They do IoT security. I hadn't even heard of them until I started digging into the data here. And I couldn't believe how well they were doing. And then of course you have AnyScale, which is doing a second best in this and the best name in the survey Hugging Face, which is a machine learning AI tool. Also doing really well on a net sentiment, but they're not as far along on that access of mindshare just yet. So these are again, emerging companies that might not be as well represented in the enterprise as they will be in a couple of years. >> Hugging Face sounds like something you do with your two year old. Like you said, you see high performers, AnyScale do machine learning and you mentioned them. They came out of Berkeley. Collibra Governance, InfluxData is on there. InfluxDB's a time series database. And yeah, of course, Alex, if you bring that back up, you get a big group of red dots, right? That's the bad zone, I guess, which Sisense does vis, Yellowbrick Data is a NPP database. How should we interpret the red dots, Erik? I mean, is it necessarily a bad thing? Could it be misinterpreted? What's your take on that? >> Sure, well, let me just explain the definition of it first from a data science perspective, right? We're a data company first. So the gray dots that you're seeing that aren't named, that's the mean that's the average. So in order for you to be on this chart, you have to be at least one standard deviation above or below that average. So that gray is where we're saying, "Hey, this is where the lump of average comes in. This is where everyone normally stands." So you either have to be an outperformer or an underperformer to even show up in this analysis. So by definition, yes, the red dots are bad. You're at least one standard deviation below the average of your peers. It's not where you want to be. And if you're on the lower left, not only are you not performing well from a utilization or an actual usage rate, but people don't even know who you are. So that's a problem, obviously. And the VCs and the PEs out there that are backing these companies, they're the ones who mostly are interested in this data. >> Yeah. Oh, that's great explanation. Thank you for that. No, nice benchmarking there and yeah, you don't want to be in the red. All right, let's get into the next segment here. Here going to look at evaluation rates, adoption and the all important churn. First new evaluations. Let's bring up that slide. And Erik, take us through this. >> So essentially I just want to explain what evaluation means is that people will cite that they either plan to evaluate the company or they're currently evaluating. So that means we're aware of 'em and we are choosing to do a POC of them. And then we'll see later how that turns into utilization, which is what a company wants to see, awareness, evaluation, and then actually utilizing them. That's sort of the life cycle for these emerging companies. So what we're seeing here, again, with very high evaluation rates. H2O, we mentioned. SecurityScorecard jumped up again. Chargebee, Snyk, Salt Security, Armis. A lot of security names are up here, Aqua, Netskope, which God has been around forever. I still can't believe it's in an Emerging Technology Survey But so many of these names fall in data and security again, which is why we decided to pick those out Dave. And on the lower side, Vena, Acton, those unfortunately took the dubious award of the lowest evaluations in our survey, but I prefer to focus on the positive. So SecurityScorecard, again, real standout in this one, they're in a security assessment space, basically. They'll come in and assess for you how your security hygiene is. And it's an area of a real interest right now amongst our ITDM community. >> Yeah, I mean, I think those, and then Arctic Wolf is up there too. They're doing managed services. You had mentioned Netskope. Yeah, okay. All right, let's look at now adoption. These are the companies whose offerings are being used the most and are above that standard deviation in the green. Take us through this, Erik. >> Sure, yet again, what we're looking at is, okay, we went from awareness, we went to evaluation. Now it's about utilization, which means a survey respondent's going to state "Yes, we evaluated and we plan to utilize it" or "It's already in our enterprise and we're actually allocating further resources to it." Not surprising, again, a lot of open source, the reason why, it's free. So it's really easy to grow your utilization on something that's free. But as you and I both know, as Red Hat proved, there's a lot of money to be made once the open source is adopted, right? You need the governance, you need the security, you need the support wrapped around it. So here we're seeing Kubernetes, Postgres, Apache Kafka, Jenkins, Grafana. These are all open source based names. But if we're looking at names that are non open source, we're going to see Databricks, Automation Anywhere, Rubrik all have the highest mindshare. So these are the names, not surprisingly, all names that probably should have been public by now. Everyone's expecting an IPO imminently. These are the names that have the highest mindshare. If we talk about the highest utilization rates, again, Miro and Figma pop up, and I know they're not household names, but they are just dominant in this survey. These are applications that are meant for design software and, again, they're going after an Autodesk or a CAD or Adobe type of thing. It is just dominant how high the utilization rates are here, which again is something Adobe should be paying attention to. And then you'll see a little bit lower, but also interesting, we see Collibra again, we see Hugging Face again. And these are names that are obviously in the data governance, ML, AI side. So we're seeing a ton of data, a ton of security and Rubrik was interesting in this one, too, high utilization and high mindshare. We know how pervasive they are in the enterprise already. >> Erik, Alex, keep that up for a second, if you would. So yeah, you mentioned Rubrik. Cohesity's not on there. They're sort of the big one. We're going to talk about them in a moment. Puppet is interesting to me because you remember the early days of that sort of space, you had Puppet and Chef and then you had Ansible. Red Hat bought Ansible and then Ansible really took off. So it's interesting to see Puppet on there as well. Okay. So now let's look at the churn because this one is where you don't want to be. It's, of course, all red 'cause churn is bad. Take us through this, Erik. >> Yeah, definitely don't want to be here and I don't love to dwell on the negative. So we won't spend as much time. But to your point, there's one thing I want to point out that think it's important. So you see Rubrik in the same spot, but Rubrik has so many citations in our survey that it actually would make sense that they're both being high utilization and churn just because they're so well represented. They have such a high overall representation in our survey. And the reason I call that out is Cohesity. Cohesity has an extremely high churn rate here about 17% and unlike Rubrik, they were not on the utilization side. So Rubrik is seeing both, Cohesity is not. It's not being utilized, but it's seeing a high churn. So that's the way you can look at this data and say, "Hm." Same thing with Puppet. You noticed that it was on the other slide. It's also on this one. So basically what it means is a lot of people are giving Puppet a shot, but it's starting to churn, which means it's not as sticky as we would like. One that was surprising on here for me was Tanium. It's kind of jumbled in there. It's hard to see in the middle, but Tanium, I was very surprised to see as high of a churn because what I do hear from our end user community is that people that use it, like it. It really kind of spreads into not only vulnerability management, but also that endpoint detection and response side. So I was surprised by that one, mostly to see Tanium in here. Mural, again, was another one of those application design softwares that's seeing a very high churn as well. >> So you're saying if you're in both... Alex, bring that back up if you would. So if you're in both like MariaDB is for example, I think, yeah, they're in both. They're both green in the previous one and red here, that's not as bad. You mentioned Rubrik is going to be in both. Cohesity is a bit of a concern. Cohesity just brought on Sanjay Poonen. So this could be a go to market issue, right? I mean, 'cause Cohesity has got a great product and they got really happy customers. So they're just maybe having to figure out, okay, what's the right ideal customer profile and Sanjay Poonen, I guarantee, is going to have that company cranking. I mean they had been doing very well on the surveys and had fallen off of a bit. The other interesting things wondering the previous survey I saw Cvent, which is an event platform. My only reason I pay attention to that is 'cause we actually have an event platform. We don't sell it separately. We bundle it as part of our offerings. And you see Hopin on here. Hopin raised a billion dollars during the pandemic. And we were like, "Wow, that's going to blow up." And so you see Hopin on the churn and you didn't see 'em in the previous chart, but that's sort of interesting. Like you said, let's not kind of dwell on the negative, but you really don't. You know, churn is a real big concern. Okay, now we're going to drill down into two sectors, security and data. Where data comprises three areas, database and data warehousing, machine learning and AI and big data analytics. So first let's take a look at the security sector. Now this is interesting because not only is it a sector drill down, but also gives an indicator of how much money the firm has raised, which is the size of that bubble. And to tell us if a company is punching above its weight and efficiently using its venture capital. Erik, take us through this slide. Explain the dots, the size of the dots. Set this up please. >> Yeah. So again, the axis is still the same, net sentiment and mindshare, but what we've done this time is we've taken publicly available information on how much capital company is raised and that'll be the size of the circle you see around the name. And then whether it's green or red is basically saying relative to the amount of money they've raised, how are they doing in our data? So when you see a Netskope, which has been around forever, raised a lot of money, that's why you're going to see them more leading towards red, 'cause it's just been around forever and kind of would expect it. Versus a name like SecurityScorecard, which is only raised a little bit of money and it's actually performing just as well, if not better than a name, like a Netskope. OneTrust doing absolutely incredible right now. BeyondTrust. We've seen the issues with Okta, right. So those are two names that play in that space that obviously are probably getting some looks about what's going on right now. Wiz, we've all heard about right? So raised a ton of money. It's doing well on net sentiment, but the mindshare isn't as well as you'd want, which is why you're going to see a little bit of that red versus a name like Aqua, which is doing container and application security. And hasn't raised as much money, but is really neck and neck with a name like Wiz. So that is why on a relative basis, you'll see that more green. As we all know, information security is never going away. But as we'll get to later in the program, Dave, I'm not sure in this current market environment, if people are as willing to do POCs and switch away from their security provider, right. There's a little bit of tepidness out there, a little trepidation. So right now we're seeing overall a slight pause, a slight cooling in overall evaluations on the security side versus historical levels a year ago. >> Now let's stay on here for a second. So a couple things I want to point out. So it's interesting. Now Snyk has raised over, I think $800 million but you can see them, they're high on the vertical and the horizontal, but now compare that to Lacework. It's hard to see, but they're kind of buried in the middle there. That's the biggest dot in this whole thing. I think I'm interpreting this correctly. They've raised over a billion dollars. It's a Mike Speiser company. He was the founding investor in Snowflake. So people watch that very closely, but that's an example of where they're not punching above their weight. They recently had a layoff and they got to fine tune things, but I'm still confident they they're going to do well. 'Cause they're approaching security as a data problem, which is probably people having trouble getting their arms around that. And then again, I see Arctic Wolf. They're not red, they're not green, but they've raised fair amount of money, but it's showing up to the right and decent level there. And a couple of the other ones that you mentioned, Netskope. Yeah, they've raised a lot of money, but they're actually performing where you want. What you don't want is where Lacework is, right. They've got some work to do to really take advantage of the money that they raised last November and prior to that. >> Yeah, if you're seeing that more neutral color, like you're calling out with an Arctic Wolf, like that means relative to their peers, this is where they should be. It's when you're seeing that red on a Lacework where we all know, wow, you raised a ton of money and your mindshare isn't where it should be. Your net sentiment is not where it should be comparatively. And then you see these great standouts, like Salt Security and SecurityScorecard and Abnormal. You know they haven't raised that much money yet, but their net sentiment's higher and their mindshare's doing well. So those basically in a nutshell, if you're a PE or a VC and you see a small green circle, then you're doing well, then it means you made a good investment. >> Some of these guys, I don't know, but you see these small green circles. Those are the ones you want to start digging into and maybe help them catch a wave. Okay, let's get into the data discussion. And again, three areas, database slash data warehousing, big data analytics and ML AI. First, we're going to look at the database sector. So Alex, thank you for bringing that up. Alright, take us through this, Erik. Actually, let me just say Postgres SQL. I got to ask you about this. It shows some funding, but that actually could be a mix of EDB, the company that commercializes Postgres and Postgres the open source database, which is a transaction system and kind of an open source Oracle. You see MariaDB is a database, but open source database. But the companies they've raised over $200 million and they filed an S-4. So Erik looks like this might be a little bit of mashup of companies and open source products. Help us understand this. >> Yeah, it's tough when you start dealing with the open source side and I'll be honest with you, there is a little bit of a mashup here. There are certain names here that are a hundred percent for profit companies. And then there are others that are obviously open source based like Redis is open source, but Redis Labs is the one trying to monetize the support around it. So you're a hundred percent accurate on this slide. I think one of the things here that's important to note though, is just how important open source is to data. If you're going to be going to any of these areas, it's going to be open source based to begin with. And Neo4j is one I want to call out here. It's not one everyone's familiar with, but it's basically geographical charting database, which is a name that we're seeing on a net sentiment side actually really, really high. When you think about it's the third overall net sentiment for a niche database play. It's not as big on the mindshare 'cause it's use cases aren't as often, but third biggest play on net sentiment. I found really interesting on this slide. >> And again, so MariaDB, as I said, they filed an S-4 I think $50 million in revenue, that might even be ARR. So they're not huge, but they're getting there. And by the way, MariaDB, if you don't know, was the company that was formed the day that Oracle bought Sun in which they got MySQL and MariaDB has done a really good job of replacing a lot of MySQL instances. Oracle has responded with MySQL HeatWave, which was kind of the Oracle version of MySQL. So there's some interesting battles going on there. If you think about the LAMP stack, the M in the LAMP stack was MySQL. And so now it's all MariaDB replacing that MySQL for a large part. And then you see again, the red, you know, you got to have some concerns about there. Aerospike's been around for a long time. SingleStore changed their name a couple years ago, last year. Yellowbrick Data, Fire Bolt was kind of going after Snowflake for a while, but yeah, you want to get out of that red zone. So they got some work to do. >> And Dave, real quick for the people that aren't aware, I just want to let them know that we can cut this data with the public company data as well. So we can cross over this with that because some of these names are competing with the larger public company names as well. So we can go ahead and cross reference like a MariaDB with a Mongo, for instance, or of something of that nature. So it's not in this slide, but at another point we can certainly explain on a relative basis how these private names are doing compared to the other ones as well. >> All right, let's take a quick look at analytics. Alex, bring that up if you would. Go ahead, Erik. >> Yeah, I mean, essentially here, I can't see it on my screen, my apologies. I just kind of went to blank on that. So gimme one second to catch up. >> So I could set it up while you're doing that. You got Grafana up and to the right. I mean, this is huge right. >> Got it thank you. I lost my screen there for a second. Yep. Again, open source name Grafana, absolutely up and to the right. But as we know, Grafana Labs is actually picking up a lot of speed based on Grafana, of course. And I think we might actually hear some noise from them coming this year. The names that are actually a little bit more disappointing than I want to call out are names like ThoughtSpot. It's been around forever. Their mindshare of course is second best here but based on the amount of time they've been around and the amount of money they've raised, it's not actually outperforming the way it should be. We're seeing Moogsoft obviously make some waves. That's very high net sentiment for that company. It's, you know, what, third, fourth position overall in this entire area, Another name like Fivetran, Matillion is doing well. Fivetran, even though it's got a high net sentiment, again, it's raised so much money that we would've expected a little bit more at this point. I know you know this space extremely well, but basically what we're looking at here and to the bottom left, you're going to see some names with a lot of red, large circles that really just aren't performing that well. InfluxData, however, second highest net sentiment. And it's really pretty early on in this stage and the feedback we're getting on this name is the use cases are great, the efficacy's great. And I think it's one to watch out for. >> InfluxData, time series database. The other interesting things I just noticed here, you got Tamer on here, which is that little small green. Those are the ones we were saying before, look for those guys. They might be some of the interesting companies out there and then observe Jeremy Burton's company. They do observability on top of Snowflake, not green, but kind of in that gray. So that's kind of cool. Monte Carlo is another one, they're sort of slightly green. They are doing some really interesting things in data and data mesh. So yeah, okay. So I can spend all day on this stuff, Erik, phenomenal data. I got to get back and really dig in. Let's end with machine learning and AI. Now this chart it's similar in its dimensions, of course, except for the money raised. We're not showing that size of the bubble, but AI is so hot. We wanted to cover that here, Erik, explain this please. Why TensorFlow is highlighted and walk us through this chart. >> Yeah, it's funny yet again, right? Another open source name, TensorFlow being up there. And I just want to explain, we do break out machine learning, AI is its own sector. A lot of this of course really is intertwined with the data side, but it is on its own area. And one of the things I think that's most important here to break out is Databricks. We started to cover Databricks in machine learning, AI. That company has grown into much, much more than that. So I do want to state to you Dave, and also the audience out there that moving forward, we're going to be moving Databricks out of only the MA/AI into other sectors. So we can kind of value them against their peers a little bit better. But in this instance, you could just see how dominant they are in this area. And one thing that's not here, but I do want to point out is that we have the ability to break this down by industry vertical, organization size. And when I break this down into Fortune 500 and Fortune 1000, both Databricks and Tensorflow are even better than you see here. So it's quite interesting to see that the names that are succeeding are also succeeding with the largest organizations in the world. And as we know, large organizations means large budgets. So this is one area that I just thought was really interesting to point out that as we break it down, the data by vertical, these two names still are the outstanding players. >> I just also want to call it H2O.ai. They're getting a lot of buzz in the marketplace and I'm seeing them a lot more. Anaconda, another one. Dataiku consistently popping up. DataRobot is also interesting because all the kerfuffle that's going on there. The Cube guy, Cube alum, Chris Lynch stepped down as executive chairman. All this stuff came out about how the executives were taking money off the table and didn't allow the employees to participate in that money raising deal. So that's pissed a lot of people off. And so they're now going through some kind of uncomfortable things, which is unfortunate because DataRobot, I noticed, we haven't covered them that much in "Breaking Analysis", but I've noticed them oftentimes, Erik, in the surveys doing really well. So you would think that company has a lot of potential. But yeah, it's an important space that we're going to continue to watch. Let me ask you Erik, can you contextualize this from a time series standpoint? I mean, how is this changed over time? >> Yeah, again, not show here, but in the data. I'm sorry, go ahead. >> No, I'm sorry. What I meant, I should have interjected. In other words, you would think in a downturn that these emerging companies would be less interesting to buyers 'cause they're more risky. What have you seen? >> Yeah, and it was interesting before we went live, you and I were having this conversation about "Is the downturn stopping people from evaluating these private companies or not," right. In a larger sense, that's really what we're doing here. How are these private companies doing when it comes down to the actual practitioners? The people with the budget, the people with the decision making. And so what I did is, we have historical data as you know, I went back to the Emerging Technology Survey we did in November of 21, right at the crest right before the market started to really fall and everything kind of started to fall apart there. And what I noticed is on the security side, very much so, we're seeing less evaluations than we were in November 21. So I broke it down. On cloud security, net sentiment went from 21% to 16% from November '21. That's a pretty big drop. And again, that sentiment is our one aggregate metric for overall positivity, meaning utilization and actual evaluation of the name. Again in database, we saw it drop a little bit from 19% to 13%. However, in analytics we actually saw it stay steady. So it's pretty interesting that yes, cloud security and security in general is always going to be important. But right now we're seeing less overall net sentiment in that space. But within analytics, we're seeing steady with growing mindshare. And also to your point earlier in machine learning, AI, we're seeing steady net sentiment and mindshare has grown a whopping 25% to 30%. So despite the downturn, we're seeing more awareness of these companies in analytics and machine learning and a steady, actual utilization of them. I can't say the same in security and database. They're actually shrinking a little bit since the end of last year. >> You know it's interesting, we were on a round table, Erik does these round tables with CISOs and CIOs, and I remember one time you had asked the question, "How do you think about some of these emerging tech companies?" And one of the executives said, "I always include somebody in the bottom left of the Gartner Magic Quadrant in my RFPs. I think he said, "That's how I found," I don't know, it was Zscaler or something like that years before anybody ever knew of them "Because they're going to help me get to the next level." So it's interesting to see Erik in these sectors, how they're holding up in many cases. >> Yeah. It's a very important part for the actual IT practitioners themselves. There's always contracts coming up and you always have to worry about your next round of negotiations. And that's one of the roles these guys play. You have to do a POC when contracts come up, but it's also their job to stay on top of the new technology. You can't fall behind. Like everyone's a software company. Now everyone's a tech company, no matter what you're doing. So these guys have to stay in on top of it. And that's what this ETS can do. You can go in here and look and say, "All right, I'm going to evaluate their technology," and it could be twofold. It might be that you're ready to upgrade your technology and they're actually pushing the envelope or it simply might be I'm using them as a negotiation ploy. So when I go back to the big guy who I have full intentions of writing that contract to, at least I have some negotiation leverage. >> Erik, we got to leave it there. I could spend all day. I'm going to definitely dig into this on my own time. Thank you for introducing this, really appreciate your time today. >> I always enjoy it, Dave and I hope everyone out there has a great holiday weekend. Enjoy the rest of the summer. And, you know, I love to talk data. So anytime you want, just point the camera on me and I'll start talking data. >> You got it. I also want to thank the team at ETR, not only Erik, but Darren Bramen who's a data scientist, really helped prepare this data, the entire team over at ETR. I cannot tell you how much additional data there is. We are just scratching the surface in this "Breaking Analysis". So great job guys. I want to thank Alex Myerson. Who's on production and he manages the podcast. Ken Shifman as well, who's just coming back from VMware Explore. Kristen Martin and Cheryl Knight help get the word out on social media and in our newsletters. And Rob Hof is our editor in chief over at SiliconANGLE. Does some great editing for us. Thank you. All of you guys. Remember these episodes, they're all available as podcast, wherever you listen. All you got to do is just search "Breaking Analysis" podcast. I publish each week on wikibon.com and siliconangle.com. Or you can email me to get in touch david.vellante@siliconangle.com. You can DM me at dvellante or comment on my LinkedIn posts and please do check out etr.ai for the best survey data in the enterprise tech business. This is Dave Vellante for Erik Bradley and The Cube Insights powered by ETR. Thanks for watching. Be well. And we'll see you next time on "Breaking Analysis". (upbeat music)

>> From the Cube studios in Palo Alto and Boston, bringing you data driven insights from theCUBE and ETR, this is Breaking Analysis with Dave Vellante. >> While the precise direction of VMware's future is unknown, given the plan Broadcom acquisition, one thing is clear. The topic of what Broadcom plans will not be the main focus of the agenda at the upcoming VMware Explore event next week in San Francisco. We believe that despite any uncertainty, VMware will lay out for its customers what it sees as its future. And that future is multi-cloud or cross-cloud services, what we call Supercloud. Hello, and welcome to this week's Wikibon Cube Insights powered by ETR. In this breaking analysis, we drill into the latest survey data on VMware from ETR. And we'll share with you the next iteration of the Supercloud definition based on feedback from dozens of contributors. And we'll give you our take on what to expect next week at VMware Explorer 2022. Well, VMware is maturing. You can see it in the numbers. VMware had a solid quarter just this week, which was announced beating earnings and growing the top line by 6%. But it's clear from its financials and the ETR data that we're showing here that VMware's Halcion glory days are behind it. This chart shows the spending profile from ETR's July survey of nearly 1500 IT buyers and CIOs. The survey included 722 VMware customers with the green bars showing elevated spending momentum, ie: growth, either new or growing at more than 6%. And the red bars show lower spending, either down 6% or worse or defections. The gray bars, that's the flat spending crowd, and it really tells a story. Look, nobody's throwing away their VMware platforms. They're just not investing as rapidly as in previous years. The blue line shows net score or spending momentum and subtracts the reds from the greens. The yellow line shows market penetration or pervasiveness in the survey. So the data is pretty clear. It's steady, but it's not remarkable. Now, the timing of the acquisition, quite rightly, is quite good, I would say. Now, this next chart shows the net score and pervasiveness juxtaposed on an XY graph and breaks down the VMware portfolio in those dimensions, the product portfolio. And you can see the dominance of respondents citing VMware as the platform. They might not know exactly which services they use, but they just respond VMware. That's on the X axis. You can see it way to the right. And the spending momentum or the net score is on the Y axis. That red dotted line at 4%, that indicates elevated levels and only VMware cloud on AWS is above that line. Notably, Tanzu has jumped up significantly from previous quarters, with the rest of the portfolio showing steady, as you would expect from a maturing platform. Only carbon black is hovering in the red zone, kind of ironic given the name. We believe that VMware is going to be a major player in cross cloud services, what we refer to as Supercloud. For months, we've been refining the concept and the definition. At Supercloud '22, we had discussions with more than 30 technology and business experts, and we've gathered input from many more. Based on that feedback, here's the definition we've landed on. It's somewhat refined from our earlier definition that we published a couple weeks ago. Supercloud is an emerging computing architecture that comprises a set of services abstracted from the underlying primitives of hyperscale clouds, e.g. compute, storage, networking, security, and other native resources, to create a global system spanning more than one cloud. Supercloud is three essential properties, three deployment models, and three service models. So what are those essential elements, those properties? We've simplified the picture from our last report. We show them here. I'll review them briefly. We're not going to go super in depth here because we've covered this topic a lot. But supercloud, it runs on more than one cloud. It creates that common or identical experience across clouds. It contains a necessary capability that we call a superPaaS that acts as a cloud interpreter, and it has metadata intelligence to optimize for a specific purpose. We'll publish this definition in detail. So again, we're not going to spend a ton of time here today. Now, we've identified three deployment models for Supercloud. The first is a single instantiation, where a control plane runs on one cloud but supports interactions with multiple other clouds. An example we use is Kubernetes cluster management service that runs on one cloud but can deploy and manage clusters on other clouds. The second model is a multi-cloud, multi-region instantiation where a full stack of services is instantiated on multiple clouds and multiple cloud regions with a common interface across them. We've used cohesity as one example of this. And then a single global instance that spans multiple cloud providers. That's our snowflake example. Again, we'll publish this in detail. So we're not going to spend a ton of time here today. Finally, the service models. The feedback we've had is IaaS, PaaS, and SaaS work fine to describe the service models for Supercloud. NetApp's Cloud Volume is a good example in IaaS. VMware cloud foundation and what we expect at VMware Explore is a good PaaS example. And SAP HANA Cloud is a good example of SaaS running as a Supercloud service. That's the SAP HANA multi-cloud. So what is it that we expect from VMware Explore 2022? Well, along with what will be an exciting and speculation filled gathering of the VMware community at the Moscone Center, we believe VMware will lay out its future architectural direction. And we expect it will fit the Supercloud definition that we just described. We think VMware will show its hand on a set of cross-cloud services and will promise a common experience for users and developers alike. As we talked about at Supercloud '22, VMware kind of wants to have its cake, eat it too, and lose weight. And by that, we mean that it will not only abstract the underlying primitives of each of the individual clouds, but if developers want access to them, they will allow that and actually facilitate that. Now, we don't expect VMware to use the term Supercloud, but it will be a cross-cloud multi-cloud services model that they put forth, we think, at VMworld Explore. With IaaS comprising compute, storage, and networking, a very strong emphasis, we believe, on security, of course, a governance and a comprehensive set of data protection services. Now, very importantly, we believe Tanzu will play a leading role in any announcements this coming week, as a purpose-built PaaS layer, specifically designed to create a common experience for cross clouds for data and application services. This, we believe, will be VMware's most significant offering to date in cross-cloud services. And it will position VMware to be a leader in what we call Supercloud. Now, while it remains to be seen what Broadcom exactly intends to do with VMware, we've speculated, others have speculated. We think this Supercloud is a substantial market opportunity generally and for VMware specifically. Look, if you don't own a public cloud, and very few companies do, in the tech business, we believe you better be supporting the build out of superclouds or building a supercloud yourself on top of hyperscale infrastructure. And we believe that as cloud matures, hyperscalers will increasingly I cross cloud services as an opportunity. We asked David Floyer to take a stab at a market model for super cloud. He's really good at these types of things. What he did is he took the known players in cloud and estimated their IaaS and PaaS cloud services, their total revenue, and then took a percentage. So this is super set of just the public cloud and the hyperscalers. And then what he did is he took a percentage to fit the Supercloud definition, as we just shared above. He then added another 20% on top to cover the long tail of Other. Other over time is most likely going to grow to let's say 30%. That's kind of how these markets work. Okay, so this is obviously an estimate, but it's an informed estimate by an individual who has done this many, many times and is pretty well respected in these types of forecasts, these long term forecasts. Now, by the definition we just shared, Supercloud revenue was estimated at about $3 billion in 2022 worldwide, growing to nearly $80 billion by 2030. Now remember, there's not one Supercloud market. It comprises a bunch of purpose-built superclouds that solve a specific problem. But the common attribute is it's built on top of hyperscale infrastructure. So overall, cloud services, including Supercloud, peak by the end of the decade. But Supercloud continues to grow and will take a higher percentage of the cloud market. The reasoning here is that the market will change and compute, will increasingly become distributed and embedded into edge devices, such as automobiles and robots and factory equipment, et cetera, and not necessarily be a discreet... I mean, it still will be, of course, but it's not going to be as much of a discrete component that is consumed via services like EZ2, that will mature. And this will be a key shift to watch in spending dynamics and really importantly, computing economics, the things we've talked about around arm and edge and AI inferencing and new low cost computing architectures at the edge. We're talking not the near edge, like, Lowes and Home Depot, we're talking far edge and embedded devices. Now, whether this becomes a seamless part of Supercloud remains to be seen. Look, if that's how we see it, the current and the future state of Supercloud, and we're committed to keeping the discussion going with an inclusive model that gathers input from all parts of the industry. Okay, that's it for today. Thanks to Alex Morrison, who's on production, and he also manages the podcast. Ken Schiffman, as well, is on production in our Boston office. Kristin Martin and Cheryl Knight, they help us get the word out on social media and in our newsletters. And Rob Hoffe is our editor in chief over at Silicon Angle and does some helpful editing. Thank you, all. Remember these episodes, they're all available as podcasts, wherever you listen. All you got to do is search Breaking Analysis Podcast. I publish each 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. Please do check out etr.ai. They've got some great enterprise survey research. So please go there and poke around, And if you need any assistance, let them know. This is Dave Vellante for the Cube Insights powered by ETR. Thanks for watching, and we'll see you next time on Breaking Analysis. (lively music)

>> From theCUBE Studios in Palo Alto and Boston, bringing you data-driven insights from theCUBE and ETR. This is "Breaking Analysis" with Dave Vallante. >> Welcome to this week's Wikibon CUBE Insights powered by ETR. As we exited the isolation economy last year, Supercloud is a term that we introduced to describe something new that was happening in the world of cloud. In this "Breaking Analysis," we address the 10 most frequently asked questions we get around Supercloud. Okay, let's review these frequently asked questions on Supercloud that we're going to try to answer today. Look at an industry that's full of hype and buzzwords. Why the hell does anyone need a new term? Aren't hyperscalers building out Superclouds? We'll try to answer why the term Supercloud connotes something different from hyperscale clouds. And we'll talk about the problems that Superclouds solve specifically, and we'll further define the critical aspects of a Supercloud architecture. We often get asked, "Isn't this just multi-cloud?" Well, we don't think so, and we'll explain why in this "Breaking Analysis." Now, in an earlier episode, we introduced the notion of super PaaS. Well, isn't a plain vanilla PaaS already a super PaaS? Again, we don't think so, and we'll explain why. Who will actually build and who are the players currently building Superclouds? What workloads and services will run on Superclouds? And eight A or number nine, what are some examples that we can share of Supercloud? And finally, we'll answer what you can expect next from us on Supercloud. Okay, let's get started. Why do we need another buzzword? Well, late last year ahead of re:Invent, we were inspired by a post from Jerry Chen called castles in the cloud. Now, in that blog post, he introduced the idea that there were submarkets emerging in cloud that presented opportunities for investors and entrepreneurs. That the cloud wasn't going to suck the hyperscalers, weren't going to suck all the value out of the industry. And so we introduced this notion of Supercloud to describe what we saw as a value layer emerging above the hyperscalers CAPEX gift, we sometimes call it. Now, it turns out that we weren't the only ones using the term, as both Cornell and MIT, have used the phrase in somewhat similar, but different contexts. The point is, something new was happening in the AWS and other ecosystems. It was more than IS and PaaS, and wasn't just SaaS running in the cloud. It was a new architecture that integrates infrastructure, platform and software as services, to solve new problems that the cloud vendors, in our view, weren't addressing by themselves. It seemed to us that the ecosystem was pursuing opportunities across clouds that went beyond conventional implementations of multi-cloud. And we felt there was a structural change going on at the industry level. The Supercloud metaphorically was highlighting. So that's the background on why we felt a new catch phrase was warranted. Love it or hate it, it's memorable and it's what we chose. Now, to that last point about structural industry transformation. Andy Rapaport is sometimes and often credited with identifying the shift from the vertically integrated IBM mainframe era to the fragmented PC microprocesor based era in his HBR article in 1991. In fact, it was David Moschella, who at the time was an IDC analyst who first introduced the concept in 1987, four years before Rapaport's article was published. Moschella saw that it was clear that Intel, Microsoft, Seagate and others would replace the system vendors and put that forth in a graphic that looked similar to the first two on this chart. We don't have to review the shift from IBM as the center of the industry to Wintel. That's well understood. What isn't as well known or accepted is what Moschella put out in his 2018 book called "Seeing Digital" which introduced the idea of the matrix that's shown on the right hand side of this chart. Moschella posited that new services were emerging, built on top of the internet and hyperscale clouds that would integrate other innovations and would define the next era of computing. He used the term matrix, because the conceptual depiction included, not only horizontal technology rows, like the cloud and the internet, but for the first time included connected industry verticals, the columns in this chart. Moschella pointed out that, whereas historically, industry verticals had a closed value chain or stack and ecosystem of R&D and production and manufacturing and distribution. And if you were in that industry, the expertise within that vertical generally stayed within that vertical and was critical to success. But because of digital and data, for the first time, companies were able to traverse industries jump across industries and compete because data enabled them to do that. Examples, Amazon and content, payments, groceries, Apple and payments, and content and so forth. There are many examples. Data was now this unifying enabler and this marked a change in the structure of the technology landscape. And Supercloud is meant to imply more than running in hyperscale clouds. Rather, it's the combination of multiple technologies, enabled by cloud scale with new industry participants from those verticals; financial services, and healthcare, and manufacturing, energy, media, and virtually all and any industry. Kind of an extension of every company is a software company. Basically, every company now has the opportunity to build their own cloud or Supercloud. And we'll come back to that. Let's first address what's different about Superclouds relative to hyperscale clouds. Now, this one's pretty straightforward and obvious, I think. Hyperscale clouds, they're walled gardens where they want your data in their cloud and they want to keep you there. Sure, every cloud player realizes that not all data will go to their particular cloud. So they're meeting customers where their data lives with initiatives like Amazon Outposts and Azure Arc and Google Antos. But at the end of the day, the more homogeneous they can make their environments, the better control, security, costs, and performance they can deliver. The more complex the environment, the more difficult it is to deliver on their brand promises. And, of course, the less margin that's left for them to capture. Will the hyperscalers get more serious about cross cloud services? Maybe, but they have plenty of work to do within their own clouds and within enabling their own ecosystems. They have a long way to go, a lot of runway. So let's talk about specifically, what problems Superclouds solve. We've all seen the stats from IDC or Gartner or whomever, that customers on average use more than one cloud, two clouds, three clouds, five clouds, 20 clouds. And we know these clouds operate in disconnected silos for the most part. And that's a problem, because each cloud requires different skills, because the development environment is different as is the operating environment. They have different APIs, different primitives, and different management tools that are optimized for each respective hyperscale cloud. Their functions and value props don't extend to their competitors' clouds for the most part. Why would they? As a result, there's friction when moving between different clouds. It's hard to share data. It's hard to move work. It's hard to secure and govern data. It's hard to enforce organizational edicts and policies across these clouds and on-prem. Supercloud is an architecture designed to create a single environment that enables management of workloads and data across clouds in an effort to take out complexity, accelerate application development, streamline operations, and share data safely, irrespective of location. It's pretty straightforward, but non-trivial, which is why I always ask a company's CEO and executives if stock buybacks and dividends will yield as much return as building out Superclouds that solve really specific and hard problems and create differential value. Okay, let's dig a bit more into the architectural aspects of Supercloud. In other words, what are the salient attributes of Supercloud? So, first and foremost, a Supercloud runs a set of specific services designed to solve a unique problem, and it can do so in more than one cloud. Superclouds leverage the underlying cloud native tooling of a hyperscale cloud, but they're optimized for a specific objective that aligns with the problem that they're trying to solve. For example, Supercloud might be optimized for lowest cost or lowest latency or sharing data or governing or securing that data or higher performance for networking, for example. But the point is, the collection of services that is being delivered is focused on a unique value proposition that is not being delivered by the hyperscalers across clouds. A Supercloud abstracts the underlying and siloed primitives of the native PaaS layer from the hyperscale cloud, and then using its own specific platform as a service tooling, creates a common experience across clouds for developers and users. And it does so in the most efficient manner, meaning it has the metadata knowledge and management capabilities that can optimize for latency, bandwidth, or recovery or data sovereignty, or whatever unique value that Supercloud is delivering for the specific use case in their domain. And a Supercloud comprises a super PaaS capability that allows ecosystem partners through APIs to add incremental value on top of the Supercloud platform to fill gaps, accelerate features, and of course, innovate. The services can be infrastructure related, they could be application services, they could be data services, security services, user services, et cetera, designed and packaged to bring unique value to customers. Again, that hyperscalers are not delivering across clouds or on premises. Okay, so another common question we get is, "Isn't that just multi-cloud?" And what we'd say to that is yeah, "Yes, but no." You can call it multi-cloud 2.0, if you want. If you want to use, it's kind of a commonly used rubric. But as Dell's Chuck Whitten proclaimed at Dell Technologies World this year, multi-cloud, by design, is different than multi-cloud by default. Meaning, to date, multi-cloud has largely been a symptom of what we've called multi-vendor or of M&A. You buy a company and they happen to use Google cloud. And so you bring it in. And when you look at most so-called multi-cloud implementations, you see things like an on-prem stack, which is wrapped in a container and hosted on a specific cloud. Or increasingly, a technology vendor has done the work of building a cloud native version of their stack and running it on a specific cloud. But historically, it's been a unique experience within each cloud, with virtually no connection between the cloud silos. Supercloud sets out to build incremental value across clouds and above hyperscale CAPEX that goes beyond cloud compatibility within each cloud. So, if you want to call it multi-cloud 2.0, that's fine, but we chose to call it Supercloud. Okay, so at this point you may be asking, "Well isn't PaaS already a version of Supercloud?" And again, we would say, "No." That Supercloud and its corresponding super PaaS layer, which is a prerequisite, gives the freedom to store, process, and manage and secure and connect islands of data across a continuum with a common experience across clouds. And the services offered are specific to that Supercloud and will vary by each offering. OpenShift, for example, can be used to construct a super PaaS, but in and of itself, isn't a super PaaS, it's generic. A super PaaS might be developed to support, for instance, ultra low latency database work. It would unlikely, again, taking the OpenShift example, it's unlikely that off the shelf OpenShift would be used to develop such a low latency, super PaaS layer for ultra low latency database work. The point is, Supercloud and its inherent super PaaS will be optimized to solve specific problems like that low latency example for distributed databases or fast backup in recovery for data protection and ransomware, or data sharing or data governance. Highly specific use cases that the Supercloud is designed to solve for. Okay, another question we often get is, "Who has a Supercloud today and who's building a Supercloud and who are the contenders?" Well, most companies that consider themselves cloud players will, we believe, be building or are building Superclouds. Here's a common ETR graphic that we like to show with net score or spending momentum on the Y axis, and overlap or pervasiveness in the ETR surveys on the X axis. And we've randomly chosen a number of players that we think are in the Supercloud mix. And we've included the hyperscalers because they are enablers. Now, remember, this is a spectrum of maturity. It's a maturity model. And we've added some of those industry players that we see building Superclouds like Capital One, Goldman Sachs, Walmart. This is in deference to Moschella's observation around the matrix and the industry structural changes that are going on. This goes back to every company being a software company. And rather than pattern match and outdated SaaS model, we see new industry structures emerging where software and data and tools specific to an industry will lead the next wave of innovation and bring in new value that traditional technology companies aren't going to solve. And the hyperscalers aren't going to solve. We've talked a lot about Snowflake's data cloud as an example of Supercloud. After being at Snowflake Summit, we're more convinced than ever that they're headed in this direction. VMware is clearly going after cross cloud services, perhaps creating a new category. Basically, every large company we see either pursuing Supercloud initiatives or thinking about it. Dell showed Project Alpine at Dell Tech World. That's a Supercloud. Snowflake introducing a new application development capability based on their super PaaS, our term, of course. They don't use the phrase. Mongo, Couchbase, Nutanix, Pure Storage, Veeam, CrowdStrike, Okta, Zscaler. Yeah, all of those guys. Yes, Cisco and HPE. Even though on theCUBE at HPE Discover, Fidelma Russo said on theCUBE, she wasn't a fan of cloaking mechanisms. (Dave laughing) But then we talked to HPE's head of storage services, Omer Asad, and he's clearly headed in the direction that we would consider Supercloud. Again, those cross cloud services, of course, their emphasis is connecting as well on-prem. That single experience, which traditionally has not existed with multi-cloud or hybrid. And we're seeing the emergence of smaller companies like Aviatrix and Starburst and Clumio and others that are building versions of Superclouds that solve for a specific problem for their customers. Even ISVs like Adobe, ADP, we've talked to UiPath. They seem to be looking at new ways to go beyond the SaaS model and add value within their cloud ecosystem, specifically around data as part of their and their customer's digital transformations. So yeah, pretty much every tech vendor with any size or momentum, and new industry players are coming out of hiding and competing, building Superclouds that look a lot like Moschella's matrix, with machine intelligence and blockchains and virtual realities and gaming, all enabled by the internet and hyperscale cloud CAPEX. So it's moving fast and it's the future in our opinion. So don't get too caught up in the past or you'll be left behind. Okay, what about examples? We've given a number in the past but let's try to be a little bit more specific. Here are a few we've selected and we're going to answer the two questions in one section here. What workloads and services will run in Superclouds and what are some examples? Let's start with analytics. Our favorite example of Snowflake. It's one of the furthest along with its data cloud, in our view. It's a Supercloud optimized for data sharing and governance, and query performance, and security, and ecosystem enablement. When you do things inside of that data cloud, what we call a super data cloud. Again, our term, not theirs. You can do things that you could not do in a single cloud. You can't do this with Redshift. You can't do this with SQL server. And they're bringing new data types now with merging analytics or at least accommodate analytics and transaction type data and bringing open source tooling with things like Apache Iceberg. And so, it ticks the boxes we laid out earlier. I would say that a company like Databricks is also in that mix, doing it, coming at it from a data science perspective trying to create that consistent experience for data scientists and data engineering across clouds. Converge databases, running transaction and analytic workloads is another example. Take a look at what Couchbase is doing with Capella and how it's enabling stretching the cloud to the edge with arm based platforms and optimizing for low latency across clouds, and even out to the edge. Document database workloads, look at Mongo DB. A very developer friendly platform that where the Atlas is moving toward a Supercloud model, running document databases very, very efficiently. How about general purpose workloads? This is where VMware comes into play. Very clearly, there's a need to create a common operating environment across clouds and on-prem and out to the edge. And I say, VMware is hard at work on that, managing and moving workloads and balancing workloads, and being able to recover very quickly across clouds for everyday applications. Network routing, take a look at what Aviatrix is doing across clouds. Industry workloads, we see Capital One. It announced its cost optimization platform for Snowflake, piggybacking on Snowflake's Supercloud or super data cloud. And in our view, it's very clearly going to go after other markets. It's going to test it out with Snowflake, optimizing on AWS, and it's going to expand to other clouds as Snowflake's business and those other clouds grows. Walmart working with Microsoft to create an on-premed Azure experience that's seamless. Yes, that counts, on-prem counts. If you can create that seamless and continuous experience, identical experience from on-prem to a hyperscale cloud, we would include that as a Supercloud. We've written about what Goldman is doing. Again, connecting its on-prem data and software tooling, and other capabilities to AWS for scale. And you can bet dollars to donuts that Oracle will be building a Supercloud in healthcare with its Cerner acquisition. Supercloud is everywhere you look. So I'm sorry, naysayers, it's happening all around us. So what's next? Well, with all the industry buzz and debate about the future, John Furrier and I have decided to host an event in Palo Alto. We're motivated and inspired to further this conversation. And we welcome all points of view, positive, negative, multi-cloud, Supercloud, HyperCloud, all welcome. So theCUBE on Supercloud is coming on August 9th out of our Palo Alto studios. We'll be running a live program on the topic. We've reached out to a number of industry participants; VMware, Snowflake, Confluent, Skyhigh Security, G. Written House's new company, HashiCorp, CloudFlare. We've hit up Red Hat and we expect many of these folks will be in our studios on August 9th. And we've invited a number of industry participants as well that we're excited to have on. From industry, from financial services, from healthcare, from retail, we're inviting analysts, thought leaders, investors. We're going to have more detail in the coming weeks, but for now, if you're interested, please reach out to me or John with how you think you can advance the discussion, and we'll see if we can fit you in. So mark your calendars, stay tuned for more information. Okay, that's it for today. Thanks to Alex Myerson who handles production and manages the podcast for "Breaking Analysis." And I want to thank Kristen Martin and Cheryl Knight. They help get the word out on social and in our newsletters. And Rob Hof is our editor in chief over at SiliconANGLE, who does a lot of editing and appreciate you posting on SiliconANGLE, Rob. Thanks to all of you. Remember, all these episodes are available as podcasts wherever you listen. All you got to do is search, breaking analysis podcast. I publish each week on wikibon.com and siliconangle.com. Or you can email me directly at david.vellante@siliconangle.com. Or DM me @DVallante, or comment on my LinkedIn post. And please, do check out etr.ai for the best survey data in the enterprise tech business. We'll be at AWS NYC summit next Tuesday, July 12th. So if you're there, please do stop by and say hello to theCUBE. It's at the Javits Center. This is Dave Vallante for theCUBE Insights, powered by ETR. Thanks for watching. And we'll see you next time on "Breaking Analysis." (slow 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. >> Last year, we noted in a breaking analysis that the cloud ecosystem is innovating beyond the idea or notion of multi-cloud. We've said for years that multi-cloud is really not a strategy but rather a symptom of multi-vendor. And we coined this term supercloud to describe an abstraction layer that lives above the hyperscale infrastructure that hides the underlying complexities, the APIs, and the primitives of each of the respective clouds. It interconnects whether it's On-Prem, AWS, Azure, Google, stretching out to the edge and creates a value layer on top of that. So our vision is that supercloud is more than running an individual service in cloud native mode within an individual individual cloud rather it's this new layer that builds on top of the hyperscalers. And does things irrespective of location adds value and we'll get into that in more detail. Now it turns out that we weren't the only ones thinking about this, not surprisingly, the majority of the technology ecosystem has been working towards this vision in various forms, including some examples that actually don't try to hide the underlying primitives. And we'll talk about that, but give a consistent experience across the DevSecOps tool chain. Hello, and welcome to this week's Wikibon, Cube insights powered by ETR. In this breaking analysis, we're going to share some recent examples and direct quotes about supercloud from the many Cube guests that we've had on over the last several weeks and months. And we've been trying to test this concept of supercloud. Is it technically feasible? Is it business rational? Is there business case for it? And we'll also share some recent ETR data to put this into context with some of the players that we think are going after this opportunity and where they are in their supercloud build out. And as you can see I'm not in the studio, everybody's got COVID so the studios shut down temporarily but breaking analysis continues. So here we go. Now, first thing is we uncovered an article from earlier this year by Lori MacVittie, is entitled, Supercloud: The 22 Answer to Multi-Cloud Challenges. What a great title. Of course we love it. Now, what really interested us here is not just the title, but the notion that it really doesn't matter what it's called, who cares? Supercloud, distributed cloud, someone even called it Metacloud recently, and we'll get into that. But Lori is a technologist. She's a developer by background. She works at F-Five and she's partial to the supercloud definition that was put forth by Cornell. You can see it here. That's a cloud architecture that enables application migration as a service across different availability zones or cloud providers, et cetera. And that the supercloud provides interfaces to allocate, migrate and terminate resources... And can span all major public cloud providers as well as private clouds. Now, of course, we would take that as well to the edge. So sure. That sounds about right and provides further confirmation that something new is really happening out there. And that was our initial premise when we put this fourth last year. Now we want to dig deeper and hear from the many Cube guests that we've interviewed recently probing about this topic. We're going to start with Chuck Whitten. He's Dell's new Co-COO and most likely part of the Dell succession plan, many years down the road hopefully. He coined the phrase multi-cloud by default versus multi-cloud by design. And he provides a really good business perspective. He's not a deep technologist. We're going to hear from Chuck a couple of times today including one where John Furrier asks him about leveraging hyperscale CapEx. That's an important concept that's fundamental to supercloud. Now, Ashesh Badani heads products at Red Hat and he talks about what he calls Metacloud. Again, it doesn't matter to us what you call it but it's the ecosystem gathering and innovating and we're going to get his perspective. Now we have a couple of clips from Danny Allan. He is the CTO of Veeam. He's a deep technologist and super into the weeds, which we love. And he talks about how Veeam abstracts the cloud layer. Again, a concept that's fundamental to supercloud and he describes what a supercloud is to him. And we also bring with Danny the edge discussion to the conversation. Now the bottom line from Danny is we want to know is supercloud technically feasible? And is it a thing? And then we have Jeff Clarke. Jeff Clark is the Co-COO and Vice Chairman of Dell super experienced individual. He lays out his vision of supercloud and what John Furrier calls a business operating system. You're going to hear from John a couple times. And he, Jeff Clark has a dropped the mic moment, where he says, if we can do this X, we'll describe what X is, it's game over. Okay. So of course we wanted to then go to HPE, one of Dell's biggest competitors and Patrick Osborne is the vice president of the storage business unit at Hewlett Packet Enterprise. And so given Jeff Clarke's game over strategy, we want to understand how HPE sees supercloud. And the bottom line, according to Patrick Osborne is that it's real. So you'll hear from him. And now Raghu Raghuram is the CEO of VMware. He threw a curve ball at this supercloud concept. And he flat out says, no, we don't want to hide the underlying primitives. We want to give developers access to those. We want to create a consistent developer experience in that DevsSecOps tool chain and Kubernetes runtime environments, and connect all the elements in the application development stack. So that's a really interesting perspective that Raghu brings. And then we end on Itzik Reich. Itzik is a technologist and a technical team leader who's worked as a go between customers and product developers for a number of years. And we asked Itzik, is supercloud technically feasible and will it be a reality? So let's hear from these experts and you can decide for yourselves how real supercloud is today and where it is, run the sizzle >> Operative phrase is multi-cloud by default that's kind of the buzz from your keynote. What do you mean by that? >> Well, look, customers have woken up with multiple clouds, multiple public clouds, On-Premise clouds increasingly as the edge becomes much more a reality for customers clouds at the edge. And so that's what we mean by multi-cloud by default. It's not yet been designed strategically. I think our argument yesterday was, it can be and it should be. It is a very logical place for architecture to land because ultimately customers want the innovation across all of the hyperscale public clouds. They will see workloads and use cases where they want to maintain an On-Premise cloud, On-Premise clouds are not going away, I mentioned edge clouds, so it should be strategic. It's just not today. It doesn't work particularly well today. So when we say multi-cloud by default we mean that's the state of the world today. Our goal is to bring multi-cloud by design as you heard. >> Really great question, actually, since you and I talked, Dave, I've been spending some time noodling just over that. And you're right. There's probably some terminology, something that will get developed either by us or in collaboration with the industry. Where we sort of almost have the next almost like a Metacloud that we're working our way towards. >> So we manage both the snapshots and we convert it into the Veeam portable data format. And here's where the supercloud comes into play. Because if I can convert it into the Veeam portable data format, I can move that OS anywhere. I can move it from physical to virtual, to cloud, to another cloud, back to virtual, I can put it back on physical if I want to. It actually abstracts the cloud layer. There are things that we do when we go between cloud some use BIOS, some use UEFI, but we have the data in backup format, not snapshot format, that's theirs, but we have it in backup format that we can move around and abstract workloads across all of the infrastructure. >> And your catalog is control in control of that. Is that right? Am I thinking about that the right way? >> Yeah it is, 100%. And you know what's interesting about our catalog, Dave, the catalog is inside the backup. Yes. So here's, what's interesting about the edge, two things, on the edge you don't want to have any state, if you can help it. And so containers help with that You can have stateless environments, some persistent data storage But we not not only provide the portability in operating systems, we also do this for containers. And that's true. If you go to the cloud and you're using say EKS with relational database services RDS for the persistent data later, we can pick that up and move it to GKE or move it to OpenShift On-Premises. And so that's why I call this the supercloud, we have all of this data. Actually, I think you termed the term supercloud. >> Yeah. But thank you for... I mean, I'm looking for a confirmation from a technologist that it's technically feasible. >> It is technically feasible and you can do it today. >> You said also technology and business models are tied together and enabler. If you believe that then you have to believe that it's a business operating system that they want. They want to leverage whatever they can. And at the end of the day, they have to differentiate what they do. >> Well, that's exactly right. If I take that in what Dave was saying and I summarize it the following way, if we can take these cloud assets and capabilities, combine them in an orchestrated way to deliver a distributed platform, game over. >> We have a number of platforms that are providing whether it's compute or networking or storage, running those workloads that they plum up into the cloud they have an operational experience in the cloud and they now they have data services that are running in the cloud for us in GreenLake. So it's a reality, we have a number of platforms that support that. We're going to have a a set of big announcements coming up at HPE Discover. So we led with Electra and we have a block service. We have VM backup as a service and DR on top of that. So that's something that we're providing today. GreenLake has over, I think it's actually over 60 services right now that we're providing in the GreenLake platform itself. Everything from security, single sign on, customer IDs, everything. So it's real. We have the proofpoint for it. >> Yeah. So I want to clarify something that you said because this tends to be very commonly confused by customers. I use the word abstraction. And usually when people think of abstraction, they think it hides capabilities of the cloud providers. That's not what we are trying to do. In fact, that's the last thing we are trying to do. What we are trying to do is to provide a consistent developer experience regardless of where you want to build your application. So that you can use the cloud provider services if that's what you want to use. But the DevSecOp tool chain, the runtime environment which turns out to be Kubernetes and how you control the Kubernetes environment, how do you manage and secure and connect all of these things. Those are the places where we are adding the value. And so really the VMware value proposition is you can build on the cloud of your choice but providing these consistent elements, number one, you can make better use of us, your scarce developer or operator resources and expertise. And number two, you can move faster. And number three, you can just spend less as a result of this. So that's really what we are trying to do. We are not... So I just wanted to clarify the word abstraction. In terms of where are we? We are still, I would say, in the early stages. So if you look at what customers are trying to do, they're trying to build these greenfield applications. And there is an entire ecosystem emerging around Kubernetes. There is still, Kubernetes is not a developer platform. The developer experience on top of Kubernetes is highly inconsistent. And so those are some of the areas where we are introducing new innovations with our Tanzu Application Platform. And then if you take enterprise applications, what does it take to have enterprise applications running all the time be entirely secure, et cetera. >> Well, look, the multi-cloud by default today are isolated clouds. They don't work together. Your data is siloed. It's locked up and it is expensive to move and make sense of it. So I think the word you and I were batting around before, this is an interconnected tissue. That's what the world needs. They need the clouds to work together as a single platform. That's the problem that we're trying to solve. And you saw it in some of our announcements here that we're starting to make steps on that journey to make multi-cloud work together much simpler. >> It's interesting, you mentioned the hyperscalers and all that CapEx investments. Why wouldn't you want to take advantage of a cloud and build on the CapEx and then ultimately have the solutions machine learning as one area. You see some specialization with the clouds. But you start to see the rise of superclouds, Dave calls them, and that's where you can innovate on a cloud then go to the multiple clouds. Snowflakes is one, we see a lot of examples of supercloud... >> Project Alpine was another one. I mean, it's early, but it's its clearly where you're going. The technology is just starting to come around. I mean it's real. >> Yeah. I mean, why wouldn't you want to take advantage of all of the cloud innovation out there? >> Is that something that's, that supercloud idea is a reality from a technologist perspective. >> I think it is. So for example Katie Gordon, which I believe you've interviewed earlier this week, was demonstrating the Kubernetes data mobility aspect which is another project. That's exactly part of the it's rationale, the rationale of customers being able to move some of their Kubernetes workloads to the cloud and back and between different clouds. Why are we doing? Because customers wants to have the ability to move between different cloud providers, using a common API that will be able to orchestrate all of those things with a self-service that may be offered via the APEX console itself. So it's all around enabling developers and meeting them where they are today and also meeting them into tomorrow's world where they actually may have changed their mind to do those things. So yes we are walking on all of those different aspects. >> Okay. Let's take a quick look at some of the ETR data. This is an X-Y graph. You've seen it a number of times on breaking analysis, it plots the net score or spending momentum on the Y-axis and overlap or pervasiveness in the ETR dataset on the X-axis, used to be called market share. I think that term was off putting to some people, but anyway it's an indicator of presence in the dataset. Now that red dotted line that's rarefied air where anything above that line is considered highly elevated. Now you can see we've plotted Azure and AWS in the upper right. GCP is in there and Kubernetes. We've done that as reference points. They're not necessarily building supercloud platforms. We'll see if they ever want to do so. And Kubernetes of course not a company, but we put 'em in there for context. And we've cherry picked a few players that we believe are building out or are important for supercloud build out. Let's start with Snowflake. We've talked a lot about this company. You can see they're highly elevated on the vertical axis. We see the data cloud as a supercloud in the making. You've got pure storage in there. They made the public, the early part of its supercloud journey at Accelerate 2019 when it unveiled a hybrid block storage service inside of AWS, it connects its On-Prem to AWS and creates that singular experience for pure customers. We see Hashi, HashiCorp as an enabling infrastructure, as code. So they're enabling infrastructure as code across different clouds and different locations. You see Nutanix. They're embarking on their multi-cloud strategy but it's doing so in a way that we think is supercloud, like now. Now Veeam, we were just at VeeamON. And this company has tied Dell for the number one revenue player in data protection. That's according to IDC. And we don't think it won't be long before it holds that position alone at the top as it's growing faster than in Dell in the space. We'll see, Dell is kind of waking up a little bit and putting more resource on that. But Veeam, they're a pure play vendor in data protection. And you heard their CTO, Danny Allan's view on Supercloud, they're doing it today. And we heard extensive comments as well from Dell that's clearly where they're headed, project Alpine was an early example from Dell technologies world of Supercloud in our view. And HPE with GreenLake. Finally beginning to talk about that cross cloud experience. I think it in initially HPE has been more focused on the private cloud, we'll continue to probe. We'll be at HPE discover later on the spring, actually end of June. And we'll continue to probe to see what HPE is doing specifically with GreenLake. Now, finally, Cisco, we put them on the chart. We don't have direct quotes from recent shows and events but this data really shows you the size of Cisco's footprint within the ETR data set that's on the X-axis. Now the cut of this ETR data includes all sectors across the ETR taxonomy which is not something that we commonly show but you can see the magnitude of Cisco's presence. It's impressive. Now, they had better, Cisco that is, had better be building out a supercloud in our view or they're going to be left behind. And I'm quite certain that they're actually going to do so. So we have a lot of evidence that we're putting forth here and seeing in the marketplace what we said last year, the ecosystem is take taking shape, supercloud is forming and becoming a thing. And really in our view, is the future of cloud. But there are always risks to these predictive scenarios and we want to acknowledge those. So first, look, we could end up with a bunch of bespoke superclouds. Now one supercloud is better than three separate cloud native services that do fundamentally the same thing from the same vendor. One for AWS, one for GCP and one for Azure. So maybe that's not all that bad. But to point number two, we hope there evolves a set of open standards for self-service infrastructure, federated governance, and data sharing that will evolve as a horizontal layer versus a set of proprietary vendor specific tools. Now, maybe a company like Veeam will provide that as a data management layer or some of Veeam's competitors or maybe it'll emerge again as open source. As well, and this next point, we see the potential for edge disruptions, changing the economics of the data center. Edge in fact could evolve on its own, independent of the cloud. In fact, David Floria sees the edge somewhat differently from Danny Allan. Floria says he sees a requirement for distributed stateful environments that are ephemeral where recovery is built in. And I said, David, stateful? Ephemeral? Stateful ephemeral? Isn't that an oxymoron? And he responded that, look, if it's not ephemeral the costs are going to be prohibitive. He said the biggest mistake the companies could make is thinking that the edge is simply an extension of their current cloud strategies. We're seeing that a lot. Dell largely talks about the edge as retail. Now, and Telco is a little bit different, but back to Floria's comments, he feels companies have to completely reimagine an integrated file and recovery system which is much more data efficient. And he believes that the technology will evolve with massive volumes and eventually seep into enterprise cloud and distributed data centers with better economics. In other words, as David Michelle recently wrote, we're about 15 years into the most recent cloud cycle and history shows that every 15 years or so, something new comes along that is a blind spot and highly disruptive to existing leaders. So number four here is really important. Remember, in 2007 before AWS introduced the modern cloud, IBM outpost, sorry, IBM outspent Amazon and Google and RND and CapEx and was really comparable to Microsoft. But instead of inventing cloud, IBM spent hundreds of billions of dollars on stock buybacks and dividends. And so our view is that innovation rewards leaders. And while it's not without risks, it's what powers the technology industry it always has and likely always will. So we'll be watching that very closely, how companies choose to spend their free cash flow. Okay. That's it for now. Thanks for watching this episode of The Cube Insights, powered by ETR. Thanks to Stephanie Chan who does some of the background research? Alex Morrison is on production and is going to compile all this stuff. Thank you, Alex. We're all remote this week. Kristen Nicole and Cheryl Knight do Cube distribution and social distribution and get the word out, so thank you. Robert Hof is our editor in chief. Don't forget the checkout etr.ai for all the survey action. Remember I publish each week on wikibon.com and siliconangle.com and you can check out all the breaking analysis podcasts. All you can do is search breaking analysis podcast so you can pop in the headphones and listen while you're on a walk. You can email me at david.vellante@siliconangle.com. If you want to get in touch or DM me at DVellante, you can always hit me up into a comment on our LinkedIn posts. This is Dave Vellante. Thank you for watching this episode of break analysis, stay safe, be well and we'll see you next time. (upbeat music)

>> From theCUBE Studios in Palo Alto, in Boston bringing you Data Driven Insights from theCUBE and ETR. This is Breaking Analysis with Dave Vellante. >> In the pre-cloud era hardware companies would run benchmarks, showing how database and or application performance ran better on their systems relative to competitors or previous generation boxes. And they would make a big deal out of it. And the independent software vendors, you know they'd do a little golf clap if you will, in the form of a joint press release it became a game of leaprog amongst hardware competitors. That was pretty commonplace over the years. The Dell Snowflake Deal underscores that the value proposition between hardware companies and ISVs is changing and has much more to do with distribution channels, volumes and the amount of data that lives On-Prem in various storage platforms. For cloud native ISVs like Snowflake they're realizing that despite their Cloud only dogma they have to grit their teeth and deal with On-premises data or risk getting shut out of evolving architectures. Hello and welcome to this week's Wikibon Cube Insights powered by ETR. In this breaking analysis, we unpack what little is known about the Snowflake announcement from Dell Technologies World and discuss the implications of a changing Cloud landscape. We'll also share some new data for Cloud and Database platforms from ETR that shows Snowflake has actually entered the Earth's orbit when it comes to spending momentum on its platform. Now, before we get into the news I want you to listen to Frank's Slootman's answer to my question as to whether or not Snowflake would ever architect the platform to run On-Prem because it's doable technically, here's what he said, play the clip >> Forget it, this will only work in the Public Cloud. Because it's, this is how the utility model works, right. I think everybody is coming through this realization, right? I mean, excuses are running out at this point. You know, we think that it'll, people will come to the Public Cloud a lot sooner than we will ever come to the Private Cloud. It's not that we can't run a private Cloud. It's just diminishes the potential and the value that we bring. >> So you may be asking yourselves how do you square that circle? Because basically the Dell Snowflake announcement is about bringing Snowflake to the private cloud, right? Or is it let's get into the news and we'll find out. Here's what we know at Dell Technologies World. One of the more buzzy announcements was the, by the way this was a very well attended vet event. I should say about I would say 8,000 people by my estimates. But anyway, one of the more buzzy announcements was Snowflake can now run analytics on Non-native Snowflake data that lives On-prem in a Dell object store Dell's ECS to start with. And eventually it's software defined object store. Here's Snowflake's clark, Snowflake's Clark Patterson describing how it works this past week on theCUBE. Play the clip. The way it works is I can now access Non-native Snowflake data using what materialized views, external tables How does that work? >> Some combination of the, all the above. So we've had in Snowflake, a capability called External Tables, which you refer to, it goes hand in hand with this notion of external stages. Basically there's a through the combination of those two capabilities, it's a metadata layer on data, wherever it resides. So customers have actually used this in Snowflake for data lake data outside of Snowflake in the Cloud, up until this point. So it's effectively an extension of that functionality into the Dell On-Premises world, so that we can tap into those things. So we use the external stages to expose all the metadata about what's in the Dell environment. And then we build external tables in Snowflake. So that data looks like it is in Snowflake. And then the experience for the analyst or whomever it is, is exactly as though that data lives in the Snowflake world. >> So as Clark explained, this capability of External tables has been around in the Cloud for a while, mainly to suck data out of Cloud data lakes. Snowflake External Tables use file level metadata, for instance, the name of the file and the versioning so that it can be queried in a stage. A stage is just an external location outside of Snowflake. It could be an S3 bucket or an Azure Blob and it's soon will be a Dell object store. And in using this feature, the Dell looks like it lives inside of Snowflake and Clark essentially, he's correct to say to an analyst that looks exactly like the data is in Snowflake, but uh, not exactly the data's read only which means you can't do what are called DML operations. DML stands for Data Manipulation Language and allows for things like inserting data into tables or deleting and modifying existing data. But the data can be queried. However, the performance of those queries to External Tables will almost certainly be slower. Now users can build things like materialized views which are going to speed things up a bit, but at the end of the day, it's going to run faster than the Cloud. And you can be almost certain that's where Snowflake wants it to run, but some organizations can't or won't move data into the Cloud for a variety of reasons, data sovereignty, compliance security policies, culture, you know, whatever. So data can remain in place On-prem, or it can be moved into the Public Cloud with this new announcement. Now, the compute today presumably is going to be done in the Public Cloud. I don't know where else it's going to be done. They really didn't talk about the compute side of things. Remember, one of Snowflake's early innovations was to separate compute from storage. And what that gave them is you could more efficiently scale with unlimited resources when you needed them. And you could shut off the compute when you don't need us. You didn't have to buy, and if you need more storage you didn't have to buy more compute and vice versa. So everybody in the industry has copied that including AWS with Redshift, although as we've reported not as elegantly as Snowflake did. RedShift's more of a storage tiering solution which minimizes the compute required but you can't really shut it off. And there are companies like Vertica with Eon Mode that have enabled this capability to be done On-prem, you know, but of course in that instance you don't have unlimited elastic compute scale on-Prem but with solutions like Dell Apex and HPE GreenLake, you can certainly, you can start to simulate that Cloud elasticity On-prem. I mean, it's not unlimited but it's sort of gets you there. According to a Dell Snowflake joint statement, the companies the quote, the companies will pursue product integrations and joint go to market efforts in the second half of 2022. So that's a little vague and kind of benign. It's not really clear when this is going to be available based on that statement from the two first, but, you know, we're left wondering will Dell develop an On-Prem compute capability and enable queries to run locally maybe as part of an extended apex offering? I mean, we don't know really not sure there's even a market for that but it's probably a good bet that again, Snowflake wants that data to land in the Snowflake data Cloud kind of makes you wonder how this deal came about. You heard Sloop on earlier Snowflake has always been pretty dogmatic about getting data into its native snowflake format to enable the best performance as we talked about but also data sharing and governance. But you could imagine that data architects they're building out their data mesh we've reported on this quite extensively and their data fabric and those visions around that. And they're probably telling Snowflake, Hey if you want to be a strategic partner of ours you're going to have to be more inclusive of our data. That for whatever reason we're not putting in your Cloud. So Snowflake had to kind of hold its nose and capitulate. Now the good news is it further opens up Snowflakes Tam the total available market. It's obviously good marketing posture. And ultimately it provides an on ramp to the Cloud. And we're going to come back to that shortly but let's look a little deeper into what's happening with data platforms and to do that we'll bring in some ETR data. Now, let me just say as companies like Dell, IBM, Cisco, HPE, Lenovo, Pure and others build out their hybrid Clouds. The cold hard fact is not only do they have to replicate the Cloud Operating Model. You will hear them talk about that a lot, but they got to do that. So it, and that's critical from a user experience but in order to gain that flywheel momentum they need to build a robust ecosystem that goes beyond their proprietary portfolios. And, you know, honestly they're really not even in the first inning most companies and for the likes of Snowflake to sort of flip this, they've had to recognize that not everything is moving into the Cloud. Now, let's bring up the next slide. One of the big areas of discussion at Dell Tech World was Apex. That's essentially Dell's nascent as a service offering. Apex is infrastructure as a Service Cloud On-prem and obviously has the vision of connecting to the Cloud and across Clouds and out to the Edge. And it's no secret that database is one of the most important ingredients of infrastructure as a service generally in Cloud Infrastructure specifically. So this chart here shows the ETR data for data platforms inside of Dell accounts. So the beauty of ETR platform is you can cut data a million different ways. So we cut it. We said, okay, give us the Cloud platforms inside Dell accounts, how are they performing? Now, this is a two dimensional graphic. You got net score or spending momentum on the vertical axis and what ETR now calls Overlap formally called Market Share which is a measure of pervasiveness in the survey. That's on the horizontal axis that red dotted line at 40% represents highly elevated spending on the Y. The table insert shows the raw data for how the dots are positioned. Now, the first call out here is Snowflake. According to ETR quote, after 13 straight surveys of astounding net scores, Snowflake has finally broken the trend with its net score dropping below the 70% mark among all respondents. Now, as you know, net score is measured by asking customers are you adding the platform new? That's the lime green in the bar that's pointing from Snowflake in the graph and or are you increasing spend by 6% or more? That's the forest green is spending flat that's the gray is you're spend decreasing by 6% or worse. That's the pinkish or are you decommissioning the platform bright red which is essentially zero for Snowflake subtract the reds from the greens and you get a net score. Now, what's somewhat interesting is that snowflakes net score overall in the survey is 68 which is still huge, just under 70%, but it's net score inside the Dell account base drops to the low sixties. Nonetheless, this chart tells you why Snowflake it's highly elevated spending momentum combined with an increasing presence in the market over the past two years makes it a perfect initial data platform partner for Dell. Now and in the Ford versus Ferrari dynamic. That's going on between the likes of Dell's apex and HPE GreenLake database deals are going to become increasingly important beyond what we're seeing with this recent Snowflake deal. Now noticed by the way HPE is positioned on this graph with its acquisition of map R which is now part of HPE Ezmeral. But if these companies want to be taken seriously as Cloud players, they need to further expand their database affinity to compete ideally spinning up databases as part of their super Clouds. We'll come back to that that span multiple Clouds and include Edge data platforms. We're a long ways off from that. But look, there's Mongo, there's Couchbase, MariaDB, Cloudera or Redis. All of those should be on the short list in my view and why not Microsoft? And what about Oracle? Look, that's to be continued on maybe as a future topic in a, in a Breaking Analysis but I'll leave you with this. There are a lot of people like John Furrier who believe that Dell is playing with fire in the Snowflake deal because he sees it as a one way ticket to the Cloud. He calls it a one way door sometimes listen to what he said this past week. >> I would say that that's a dangerous game because we've seen that movie before, VMware and AWS. >> Yeah, but that we've talked about this don't you think that was the right move for VMware? >> At the time, but if you don't nurture the relationship AWS will take all those customers ultimately from VMware. >> Okay, so what does the data say about what John just said? How is VMware actually doing in Cloud after its early missteps and then its subsequent embracing of AWS and other Clouds. Here's that same XY graphic spending momentum on the Y and pervasiveness on the X and the same table insert that plots the dots and the, in the breakdown of Dell's net score granularity. You see that at the bottom of the chart in those colors. So as usual, you see Azure and AWS up and to the right with Google well behind in a distant third, but still in the mix. So very impressive for Microsoft and AWS to have both that market presence in such elevated spending momentum. But the story here in context is that the VMware Cloud on AWS and VMware's On-Prem Cloud like VMware Cloud Foundation VCF they're doing pretty well in the market. Look, at HPE, gaining some traction in Cloud. And remember, you may not think HPE and Dell and VCF are true Cloud but these are customers answering the survey. So their perspective matters more than the purest view. And the bad news is the Dell Cloud is not setting the world on fire from a momentum standpoint on the vertical axis but it's above the line of zero and compared to Dell's overall net score of 20 you could see it's got some work to do. Okay, so overall Dell's got a pretty solid net score to you know, positive 20, as I say their Cloud perception needs to improve. Look, Apex has to be the Dell Cloud brand not Dell reselling VMware. And that requires more maturity of Apex it's feature sets, its selling partners, its compensation models and it's ecosystem. And I think Dell clearly understands that. I think they're pretty open about that. Now this includes partners that go beyond being just sellers has to include more tech offerings in the marketplace. And actually they got to build out a marketplace like Cloud Platform. So they got a lot of work to do there. And look, you've got Oracle coming up. I mean they're actually kind of just below the magic 40% in the line which is pro it's pretty impressive. And we've been telling you for years, you can hate Oracle all you want. You can hate its price, it's closed system all of that it's red stack shore. You can say it's legacy. You can say it's old and outdated, blah, blah, blah. You can say Oracle is irrelevant in trouble. You are dead wrong. When it comes to mission critical workloads. Oracle is the king of the hill. They're a founder led company that knows exactly what it's doing and they're showing Cloud momentum. Okay, the last point is that while Microsoft AWS and Google have major presence as shown on the X axis. VMware and Oracle now have more than a hundred citations in the survey. You can see that on the insert in the right hand, right most column. And IBM had better keep the momentum from last quarter going, or it won't be long before they get passed by Dell and HP in Cloud. So look, John might be right. And I would think Snowflake quietly agrees that this Dell deal is all about access to Dell's customers and their data. So they can Hoover it into the Snowflake Data Cloud but the data right now, anyway doesn't suggest that's happening with VMware. Oh, by the way, we're keeping an eye close eye on NetApp who last September ink, a similar deal to VMware Cloud on AWS to see how that fares. Okay, let's wrap with some closing thoughts on what this deal means. We learned a lot from the Cloud generally in AWS, specifically in two pizza teams, working backwards, customer obsession. We talk about flywheel all the time and we've been talking today about marketplaces. These have all become common parlance and often fundamental narratives within strategic plans investor decks and customer presentations. Cloud ecosystems are different. They take both competition and partnerships to new heights. You know, when I look at Azure service offerings like Apex, GreenLake and similar services and I see the vendor noise or hear the vendor noise that's being made around them. I kind of shake my head and ask, you know which movie were these companies watching last decade? I really wish we would've seen these initiatives start to roll out in 2015, three years before AWS announced Outposts not three years after but Hey, the good news is that not only was Outposts a wake up call for the On-Prem crowd but it's showing how difficult it is to build a platform like Outposts and bring it to On-Premises. I mean, Outpost isn't currently even a rounding era in the marketplace. It really doesn't do much in terms of database support and support of other services. And, you know, it's unclear where that that is going. And I don't think it has much momentum. And so the Hybrid Cloud Vendors they've had time to figure it out. But now it's game on, companies like Dell they're promising a consistent experience between On-Prem into the Cloud, across Clouds and out to the Edge. They call it MultCloud which by the way my view has really been multi-vendor Chuck, Chuck Whitten. Who's the new co-COO of Dell called it Multi-Cloud by default. (laughing) That's really, I think an accurate description of that. I call this new world Super Cloud. To me, it's different than MultiCloud. It's a layer that runs on top of hyperscale infrastructure kind of hides the underlying complexity of the Cloud. It's APIs, it's primitives. And it stretches not only across Clouds but out to the Edge. That's a big vision and that's going to require some seriously intense engineering to build out. It's also going to require partnerships that go beyond the portfolios of companies like Dell like their own proprietary stacks if you will. It's going to have to replicate the Cloud Operating Model and to do that, you're going to need more and more deals like Snowflake and even deeper than Snowflake, not just in database. Sure, you'll need to have a catalog of databases that run in your On-Prem and Hybrid and Super Cloud but also other services that customers can tap. I mean, can you imagine a day when Dell offers and embraces a directly competitive service inside of apex. I have trouble envisioning that, you know not with their historical posture, you think about companies like, you know, Nutanix, you know, or Cisco where they really, you know those relationships cooled quite quickly but you know, look, think about it. That's what AWS does. It offers for instance, Redshift and Snowflake side by side happily and the Redshift guys they probably hate Snowflake. I wouldn't blame them, but the EC Two Folks, they love them. And Adam SloopesKy understands that ISVs like Snowflake are a key part of the Cloud ecosystem. Again, I have a hard time envisioning that occurring with Dell or even HPE, you know maybe less so with HPE, but what does this imply that the Edge will allow companies like Dell to a reach around on the Cloud and somehow create a new type of model that begrudgingly accommodates the Public Cloud but drafts of the new momentum of the Edge, which right now to these companies is kind of mostly telco and retail. It's hard to see that happening. I think it's got to evolve in a more comprehensive and inclusive fashion. What's much more likely is companies like Dell are going to substantially replicate that Cloud Operating Model for the pieces that they own pieces that they control which admittedly are big pieces of the market. But unless they're able to really tap that ecosystem magic they're not going to be able to grow much beyond their existing install bases. You take that lime green we showed you earlier that new adoption metric from ETR as an example, by my estimates, AWS and Azure are capturing new accounts at a rate between three to five times faster than Dell and HPE. And in the more mature US and mere markets it's probably more like 10 X and a major reason is because of the Cloud's robust ecosystem and the optionality and simplicity of transaction that that is bringing to customers. Now, Dell for its part is a hundred billion dollar revenue company. And it has the capability to drive that kind of dynamic. If it can pivot its partner ecosystem mindset from kind of resellers to Cloud services and technology optionality. Okay, that's it for now? Thanks to my colleagues, Stephanie Chan who helped research topics for Breaking Analysis. Alex Myerson is on the production team. Kristen Martin and Cheryl Knight and Rob Hof, on editorial they helped get the word out and thanks to Jordan Anderson for the new Breaking Analysis branding and graphics package. Remember these episodes are all available as podcasts wherever you listen. All you do is search Breaking Analysis podcasts. You could check out ETR website @etr.ai. We publish a full report every week on wikibon.com and siliconangle.com. You want to get in touch. @dave.vellente @siliconangle.com. You can DM me @dvellante. You can make a 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. (upbeat music)

>> From the theCUBE studios in Palo Alto, in Boston, bringing you data-driven insights from theCUBE and ETR. This is "Breaking Analysis", with Dave Vellante. >> The recent security breach of an Okta third party supplier has been widely reported. The criticisms of Okta's response have been harsh, and the impact on Okta's value has been obvious, investors shaved about $6 billion off the company's market cap during the week the hack was made public. We believe Okta's claim that the customer technical impact was, "Near zero," may be semantically correct. However, based on customer data, we feel Okta has a blind spot. There are customer ripple effects that require clear action which are missed in Okta's public statements, in our view. Okta's product portfolio remains solid, it's a clear leader in the identity space. But in our view, one part of the long journey back to credibility requires Okta to fully understand and recognize the true scope of this breach on its customers. Hello, and welcome to this week's Wikibon "CUBE Insights", powered by ETR. In this "Breaking Analysis", we welcome our ETR colleague, Erik Bradley, to share new data from the community. Erik, welcome. >> Thank you, Dave, always enjoy being on the show, particularly when we get to talk about a topic that's not being well covered in the mainstream media in my opinion. >> Yeah, I agree, you've got some new data, and we're going to share some of that today. Let's first review the timeline of this hack. On January 20th this year, Okta got an alert that something was amiss at one of its partners, a company called Sitel, that provides low-level contact center support for Okta. The next day, Sitel retained a forensic firm to investigate, which was completed, that investigation was completed on February 28th. A report dated March 10th was created, and Okta received a summary of that from Sitel on March 17th. Five days later, Lapsus$ posted the infamous screenshots on Twitter. And later that day, sheesh, Okta got the full report from Sitel, and then responded publicly. Then the media frenzy in the back and forth ensued. So Erik, you know, there's so much wrong with this timeline, it's been picked apart by the media. But I will say this, what appeared to be a benign incident and generally has turned into a PR disaster for Okta, and I imagine Sitel as well. Who I reached out to by the way, but they did not provide a comment, whereas Okta did. We'll share that later. I mean, where do we start on this, Erik? >> It's a great question, "Where do we start?" As you know, our motto here is opinions only exist due to a lack of data, so I'm going to start with the data. What we were able to do is because we had a survey that was in the field when the news broke, is that we were able to observe the data in realtime. So we sequestered the data up until that moment when it was announced, so before March 23rd and then after March 23rd. And although most of the responses came in prior, so it wasn't as much of an end as we would've liked. It really was telling to see the difference of how the survey responses changed from before the breach was announced to after, and we can get into a little bit more- >> So let's... Sorry, sorry to interrupt, let's bring that up, let's look at some of that data. And as followers of this program know... Let me just set it up, Erik. Every quarter, ETR, they have a proprietary net score methodology to determine customer spending momentum, and that's what we're talking about here. Essentially measuring the net number of customers spending more on a particular product or platform. So apologize for interrupting, but you're on this data right here. >> Not at all. >> So take us through this. >> Yeah, so again, let's caveat. Okta is still a premier company in our work. Top five in overall security, not just in their niche, and they still remained extremely strong at the end of the survey. However, when you kind of look at that at a more of a micro analysis, what you noticed was a true difference between before March 23rd and after. Overall, their cumulative net score or proprietary spending intention score that we use, was 56% prior. That dropped to 44% during the time period after, that is a significant drop. Even a little bit more telling, and again, small sample size, I want to be very fair about that. Before March 23rd, only three of our community members indicated any indication of replacing Okta. That number went to eight afterwards. So again, small number, but a big difference when you're talking about a percentage change. >> Yeah, so that's that sort of green line that was shown there. You know, not too damaging, but definitely a noticeable downturn with the caveat that it's a small end. But here's the thing that I love working with you, we didn't stop there. You went out, you talked to customers, I talked to a number of customers. You actually organized a panel. This week, Erik hosted a deep dive on the topic with CISOs. And we have, if we could bring up that next slide, Alex. These are some of the top CISOs in the community, and I'm going to just summarize the comments and then turn it over to you, Erik. The first one was really concerning, "We heard about this in the media," ooh, ooh, ouch. Next one, "Not a huge hit, but loss of trust." "We can't just shut Okta off like SolarWinds." So there's definitely a lock in effect there. "We may need to hire new people," i.e, "There's a business impact to us beyond the technical impact." "We're rethinking contract negotiations with Okta." And bottom line, "It's still a strong solution." "We're not really worried about our Okta environment, but this is a trust and communications issue." Erik, these are painful to read, and in the end of the day, Okta has to own this. Todd McKinnon did acknowledge this. As I said at the top, there are domino business impacts that Okta may not be seeing. What are your thoughts? >> There's a lot we're going to need to get into in a little bit, and I think you were spot on earlier, when McKinnon said there was no impact. And that's not actually true, there's a lot of peripheral, derivative impact that was brought up in our panel. Before we even did the panel though, I do want to say we went out quickly to about 20 customers and asked them if they were willing to give an opinion. And it was sort of split down the middle where about, you know, half of them were saying, "You know, this is okay. We're going to stand by 'em, Okta's the best in the industry." A few were cautious, "Opinion's unchanged, but we're going to take a look deeper." And then another 40% were just flat out negative. And again, small sample size, but you don't want to see that. It's indicative of reputational damage right away. That was what led us to say, "You know what, let's go do this panel." And as you know, from reading it and looking at the panel, well, a lot of topics were brought up about the derivative impact of it. And whether that's your own, you know, having to hire people to go look into your backend to deal with and manage Okta. Whether it's cyber insurance ramifications down the road, there's a lot of aspects that need to be discussed about this. >> Yeah now, so before I go on... And by the way, I've spent a fair amount of time just parsing, listening very carefully to Todd McKinnon's commentary. He did an interview with Emily Chang, it was quite useful. But before I go on, I reached out to Okta, and they were super responsive and I appreciate that. And I do believe they're taking this seriously, here's a statement they provided to theCUBE. Quote, "As a global leader in identity, we recognize the critical role Okta plays for our customers and our customers' end users. Okta has a culture of learning and improving, and we are taking the steps to prevent this from happening again. We know trust is earned, and building back our customers' trust in Okta through our actions and our ongoing support as their secure identity partner is our top priority." Okay, so look, you know, what are you going to say, right? I mean, I think they do own it. Again, the concern is the blind spots. So we put together this visual to try to explain how Okta is describing the impact, and maybe another way to look at it. So let me walk you through this. Here's a simple way in which organizations think about the impact of a breach. What's the probability of a breach, that's the vertical axis, and what's the impact on the horizontal. Now I feel as though business impact really is the financial, you know, condition. But we've narrowed this to map to Todd McKinnon's statements of the technical impact. And they've said the technical impact in terms of things customers need to do or change, is near zero, and that's the red dot that you see there. Look, the fact is, that Okta has more than 15,000 customers, and at most, 366 were directly impacted by this. That's less than 3% of the base, and it's probably less than that, they're just being conservative. And the technical impact which Todd McKinnon described in an interview, again, with Emily Chang, was near zero in terms of actions the customers had to take on things like reporting and changes and remediation. Basically negligible. But based on the customer feedback outside of that 366, that's what we're calling that blind spot and that bracket. And then we list the items that we are hearing from customers on things that they have to do now, despite that minimal exposure. Erik, this is new information that we've uncovered through the ETR process, and there's a long list of collateral impacts that you just referred to before, actions that customers have to take, right? >> Yeah, there's a lot, and the panel really brought that to life even more than I expected to be quite honest. First of all, you're right, most of them believe that this was a minimal impact. The true damage here was reputational, and the derivatives that come from it. We had one panelist say that they now have to go hire people, because, and I hate to say this, but Okta isn't known for their best professional support. So they have to go get people now in to kind of do that themselves and manage that. That's obviously not the easiest thing to do in this environment. We had other ones express concern about, "Hey I'm an Okta customer. When I have to do my cyber insurance renewal, is my policy going to go up? Is my premium going to go up?" And it's not something that they even want to have to handle, but they do. There were a lot of concerns. One particular person didn't think the impact was minimal, and I just think it's worth bringing up. There was no demand for ransom here. So there were only two and a half percent of Okta customers that were hit, but we don't know what the second play is, right, this could just be stage one. And I think that there was one particular person on the panel who truly believes that, that could be the case, that this was just the first step. And in his opinion, there wasn't anything specific about those 366 customers that made him feel like the bad actor was targeting them. So he does believe that this might be a step one of a step two situation. Now that's a, you know, bit of an alarmist opinion and the rest of the panel didn't really echo it, but it is something that's kind of worth bringing up out there. >> Well, you know, it just pays to be paranoid. I mean, you know, it was reported that supposedly, this hack was done by a 16-year-old in England, out of his, you know, mother's house, but who knows? You know, other actors might have paid that individual to see what they could do. It could have been a little bit of reconnaissance, throw the pawn in there and see how, you know, what the response is like. So I want to parse some of Todd McKinnon's statements from that Bloomberg interview. Look, we've always, you and I both have been impressed with Okta, and Todd McKinnon's management. His decisions, execution, leadership, super impressive individual. You know, big fans of the company. And in the interview, it looked like (chuckles) the guy hadn't slept in three weeks, so really you have to feel for him. But I think there are some statements that have to be unpacked. The first one, McKinnon took responsibility and talked about how they'll be transparent about steps they're taking in the future to avoid you know, similar problems. We talked about the near-zero technical impact, we don't need to go there anymore. But Erik, the two things that struck me as communication misfires were the last two. Especially the penultimate statement there, quote, "The competitor product was at fault for this breach." You know, by the way, I believe this to be true. Evidently, Sitel was not using Okta as its identity access platform. You know, we're all trying to figure out who that is. I can tell you it definitely was not CyberArk, we're still digging to find out who. But you know, you can't say in my view, "We are taking responsibility," and then later say it was the competitor's fault. And I know that's not what he meant, but that's kind of how it came across. And even if it's true, you just don't say that later in a conversation after saying that, "We own it." Now on the last point, love your thoughts on this, Erik? My first reaction was Okta's throwing Sitel under the bus. You know, Okta's asking for forgiveness from its customers, but it just shot its partner, and I kind of get it. This shows that they're taking action but I would've preferred something like, "Look, we've suspended our use of Sitel for the time being pending a more detailed review. We've shut down that relationship to block any exposures. Our focus right now is on customers, and we'll take a look at that down the road." But I have to say in looking at the timeline, it looks like Sitel did hide the ball a little bit, and so you can't blame 'em. And you know, what are your thoughts on that? >> Well, I'll go back to my panelists again, who unanimously agreed this was a masterclass on how not to handle crisis management. And I do feel for 'em, they're a fantastic management team. The acquisition of Auth0 alone, was just such a brilliant move that you have to kind of wonder what went wrong here, they clearly were blindsided. I agree with you that Sitel was not forthcoming quickly enough, and I have a feeling that, that's what got them in this position, in a bad PR. However, you can't go ahead and fire your partner and then turn around and ask other people not to fire you. Particularly until a very thorough investigation and a root cause analysis has been released to everyone. And the customers that I have spoken to don't believe that, that is done yet. Now, when I ask them directly, "Would you consider leaving Okta?" Their answers were, "No, it is not easy to rip and replace, and we're not done doing our due diligence." So it's interesting that Okta's customers are giving them that benefit of the doubt, but we haven't seen it, you know, flow the other way with Okta's partner. >> Yeah, and that's why I would've preferred a different public posture, because who knows? I mean, is Sitel the only partner that's not using Okta as its identity management, who knows? I'd like to learn more about that. And to your point, you know, maybe Okta's got to vertically integrate here and start, you know, supporting the lower level stuff directly itself, you know, and/or tightening up those partnerships. Now of course, the impact on Okta obviously has been really serious, big hit on the stock. You know, they're piling on inflation and quantitative tightening and rate hikes. But the real damage, as we've said, is trust and reputation, which Okta has earned, and now it has to work hard to earn back. And it's unfortunate. Look, Okta was founded in 2009 and in over a decade, you know, by my count, there have been no major incidents that are obvious. And we've seen the damage that hackers can do by going after the digital supply chain and third and fourth party providers. You know, rules on disclosure is still not tight and that maybe is part of the problem here. Perhaps the new law The House just sent over to President Biden, is going to help. But the point, Erik, is Okta is not alone here. It feels like they got what looked like a benign alert. Sitel wasn't fully transparent, and Okta is kind of fumbling on the comms, which creates this spiraling effect. Look, we're going to have to wait for the real near-term and midterm impacts, but longterm, I personally believe Okta is going to be fine. But they're going to have to sacrifice some margin possibly in the near to midterm, and go through more pain to regain the loyalty of its customers. And I really would like to hear from Okta that they understand that customers, the impact of this breach to customers, actually does go beyond the 366 that were possibly compromised. Erik, I'll give you the final word. >> Yeah, there's a couple of things there if I can have a moment, and yes, Okta... Well, there was a great quote, one of the guys said, "Okta's built like a tank, but they just gave the keys to a 16 year old valet." So he said, "There is some concern here." But yes, they are best of breed, they are the leader, but there is some concern. And every one of the guys I spoke to, all CISOs, said, "This is going to come up at renewal time. At a minimum, this is leverage. I have to ask them to audit their third parties and their partners. I have to bring this up when it comes time." And then the other one that's a little bit of a concern is data-wise. We saw Ping Identity jump big, from 9% net score to 24% net score. Don't know if it's causative or correlated, but it did happen. Another thing to be concerned about out there, is Microsoft is making absolutely massive strides in security. And all four of the panelists said, "Hey, I've got an E5 license, why don't I get the most out of it? I'm at least going to look." So for Okta to say, you know, "Hey, there's no impact here," it's just not true, there is an impact, they're saying what they need to say. But there's more to this, you know, their market cap definitely got hit. But you know, I think over time if the market stabilized, we could see that recover. It's a great management team, but they did just open the door for a big, big player like Microsoft. And you and I also both know that there's a lot of emerging names out there too, that would like to, you know, take a little bit of that share. >> And you know, but here's the thing, I want to keep going here for a minute. Microsoft got hit by lapses, Nvidia got hit by lapses. But I think, Erik, I feel like people, "Oh yeah, Microsoft, they get hit all the time." They're kind of used to it with Microsoft, right? So that's why I'm saying, it's really interesting here. Customers want to consolidate their security portfolio and the number of tools that they have, you know. But then you look at something like this and you say, "Okay, we're narrowing the blast radius. You know, maybe we have to rethink that and that creates more complexity," and so it's a very complicated situation. But you know, your point about Microsoft is ironic, right. Because you know, when you see Microsoft, Amazon, you know, customers get hit all the time and it's oftentimes the fault of the customer, or the partner. And so it seems like, again, coming back to the comms of this, is that really is the one thing that they just didn't get right. >> Yeah, the biggest takeaway from this without a doubt is it's not the impact of the breach, it was the impact of their delay and how they handled it and how they managed it. That's through the course of 25 CISOs I've spoken to now, that's unanimous. It's not about that this was a huge damaging hit, but the damage really came from their reaction or lack thereof. >> Yeah, and it's unfortunate, 'cause it feels like a lot of it was sort of, I want to say out of their control because obviously they could have audited the partners. But still, I feel like they got thrown a curve ball that they really had a, you know, difficult time, you know, parsing through that. All right, hey, we got to leave it there for now. Thank you, Erik Bradley, appreciate you coming on, It's always a pleasure to have you >> Always good talking to you too, Dave, thanks a lot. >> ETR team, you guys are amazing, do some great work. I want to thank Stephanie Chan, who helps me with background research for "Breaking Analysis". Kristen Martin and Cheryl Knight, help get the word out, as do some others. Alex Myerson on production, Alex, thank you. And Rob Hof, is our EIC at SiliconANGLE. Remember, all these episodes, they are available as podcasts. Wherever you listen, just search, "Breaking Analysis podcast." I publish each week on wikibon.com and siliconangle.com. Check out etr.ai, it's the best in the business for real customer data real-time, near real-time, awesome platform. You can reach out to me at david.vellante@siliconangle.com, or @DVellante, or comment on my LinkedIn post. This is Dave Vellante, for Erik Bradley, and "theCUBE Insights", powered by ETR. Thanks for watching, be well, and we'll see you next time. (bright music)