(upbeat music beginning) >> From the Cube Studios in Palo Alto and Boston, bringing you data-driven insights from the Cube and ETR, this is "Breaking Analysis" with Dave Vellante. >> Making predictions about the future of enterprise tech is more challenging if you strive to lay down forecasts that are measurable. In other words, if you make a prediction, you should be able to look back a year later and say, with some degree of certainty, whether the prediction came true or not, with evidence to back that up. Hello and welcome to this week's Wikibon Cube Insights, powered by ETR. In this breaking analysis, we aim to do just that, with predictions about the macro IT spending environment, cost optimization, security, lots to talk about there, generative AI, cloud, and of course supercloud, blockchain adoption, data platforms, including commentary on Databricks, snowflake, and other key players, automation, events, and we may even have some bonus predictions around quantum computing, and perhaps some other areas. To make all this happen, we welcome back, for the third year in a row, my colleague and friend Eric Bradley from ETR. Eric, thanks for all you do for the community, and thanks for being part of this program. Again. >> I wouldn't miss it for the world. I always enjoy this one. Dave, good to see you. >> Yeah, so let me bring up this next slide and show you, actually come back to me if you would. I got to show the audience this. These are the inbounds that we got from PR firms starting in October around predictions. They know we do prediction posts. And so they'll send literally thousands and thousands of predictions from hundreds of experts in the industry, technologists, consultants, et cetera. And if you bring up the slide I can show you sort of the pattern that developed here. 40% of these thousands of predictions were from cyber. You had AI and data. If you combine those, it's still not close to cyber. Cost optimization was a big thing. Of course, cloud, some on DevOps, and software. Digital... Digital transformation got, you know, some lip service and SaaS. And then there was other, it's kind of around 2%. So quite remarkable, when you think about the focus on cyber, Eric. >> Yeah, there's two reasons why I think it makes sense, though. One, the cybersecurity companies have a lot of cash, so therefore the PR firms might be working a little bit harder for them than some of their other clients. (laughs) And then secondly, as you know, for multiple years now, when we do our macro survey, we ask, "What's your number one spending priority?" And again, it's security. It just isn't going anywhere. It just stays at the top. So I'm actually not that surprised by that little pie chart there, but I was shocked that SaaS was only 5%. You know, going back 10 years ago, that would've been the only thing anyone was talking about. >> Yeah. So true. All right, let's get into it. First prediction, we always start with kind of tech spending. Number one is tech spending increases between four and 5%. ETR has currently got it at 4.6% coming into 2023. This has been a consistently downward trend all year. We started, you know, much, much higher as we've been reporting. Bottom line is the fed is still in control. They're going to ease up on tightening, is the expectation, they're going to shoot for a soft landing. But you know, my feeling is this slingshot economy is going to continue, and it's going to continue to confound, whether it's supply chains or spending. The, the interesting thing about the ETR data, Eric, and I want you to comment on this, the largest companies are the most aggressive to cut. They're laying off, smaller firms are spending faster. They're actually growing at a much larger, faster rate as are companies in EMEA. And that's a surprise. That's outpacing the US and APAC. Chime in on this, Eric. >> Yeah, I was surprised on all of that. First on the higher level spending, we are definitely seeing it coming down, but the interesting thing here is headlines are making it worse. The huge research shop recently said 0% growth. We're coming in at 4.6%. And just so everyone knows, this is not us guessing, we asked 1,525 IT decision-makers what their budget growth will be, and they came in at 4.6%. Now there's a huge disparity, as you mentioned. The Fortune 500, global 2000, barely at 2% growth, but small, it's at 7%. So we're at a situation right now where the smaller companies are still playing a little bit of catch up on digital transformation, and they're spending money. The largest companies that have the most to lose from a recession are being more trepidatious, obviously. So they're playing a "Wait and see." And I hope we don't talk ourselves into a recession. Certainly the headlines and some of their research shops are helping it along. But another interesting comment here is, you know, energy and utilities used to be called an orphan and widow stock group, right? They are spending more than anyone, more than financials insurance, more than retail consumer. So right now it's being driven by mid, small, and energy and utilities. They're all spending like gangbusters, like nothing's happening. And it's the rest of everyone else that's being very cautious. >> Yeah, so very unpredictable right now. All right, let's go to number two. Cost optimization remains a major theme in 2023. We've been reporting on this. You've, we've shown a chart here. What's the primary method that your organization plans to use? You asked this question of those individuals that cited that they were going to reduce their spend and- >> Mhm. >> consolidating redundant vendors, you know, still leads the way, you know, far behind, cloud optimization is second, but it, but cloud continues to outpace legacy on-prem spending, no doubt. Somebody, it was, the guy's name was Alexander Feiglstorfer from Storyblok, sent in a prediction, said "All in one becomes extinct." Now, generally I would say I disagree with that because, you know, as we know over the years, suites tend to win out over, you know, individual, you know, point products. But I think what's going to happen is all in one is going to remain the norm for these larger companies that are cutting back. They want to consolidate redundant vendors, and the smaller companies are going to stick with that best of breed and be more aggressive and try to compete more effectively. What's your take on that? >> Yeah, I'm seeing much more consolidation in vendors, but also consolidation in functionality. We're seeing people building out new functionality, whether it's, we're going to talk about this later, so I don't want to steal too much of our thunder right now, but data and security also, we're seeing a functionality creep. So I think there's further consolidation happening here. I think niche solutions are going to be less likely, and platform solutions are going to be more likely in a spending environment where you want to reduce your vendors. You want to have one bill to pay, not 10. Another thing on this slide, real quick if I can before I move on, is we had a bunch of people write in and some of the answer options that aren't on this graph but did get cited a lot, unfortunately, is the obvious reduction in staff, hiring freezes, and delaying hardware, were three of the top write-ins. And another one was offshore outsourcing. So in addition to what we're seeing here, there were a lot of write-in options, and I just thought it would be important to state that, but essentially the cost optimization is by and far the highest one, and it's growing. So it's actually increased in our citations over the last year. >> And yeah, specifically consolidating redundant vendors. And so I actually thank you for bringing that other up, 'cause I had asked you, Eric, is there any evidence that repatriation is going on and we don't see it in the numbers, we don't see it even in the other, there was, I think very little or no mention of cloud repatriation, even though it might be happening in this in a smattering. >> Not a single mention, not one single mention. I went through it for you. Yep. Not one write-in. >> All right, let's move on. Number three, security leads M&A in 2023. Now you might say, "Oh, well that's a layup," but let me set this up Eric, because I didn't really do a great job with the slide. I hid the, what you've done, because you basically took, this is from the emerging technology survey with 1,181 responses from November. And what we did is we took Palo Alto and looked at the overlap in Palo Alto Networks accounts with these vendors that were showing on this chart. And Eric, I'm going to ask you to explain why we put a circle around OneTrust, but let me just set it up, and then have you comment on the slide and take, give us more detail. We're seeing private company valuations are off, you know, 10 to 40%. We saw a sneak, do a down round, but pretty good actually only down 12%. We've seen much higher down rounds. Palo Alto Networks we think is going to get busy. Again, they're an inquisitive company, they've been sort of quiet lately, and we think CrowdStrike, Cisco, Microsoft, Zscaler, we're predicting all of those will make some acquisitions and we're thinking that the targets are somewhere in this mess of security taxonomy. Other thing we're predicting AI meets cyber big time in 2023, we're going to probably going to see some acquisitions of those companies that are leaning into AI. We've seen some of that with Palo Alto. And then, you know, your comment to me, Eric, was "The RSA conference is going to be insane, hopping mad, "crazy this April," (Eric laughing) but give us your take on this data, and why the red circle around OneTrust? Take us back to that slide if you would, Alex. >> Sure. There's a few things here. First, let me explain what we're looking at. So because we separate the public companies and the private companies into two separate surveys, this allows us the ability to cross-reference that data. So what we're doing here is in our public survey, the tesis, everyone who cited some spending with Palo Alto, meaning they're a Palo Alto customer, we then cross-reference that with the private tech companies. Who also are they spending with? So what you're seeing here is an overlap. These companies that we have circled are doing the best in Palo Alto's accounts. Now, Palo Alto went and bought Twistlock a few years ago, which this data slide predicted, to be quite honest. And so I don't know if they necessarily are going to go after Snyk. Snyk, sorry. They already have something in that space. What they do need, however, is more on the authentication space. So I'm looking at OneTrust, with a 45% overlap in their overall net sentiment. That is a company that's already existing in their accounts and could be very synergistic to them. BeyondTrust as well, authentication identity. This is something that Palo needs to do to move more down that zero trust path. Now why did I pick Palo first? Because usually they're very inquisitive. They've been a little quiet lately. Secondly, if you look at the backdrop in the markets, the IPO freeze isn't going to last forever. Sooner or later, the IPO markets are going to open up, and some of these private companies are going to tap into public equity. In the meantime, however, cash funding on the private side is drying up. If they need another round, they're not going to get it, and they're certainly not going to get it at the valuations they were getting. So we're seeing valuations maybe come down where they're a touch more attractive, and Palo knows this isn't going to last forever. Cisco knows that, CrowdStrike, Zscaler, all these companies that are trying to make a push to become that vendor that you're consolidating in, around, they have a chance now, they have a window where they need to go make some acquisitions. And that's why I believe leading up to RSA, we're going to see some movement. I think it's going to pretty, a really exciting time in security right now. >> Awesome. Thank you. Great explanation. All right, let's go on the next one. Number four is, it relates to security. Let's stay there. Zero trust moves from hype to reality in 2023. Now again, you might say, "Oh yeah, that's a layup." A lot of these inbounds that we got are very, you know, kind of self-serving, but we always try to put some meat in the bone. So first thing we do is we pull out some commentary from, Eric, your roundtable, your insights roundtable. And we have a CISO from a global hospitality firm says, "For me that's the highest priority." He's talking about zero trust because it's the best ROI, it's the most forward-looking, and it enables a lot of the business transformation activities that we want to do. CISOs tell me that they actually can drive forward transformation projects that have zero trust, and because they can accelerate them, because they don't have to go through the hurdle of, you know, getting, making sure that it's secure. Second comment, zero trust closes that last mile where once you're authenticated, they open up the resource to you in a zero trust way. That's a CISO of a, and a managing director of a cyber risk services enterprise. Your thoughts on this? >> I can be here all day, so I'm going to try to be quick on this one. This is not a fluff piece on this one. There's a couple of other reasons this is happening. One, the board finally gets it. Zero trust at first was just a marketing hype term. Now the board understands it, and that's why CISOs are able to push through it. And what they finally did was redefine what it means. Zero trust simply means moving away from hardware security, moving towards software-defined security, with authentication as its base. The board finally gets that, and now they understand that this is necessary and it's being moved forward. The other reason it's happening now is hybrid work is here to stay. We weren't really sure at first, large companies were still trying to push people back to the office, and it's going to happen. The pendulum will swing back, but hybrid work's not going anywhere. By basically on our own data, we're seeing that 69% of companies expect remote and hybrid to be permanent, with only 30% permanent in office. Zero trust works for a hybrid environment. So all of that is the reason why this is happening right now. And going back to our previous prediction, this is why we're picking Palo, this is why we're picking Zscaler to make these acquisitions. Palo Alto needs to be better on the authentication side, and so does Zscaler. They're both fantastic on zero trust network access, but they need the authentication software defined aspect, and that's why we think this is going to happen. One last thing, in that CISO round table, I also had somebody say, "Listen, Zscaler is incredible. "They're doing incredibly well pervading the enterprise, "but their pricing's getting a little high," and they actually think Palo Alto is well-suited to start taking some of that share, if Palo can make one move. >> Yeah, Palo Alto's consolidation story is very strong. Here's my question and challenge. Do you and me, so I'm always hardcore about, okay, you've got to have evidence. I want to look back at these things a year from now and say, "Did we get it right? Yes or no?" If we got it wrong, we'll tell you we got it wrong. So how are we going to measure this? I'd say a couple things, and you can chime in. One is just the number of vendors talking about it. That's, but the marketing always leads the reality. So the second part of that is we got to get evidence from the buying community. Can you help us with that? >> (laughs) Luckily, that's what I do. I have a data company that asks thousands of IT decision-makers what they're adopting and what they're increasing spend on, as well as what they're decreasing spend on and what they're replacing. So I have snapshots in time over the last 11 years where I can go ahead and compare and contrast whether this adoption is happening or not. So come back to me in 12 months and I'll let you know. >> Now, you know, I will. Okay, let's bring up the next one. Number five, generative AI hits where the Metaverse missed. Of course everybody's talking about ChatGPT, we just wrote last week in a breaking analysis with John Furrier and Sarjeet Joha our take on that. We think 2023 does mark a pivot point as natural language processing really infiltrates enterprise tech just as Amazon turned the data center into an API. We think going forward, you're going to be interacting with technology through natural language, through English commands or other, you know, foreign language commands, and investors are lining up, all the VCs are getting excited about creating something competitive to ChatGPT, according to (indistinct) a hundred million dollars gets you a seat at the table, gets you into the game. (laughing) That's before you have to start doing promotion. But he thinks that's what it takes to actually create a clone or something equivalent. We've seen stuff from, you know, the head of Facebook's, you know, AI saying, "Oh, it's really not that sophisticated, ChatGPT, "it's kind of like IBM Watson, it's great engineering, "but you know, we've got more advanced technology." We know Google's working on some really interesting stuff. But here's the thing. ETR just launched this survey for the February survey. It's in the field now. We circle open AI in this category. They weren't even in the survey, Eric, last quarter. So 52% of the ETR survey respondents indicated a positive sentiment toward open AI. I added up all the sort of different bars, we could double click on that. And then I got this inbound from Scott Stevenson of Deep Graham. He said "AI is recession-proof." I don't know if that's the case, but it's a good quote. So bring this back up and take us through this. Explain this chart for us, if you would. >> First of all, I like Scott's quote better than the Facebook one. I think that's some sour grapes. Meta just spent an insane amount of money on the Metaverse and that's a dud. Microsoft just spent money on open AI and it is hot, undoubtedly hot. We've only been in the field with our current ETS survey for a week. So my caveat is it's preliminary data, but I don't care if it's preliminary data. (laughing) We're getting a sneak peek here at what is the number one net sentiment and mindshare leader in the entire machine-learning AI sector within a week. It's beating Data- >> 600. 600 in. >> It's beating Databricks. And we all know Databricks is a huge established enterprise company, not only in machine-learning AI, but it's in the top 10 in the entire survey. We have over 400 vendors in this survey. It's number eight overall, already. In a week. This is not hype. This is real. And I could go on the NLP stuff for a while. Not only here are we seeing it in open AI and machine-learning and AI, but we're seeing NLP in security. It's huge in email security. It's completely transforming that area. It's one of the reasons I thought Palo might take Abnormal out. They're doing such a great job with NLP in this email side, and also in the data prep tools. NLP is going to take out data prep tools. If we have time, I'll discuss that later. But yeah, this is, to me this is a no-brainer, and we're already seeing it in the data. >> Yeah, John Furrier called, you know, the ChatGPT introduction. He said it reminded him of the Netscape moment, when we all first saw Netscape Navigator and went, "Wow, it really could be transformative." All right, number six, the cloud expands to supercloud as edge computing accelerates and CloudFlare is a big winner in 2023. We've reported obviously on cloud, multi-cloud, supercloud and CloudFlare, basically saying what multi-cloud should have been. We pulled this quote from Atif Kahn, who is the founder and CTO of Alkira, thanks, one of the inbounds, thank you. "In 2023, highly distributed IT environments "will become more the norm "as organizations increasingly deploy hybrid cloud, "multi-cloud and edge settings..." Eric, from one of your round tables, "If my sources from edge computing are coming "from the cloud, that means I have my workloads "running in the cloud. "There is no one better than CloudFlare," That's a senior director of IT architecture at a huge financial firm. And then your analysis shows CloudFlare really growing in pervasion, that sort of market presence in the dataset, dramatically, to near 20%, leading, I think you had told me that they're even ahead of Google Cloud in terms of momentum right now. >> That was probably the biggest shock to me in our January 2023 tesis, which covers the public companies in the cloud computing sector. CloudFlare has now overtaken GCP in overall spending, and I was shocked by that. It's already extremely pervasive in networking, of course, for the edge networking side, and also in security. This is the number one leader in SaaSi, web access firewall, DDoS, bot protection, by your definition of supercloud, which we just did a couple of weeks ago, and I really enjoyed that by the way Dave, I think CloudFlare is the one that fits your definition best, because it's bringing all of these aspects together, and most importantly, it's cloud agnostic. It does not need to rely on Azure or AWS to do this. It has its own cloud. So I just think it's, when we look at your definition of supercloud, CloudFlare is the poster child. >> You know, what's interesting about that too, is a lot of people are poo-pooing CloudFlare, "Ah, it's, you know, really kind of not that sophisticated." "You don't have as many tools," but to your point, you're can have those tools in the cloud, Cloudflare's doing serverless on steroids, trying to keep things really simple, doing a phenomenal job at, you know, various locations around the world. And they're definitely one to watch. Somebody put them on my radar (laughing) a while ago and said, "Dave, you got to do a breaking analysis on CloudFlare." And so I want to thank that person. I can't really name them, 'cause they work inside of a giant hyperscaler. But- (Eric laughing) (Dave chuckling) >> Real quickly, if I can from a competitive perspective too, who else is there? They've already taken share from Akamai, and Fastly is their really only other direct comp, and they're not there. And these guys are in poll position and they're the only game in town right now. I just, I don't see it slowing down. >> I thought one of your comments from your roundtable I was reading, one of the folks said, you know, CloudFlare, if my workloads are in the cloud, they are, you know, dominant, they said not as strong with on-prem. And so Akamai is doing better there. I'm like, "Okay, where would you want to be?" (laughing) >> Yeah, which one of those two would you rather be? >> Right? Anyway, all right, let's move on. Number seven, blockchain continues to look for a home in the enterprise, but devs will slowly begin to adopt in 2023. You know, blockchains have got a lot of buzz, obviously crypto is, you know, the killer app for blockchain. Senior IT architect in financial services from your, one of your insight roundtables said quote, "For enterprises to adopt a new technology, "there have to be proven turnkey solutions. "My experience in talking with my peers are, "blockchain is still an open-source component "where you have to build around it." Now I want to thank Ravi Mayuram, who's the CTO of Couchbase sent in, you know, one of the predictions, he said, "DevOps will adopt blockchain, specifically Ethereum." And he referenced actually in his email to me, Solidity, which is the programming language for Ethereum, "will be in every DevOps pro's playbook, "mirroring the boom in machine-learning. "Newer programming languages like Solidity "will enter the toolkits of devs." His point there, you know, Solidity for those of you don't know, you know, Bitcoin is not programmable. Solidity, you know, came out and that was their whole shtick, and they've been improving that, and so forth. But it, Eric, it's true, it really hasn't found its home despite, you know, the potential for smart contracts. IBM's pushing it, VMware has had announcements, and others, really hasn't found its way in the enterprise yet. >> Yeah, and I got to be honest, I don't think it's going to, either. So when we did our top trends series, this was basically chosen as an anti-prediction, I would guess, that it just continues to not gain hold. And the reason why was that first comment, right? It's very much a niche solution that requires a ton of custom work around it. You can't just plug and play it. And at the end of the day, let's be very real what this technology is, it's a database ledger, and we already have database ledgers in the enterprise. So why is this a priority to move to a different database ledger? It's going to be very niche cases. I like the CTO comment from Couchbase about it being adopted by DevOps. I agree with that, but it has to be a DevOps in a very specific use case, and a very sophisticated use case in financial services, most likely. And that's not across the entire enterprise. So I just think it's still going to struggle to get its foothold for a little bit longer, if ever. >> Great, thanks. Okay, let's move on. Number eight, AWS Databricks, Google Snowflake lead the data charge with Microsoft. Keeping it simple. So let's unpack this a little bit. This is the shared accounts peer position for, I pulled data platforms in for analytics, machine-learning and AI and database. So I could grab all these accounts or these vendors and see how they compare in those three sectors. Analytics, machine-learning and database. Snowflake and Databricks, you know, they're on a crash course, as you and I have talked about. They're battling to be the single source of truth in analytics. They're, there's going to be a big focus. They're already started. It's going to be accelerated in 2023 on open formats. Iceberg, Python, you know, they're all the rage. We heard about Iceberg at Snowflake Summit, last summer or last June. Not a lot of people had heard of it, but of course the Databricks crowd, who knows it well. A lot of other open source tooling. There's a company called DBT Labs, which you're going to talk about in a minute. George Gilbert put them on our radar. We just had Tristan Handy, the CEO of DBT labs, on at supercloud last week. They are a new disruptor in data that's, they're essentially making, they're API-ifying, if you will, KPIs inside the data warehouse and dramatically simplifying that whole data pipeline. So really, you know, the ETL guys should be shaking in their boots with them. Coming back to the slide. Google really remains focused on BigQuery adoption. Customers have complained to me that they would like to use Snowflake with Google's AI tools, but they're being forced to go to BigQuery. I got to ask Google about that. AWS continues to stitch together its bespoke data stores, that's gone down that "Right tool for the right job" path. David Foyer two years ago said, "AWS absolutely is going to have to solve that problem." We saw them start to do it in, at Reinvent, bringing together NoETL between Aurora and Redshift, and really trying to simplify those worlds. There's going to be more of that. And then Microsoft, they're just making it cheap and easy to use their stuff, you know, despite some of the complaints that we hear in the community, you know, about things like Cosmos, but Eric, your take? >> Yeah, my concern here is that Snowflake and Databricks are fighting each other, and it's allowing AWS and Microsoft to kind of catch up against them, and I don't know if that's the right move for either of those two companies individually, Azure and AWS are building out functionality. Are they as good? No they're not. The other thing to remember too is that AWS and Azure get paid anyway, because both Databricks and Snowflake run on top of 'em. So (laughing) they're basically collecting their toll, while these two fight it out with each other, and they build out functionality. I think they need to stop focusing on each other, a little bit, and think about the overall strategy. Now for Databricks, we know they came out first as a machine-learning AI tool. They were known better for that spot, and now they're really trying to play catch-up on that data storage compute spot, and inversely for Snowflake, they were killing it with the compute separation from storage, and now they're trying to get into the MLAI spot. I actually wouldn't be surprised to see them make some sort of acquisition. Frank Slootman has been a little bit quiet, in my opinion there. The other thing to mention is your comment about DBT Labs. If we look at our emerging technology survey, last survey when this came out, DBT labs, number one leader in that data integration space, I'm going to just pull it up real quickly. It looks like they had a 33% overall net sentiment to lead data analytics integration. So they are clearly growing, it's fourth straight survey consecutively that they've grown. The other name we're seeing there a little bit is Cribl, but DBT labs is by far the number one player in this space. >> All right. Okay, cool. Moving on, let's go to number nine. With Automation mixer resurgence in 2023, we're showing again data. The x axis is overlap or presence in the dataset, and the vertical axis is shared net score. Net score is a measure of spending momentum. As always, you've seen UI path and Microsoft Power Automate up until the right, that red line, that 40% line is generally considered elevated. UI path is really separating, creating some distance from Automation Anywhere, they, you know, previous quarters they were much closer. Microsoft Power Automate came on the scene in a big way, they loom large with this "Good enough" approach. I will say this, I, somebody sent me a results of a (indistinct) survey, which showed UiPath actually had more mentions than Power Automate, which was surprising, but I think that's not been the case in the ETR data set. We're definitely seeing a shift from back office to front soft office kind of workloads. Having said that, software testing is emerging as a mainstream use case, we're seeing ML and AI become embedded in end-to-end automations, and low-code is serving the line of business. And so this, we think, is going to increasingly have appeal to organizations in the coming year, who want to automate as much as possible and not necessarily, we've seen a lot of layoffs in tech, and people... You're going to have to fill the gaps with automation. That's a trend that's going to continue. >> Yep, agreed. At first that comment about Microsoft Power Automate having less citations than UiPath, that's shocking to me. I'm looking at my chart right here where Microsoft Power Automate was cited by over 60% of our entire survey takers, and UiPath at around 38%. Now don't get me wrong, 38% pervasion's fantastic, but you know you're not going to beat an entrenched Microsoft. So I don't really know where that comment came from. So UiPath, looking at it alone, it's doing incredibly well. It had a huge rebound in its net score this last survey. It had dropped going through the back half of 2022, but we saw a big spike in the last one. So it's got a net score of over 55%. A lot of people citing adoption and increasing. So that's really what you want to see for a name like this. The problem is that just Microsoft is doing its playbook. At the end of the day, I'm going to do a POC, why am I going to pay more for UiPath, or even take on another separate bill, when we know everyone's consolidating vendors, if my license already includes Microsoft Power Automate? It might not be perfect, it might not be as good, but what I'm hearing all the time is it's good enough, and I really don't want another invoice. >> Right. So how does UiPath, you know, and Automation Anywhere, how do they compete with that? Well, the way they compete with it is they got to have a better product. They got a product that's 10 times better. You know, they- >> Right. >> they're not going to compete based on where the lowest cost, Microsoft's got that locked up, or where the easiest to, you know, Microsoft basically give it away for free, and that's their playbook. So that's, you know, up to UiPath. UiPath brought on Rob Ensslin, I've interviewed him. Very, very capable individual, is now Co-CEO. So he's kind of bringing that adult supervision in, and really tightening up the go to market. So, you know, we know this company has been a rocket ship, and so getting some control on that and really getting focused like a laser, you know, could be good things ahead there for that company. Okay. >> One of the problems, if I could real quick Dave, is what the use cases are. When we first came out with RPA, everyone was super excited about like, "No, UiPath is going to be great for super powerful "projects, use cases." That's not what RPA is being used for. As you mentioned, it's being used for mundane tasks, so it's not automating complex things, which I think UiPath was built for. So if you were going to get UiPath, and choose that over Microsoft, it's going to be 'cause you're doing it for more powerful use case, where it is better. But the problem is that's not where the enterprise is using it. The enterprise are using this for base rote tasks, and simply, Microsoft Power Automate can do that. >> Yeah, it's interesting. I've had people on theCube that are both Microsoft Power Automate customers and UiPath customers, and I've asked them, "Well you know, "how do you differentiate between the two?" And they've said to me, "Look, our users and personal productivity users, "they like Power Automate, "they can use it themselves, and you know, "it doesn't take a lot of, you know, support on our end." The flip side is you could do that with UiPath, but like you said, there's more of a focus now on end-to-end enterprise automation and building out those capabilities. So it's increasingly a value play, and that's going to be obviously the challenge going forward. Okay, my last one, and then I think you've got some bonus ones. Number 10, hybrid events are the new category. Look it, if I can get a thousand inbounds that are largely self-serving, I can do my own here, 'cause we're in the events business. (Eric chuckling) Here's the prediction though, and this is a trend we're seeing, the number of physical events is going to dramatically increase. That might surprise people, but most of the big giant events are going to get smaller. The exception is AWS with Reinvent, I think Snowflake's going to continue to grow. So there are examples of physical events that are growing, but generally, most of the big ones are getting smaller, and there's going to be many more smaller intimate regional events and road shows. These micro-events, they're going to be stitched together. Digital is becoming a first class citizen, so people really got to get their digital acts together, and brands are prioritizing earned media, and they're beginning to build their own news networks, going direct to their customers. And so that's a trend we see, and I, you know, we're right in the middle of it, Eric, so you know we're going to, you mentioned RSA, I think that's perhaps going to be one of those crazy ones that continues to grow. It's shrunk, and then it, you know, 'cause last year- >> Yeah, it did shrink. >> right, it was the last one before the pandemic, and then they sort of made another run at it last year. It was smaller but it was very vibrant, and I think this year's going to be huge. Global World Congress is another one, we're going to be there end of Feb. That's obviously a big big show, but in general, the brands and the technology vendors, even Oracle is going to scale down. I don't know about Salesforce. We'll see. You had a couple of bonus predictions. Quantum and maybe some others? Bring us home. >> Yeah, sure. I got a few more. I think we touched upon one, but I definitely think the data prep tools are facing extinction, unfortunately, you know, the Talons Informatica is some of those names. The problem there is that the BI tools are kind of including data prep into it already. You know, an example of that is Tableau Prep Builder, and then in addition, Advanced NLP is being worked in as well. ThoughtSpot, Intelius, both often say that as their selling point, Tableau has Ask Data, Click has Insight Bot, so you don't have to really be intelligent on data prep anymore. A regular business user can just self-query, using either the search bar, or even just speaking into what it needs, and these tools are kind of doing the data prep for it. I don't think that's a, you know, an out in left field type of prediction, but it's the time is nigh. The other one I would also state is that I think knowledge graphs are going to break through this year. Neo4j in our survey is growing in pervasion in Mindshare. So more and more people are citing it, AWS Neptune's getting its act together, and we're seeing that spending intentions are growing there. Tiger Graph is also growing in our survey sample. I just think that the time is now for knowledge graphs to break through, and if I had to do one more, I'd say real-time streaming analytics moves from the very, very rich big enterprises to downstream, to more people are actually going to be moving towards real-time streaming, again, because the data prep tools and the data pipelines have gotten easier to use, and I think the ROI on real-time streaming is obviously there. So those are three that didn't make the cut, but I thought deserved an honorable mention. >> Yeah, I'm glad you did. Several weeks ago, we did an analyst prediction roundtable, if you will, a cube session power panel with a number of data analysts and that, you know, streaming, real-time streaming was top of mind. So glad you brought that up. Eric, as always, thank you very much. I appreciate the time you put in beforehand. I know it's been crazy, because you guys are wrapping up, you know, the last quarter survey in- >> Been a nuts three weeks for us. (laughing) >> job. I love the fact that you're doing, you know, the ETS survey now, I think it's quarterly now, right? Is that right? >> Yep. >> Yep. So that's phenomenal. >> Four times a year. I'll be happy to jump on with you when we get that done. I know you were really impressed with that last time. >> It's unbelievable. This is so much data at ETR. Okay. Hey, that's a wrap. Thanks again. >> Take care Dave. Good seeing you. >> All right, many thanks to our team here, Alex Myerson as production, he manages the podcast force. Ken Schiffman as well is a critical component of our East Coast studio. Kristen Martin and Cheryl Knight help get the word out on social media and in our newsletters. And Rob Hoof is our editor-in-chief. He's at siliconangle.com. He's just a great editing for us. Thank you all. Remember all these episodes that are available as podcasts, wherever you listen, podcast is doing great. Just search "Breaking analysis podcast." Really appreciate you guys listening. I publish each week on wikibon.com and siliconangle.com, or you can email me directly if you want to get in touch, david.vellante@siliconangle.com. That's how I got all these. I really appreciate it. I went through every single one with a yellow highlighter. It took some time, (laughing) but I appreciate it. You could DM me at dvellante, or comment on our LinkedIn post and please check out etr.ai. Its data is amazing. Best survey data in the enterprise tech business. This is Dave Vellante for theCube Insights, powered by ETR. Thanks for watching, and we'll see you next time on "Breaking Analysis." (upbeat music beginning) (upbeat music ending)

(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. >> While by no means a safe haven, the cybersecurity sector has outpaced the broader tech market by a meaningful margin, that is up until very recently. Cybersecurity remains the number one technology priority for the C-suite, but as we've previously reported the CISO's budget has constraints just like other technology investments. Recent trends show that economic headwinds have elongated sales cycles, pushed deals into future quarters, and just like other tech initiatives, are pacing cybersecurity investments and breaking them into smaller chunks. Hello and welcome to this week's Wikibon Cube Insights powered by ETR. In this Breaking Analysis we explain how cybersecurity trends are reverting to the mean and tracking more closely with other technology investments. We'll make a couple of valuation comparisons to show the magnitude of the challenge and which cyber firms are feeling the heat, which aren't. There are some exceptions. We'll then show the latest survey data from ETR to quantify the contraction in spending momentum and close with a glimpse of the landscape of emerging cybersecurity companies, the private companies that could be ripe for acquisition, consolidation, or disruptive to the broader market. First, let's take a look at the recent patterns for cyber stocks relative to the broader tech market as a benchmark, as an indicator. Here's a year to date comparison of the bug ETF, which comprises a basket of cyber security names, and we compare that with the tech heavy NASDAQ composite. Notice that on April 13th of this year the cyber ETF was actually in positive territory while the NAS was down nearly 14%. Now by August 16th, the green turned red for cyber stocks but they still meaningfully outpaced the broader tech market by more than 950 basis points as of December 2nd that Delta had contracted. As you can see, the cyber ETF is now down nearly 25%, year to date, while the NASDAQ is down 27% and change. Now take a look at just how far a few of the high profile cybersecurity names have fallen. Here are six security firms that we've been tracking closely since before the pandemic. We've been, you know, tracking dozens but let's just take a look at this data and the subset. We show for comparison the S&P 500 and the NASDAQ, again, just for reference, they're both up since right before the pandemic. They're up relative to right before the pandemic, and then during the pandemic the S&P shot up more than 40%, relative to its pre pandemic level, around February is what we're using for the pre pandemic level, and the NASDAQ peaked at around 65% higher than that February level. They're now down 85% and 71% of their previous. So they're at 85% and 71% respectively from their pandemic highs. You compare that to these six companies, Splunk, which was and still is working through a transition is well below its pre pandemic market value and 44, it's 44% of its pre pandemic high as of last Friday. Palo Alto Networks is the most interesting here, in that it had been facing challenges prior to the pandemic related to a pivot to the Cloud which we reported on at the time. But as we said at that time we believe the company would sort out its Cloud transition, and its go to market challenges, and sales compensation issues, which it did as you can see. And its valuation jumped from 24 billion prior to Covid to 56 billion, and it's holding 93% of its peak value. Its revenue run rate is now over 6 billion with a healthy growth rate of 24% expected for the next quarter. Similarly, Fortinet has done relatively well holding 71% of its peak Covid value, with a healthy 34% revenue guide for the coming quarter. Now, Okta has been the biggest disappointment, a darling of the pandemic Okta's communication snafu, with what was actually a pretty benign hack combined with difficulty absorbing its 7 billion off zero acquisition, knocked the company off track. Its valuation has dropped by 35 billion since its peak during the pandemic, and that's after a nice beat and bounce back quarter just announced by Okta. Now, in our view Okta remains a viable long-term leader in identity. However, its recent fiscal 24 revenue guide was exceedingly conservative at around 16% growth. So either the company is sandbagging, or has such poor visibility that it wants to be like super cautious or maybe it's actually seeing a dramatic slowdown in its business momentum. After all, this is a company that not long ago was putting up 50% plus revenue growth rates. So it's one that bears close watching. CrowdStrike is another big name that we've been talking about on Breaking Analysis for quite some time. It like Okta has led the industry in a key ETR performance indicator that measures customer spending momentum. Just last week, CrowdStrike announced revenue increased more than 50% but new ARR was soft and the company guided conservatively. Not surprisingly, the stock got absolutely crushed as CrowdStrike blamed tepid demand from smaller and midsize firms. Many analysts believe that competition from Microsoft was one factor along with cautious spending amongst those midsize and smaller customers. Notably, large customers remain active. So we'll see if this is a longer term trend or an anomaly. Zscaler is another company in the space that we've reported having great customer spending momentum from the ETR data. But even though the company beat expectations for its recent quarter, like other companies its Outlook was conservative. So other than Palo Alto, and to a lesser extent Fortinet, these companies and others that we're not showing here are feeling the economic pinch and it shows in the compression of value. CrowdStrike, for example, had a 70 billion valuation at one point during the pandemic Zscaler top 50 billion, Okta 45 billion. Now, having said that Palo Alto Networks, Fortinet, CrowdStrike, and Zscaler are all still trading well above their pre pandemic levels that we tracked back in February of 2020. All right, let's go now back to ETR'S January survey and take a look at how much things have changed since the beginning of the year. Remember, this is obviously pre Ukraine, and pre all the concerns about the economic headwinds but here's an X Y graph that shows a net score, or spending momentum on the y-axis, and market presence on the x-axis. The red dotted line at 40% on the vertical indicates a highly elevated net score. Anything above that we think is, you know, super elevated. Now, we filtered the data here to show only those companies with more than 50 responses in the ETR survey. Still really crowded. Note that there were around 20 companies above that red 40% mark, which is a very, you know, high number. It's a, it's a crowded market, but lots of companies with, you know, positive momentum. Now let's jump ahead to the most recent October survey and take a look at what, what's happening. Same graphic plotting, spending momentum, and market presence, and look at the number of companies above that red line and how it's been squashed. It's really compressing, it's still a crowded market, it's still, you know, plenty of green, but the number of companies above 40% that, that key mark has gone from around 20 firms down to about five or six. And it speaks to that compression and IT spending, and of course the elongated sales cycles pushing deals out, taking them in smaller chunks. I can't tell you how many conversations with customers I had, at last week at Reinvent underscoring this exact same trend. The buyers are getting pressure from their CFOs to slow things down, do more with less and, and, and prioritize projects to those that absolutely are critical to driving revenue or cutting costs. And that's rippling through all sectors, including cyber. Now, let's do a bit more playing around with the ETR data and take a look at those companies with more than a hundred citations in the survey this quarter. So N, greater than or equal to a hundred. Now remember the followers of Breaking Analysis know that each quarter we take a look at those, what we call four star security firms. That is, those are the, that are in, that hit the top 10 for both spending momentum, net score, and the N, the mentions in the survey, the presence, the pervasiveness in the survey, and that's what we show here. The left most chart is sorted by spending momentum or net score, and the right hand chart by shared N, or the number of mentions in the survey, that pervasiveness metric. that solid red line denotes the cutoff point at the top 10. And you'll note we've actually cut it off at 11 to account for Auth 0, which is now part of Okta, and is going through a go to market transition, you know, with the company, they're kind of restructuring sales so they can take advantage of that. So starting on the left with spending momentum, again, net score, Microsoft leads all vendors, typical Microsoft, very prominent, although it hadn't always done so, it, for a while, CrowdStrike and Okta were, were taking the top spot, now it's Microsoft. CrowdStrike, still always near the top, but note that CyberArk and Cloudflare have cracked the top five in Okta, which as I just said was consistently at the top, has dropped well off its previous highs. You'll notice that Palo Alto Network Palo Alto Networks with a 38% net score, just below that magic 40% number, is healthy, especially as you look over to the right hand chart. Take a look at Palo Alto with an N of 395. It is the largest of the independent pure play security firms, and has a very healthy net score, although one caution is that net score has dropped considerably since the beginning of the year, which is the case for most of the top 10 names. The only exception is Fortinet, they're the only ones that saw an increase since January in spending momentum as ETR measures it. Now this brings us to the four star security firms, that is those that hit the top 10 in both net score on the left hand side and market presence on the right hand side. So it's Microsoft, Palo Alto, CrowdStrike, Okta, still there even not accounting for a Auth 0, just Okta on its own. If you put in Auth 0, it's, it's even stronger. Adding then in Fortinet and Zscaler. So Microsoft, Palo Alto, CrowdStrike, Okta, Fortinet, and Zscaler. And as we've mentioned since January, only Fortinet has shown an increase in net score since, since that time, again, since the January survey. Now again, this talks to the compression in spending. Now one of the big themes we hear constantly in cybersecurity is the market is overcrowded. Everybody talks about that, me included. The implication there, is there's a lot of room for consolidation and that consolidation can come in the form of M&A, or it can come in the form of people consolidating onto a single platform, and retiring some other vendors, and getting rid of duplicate vendors. We're hearing that as a big theme as well. Now, as we saw in the previous, previous chart, this is a very crowded market and we've seen lots of consolidation in 2022, in the form of M&A. Literally hundreds of M&A deals, with some of the largest companies going private. SailPoint, KnowBe4, Barracuda, Mandiant, Fedora, these are multi billion dollar acquisitions, or at least billion dollars and up, and many of them multi-billion, for these companies, and hundreds more acquisitions in the cyberspace, now less you think the pond is overfished, here's a chart from ETR of emerging tech companies in the cyber security industry. This data comes from ETR's Emerging Technologies Survey, ETS, which is this diamond in a rough that I found a couple quarters ago, and it's ripe with companies that are candidates for M&A. Many would've liked, many of these companies would've liked to, gotten to the public markets during the pandemic, but they, you know, couldn't get there. They weren't ready. So the graph, you know, similar to the previous one, but different, it shows net sentiment on the vertical axis and that's a measurement of, of, of intent to adopt against a mind share on the X axis, which measures, measures the awareness of the vendor in the community. So this is specifically a survey that ETR goes out and, and, and fields only to track those emerging tech companies that are private companies. Now, some of the standouts in Mindshare, are OneTrust, BeyondTrust, Tanium and Endpoint, Net Scope, which we've talked about in previous Breaking Analysis. 1Password, which has been acquisitive on its own. In identity, the managed security service provider, Arctic Wolf Network, a company we've also covered, we've had their CEO on. We've talked about MSSPs as a real trend, particularly in small and medium sized business, we'll come back to that, Sneek, you know, kind of high flyer in both app security and containers, and you can just see the number of companies in the space this huge and it just keeps growing. Now, just to make it a bit easier on the eyes we filtered the data on these companies with with those, and isolated on those with more than a hundred responses only within the survey. And that's what we show here. Some of the names that we just mentioned are a bit easier to see, but these are the ones that really stand out in ERT, ETS, survey of private companies, OneTrust, BeyondTrust, Taniam, Netscope, which is in Cloud, 1Password, Arctic Wolf, Sneek, BitSight, SecurityScorecard, HackerOne, Code42, and Exabeam, and Sim. All of these hit the ETS survey with more than a hundred responses by, by the IT practitioners. Okay, so these firms, you know, maybe they do some M&A on their own. We've seen that with Sneek, as I said, with 1Password has been inquisitive, as have others. Now these companies with the larger footprint, these private companies, will likely be candidate for both buying companies and eventually going public when the markets settle down a bit. So again, no shortage of players to affect consolidation, both buyers and sellers. Okay, so let's finish with some key questions that we're watching. CrowdStrike in particular on its earnings calls cited softness from smaller buyers. Is that because these smaller buyers have stopped adopting? If so, are they more at risk, or are they tactically moving toward the easy button, aka, Microsoft's good enough approach. What does that mean for the market if smaller company cohorts continue to soften? How about MSSPs? Will companies continue to outsource, or pause on on that, as well as try to free up, to try to free up some budget? Adam Celiski at Reinvent last week said, "If you want to save money the Cloud's the best place to do it." Is the cloud the best place to save money in cyber? Well, it would seem that way from the standpoint of controlling budgets with lots of, lots of optionality. You could dial up and dial down services, you know, or does the Cloud add another layer of complexity that has to be understood and managed by Devs, for example? Now, consolidation should favor the likes of Palo Alto and CrowdStrike, cause they're platform players, and some of the larger players as well, like Cisco, how about IBM and of course Microsoft. Will that happen? And how will economic uncertainty impact the risk equation, a particular concern is increase of tax on vulnerable sectors of the population, like the elderly. How will companies and governments protect them from scams? And finally, how many cybersecurity companies can actually remain independent in the slingshot economy? In so many ways the market is still strong, it's just that expectations got ahead of themselves, and now as earnings forecast come, come, come down and come down to earth, it's going to basically come down to who can execute, generate cash, and keep enough runway to get through the knothole. And the one certainty is nobody really knows how tight that knothole really is. All right, let's call it a wrap. Next week we dive deeper into Palo Alto Networks, and take a look at how and why that company has held up so well and what to expect at Ignite, Palo Alto's big user conference coming up later this month in Las Vegas. We'll be there with theCube. Okay, many thanks to Alex Myerson on production and manages the podcast, Ken Schiffman as well, as our newest edition to our Boston studio. Great to have you Ken. Kristin Martin and Cheryl Knight help get the word out on social media and in our newsletters. And Rob Hof is our EIC over at Silicon Angle. He does some great editing for us. Thank you to all. Remember these episodes are all available as podcasts. Wherever you listen, just search Breaking Analysis podcast. I publish each week on wikibond.com and siliconangle.com, or you can email me directly David.vellante@siliconangle.com or DM me @DVellante, or comment on our LinkedIn posts. Please do checkout etr.ai, they got the best survey data in the enterprise tech business. This is Dave Vellante for theCube Insights powered by ETR. Thanks for watching, and we'll see you next time on Breaking Analysis. (upbeat music)

>>Hi, I'm John Ferry with the Cube. We're here for a special exclusive conversation with David Geria, the CEO of Mongo MongoDB. Well established leading platform. It's been around for, I mean, decades. So continues to become the platform of choice for high performance data. This modern data stack that's emerging, a big part of the story here at a reinvent 2022 on top of an already performing a cloud with, you know, chips and silicon specialized instances, the world's gonna be getting faster, smaller, higher performance, lower cost specialized. Dave, thanks for taking the time with me today, >>John. It's great to be here. Thank you for having me. >>Do you see yourself as a ISV or you just go with that, because that's kind of a nomenclature >>When, when I think of the term isv, I think of the notion of someone building an end solution for customer to get something done. Or what we're building is essentially a developer data platform and we have thousands of ISVs who build software applications on our platform. So how could we be an isv? Because by definition I, you know, we enable people to do so many different things and you know, they can be the, you know, the largest companies of the world trying to transform their business or startups who are trying to disrupt either existing industries or create new ones. And so that's, and, and that's how our customers view MongoDB and, and the whole Atlas platform basically enables them to do some amazing things. The reason for that is, you know, you know, we believe that what we are enabling developers to do is be able to reduce the friction and the work required to build modern applications through the document model, which is really intuitive to the way developers think and code through the distributed nature of platforms. >>So, you know, things like charting no other company on the planet offers the capabilities we do to enable people to build the most highly performant and scalable applications. And also what we also do is enable people to, you know, run different types of workloads on our platform. So we have obviously transactional, we have search, we have time series, we enable people to do things like sophisticated device synchronization from Edge to the back end. We do graph, we do real time analytics. So being able to consolidate all that with developers on one elegant unified platform really makes, you know, it attractive for developers to build on long >>Db. You know, you guys are a feature partner of aws and I would speculate, I don't know if you can comment on this, but I would imagine that you probably produce a lot of revenue for Amazon because you really can't turn off EC two when you do a database work. So, you know, you kind of crank it all the time. You guys are a top partner. How long have you guys been a partner with aws? What's the relationship? >>The relationship's been strong, actually, Amazon spoke at one of our first user conferences in 2013. And since then we've been working together. We've been at reinvent since essentially 2015. And we've been a premier partner, an Emerald sponsor for the last Nu you know, I think four or five years. And so we're very committed to the relationship and I think there's some things that we have a lot, we have a lot of things in common. We care a lot about customers and for us, our customers, our developers, we care a lot about removing friction from their day to day work to move, be able to move fast and be able to, in order to seize new opportunities and respond to new threats. And so consequently, I think the partnership, obviously by nature of our, our common objectives has really come together. >>Talk about the journey of Mongo. I mean, you look back at the history, I, you go back the old lamp stack days, right? So you know, the day developer traction is just really kind of stuck at the none. I mean, it's, it's really well known. And I remember over the conversations, Dave Mongo doesn't scale. I mean, every year we heard something along those lines cuz it just kept scaling. I heard the same thing with AWS back in 2013 timeframe. You, oh, it's just, it's really not for a real prime time. It's, it's for hobbyists, not so much builders, maybe startup cloud, but that developer traction is translated. Can you take us through the journey of Mongo where it is now and, and kinda look back and, and, and take us through what's the state of the art now, >>Right? So just for those of you who, who, those, you know, those in your audience who don't know too much about Mon Be I'll just, you know, start with the background. The company was astounded by developers. It was basically the CTO and some key developers from Double Click who really saw the challenges and the limitations of the relational database architecture because they're trying to serve billions of ads per day and they constantly need to work on the constraints and relational database. And so they essentially decided, why don't we just build a database that we'd want to use? And that was a catalyst to starting MongoDB. The first thing they focused on was, rather than having a tabler data structure, they focused on a document data structure. Why documents? Because there's much more natural and intuitive to work with data and documents in terms of you can set parent child relationships and how you just think about the relationship with data is much more natural in a document than trying to connect data in a, you know, in hundreds of different tables. >>And so that enabled developers to just move so much faster. The second thing they focused on was building a truly distributed architecture, not kind of some adjunct, you know, you know, architecture that maybe made the existing architecture a little bit more scalable. They really took from the ground up a truly distributed architecture. So where you can do native replication, you can do charting and you can do it on a global basis. And so that was the, the other profound, you know, thing that they did. And then since then, what we've also done is, you know, the document model is truly a super set of other models. So we enabled other capabilities like search you can do joins, so you can do very transaction intensive use case among be where fully asset compliant. So you have the highest forms of data guarantees you can do very sophisticated things like time series, you can do device synchronization, you can do real time analytics because we can carve off read only nodes to be able to read and query data in real time rather than have to offload that data into a data warehouse. >>And so that enables developers to just build a wide variety of, of application longing to be, and they get one unified developer interface. It's highly elegant and seamless. And so essentially the cost and tax of matching multiple point tools goes away when, when I think of the term isv, I think of the notion of someone building an end solution for a customer to get something done. Or what we're building is essentially a developer data platform and we have thousands of ISVs who build software applications on our platform. So how could we be an isv? Because by definition I, you know, we enable people to do so many different things and you know, they can be the, you know, the largest companies in the world trying to transform their business or startups or trying to disrupt either existing industries or create new ones. And so that's, and and that's how our customers view MongoDB and, and the whole Atlas platform basically enables them to do some amazing things. >>Yeah, we're seeing a lot of activity on the Atlas. Do you see yourself as a ISV or you just go with that because that's kind of a nomenclature? >>No, we don't view ourselves as ISV at all. We view ourselves as a developer data platform. And the reason for that is, you know, you know, we believe that what we are enabling developers to do is be able to reduce the friction and the work required to build modern applications through the document model, which is really intuitive to the way developers think and code through the distributed nature of platforms. So, you know, things like sharding, no other company on the planet offers the capabilities we do to enable people to build the most highly performant and scalable applications. And also what we also do is enable people to, you know, run different types of workflows on our platform. So we have obviously transactional, we have search, we have time series, we enable people to do things like sophisticated device synchronization from Edge to the back end. We do graph, we do real time analytics. So being able to consolidate all that with developers on one elegant unified platform really makes, you know, it attractive for developers to build on long ndb. >>You know, the cloud adoption really is putting a lot of pressure on these systems and you're seeing companies in the ecosystem and AWS stepping up, you guys are doing great job, but we're seeing a lot more acceleration around it, on staying on premise for certain use cases. Yet you got the cloud as well growing for workloads and, and you get this hybrid steady state as an operational mode. I call that 10 of the classic cloud adoption track record. You guys are an example of multiple iterations in cloud. You're doing a lot more, we're starting to see this tipping point with others and customers coming kind of on that same pattern. Building platforms on top of aws on top of the primitives, more horsepower, higher level services, industry specific capabilities with data. I mean this is a new kind of cloud, kind of a next generation, you knows next gen you got the classic high performance infrastructure, it's getting better and better, but now you've got this new application platform, you know, reminds me of the old asp, you know, if you will. I mean, so are you seeing customers doing things differently? Can you share your, your reaction to this role of, you know, this new kind of SaaS platform that just isn't an application, it's, it's more, it's deeper than that. What's going on here? We call it super cloud, but >>Like what? Yeah, so essentially what what, you know, a lot of our customers doing, and by the way we have over 37,000 customers of all shapes and sizes from the largest companies in the world to cutting edge startups who are building applications among B, why do they choose MongoDB? Because essentially it's the, you know, the fastest way to innovate and the reason it's the fastest way to innovate is because they can work with data so much easier than working with data on other types of architecture. So the document model is profoundly a breakthrough way to work with data to make it very, very easy. So customers are essentially building these modern applications, you know, applications built on microservices, event driven architectures, you know, addressing sophisticated use cases like time series to, and then ultimately now they're getting into machine learning. We have a bunch of companies building machine learning applications on top of MongoDB. And the reason they're doing that is because one, they get the benefits of being able to, you know, build and work with, with data so much easier than any other platform. And it's highly scale and performant in a way that no other platform is. So literally they can run their, you know, workloads both locally and one, you know, autonomous zone or they can basically be or available zone or they could be basically, you know, anywhere in the world. And we also offer multicloud capabilities, which I can get into later. >>Let's talk about the performance side. I know I was speaking with some Amazon folks every year it's the same story. They're really working on the physics, they're getting the chips, they wanna squeeze as much energy out of that. I've never met a developer that said they wanna run their workload on a slower platform or slower hardware. We know said no developer, right? No one wants to do that. >>Correct. >>So you guys have a lot of experience tuning in with Graviton instances, we're seeing a lot more AWS EC two instances, we're seeing a lot more kind of integrated end to end stories. Data is now security, it's tied into data stacks or data modern kind of data hybrid stack. A lot going on around the hardware performance specialization, the role of data, kind of a modern data stack emerging. What, what's your thoughts on the that that Yeah, >>I, I think if you had asked me, you know, when the cloud started going vogue, like you know, the, you know, the, the later part of the last decade and told me, you know, sitting here 12, 15 years later, would you know, would we be talking about, you know, chip processing speeds? I'd probably thought, nah, we would've moved on by then. But what's really clear is that customers, to your point, customers care about performance, they care about price performance, right? So AWS's investments in Graviton, we have actually deployed a significant portion of our at fleet on Amazon now runs on Graviton. You know, they've built other chip sets like train and, and inferential for like, you know, training models and running inferences. They're doing things like Nitro. And so what that really speaks to is that the cloud providers are focusing on the price performance of their, as you call it, their primitives and their infrastructure and the infrastructure layer that are still very, very important. >>And, and you know, if you look at their revenue, about 60 to 70% of the revenue comes from that pure infrastructure. So to your point, they can't offer a second class solution and still win. So given that now they're seeing a lot of competition from Azure, Azure's building their own chip sets, Google's already obviously doing that and and building specialized chip sets for machine learning. You're seeing these cloud providers compete. So they have to really compete to make their platform the most performant, the most price competitive in the marketplace. Which gives us a great platform to build on to enable developers to build these incredibly highly performant applications that customers are now demand. >>I think that's a really great point. I mean, you know, it's so funny Dave, because you know, I remember those, we don't talk speeds and feeds anymore. We're not talking about boxes. I mean that's old kind of school thinking because it was a data center mentality, speeds and feeds and that was super important. But we're kind of coming back to that in the cloud now in distributed architecture, as you put your platforms out there for developers, you have to run fast. You gotta, you can't give the developer subpar or any kind of performance that's, they'll, they'll go somewhere else. I mean that's the reality of what developers, no one, again, no one says I wanna go on the slower platform unless it's some sort of policy based on price or some sort of thing. But, but for the most part it's gotta run fast. So you got the tail of two clouds going on here, you got Amazon classic ias, keep making it faster under the hood. >>And then you got the new abstraction layers of the higher level services. That's where you guys are bridging this new, new generational shift where it's like, hey, you know what? I can go, I can run a headless application, I can run a SAS app that's refactored with data. So you've seen a lot more innovation with developers, you know, running stuff in, in the C I C D pipeline that was once it, and you're seeing security and data operations kind of emerging as a structural change of how companies are, are are transforming on the business side. What's your reaction to that business transformation and the role of the developer? >>Right, so I mean I have to obviously give amazing kudos to the, you know, to AWS and the Amazon team for what they've built. Obviously they're the ones who kind of created the cloud industry and they continue to push the innovation in the space. I mean today they have over 300 services and you know, obviously, you know, no star today is building anything not on the cloud because they have so many building blocks to start with. But what we though have found from our talking to our customers is that in some ways there is still, you know, the onus is on the customer to figure out which building block to use to be able to stitch together the applications and solutions they wanna build. And what we have done is taken essentially an opinionated point of view and said we will enable you to do that. >>You know, using one data model. You know, Amazon today offers I think 17 or 18 different types of databases. We don't think like, you know, having a tool for every job makes sense because over time the tax and cost of learning, managing and supporting those different applications just don't make a lot of sense or just become cost prohibitive. And so we think offering one data model, one, you know, elegant user experience, you know, one way to address the broadest set of of use cases is that we think is a better way. But clearly customers have choice. They can use Amazon's primitives and those second layer services as you as you described, or they can use us. Unfortunately we've seen a lot of customers come to us with our approach and so does Amazon. And I have to give obviously again kudos and Amazon is very customer obsessed and so we have a great relationship with them, both technically in terms of the product integrations we do as well as working with 'em in the field, you know, on joint customer opportunities. >>Speaking of, while you mentioned that, I wanna just ask you, how is that marketplace relationship going with aws? Some of the partners are really seeing great economic and joint selling or them selling your, your stuff. So there's a real revenue pop there in that religion. Can you comment on that? >>So we had been working the partner in the marketplace for many years now, more from a field point of view where customers could leverage their existing commitments to AWS and leverage essentially, you know, using Atlas and applying in an atlas towards their commits. There was also some sales incentives for people in the field to basically work together so that, you know, everyone won should we collectively win a customer? What we recently announced is as pay as you Go initiative, where literally a customer on the Amazon marketplace can basically turn up, you know, an Alice instance with no commitment. So it's so easy. So we're just pushing the envelope to just reduce the friction for people to use Atlas on aws. And it's working really very well. The uptake has been been very strong and and we feel like we're just getting started because we're so excited about the results we're >>Seeing. You know, one of the things that's kind of not core in the keynote theme, but I think it's underlying message is clear in the industry, is the developer productivity. You said making things easy is a big deal, self-service, getting in and trying, these are what developer friendly tools are like and platform. So I have to ask you, cuz this comes up a lot in our kind of business conversation, is, is if you take digital transformation concept to its completion, assuming now you know, as a thought exercise, you completely transform a company with technology that's, that is the business transformation outcome. Take it to completion. What does that look like? I mean, if you go there you'd say, okay, the company is the app, the company is the data, it's not a department serving the business, it's the business. And so I think this is kind of what we're seeing as the next big mountain climb, which is companies that do transform there, they are technology companies, they're not a department like it. So I think a lot of companies are kind of saying, wait a minute, why would we have a department? It should be the company. What's your your your view on this because this >>Yeah, so I I've had the for good fortune of being able to talk to thousand customers all over the world. And you know, one thing John, they never tell me, they never tell me that they're innovating too quickly. In fact, they always tell me the reverse. They tell me all the obstacles and impediments they have to be able to be able to be able to move fast. So one of the reasons they gravitate to MongoDB is just the speed that they wish they can build applications to, to your point, developer productivity. And by definition, developer productivity is a proxy for innovation. The faster you can make your developers, you know, move, the faster they can push out code, the faster they can iterate and build new solutions or add more capabilities on the existing applications, the faster you can innovate either to, again, seize new opportunities or to respond to new threats in your business. >>And so that resonates with every C level executive. And to your point, the developers not some side hustle that they kind of think about once in a while. It's core to the business. So developers have amassed enormous amount of power and influence. You know, their, their, their engineering teams are front and center in terms of how they think about building capabilities and and building their business. And that's also obviously enabled, you know, to your point, every software company, every company's not becoming a software company because it all starts with softwares, software enables, defines or creates almost every company's value proposition. >>You know, it makes me smile because I love operating systems as one of my hobbies in college was, you know, systems programming and I remember those network kind of like the operating systems, the cloud. So, you know, everything's got specialized capabilities and that's a big theme here at Reinvent. If you look at the announcements Monday night with Peter DeSantis, you got, you got new instances, new chips. So this whole engine kind of specialized component is like an engine. You got a core and you got other subsystems. This is gonna be an integral part of how companies architect their platform or you know, Adam calls it the landing zone or whatever they wanna call it. But you gotta start seeing a new architectural thinking for companies. What's your, can you share your experience on how companies should look at this opportunity as a plethora of more goodness on the hardware? On hardware, but like chips and instances? Cause now you can mix and match. You've got, you've got, you got everything you need to kind of not roll your own but like really build foundational high performance capabilities. >>Yeah, so I I, so I think this is where I think Amazon is really enabling all companies, including, you know, companies like Mon db, you know, push the envelope and innovation. So for example, you know, the, the next big hurdle for us, I think we've seen two big platform shifts over the last 15 years of platform shifts, you know, to mobile and the platform shift to cloud. I believe the next big platform shift is going from dumb apps to smart apps, which you're building in, you know, machine learning and you know, AI and just very sophisticated automation. And when you start automating human decision making, rather than, you know, looking at a dashboard and saying, okay, I see the data now, now I have to do this. You can automate that into your applications and make your applications leveraging real time data become that much more smart. And that ultimately then becomes a developer challenge. And so we feel really good about our position in taking advantage of those next big trends and software leveraging the price performance curves that, you know, Amazon continues to push in terms of their hardware performance, networking performance, you know, you know, price, performance and storage to build those next generation of modern applications. >>Okay, so let me get this straight. You have next generation intelligent smart apps and you have AI generative solutions coming out around the corner. This is like pretty good position for Mongo to be in with data. I mean, this is what you do, you're in that exactly of the action. What's it like? I mean, you must be like trying to shake the world and wake up. The world's starting to wake up now through this. So what's, what's it like? >>Well, I mean we're really excited and bullish about the future. We think that we're well positioned because we know as to your point, you know, we have amassed amazing amount of developer mindshare. We are the most popular modern data platform out there in the world. There's developers in almost every corner of the planet using us to do something. And to your point, leveraging data and these advances in machine learning ai. And we think the more AI becomes democratized, not, you know, done by a bunch of data scientists sitting in some corner office, but essentially enabling developers to have the tools to build these very, very sophisticated, smart applications will, you know, will position as well. So that's, you know, obviously gonna be a focus for us over the, frankly, I think this is gonna be like a 10 year, 10 15 year run and we're just getting started in this whole >>Area. I think you guys are really well positioned. I think that's a great point. And Adam mentioned to me and, and Mike interviewed, he said on stage talk about it, the role of a data analyst kind of goes away. Everyone's a data analyst, right? You'll still see specialization on, on core data engineering, which is kind of like an SRE role for data. So data ops and data as code is a big deal making data applications. So again, exciting times and you guys are well positioned. If you had to bumper sticker the event this week here at Reinvent, what would you, how would you categorize this this point in time? I mean, Adam's great leader, he is gonna help educate customers how to use technology to, for business advantage and transformation. You know, Andy did a great job making technology great and innovative and setting the table, Adam's gotta bring it to the enterprises and businesses. So it's gonna be an interesting point in time we're in now. What, how would you categorize this year's reinvent, >>Right? I think the, the, the tech world is pivoting towards what I'd call rationalization or cost optimization. I think people obviously in, you know, the last 10 years have, you know, it's all about speed, speed, speed. And I think people still value speed, but they wanna do it at some sort of predictable cost model. And I think you're gonna see a lot more focus around cost and cost optimization. That's where we think having one platform is by definition of vendor consolidation way for people to cut costs so that they can basically, you know, still move fast but don't have to incur the tax of using a whole bunch of different point tools. And so we think we're well positioned. So the bumper sticker I think about is essentially, you know, do more for less with MongoDB. >>Yeah. And the developers on the front lines. Great stuff. You guys are great partner, a top partner at AWS and great reflection on, on where you guys been, but really where you are now and great opportunity. David Didier, thank you so much for spending the time and it's been great following Mongo and the continued rise of, of developers of the on the front lines really driving the business and that, and they are, I know, driving the business, so, and I think they're gonna continue Smart apps, intelligent apps, ai, generative apps are coming. I mean this is real. >>Thanks John. It's great speaking with >>You. Yeah, thanks. Thanks so much. Okay.

>> 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)

>>data by its very nature is distributed and siloed. But most data architectures today are highly centralized. Organizations are increasingly challenged to organize and manage data and turn that data into insights this idea of a single monolithic platform for data, it's giving way to new thinking. We're a decentralized approach with open cloud native principles and Federated governance will become an underpinning underpinning of digital transformations. Hi everybody, this is Day Volonte. Welcome back to HP discover 2021 the virtual version. You're watching the cubes continuous coverage of the event and we're here with Matt Mako is the field C T O for Israel software at H P E. And we're gonna talk about HP software strategy and esmeralda and specifically how to take a I analytics to scale and ensure the productivity of data teams. Matt, welcome to the cube. Good to see you. >>Good to see you again. Dave thanks for having me today. >>You're welcome. So talk a little bit about your role as CTO. Where do you spend your time? >>Yeah. So I spend about half of my time talking to customers and partners about where they are on their digital transformation journeys and where they struggle with this sort of last phase where we start talking about bringing those cloud principles and practices into the data world. How do I take those data warehouses, those data lakes, those distributed data systems into the enterprise and deploy them in a cloud like manner. And then the other half of my time is working with our product teams to feed that information back so that we can continually innovate to the next generation of our software platform. >>So when I remember I've been following HP and HP for a long, long time, the cube is documented. We go back to sort of when the company was breaking in two parts and at the time a lot of people were saying, oh HP is getting rid of the software business to get out of software. I said no, no, no hold on, they're really focusing and and the whole focus around hybrid cloud and and now as a service and so you're really retooling that business and sharpen your focus. So so tell us more about asthma, it's cool name. But what exactly is as moral software, >>I get this question all the time. So what is Israel? Israel is a software platform for modern data and analytics workloads using open source software components. And we came from some inorganic growth. We acquired a company called citing that brought us a zero trust approach to doing security with containers. We bought blue data who came to us with an orchestrator before kubernetes even existed in mainstream. They were orchestrating workloads using containers for some of these more difficult workloads, clustered applications, distributed applications like Hadoop. And then finally we acquired Map are which gave us this scale out, distributed file system and additional analytical capabilities. And so what we've done is we've taken those components and we've also gone out into the marketplace to see what open source projects exist, to allow us to bring those club principles and practices to these types of workloads so that we can take things like Hadoop and spark and Presto and deploy and orchestrate them using open source kubernetes, leveraging Gpu s while providing that zero trust approaches security. That's what Israel is all about. Is taking those cloud practices and principles but without locking you in again using those open source components where they exist and then committing and contributing back to the open source community where those projects don't exist. >>You know, it's interesting. Thank you for that history. And when I go back, I always been there since the early days of big data and Hadoop and so forth. The map are always had the best product. But but they can't get back then. It was like Kumbaya open source and they had this kind of proprietary system, but it worked and that's why it was the best product. And so at the same time they participated in open source projects because everybody that that's where the innovation is going. So you're making that really hard to use stuff easier to use with kubernetes orchestration. And then obviously I'm presuming with the open source chops, sort of leaning into the big trends that you're seeing in the marketplace. So my question is, what are those big trends that you're seeing when you speak to technology executives, which is a big part of what you do? >>Yeah. So the trends I think are a couple of fold and it's funny about Duke, I think the final nails in the coffin have been hammered in with the Hadoop space now. And so that that leading trend of of where organizations are going. We're seeing organizations wanting to go cloud first, but they really struggle with these data intensive workloads. Do I have to store my data in every cloud? Am I going to pay egress in every cloud? Well, what if my data scientists are most comfortable in AWS? But my data analysts are more comfortable in Azure. How do I provide that multi cloud experience for these data workloads? That's the number one question I get asked. And that's the probably the biggest struggle for these Chief Data Officers. Chief Digital Officer XYZ. How do I allow that innovation but maintaining control over my data compliance especially, we talk international standards like G. D. P. R. To restrict access to data, the ability to be forgotten in these multinational organizations. How do I sort of square all of those components and then how do I do that in a way that just doesn't lock me into another appliance or software vendors stack? I want to be able to work within the confines of the ecosystem. Use the tools that are out there but allow my organization to innovate in a very structured, compliant way. >>I mean I love this conversation. And just to me you hit on the key word which is organization. I want to I want to talk about what some of the barriers are. And again, you heard my wrap up front. I I really do think that we've created not only from a technology standpoint and yes, the tooling is important, but so is the organization. And as you said, you know, an analyst might want to work in one environment, a data scientist might want to work in another environment. The data may be very distributed. They maybe you might have situations where they're supporting the line of business. The line of business is trying to build new products. And if I have to go through this, hi this monolithic centralized organization, that's a barrier uh for me. And so we're seeing that change that kind of alluded to it upfront. But what do you see as the big, you know, barriers that are blocking this vision from becoming a reality? >>It very much is organization dave it's the technology is actually no longer the inhibitor here. We have enough technology, enough choices out there. That technology is no longer the issue. It's the organization's willingness to embrace some of those technologies and put just the right level of control around accessing that data because if you don't allow your data scientists and data analysts to innovate, they're going to do one of two things, they're either going to leave and then you have a huge problem keeping up with your competitors or they're gonna do it anyway, and they're gonna do it in a way that probably doesn't comply with the organizational standards. So the more progressive enterprises that I speak with have realized that they need to allow these various analytical users to choose the tools, they want to self provision those as they need to and get access to data in a secure and compliant way. And that means we need to bring the cloud to generally where the data is because it's a heck of a lot easier than trying to bring the data where the cloud is while conforming to those data principles. And that's, that's Hve strategy, you've heard it from our CEO for years now, everything needs to be delivered as a service. It's essential software that enables that capability, such as self service and secure data provisioning, etcetera. >>Again, I love this conversation because if you go back to the early days of the Duke, that was what was profound about. Do bring bring five megabytes of code, do a petabyte of data and it didn't happen. We shoved it all into a data lake and it became a data swamp. And so it's okay, you know, and that's okay. It's a one dato maybe maybe in data is is like data warehouses, data hubs data lake. So maybe this is now a four dot Oh, but we're getting there. Uh, so an open but open source one thing's for sure. It continues to gain momentum. It's where the innovation is. I wonder if you could comment on your thoughts on the role that open source software plays for large enterprises. Maybe some of the hurdles that are there, whether they're legal or licensing or or or just fears. How important is open source software today? >>I think the cloud native development, you know, following the 12 factor applications microservices based, pave the way over the last decade to make using open source technology tools and libraries mainstream, we have to tip our hats to red hat right for allowing organizations to embrace something. So core is an operating system within the enterprise. But what everyone realizes that its support, that's what has to come with that. So we can allow our data scientists to use open source libraries, packages and notebooks. But are we going to allow those to run in production? And so if the answer is no, then that if we can't get support, we're not going to allow that. So where HP es Merrill is taking the lead here is again embracing those open source capabilities, but if we deploy it, we're going to support it or we're going to work with the organization that has the committees to support it. You call HPD the same phone number you've been calling for years for tier 1 24 by seven support and we will support your kubernetes, your spark your presto your Hadoop ecosystem of components were that throat to choke and we'll provide all the way up to break fix support for some of these components and packages giving these large enterprises the confidence to move forward with open source but knowing that they have a trusted partner in which to do so >>and that's why we've seen such success with, say, for instance, managed services in the cloud or versus throwing out all the animals in the zoo and say, okay, figure it out yourself. But of course what we saw, which was kind of ironic was we, we saw people finally said, hey, we can do this in the cloud more easily. So that's where you're seeing a lot of data. A land. However, the definition of cloud or the notion of cloud is changing no longer. Is it just this remote set of services somewhere out there? In the cloud? Some data center somewhere. No, it's, it's moving on. Prem on prem is creating hybrid connections you're seeing, you know, co location facility is very proximate to the cloud. We're talking now about the edge, the near edge and the far edge deeply embedded, you know? And so that whole notion of cloud is, is changing. But I want to ask you, there's still a big push to cloud, everybody is a cloud first mantra. How do you see HP competing in this new landscape? >>I I think collaborating is probably a better word, although you could certainly argue if we're just leasing or renting hardware than it would be competition. But I think again, the workload is going to flow to where the data exists. So if the data is being generated at the edge and being pumped into the cloud, then cloud is prod, that's the production system. If the data is generated, the on system on premises systems, then that's where it's going to be executed, that's production. And so HBs approach is very much coexist, coexist model of if you need to do deaf tests in the cloud and bring it back on premises, fine or vice versa. The key here is not locking our customers and our prospective clients into any sort of proprietary stack, as we were talking about earlier, giving people the flexibility to move those workloads to where the data exists. That is going to allow us to continue to get share of wallet. Mindshare, continue to deploy those workloads and yes, there's going to be competition that comes along. Do you run this on a G C P or do you run it on a green lake on premises? Sure. We'll have those conversations. But again, if we're using open source software as the foundation for that, then actually where you run it is less relevant. >>So a lot of, there's a lot of choices out there when it comes to containers generally and kubernetes specifically, uh, you may have answered this, you get zero trust component, you've got the orchestrator, you've got the, the scale out, you know, peace. But I'm interested in hearing in your words why an enterprise would or should consider s morale instead of alternatives to kubernetes solutions? >>It's a fair question. And it comes up in almost every conversation. We already do kubernetes, so we have a kubernetes standard and that's largely true. And most of the enterprises I speak to their using one of the many on premises distributions of the cloud distributions and they're all fine. They're all fine for what they were built for. Israel was generally built for something a little different. Yes, everybody can run microservices based applications, devoPS based workloads, but where is Meryl is different is for those data intensive and clustered applications. Those sort of applications require a certain degree of network awareness, persistent storage etcetera, which requires either a significant amount of intelligence. Either you have to write in go lang or you have to write your own operators or Israel can be that easy button. We deploy those state full applications because we bring a persistent storage later that came from that bar we're really good at deploying those stable clustered applications and in fact we've open sourced that as a project cube director that came from Blue data and we're really good at securing these using spiffy inspire to ensure that there is that zero trust approach that came from side tail and we've wrapped all of that in kubernetes so now you can take the most difficult, gnarly, complex data intensive applications in your enterprise and deploy them using open source and if that means we have to coexist with an existing kubernetes distribution, that's fine. That's actually the most common scenario that I walk into is I start asking about what about these other applications you haven't done yet? The answer is usually we haven't gotten to him yet or we're thinking about it and that's when we talk about the capabilities of s role and I usually get the response, oh, a we didn't know you existed and be, well, let's talk about how exactly you do that. So again, it's more of a coexist model rather than a compete with model. Dave >>Well, that makes sense. I mean, I think again, a lot of people think, oh yeah, Kubernetes, no big deal, it's everywhere. But you're talking about a solution, I'm kind of taking a platform approach with capabilities, you've got to protect the data. A lot of times these microservices aren't some micro uh and things are happening really fast, You've got to be secure, you've got to be protected. And like you said, you've got a single phone number, you know, people say one throat to choke, Somebody said the other day said no, no single hand to shake, it's more of a partnership and I think that's a proposed for HPV met with your >>hair better. >>So you know, thinking about this whole, you know, we've gone through the pre big data days and the big data was all, you know, the hot buzz where people don't maybe necessarily use that term anymore, although the data is bigger and getting bigger, which is kind of ironic. Um where do you see this whole space going? We've talked about that sort of trends are breaking down the silos, decentralization. Maybe these hyper specialized roles that we've created maybe getting more embedded are lined with the line of business. How do you see it feels like the last, the next 10 years are going to be different than the last 10 years. How do you see it matt? >>I completely agree. I think we are entering this next era and I don't know if it's well defined, I don't know if I would go out on an edge to say exactly what the trend is going to be. But as you said earlier, data lakes really turned into data swamps. We ended up with lots of them in the enterprise and enterprises had to allow that to happen. They had to let each business unit or each group of users collect the data that they needed and I. T. Sort of had to deal with that down the road. And so I think the more progressive organizations are leading the way they are again taking those lessons from cloud and application developments, microservices and they're allowing a freedom of choice there, allowing data to move to where those applications are. And I think this decentralized approach is really going to be king. And you're gonna see traditional software packages, you're gonna see open source, you're going to see a mix of those. But what I think we'll probably be common throughout all of that is there's going to be this sense of automation, this sense that we can't just build an algorithm once released and then wish it luck that we've got to treat these these analytics and these these data systems as living things that there's life cycles that we have to support, which means we need to have devops for our data science. We need a ci cd for our data analytics. We need to provide engineering at scale like we do for software engineering. That's going to require automation and an organizational thinking process to allow that to actually occur. And so I think all of those things that sort of people process product, but it's all three of those things are going to have to come into play. But stealing those best ideas from cloud and application development, I think we're going to end up with probably something new over the next decade or so >>again, I'm loving this conversation so I'm gonna stick with it for a second. I it's hard to predict, but I'll some takeaways that I have matt from our conversation. I wonder if you could, you could comment. I think, you know, the future is more open source. You mentioned automation deV's are going to be key. I think governance as code, security designed in at the point of code creation is going to be critical. It's not no longer to be a bolt on and I don't think we're gonna throw away the data warehouse or the data hubs or the data lakes. I think they become a node. I like this idea and you know, jim octagon. But she has this idea of a global data mesh where these tools lakes, whatever their their node on the mesh, they're discoverable. They're shareable. They're they're governed uh in a way and that really I think the mistake a lot of people made early on in the big data movement, Oh we have data, we have to monetize our data as opposed to thinking about what products that I can I build that are based on data that then I can, you know, can lead to monetization. And I think and I think the other thing I would say is the business has gotten way too technical. All right. It's an alienated a lot of the business lines and I think we're seeing that change. Um and I think, you know, things like Edinburgh that simplify that are critical. So I'll give you the final thoughts based on my rent. >>I know you're ready to spot on. Dave. I think we we were in agreement about a lot of things. Governance is absolutely key. If you don't know where your data is, what it's used for and can apply policies to it, it doesn't matter what technology throw at it, you're going to end up in the same state that you're essentially in today with lots of swamps. Uh I did like that concept of of a note or a data mesh. It kind of goes back to the similar thing with a service smashed or a set of a P I is that you can use. I think we're going to have something similar with data that the trick is always how heavy is it? How easy is it to move about? And so I think there's always gonna be that latency issue. Maybe not within the data center, but across the land, latency is still going to be key, which means we need to have really good processes to be able to move data around. As you said, government determine who has access to what, when and under what conditions and then allow it to be free, allow people to bring their choice of tools, provision them how they need to while providing that audit compliance and control. And then again, as as you need to provision data across those notes for those use cases do so in a well measured and govern way. I think that's sort of where things are going. But we keep using that term governance. I think that's so key. And there's nothing better than using open source software because that provides traceability, the audit ability and this frankly openness that allows you to say, I don't like where this project is going. I want to go in a different direction and it gives those enterprises that control over these platforms that they've never had before. >>Matt. Thanks so much for the discussion. I really enjoyed it. Awesome perspectives. >>Well, thank you for having me. Dave are excellent conversation as always. Uh, thanks for having me again. >>All right. You're very welcome. And thank you for watching everybody. This is the cubes continuous coverage of HP discover 2021 of course, the virtual version next year. We're gonna be back live. My name is Dave a lot. Keep it right there. >>Yeah.

>>Welcome back to the doctor khan cube conversation. Dr khan 2021 virtual. I'm john for your host of the cube of mulch, Donny co founder and CTO and see so for accurate hot startup hot company. Uh, thanks for coming on the cube for dr continent and talking cybersecurity and cloud native. Super important. Thanks for coming on, >>appreciate john. Thanks for having me. >>So here dr khan. Obviously the conversations around developer experience, um, making things more productive. Obviously cloud scale cloud native with docker containers with kubernetes all lining up right in line with the trend that's now going mainstream and all commercial enterprises. I mean developer productivity security is a huge times thing if you don't get it right. So, you know, shifting left is that everyone's talking about, but this is a huge challenge. Can you, can you talk about what you guys do at your company and specifically why it relates to this conversation for developers at dr khan. >>Sure. Um, so john as we understand today, there are millions of uh, you know, code comments that are happening in cloud native environments on daily basis. Um, you know, in a recent report, Airbnb reported, they've checked in 125,000 plus times ham charts in an ear. And what that means is that, you know, the guitars revolution is here. Uh, and that also means that, well, you got your kubernetes clusters sinking up with infrastructure as code, such as ham chart customized and yarrow files right almost several times a day now, what that also means is that the opportunity to make sure that your clusters are being deployed securely by these infrastructure as code templates and deployment has called template is available before the deployment happens and not after the deployment. Also, in order to reduce the cost or detecting security challenges. The best option and opportunity is during the development time and during the deployment time, which is the pipeline time and that's what we offer. We shift your cloud, native security posture detection to left. We detect all your security posture related issues while the code is in development in the design phase as well as while it is about to get deployed, that is within the guitars pipelines or your traditional develops pipelines and not only with detect where we sell feel the code as well, specifically infrastructure as code. So we detect the problems and we fix the problem by generating the remediation code which we like to call it as remediation is called. The detection mechanisms like all this policy is called. That's the primary use case that we offer. We help developers reduce the cost of remediation and also meantime to the mediations for security problems >>and actually see them a boatload of hassle to going back and figure out how they wrote the code at that time. And kind of what happened always is a problem. Um, I gotta Okay, so I'm gonna get into this policy is code. You mentioned that also you mentioned Getafe's revolution. Let's get to that in a second. But first I want you to explain to the folks what is cloud native security and what does that mean? And what kind of attacks emerge as that surface area becomes apparent? >>Absolutely. So cloud native security is a very interesting new paradigm. Uh it's not just related with one single control pain like take, for example, Cuban haters, it's not just that, it's also the supply chain elements that go into the deployment of your cloud native clusters. Like see if kubernetes cluster you need to secure not just the application code which is running inside your container images, but also the container image itself, then the pod, then the name space, then the cluster. And also you need to do all the other cyber hygienic, high generated things that we were doing previously. So it's so much of complexity because availability of different control planes, you need to be able to make sure that you are doing security, not just right, but at a very, very cost effective in a very, very cost effective manner. And the kind of attacks that we are predicting we're going to see in cloud native world are going to be very different from what we have seen so far. Especially there's a new attack type that I am have coined. I call that as cloud native waterhole attack. What it means is that imagine that most of the cloud native infrastructures are developed out of a lot of different open source components and pieces. So imagine you're pulling up a container image from a open source container agency and that continued which contains a man there container image can directly land into your cluster and not only can enter into your so called secure cluster environment. Usually the cluster control planes are not exposed to internet but deployment of one supply chain element like a Mallory's container image and exposed to an entire cluster. And that's what is waterhole attack when it comes to chlorinated water hole attacks to supply chains. So these are some very innovative and noble attacks that you know, we Uh you know, predict are going to come to our weigh in next 12-18 months. >>So you say it's a waterhole attack. That's the that's the coin term that you've made. So basically what you're saying is the container could be infected with all the properties that is containing into a secure cluster. It's almost been penetrated like malware would or spear phishing attack, it targets the cluster and then infects it. >>So not only that because your continuing images that you're pulling in um from your registries registries can be located anywhere right? If you do not do proper sanitization and checking off your supply chain components such as a continuing image, it can land insecure zones like this. So not only in a cluster, it can become part of a system named space very soon and and that's where the risks are that, you know, you had a parameter, you know, at least of some sort when it was non cloud native environments. And now you have a kind of false sense of security that I have equivalent is cluster, which sort of air gap in one way like there's no exposure to internet of the control plane control being a P. I. Is not supposed to Internet, that doesn't mean anything. A container enters into your cluster can take over the entire cluster. >>All right, so that's cool. So I love that attacks kind of attack. So back to cloud native security definition. So you're defining cloud native security as cloud native clusters. Is it specific around kubernetes or what specifically the cloud native security? What's the category? If the if water holds the attack vector, what's cloud native security means? >>So what it means is that you need to worry about multiple different control planes in a cloud native environment. It's not just a single control pain that you have to worry about. You have to worry about your uh as I said, kubernetes control plane, you have service measures on top of it, You could have server less layers on top of it and when you have to worry about so many different control pains, but it also means is that the security needs to become part of and has to get baked into the entire process of building cloud native environment, not afterthought or it shouldn't happen after the fact. >>See the containers for containers that watch the containers security for the security to watch the security. So you get so let's get we'll get to that. I want to get back to the solution, but one more thing. Um this one piece. So your c so um there you have a lot of shops in there from your background, I know that. Um So if if people out there, other Csos are looking at expanding, You know, day one day 2 ongoing, you know, ai ops get upstate to operate what everyone call it cloud native environments. How do they consider figuring out how to deploy and understand cloud need to secure? What do they have to do if you're a c So knowing what, you know, what steps are you taking? >>Yeah, it's funny that, you know, there's a big silo today between the sea, so organizations and the devops and get ops teams. Uh so the number one priority, in my opinion, that the sea so s uh you know, have to really follow is having visibility into the uh developers. So developers who are developing not just code but also infrastructure as code. So there is a slight difference between writing python code versus writing uh say ham charts or customized templates. Right? So you need as a see saw, you know, see so our needs to have full visibility into Okay, out of 100 developers, how many do I have who are writing deployment as code? And then how many of them are continuously checking in code and introducing security issues? Those issues have to be visualized while the issues are written in code and as they are getting checked into the repositories, so catch the security issues while the code is getting checked into the repository. And the next best stages catch the issues while the pipelines are picking up the code from the repository. So sisters needs to have visibility into this. I call it as shift left visibility for CSOS. So sisters need to know, okay, what are my top 10 developers who are writing infrastructure as code? How many of those developers are committing wonderful code. How many of these pull requests which have been raised have got security violations? How many of them have been fixed and how many have not been fixed? That's what is the visibility that can uh you know, provide opportunities to seize organizations to >>react and more things to put KPI S around two to understand where the gaps are and where the potential blind spots are. Okay, shift left visibility to see. So if you've got the get ups revolution, you got the waterhole attacks. You have multiple control planes obviously complex. The benefits of cloud native though are significant and people doing modern applications are seeing that. So clearly this is direction that everyone's going. The consensus is clear. So how do you solve this? You mentioned policy as code. I'm kind of connecting the dots here. If I'm going to understand what's going on in real time as the code is in flight as it's checking in. For instance, this is kind of in the pipeline as you say. So this has to be solved. What is the answer to this? Because it's clearly the way people want it. No one wants to come back and say we got hacked or development being pulled off task to figure out what they fixed or didn't do what's the policy is code angle? >>So um you know, of course, you know, there could be more than one ways to solve this problem. The way we are solving this problem is that first thing we are bringing all top type of infrastructure as code and the control planes into a single uniform format, which we like to call it as cloud, as code. The reason why we do that so that we can normalize the representation of these different data sets in one single normalized format. And then we apply open policy agent which is a C N C F uh graduated project, which is kind of the de facto standard to do any kind of policy is called use cases in the cloud native world today. So we apply open policy agent to this middleware that we create, which basically brings all these different control plane data, all the different infrastructures code into anomalous format. We apply O P A and we use policies to apply uh Opie on this data this way. What happens is that we write, for example, we want to write a policy, you don't want certain parts to be exposed to Internet in a given name space. You can write such a policy. This policy, you can run on life cluster as well as on the hand charts, which is your development side of the artifact. Right. Because we're bringing both these datasets into middleware. So in short, one of the solutions that we are proposing is that different control planes, different infrastructures, code has to be brought into a normalized format. And then you apply frameworks like Opie a open policy agent to achieve your policy is called use cases. >>What is the attraction for this direction? O. P. A. In particular obviously controlled planes. I get that. I can see the benefit of having this abstraction away with the normalization. I think that would enable a lot of innovation on top of it. Um Makes a lot of sense, totally cool. What's the attraction? What's the vibe? Are people reacting to this? Uh Some people might say whoa hold on, you're taking on too much uh your eyes are bigger than your stomach. You're taking on too much territory. Whoa, slow down. I can I I want to own that control plane. There's a lot of people trying to own the control plane. So again it's a little bit of politics here. What's your what's your thoughts on the momentum? What's the support, what's it look like? >>Yeah, I think you are getting it right, the political side of things. So, um, you know, one responses that, look, we have launched our open source project contour a scan uh last year and uh you know, we're doing pretty well. It's a full opium based uh in a project which allows you to do policies code on not only new cloud control planes, like, you know, kubernetes and others, but also the traditional control planes provided by CSP s like cloud security, cloud service providers. So parents can can be used not just for hand charts and customized, but also for terra form. What we are uh promoting is open culture. With scan. We want community to contribute, become part of it. Um yes, we are promoting a middleware here uh but we want to do it with the help of the community and our reaction what we're getting is very very good. We are in our commercial offering also we use opa we have good adoption going on right now. We believe will be able to uh you know with the developer community, you have this thing going for us. >>I love cloud as code. It's so much more broader than infrastructure as code and I'll see the control plane benefits. You know when I talk to customers, I want to get your reaction to this because I really appreciate your experience and and leadership here. I talked to customers all the time and I wont say name, I won't name names but they're big, big and fintech and you'll big and life sciences in other areas. They all say we want to bring best to breed together but it's too hard to make it all work. We can get it done, but it's a lot of energy. So obviously building code and getting into production that is just brute force. Anyway, they got to get that done and they're working on their pipe lining. But getting other best of breed stuff together and making it work is really hard. Does this solve that? Do you, are you helping solve that problem? Is this an integration opportunity? >>Yes, that and that is true and we have realized it, you know, uh long back. So that's why we do not introduce any new tooling into the existing developer workflows, no new tool whatsoever. We integrate with all existing developer workflows. So if you are a, you know, modern uh, you know, get off shop and you're using flux or Argo, we integrate terrace can seamlessly integrated flux in Argo, you don't even get to know that you already have what policy is called enabled if you're using flux Argo or any equivalent, you know, getups, toolkit. Likewise, if you are using any kind of uh, you know, say existing developer pipeline or workflows such as, you know, the pipelines available on guitar, get lab, you know, get bucket and other pipelines. We seamlessly integrate our motor is very, very simple. We don't want to introduce one more two for developers, we want to introduce one more per security. We want to get good old days, >>no one wants another tool in the tool shed. I mean it's like, it's like really like the tool shit, they get all these tools laying around. But everyone again, this is back to the platform wars in the old days when I was younger. Breaking into the early days of the web platforms were everything you have to build your own proprietary platform Wasn't some open source being used, but mostly it was full stack. Now platforms are inter operating with hybrid and now Edge. So I want to get your thoughts on and I'm just really a little bit off topic. But it's kind of related. How should companies think about platform engineering? Because you now have the cloud scale, which in a way is half a stack. You don't really if you're gonna have horizontal scalability and you're gonna have these kind of unified control planes and infrastructure as code. Then in a way you don't really need that full stack developer. I mean I could program the network. I don't need to get into the weeds on that. I got now open policy agent on with terrorists. Can I really can focus on developing this is kind of like an OS concept. So how should companies think about platforms and hiring platform engineers and and something that will scale and have automation and all the benefits and goodness of the cloud scale. >>Yeah, I mean you actually nailed it when you began uh we've been experienced since we've been experiencing now since last at least 18 months that and if I were specifically also, I'll touch based on the security side of things as well. But platform engineering and platforms, especially now everything is about interoperability and uh, what we have started experiencing is that it has to be open. The credibility any platform can gain is only through openness interoperability and also neutrality. If these three elements are missing, it's very hard to push and capture the mind share of the users to adopt the platform. And why do you want to build a platform to actually attract partners who can build integrations and also to build apps on top of it or plug ins on top of it? And that can only be encouraged if there is, you know, totally openness, key components have to be open source, especially in security. I can give you several examples. The future of security is absolutely open source, the credibility cannot be gained without that. A quick example of that is cystic. I mean, who thought they were gonna be pulling such a huge, you know, funding round, of course that all is on the background of Falco, Right? So what I'm trying to play and sing and same for psyllium, Right? So what I'm clearly able to see is the science are that especially in cybersecurity community, you are delivering open source based platforms, you will have the credibility because that's where you will get the mindshare developers will come and you know, and work with you of course, you know, I have no shame naming fellow vendors right, who are doing this right and this is the right way to do it. >>Yeah. And I think it's it's totally true and you see the validation on that just to verify your point out that we have a little love fest here on open source, it's pretty obvious the the end user communities are controlled not the hard core and users like the hyper scholars, you know, classic enterprises are are starting not only contribute participate but add value more than they've ever have. The question I want to ask you is okay. I totally agree on open as data becomes super important because remember data is only as good as what you have and the more data the better the machine learning the better the data scale, um, sharing is important. So open sharing kind of ties into open source. What's your thoughts on data? Data policy, is this going to extend out into data control planes? What's your thoughts there? I'd love to get your input. >>We are a little little bit early in that thought. I think it's gonna take a little while uh for you know, the uh for the industry bosses to come to terms to that uh data lakes and uh you know, data control planes eventually will open up. But you know, I I see there is resistance in that space today uh but eventually it's gonna come around. You know, that has because that would be the next level of openness, you know, once the platforms uh in a mature as an example right today. Um you want to write uh you know, any kind of say policies for your same products, right. Uh you have the option available to write policies and customized, you know, languages. But then many platforms are coming up which are supporting policy is developed in in languages which are open and that's data which is going to open up, you know very soon. So you will not be measured in terms of how many policies you have as a product, but you will be measured. Can you consume? Open policies are not so i that it is going to go there, it's going to take a little while, but I think he is going to move that. >>It makes sense. Get the apparatus built on the infrastructure side. Once you have some open policy capability that's going to build an abstraction on top of it, then you can program data to be more policy driven or dynamic based upon contextual behavioural dynamics. So it makes a lot of sense. Oh, great insight here, love the conversation, Congratulations on your success. Love the vision. Love the openness. I'll see. We think uh data as code is big too. Obviously media's data where CUBA is open. We have we have the same philosophy. So thanks for sharing. Love the vision. Take a minute to plug the company. What are you guys looking to do? Uh you guys hiring, take a minute to put the plug out for the for the company? >>Absolutely. We are absolutely hiring great ingenious, you know, a great startup mind folks who want to come and work for a very, very innovative environment. Uh we are very research and development, you know driven and have brought various positions available today. Um we are trying to do something which has not been attempted before. Our focus is 100% on reducing the cost of security. And uh you know, in order to do that, you really have to do things that previously were not in development environments. And that's where we're going. We're open source uh, you know, open source initiatives, big open source lovers and we welcome people come in and apply our positions, >>reduce the cost of security, do the heavy lifting for the customer with code and have great performance, that's the ultimate goal. Great stuff. Cloud need security, threat modeling, deV stickups, shifting left in real time. You guys got a lot of hard problems you're attacking? >>Um well, you know, some of the good things uh that we're doing is also because of the team that we have right. Most of our co team comes from very heavy threat modeling, threat analysis and third intelligence background. So we have we're blending a very unique perspective of allowing developers to tackle the threats, which they're not supposed to even understand how they work. We do the heavy lifting from threat intelligence point of view, we just let the developers work on the code that we generate for them to fix those threats. So we're shipping threat intelligence and threat modeling also to left. Uh we're one of the first companies to create threat models just out of infrastructure is called, we read your infrastructure as code and we create a digital twin of your cloud late at one time, even before it has been actually built. So we do some of those things which we like to call it just advanced bridge card prediction where we can predict whether you have reach parts a lot in your runtime environment that would have been committed. >>And then the Holy Grail obviously the automation and self healing um is really kind of where you've got to get to. Right, that's the whole that's the whole ballgame, right? They're making that productive. Oh, thank you for coming on a cube here. Dr khan 2021 sharing your insights, co founder and CTO and see so. Oh much Danny. Thank you for coming on. I appreciate it, >>monsieur john thank you for having >>Okay Cube coverage of Dr Khan 2021. Um your host, John Fury? The Cube. Thanks for watching. Yeah.

>>from the Cube Studios in Palo Alto and Boston. It's the Cube covering empowering the autonomous enterprise brought to you by Oracle Consulting. >>Welcome to the special digital presentation where we're tracking the rebirth of Oracle Consulting. And my name is Dave Vellante. And we're here with Aaron Millstone. Who's the senior vice president of Oracle Consulting? Aaron, thanks for coming on. Good to talk to you. >>They appreciate you having me, and I like the introduction of the river. >>Well, it really is. I mean, you know, you guys have gone from staff augmentation to being much more of a strategic partner, and we're gonna talk about that. But I want to start with this team that you have about empowering the autonomous enterprise. It sounds good, you know, nice little marketing tag line, but give us give us what's behind that. Put some meat on the bone. >>Sure, So you know what we define is that time in this enterprise is really using artificial intelligence, using machine learning and using it to cognitively understand your actual data and processes using for enterprise and then really embedding that into everything you're doing as a company and using both Dr optimization and costs and increasing revenue. And I know that's a lot of kind of consulting to speak. So you know, we tend to think about and we've been talking about in terms of what we call try motile i t. And it's Ah, this is probably the most exciting space that I've really thought through with with my team as we build up a new consulting business, you pointed out. But this is really about pivoting away from, you know, the systems of record and the systems of interaction, and really building up the systems of intelligence capabilities that we see it all enterprises needing to invest in heavily if they're not already investing there early. >>Well, I want I want talk about a couple of things there. One is that notion of lowering costs and increasing revenue. And you're right, people say, Oh, yeah, that's insulting Speak. But good consultant digs in. It starts peeling the onion. Well, how do you How do you actually make money? You know, where are the inefficiencies in your business? And that's really what you're talking about. And that's what every business wants to know, right? Is is not. That's the end game. But the how to is really what separates the good consultants from the pack. >>Yeah, right. And we're again. We're on this journey now. We've been, you know, you mentioned it right where I'm two years into Oracle consulting myself. I spent 23 plus years at Accenture when I was a managing director with them in part of their North America leadership team. When I came over to work something we did, we pivoted from what you called staff augmentation business to a basic set of offerings which were things that you recognize right migration, services of workloads to cloud or integration of security where you know, even ah ah ah It has for SAS augmentation that we would do But, you know, pretty basic services. We're now pivoting again into sort of two areas. Infrastructure led transformation, which is really our old costs Take out play a Z You just said and sort of good consultants know how to do that. And really, what that is is we're going. I'm looking at companies that still have traditional data centers. Or maybe they've got some things on clouds and some things that still in traditional data centers and we're coming in and we're saying there's a business case here. It looks at your total cost of ownership, and we think we can take out between 40 and 65% of your run rate bus. And that's everything from, you know, facilities, fire suppression systems through to the actual compute costs through to the labor that's required to, you know, do the physical hands on activities in the data center. Right. So, you know, we have that sort of capability, and we're pushing customers hard in that space at the moment. And then driving that into a secondary conversations is, And by the way, with all these savings, you kind of have two choices, right? You can pocket the savings, obviously, or right, we would propose that you go into what we're calling the condoms enterprise space and really building up your artificial intelligence machine learning capability with centralized capabilities. Central as data versus letting every line of business every department do it >>on their own. >>So to me. But let me ask you, does that make sense? But why your cloud? You were sort of ah later entrance into cloud. So where does cloud fit into this How do you respond to a customer? Say Yeah, but you know, you guys relate. Well, >>yeah, we are. We are definitely late coming to cloud, right? There's no no two ways about it. I mean, what we to what we've got is we have what we call a generation too. And, you know, I jokingly tell customers that we have a late mover advantage and that late mover advantage basically means that we've looked at what the first generation clouds have done and, quite frankly, there they're great at what they do. They're fierce competitors. They're tough to compete with. They've got a lot of mindshare, but they fundamentally we're about targeting consumers or targeting enterprise collaboration tools. Right? So if you want cat videos, if you want to watch you humorous videos that people filmed and posted on social media was a great clouds for that stuff. But if you want really mission critical enterprise cloud workloads, right? That's where we come into play. And so when you start to look at really the key differentiators in our cloud and you know fraud, these this is how I describe it, asked me. Right. So you know, we look at sort of three layers. We have an autonomous capability, both in our operating system or database. What that basically means is that we have machine learning and artificial intelligence that's driving the key, you know, administrative activities in our cloud. We then have our exit data platform. So exit data for us is a secret weapon, right? We we think that it is a differentiator in our products. And so, you know, exit data for those for those watching that don't know what it is, right? So exit data emerged out of the sun acquisition that work well did. It is purpose built hardware that is engineered for our software products, specifically about databases. And now we've taken that concept and moved it into our cloud. And so, you know, customers can come in and take very intensive enterprise mission Critical workloads run him straight in our cloud. And then, you know, when we look at the last point, it's probably security. Where again we have total segmentation of our security layers that from the customer workloads, right. So again, we've we've taken the concepts that first generation cloud providers have implemented, and they scale it globally. So it's really tough for them to walk back on it. It's a huge investment and we're have gone into a generation to cloud, and quite frankly, that's I think that's what this is, the frontier that you know. Everyone's racing to kind of crack, >>So we got to wrap. But I want to close on sort of the again. We're talking about good consultants and good consultants have continuous improvement mindset. They got a North Star that they really never get doing that that keeps moving because you got to keep innovating. You gotta keep disrupting yourself. So maybe you could end by sort of talking about some of the things you're watching, some of the milestones you want to hit and some of that transformation that you want to keep going. How are you gonna achieve that? >>Yeah, we'll get some of that. We hit the Deloitte segment too, right? But we're definitely we've moved from. We've definitely moved from, you know, the staff augmentation to offer it to basic offerings. We're now beyond that. We're starting to sell the infrastructure led transformation plays. What's exciting to me about that with our customers is you know, Oracle is a big complex and impress, as you'd expect with, you know, >>a >>company that has a tremendous amount of technology. We're now bringing holistic approaches to our customers. They let us help you optimize everything, and then let's look at your data center. That's not look at a narrow slice. Let's not look at just sys, admin and DBS. We're looking at things comprehensively, so moving there has been a pretty big milestone for us to hit. We started to get some good momentum with our customers. Our next milestone is really gonna be taking that on time center present, blowing it out. We're in use case, an incubation period right now with that, But again, we've got some. I would argue we have the best talent in the world right now that thinks about this stuff and not not just thinking about it from a pure technology stand point, but things about how to actually make it effective for the business. And so once we get some of those motions going >>to >>take the use case for the autonomous enterprise, that's artificial intelligence driven. It should have a continuous pace of change, and it's going to start to evolve in areas that. You know, quite frankly, we can't even predict yet, but we're excited to see where it leads. >>Well, thanks for spending some time with us. I am very excited to talk about that sort of collision course between your deep tech capabilities as Oracle as a product company and this global aside deployed, we're gonna We're gonna bring in those guys in a moment. But so thanks very much for taking us through the transformation and great job. Good luck. >>Thank you. Appreciate it. >>Alright. And thank you, everybody for watching. Keep it right there. We'll be back with more coverage of Oracle's transformation. Right after this short break, you're watching the cube?

(upbeat music) >> Everybody, welcome to this special digital presentation where we're tracking the rebirth of Oracle Consulting. And my name is Dave Vellante, and we're here with Aaron Millstone who's the senior vice president of Oracle Consulting. Aaron, thanks for coming on, good to talk to you. >> Dave, appreciate you having me and I like the introduction of a rebirth of Oracle Consulting. >> Well, it really is I mean, you know, you guys have gone from staff augmentation to being much more of a strategic partner and we're going to talk about that. But I want to start with this theme that you have about empowering the autonomous enterprise. Sounds good, you know, nice little marketing tagline. But give us what's behind that, put some meat on the bone? >> Sure, so you know, what we define as autonomous enterprise is really using artificial intelligence, using machine learning and using it to cognitively understand your actual data and processes you're using for your enterprise. And then really embedding that into everything you're doing as a company, and using it to be both drive optimization and costs, and increasing revenue. And I know that's a lot of kind of consulting speak. So, we tend to think about what we've been talking about in terms of what we call tri-modal IT. This is probably the most exciting space that I've really thought through with my team, as we build up a new consulting business, you pull it out, but this is really about pivoting away from the systems of record and the systems of interaction, and really building up the systems of intelligence capabilities that we see all enterprises needing to invest in heavily, if they're not already investing there already. >> Well, I want to talk about a couple of things there. You know, one is that notion of lowering cost or increasing revenue and you're right people say, Oh, yeah, that's consultancy people, but a good consultant digs in and starts peeling the onion. Well, how do you actually make money? You know, where are the inefficiencies in your business? And that's really what you're talking about, and that's what every business wants to know, right? That's the end game, but the how to is really what separates the good consultants from the pack. >> Right right. And we're, you know, again, we're on this journey now, we've been, you mentioned it right. I'm two years into Oracle Consulting. Myself, I spent 23 plus years at Accenture, where I was a managing director with them and part of their North American leadership team. When I came over to Oracle consulting we did, we pivoted from what you called staff augmentation business to a basic set of offerings, which were things that you recognize right migration, services of workloads to cloud or integration or security work or even, step paths for SAS augmentation that we would do, but you know, pretty basic services. We're now pivoting again into sort of two areas infrastructure and transformation, which is really our bold costs take out play, as you just said, and sort of good consultants know how to do that. And really what that is, is we're going and looking at companies that still have traditional data centers, or maybe they've got some things on clouds, and something's still in traditional data centers. And we're coming in, and we're saying there's a business case here, that looks at your total cost of ownership. And we think we can take out between 40 and 65% of your run rate costs, and that's everything from, facilities, fire suppression systems, through to the actual compute cost, through to the labor that's required to do the physical hands on activities in the data center. So, we have that sort of capability and we're pushing customers hard in that space at the moment, and then driving that into a secondary conversation system and by the way, with all these savings, you kind of have to choices. You can pocket the savings, obviously or we would propose that you go into what we're calling the autonomous enterprise space, and really building up your artificial intelligence machine learning capability with centralized capabilities, centralized data, versus letting every line of business, every department do it on their own. >> Now, the other thing a good consultant does is they make the initiative self funding, and that's a win win you keep getting paid, the customer makes money, that's a good thing. But I like the idea, you're starting with the obvious business case of cost, and I think I heard you really attacking OPPEX, labor is obviously big component of that, but it's not just labor, and then you transition if they don't pocket the gain to a gain sharing going forward to look for new revenue. Did I get that I get that right? >> Yeah, you actually got that right. And actually, what I'll tell you too, is I think the labor piece, again, you know, I came from Accenture, Accenture is big outsourcing company, big technology consulting, big strategy consulting. You know, I went in for years and did pitches on outsourcing arrangements which were fundamentally lower cost bodies running in a more effective way. What we're finding or what I'm finding with customer conversations over the last two years at Oracle has been actually I think, data centers are not, there's nothing competitively advantageous about having a data center if you're a company, there is a lot of advantageous. There's an advantage to having cloud and what we're seeing is that companies that might have outsourced their data center are just the lowest cost provider are now considering insourcing or co-sourcing as they pivot the cloud. So the funny thing is actually labor savings is not the big driver of that 40 to 65%, that plays a role of course, that's how you get to the 65%. But even go into the 40% you can get there by insourcing your labor and bringing them in house and recognizing that the speed at which you can operate on your cloud gives you a competitive advantage. >> So this requires a whole new skill set for Oracle, you mentioned, you came in from Accenture where I talked to another number of other folks in Oracle's North America Consulting Operation that came from, brand name firms, we're going to be talking to Deloitte we have and will continue. So there I know, a big part of you talk about the skills transformation that you've affected inside of Oracle Consulting. >> Sure, yeah I mean, it started when I showed up. It was primarily a staff augmentation business in our commercial space in particular, you know, if you need a DBA, here's a DBA. If you need a SAS admin, here's a SAS admin. Here's the hourly rates and quite frankly, very, very talented group of people, very talented, but focused on doing, you know, sort of nuts and bolts level work, very deep work on the Oracle technology stack, but also weren't particularly cloud certified. So we started by focusing on getting the team certified in our cloud products, invested a ton of hours, thousands and thousands of hours in training. It takes you know, we're doing something like six months investment initially to get people up and certified on multiple cloud products that Oracle is selling. And then right from there, we started putting together our basic offerings, again moved from staff augmentation to saying, look, would you like to move a workload. To move a workload is going to cost a fixed price, whatever that is 100, $200,000 move away from rate card conversations with augmentation. And we shifted the commercial contracts that had payments based on outcomes so they don't move successfully, there's no payment. And so you know that was really the focus. >> I'm going to come back to this notion of gain sharing and particularly focus on the revenue side for a moment. You mentioned a what I'll call a buzzword tri-modal IT and a buzzword because Gartner kind of with bimodal IT popularized that concept. And I think part of the problem that people had with bimodal IT was kind of had the legacy systems of record and then you had all the new cool stuff, the big data and you know now AI and systems of engagement and so forth. And everybody wanted to go to the ladder and run away from the former. But now, if I understand tri-model IT, you're talking about bringing machine intelligence to both of those spheres such that people can stay current, stay relevant and add new value to their organization. >> Yeah, that's exactly it. And we're trying to bring it to both but we're trying to make it its own sphere, independent of the other two. So, again, as we looked at this consulting evolution, I didn't come over to Oracle and Oracle is not interested in us, creating a consulting business, that's a me too consulting business that kind of looks like whatever everyone else is doing. So the goal really was okay. So if we started with sort of staff augmentation, and you know, really Oracle's legacy, a system of record stuff, we sell big back office systems, we have mission critical databases. Like it's the clunky stuff that has to work, but really at the end of the day, that's our heritage, going over to the systems of interaction which is, where the bimodal IT really came in from Gartner. That's a pretty saturated place, so again, coming from the background, I had a consulting, I looked at all the eight design agencies that were out there that were all selling digital, and we looked at the digital sales tactics going on, we're like, well, that's pretty saturated, it's not really a smart place for us to go make a lot of headway into. And so we looked and said, well really, the next layer, the next evolution of IT is this third sphere systems of intelligence. And really, since Oracle is, our heritage is mission critical and data, fundamentally, the logical step for us was to go okay, systems intelligence are powered by data, and they serve artificial intelligence as the primary consumer. So again, our thought process was you have a system of record which is process centric and really geared towards the CFO or a head of HR, you have systems of interaction, which is really geared towards the users, it's trying to make business frictionless. Those users can be consumers, they can be employees, whomever. And then systems intelligence is around artificial intelligence is the primary consumer of it. I mean really pivoting to that, and then making that something that is pervasive and structurally place across both those other two spheres, really felt like where we should be differentiating. When I brought in the talent rate that we looked to bring in, we were getting kind of affirmation that, yeah, the best talent in the market was starting to see this trend and so we kind of knew we were onto something there. >> Yeah, I mean, that makes a lot of sense, because as you as you point out, some of those new workloads, many of them are very consumer oriented, that's kind of you know, not your wheelhouse. I mean, that's your customers are, selling to consumers, but Oracle's B2B, hardcore data mission critical. But let me ask you, to that make sets, but by your cloud, you were sort of a later entrant into cloud. So where does cloud fit into this? How do you respond to when customers say, yeah, but you know, you guys were late on the cloud. >> Yeah, we are definitely late coming to cloud, like there's no two ways about it. I mean, what we've got is we have what we call a Generation 2 Cloud. And I jokingly tell customers that we have a late mover advantage. And that late mover advantage basically means that we've looked at what the first generation clouds have done. And quite frankly, they're great at what they do, they're fierce competitors, they're tough to compete with, they've got a lot of mindshare, but they fundamentally were about targeting consumers, or targeting enterprise collaboration tools, so if you want cat videos, if you want to watch humorous videos that people filmed and posted on social media, those are great clouds for that stuff. But if you want really mission critical enterprise cloud workloads, that's where we come into play. And so when you start to look at really the key differentiators in our cloud and through out, at least this is how I describe it to customers. So, we look at sort of three layers, we have an autonomous capability both on our operating system and our database. What that basically means is that we have machine learning and artificial intelligence that's driving the key, administrative activities in our cloud, we then have our Exadata platform. So Exadata for us is a secret weapon, we think that it is a differentiator in our products. And so, Exadata for those watching that doesn't know what it is, so Exadata emerged out of the Sun acquisition that Oracle did. It is purpose built hardware that is engineered for our software products, specifically our databases. And now we've taken that concept and moved it into our cloud and so customers can come in and take very intensive enterprise, mission critical workloads, run them straight in our cloud. And then, when we look at the last point, it's probably security where, again, we have total segmentation of our security layers from the customer workloads. So again, we've taken the concepts that first generation cloud providers have implemented, and they've scaled it globally. So it's really tough for them to walk back on it, it's a huge investment and we're now gone into a Generation 2 Cloud and quite frankly, I think that's what this is the frontier that everyone's racing to kind of grab. >> You know, we actually in our community, talk to a lot of Exadata customers and they get very intense, they do some really hardcore things with with Exadata. To me, the key to your cloud strategy, and specifically Exadata is you've got the same exact infrastructure, control plane, data plane, software, either on prem or in the cloud. So that's your same same narrative. But the real key, new key anyway is what autonomous, tell me if you agree with this. What autonomous gives you a scale, because as you say, you're related to cloud, you're not a hyper scalar in that sense, you're not selling just, race to the bottom infrastructure as a service. You're bringing applications and mission critical applications, so eponymous gives you the ability to scale and compete more effectively with some of those other, earlier movers. You buy that? >> Yeah, absolutely. So scaling and scaling in terms of, what has been historically human activities, when I say human activities, we're not replacing the humans, we're making some of the human activities that were highly repetitive way more efficient. So easy example I can give you is patching. Like security(mumbles) bases are very time consuming, I've talked to customers as recently as a couple weeks ago, that are three years behind on their patching. And when I look at that, it's you're like, why wouldn't you consider autonomous, they have their board of directors and their auditors are actually now demanding that they do something different about their patching problems. And they're talking about, man months, people months of trying to roll out this patching, and they're worried about breaking stuff, and they're worried about human error. Like when you look at something like autonomous, that patching would take place, pretty much instantaneous with no downtime. And we've seen it in our own cloud and our own services internally and we're able to patch, thousands and thousands of cores very, very quickly. >> So we got to wrap but I wanted to close on sort of the, I mean, again, we talked about good consultants and good consultants have continuous improvement mindset. They got a North star that they really never get through and that keeps moving because you got to keep innovating, you got to keep disrupting yourself, so maybe you could end by sort of talking about some of the things you're watching, some of the milestones you want to hit and some of that transformation that you want to keep going. How are you going to achieve that? >> Yeah, and it will skip some of it, when we hit the Deloitte segment too, but like we're definitely we've moved from, we've definitely move from the staff augmentation to basic offerings. We're now beyond that we're starting to sell the infrastructure lead transformation plays. What's exciting to me about that with our customers is, you know, Oracle's a big complex enterprise, as you'd expect with a company that has a tremendous amount of technology. We're now bringing holistic approaches to our customer say, let us help you optimize everything end to end, let's look at your data center, let's not look at a narrow slice, let's not look at just SAS admins and DBAs, we're looking at things comprehensively. So moving there has been a pretty big milestone for us to hit, we've started to get some good momentum with our customers. Our next milestone is really going to be taking that autonomous enterprise and blowing it out. We're in use case and incubation period right now with that, but again we've got some, I would argue we have the best talent in the world right now that thinks about this stuff and not just thinks about it from a pure technology standpoint, but thinks about how to actually make it effective for the business. And so once we get some of those motions going, like the use case for the autonomous enterprise that's artificial intelligence driven, it should have a continuous pace of change, and it's going to start to evolve in areas that you know, quite frankly, we can't even predict yet. But we're excited to see where it leads. >> Alright, thanks for spending some time with us. I am very excited to talk about that sort of collision course between your deep tech capabilities as Oracle as a product company and this, the Global SI, Deloitte, we're going to bring in those guys in a moment. So thanks very much for taking us through the transformation and great job, good luck. >> Thank you, appreciate it. >> All right, and thank you, everybody for watching. Keep right there, we'll be back with more coverage of Oracle's transformation. Right after the short break, you're watching the CUBE. (upbeat music)

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

>>Live from Atlanta, Georgia. It's the cube covering Ansible Fest 2019. Brought to you by red hat. >>Welcome back everyone. Live cube coverage here in Atlanta. This is the keeps coverage of Ansible Fest. This is red hat and suppose two days of live coverage. They had a contributor day yesterday before the conference all being covered by the cube. I'm John furrier, Miko Stu Miniman. Our next guest is Chris Gardner, principal analyst at Forrester Gardner. Welcome to the cube. Thanks. See you. Good to talk to you. Hey, analyzing the players in this space is really challenging. You've got a new wave that came out a few months ago. Yep. Laying it all out. Um, certainly the world changed. You go back eight years. Cloud was just hitting the scene on premises. Look good. Data's Stanley was rocking. You're doing network management, you're doing some configuration management now you've got observability, you've got automation apps. The world's changing big time. What's your take? What's this? I mean, it's interesting because the prior versions of that wave focused entirely on configuration management and the feedback I got was, um, the world's a lot bigger than that, right? >>And we have to talk about platforms and you heard it this morning during the keynote about Redhat moving towards an platform and automation platform. And my definition of a platform is things like configuration management, hybrid cloud management, all the various types of automation and orchestration need to be there. But you also need compliance. You need governance, you need the ability to hopefully make a call as to what is actually occurring and have some intelligence behind the automation. And obviously you need the integrations. It's not a situation to simply have as many people as possible, although that's nice as many vendors you work with. But to have real relationships, if you have Microsoft working on automation code with you, if, if Amazon working on automation code with you, that makes a true platform, right? It's John said earlier day a platform needs to be an enabler. And we've even said, if you can't build on top of this, like the collections that Ansible announced here seems like it might fit under that definition. >>And there's an old joke that everything becomes a platform eventually. Right? Um, but I think that, I think it bears it. There's some merit in this one. Um, the other thing is that I'm seeing a lot of folks want a holistic automation solution and the only way you're going to do that is to have a platform that you can build things on top of it and connect the pieces and provide the proper governance. So, um, I'm mostly in agreement with the definition that's been described here and I think you could tackle different ways. Uh, and all the vendors in the space are certainly doing that. Definitely platform thinking is different. Um, you know, the easy way to look at it and the old big data space do, we'll use to cover that was a tool versus a platform, you know, tools, a hammer, everything looks like a nail, did great things. >>One thing great are a few things. Good platform is more of a systems thinking. Yes, yes. And you've got glue layers, you've got data. So it's really more of that systems thinking that separates the winners from the losers, at least at our opinion. Absolutely. I mean, when you looked at who was the leaders in my wave, it wasn't the basics of automating or orchestration and configuration management, they all had that. The, the ones that were winners, where can I do compliance in a different way? Can I actually have people come into the system that aren't it people and make a call on some of these things? Can I apply AI and machine learning to some of this? Can I make some recommendations and hopefully direct people in the right, you know, the way they should go. And you know, the folks that were able to do that Rose to the top, the folks that weren't were average and below. >>Yeah. Chris bring us inside to some of the competitive dynamics here. We understand that, you know, there's a lot of open source here and therefore everybody holds hands and things can buy y'all. But, you know, there's, you know, product tools, there's the public clouds and what they do. And then, you know, Ansible, uh, you know, fit, fits in a lot of different places. Yeah. It's, it's a bit ironic because, uh, you know, this is one of those waves where, and it's very rare that everyone was sitting was, was at least preaching kumbaya. They are all saying that they were friendly with one another. And, and, uh, quite frankly, I, I tend to believe it. We're in a situation right now where you can't get by, especially in a hybrid cloud world. We are going to have resources that live in multiple, you know, AWS and Azure, but also on premises and at the edge. You need to have these integrations. You need to be able to talk to one another. So, um, that said, there's certainly a lot of coopertition going on where people are saying, if I can integrate these tools better, if I could provide a better governance layer, if I can again, hand things off to the enterprise in a way that has not been handed off before that I don't even have to go through an INO group and infrastructure operations group, those are willing, could be the ones that truly succeed in this space. >>Software defined data center, software defined cloud, everything software defined. Yep. These abstraction layers, data and software. We had a guest on the cube a week ago saying, data's the new software I get. Okay, it's nice, nice gimmick. But if you think about it, this abstraction layer, it's like a control plan. Everyone wants to go for these control planes, which is a feature of platform. As this automation platform becomes ultimately the AI platform, how do you see it evolving and expanding? Because you see organic growth, you see certainly key positions, 6 million stars on get hub. I mean, it's running the plumbing. I mean, come on. Like it's not, it's not like it's just some corner case. >>Yeah, yeah. Infrastructure. Yeah. I mean, you know, in an idealistic way, I'd like to see, we us resolve on singular holistic platforms for enterprises. The reality is that's not not the way you can do it today. What I do try to help clients do is at least rationalize their portfolio. If they have 12 different automation products they're running, chances are that's not the best idea. Um, I've actually had situations where someone will say to me, um, I'm running Ansible in one portion of my organization and chef and another, and I say, well, it's some, they do similar things. And the reason for it was because they were stood up organically. Each group kind of figured out the things along the way. And I have to at least guide them and say, you know, where are the similarities? Where can you potentially, you know, move some stuff from there. >>But the cloud discussion, you know, always debate upon, you know, multi-cloud, Seoul cloud, ultimately the workload needs something underneath. And I think workload definition dictates kind of what might be underneath. So it might be okay to have a couple, you know, automation platforms or it could be great to have one. I mean, this is really the eye of the beholder. Beauty is in the eye of the, >>yeah, in my view. Um, I, I've been an analyst for a couple of years before that I was doing this stuff for a living. I have the worst scars and in my view it's, it's not even a matter of how many tools you use. It's putting the workload where it belongs, that matters. And if you could do that with fewer tools, obviously that from an operational level that makes life a lot easier. Um, but I'm not going to say to somebody, you know, completely dismantle your entire automation and orchestration workflow just because I think this one tool is better. Let's talk about how we can, >>that's the worst case scenario because if you have to dictate workloads based on what tool you have, that's supposed to be the other way around. >>Yes. Setting up a nuclear bomb in the data center or in the cloud has never worked. Note to self, don't do that. Yes. One of the interesting conversations we've already been having here at the show is that the tool is actually helping to drive some of the cultural change in collaboration. So, you know, what are you finding in your research? How is that, you know, kind of this admin role and you know, to the cloud in applications. You know, it's interesting. I, we continued to beat the drum that these folks are becoming developers, but we've been beating that drum for a decade now and quite frankly we had to continue to beat it. But what I think is more even more interesting is we have groups starting to pop up in our research that are separate from it, that focus on automation in a way that no one has done before. >>Some we went into it saying, Oh, that's a center of excellence, right? And the teams that we talked to said no, do not call us a center of excellence. A two reasons. One is that term is tainted. Uh, but secondly, we're not one team. There's multiple automation teams. So we're actually starting to call these groups, strike teams that come in and standardize and say, okay, I have a lead architect, a lead robot architects say it's around infrastructure automation. I'm going to standardize across the board and when other groups need to come on board, I have the principles already laid out. I have the, the process is already laid out. I come in, I accelerate that, I set it up and then I back off. I don't own the process and I'm not part of it either. I T's got operations of its own that's got to worry about. >>I'm going between the two and when we talk to especially the fortune 100 they are setting these groups up. Now when I ask them what do you called them? They don't have a name yet, so I think strike team sounds sexy, but ultimately this is not like a, a section of it that's been severed off and becomes this role. It's a completely true committee. I yeah. Oh yeah. I want our falls slow process. Exactly, exactly. And it better fits what the role is. The role is to come in, nail the process, get it automated and the get out. It's not to stand there and be a standards body forever. Um, there's certainly some groups that in some types of automation like RPA where you want them to stick around because you may want them to manage the bots. There's a whole role called bot masters, which is specifically for that role. But most of the time you want them to be part of that process and then you know, hand it back off. >>Yeah. We've seen some interesting patterns. I want to get your thoughts on this as a little bit of a non-sequitur. Want to bring it in, but in the security space you seeing a CSOs chief information security officers building their own stacks internally, they're picking one cloud, Amazon or Azure and they're building all in maybe some hedge with some people working on some backup cloud, but they don't want to fork their talent all on one cloud and they cause they need to be bad ass responsive strike teams for security pressure. Yeah, yeah, absolutely. Not as critical with the security side with automation, but certainly relevance. Is that the same thing going on here with this development Durham, this being continued to be as much more around core competency and building internally stacks and building some standards? >>I I, I think it is, and you know what's interesting too is that I work with, I'm on the infrastructure and operations team at Forrester. I talk with INO people all day long, but I work alongside the security team and I said to them a couple of years ago, um, you guys are going to have to get your hands dirty with this stuff that I cover. You guys have to know infrastructure, automation, API APIs, you need to know how to code these things. And I said, are you comfortable telling your sec ops folks, your clients that they go, no, by all means they have to be part of this. So they're okay with them talking to me, talking to them and saying that you need to be part of the infrastructure design process and need to be part of this decision making process. Right. Um, which is different than their sec ops role used to be. So my point is, is that these worlds are not that dissimilar as some people might think they are sec dev ops or whatever we're going to call it. We keep tacking letters onto this thing, uhm, is a actual discipline. And it is a reality in most organizations I talked to the people should. >>So a system has all of these things as data across the system. They have high blood subsystem you're talking about and yet it's this holistic system security and data. Yeah. >>And we're in a world now, especially around things like edge computing where data gravity matters. So all these pieces, you know, it's, if you go back to the old school kind of computer science folks from the, you know, 50 sixties and seventies, they're like, this is not new. We've been thinking systems thinking for awhile, but I think we're finally at a place where we're actually now breaking down the silos that we've been championing to do. So for, >>I got to ask you the analyst questions since you're watching the landscape. Sue wants to jump in, but I want to get this out. So observability became a category at a network management. I mean, network management was like this boring kind of plotting along white space. I mean, super important. People need to do network management. Then in comes the cloud becomes a data problem. Whether it's observability you get to microservices, you got security signal FX, all these companies going public. Um, well a lot of M and a activities basically large segment, a lot of frothiness automation feels like it's growing to be big. Is there startup opportunities here? If, if platforms are becoming being a combination of things, is there room for startups and if so, what would you say? Um, those stars would look like? There are, I think >>what we're seeing is, and it speaks to the observer, observe the word you just said. Um, uh, I can, I can S I can know what it is, but I can't say it. Um, we're seeing the APM vendors move down the stack. We're seeing the infrastructure monitoring vendors move up the stack and in the middle we're seeing them both try to automate the same things. Um, you cannot pull off some of the infrastructure as code automation that we need to pull off without observability, but you can't get that observability unless you are able to pull it from the top of the stack. Um, what we're going to see is consolidation and we're already starting to see it, um, where you're gonna have different groups come together and say, why did have to tools to do this? Why not do one? Um, the reason why you do multiple tools today is because no one is truly strong at the entire stack. >>A lot of the folks that are going down the stack to say that they're not quite infrastructure automation players just yet, but watch this space, they will eventually, Oh, this change happening. Absolutely. Startups getting funded. Do you think there's opportunity to take some territory down? If there's any opportunity? And, and I'm, I'm pushing for this, it's in the AI AI ops space when it comes to these things is actually going beyond where we stand today. So I want to be clear that, um, AI ops is a great concept. The reality of is that we're still a ways away from being practical. I'd like to see not just recommendations from these tools that the startups are providing, but actually trust in them to make the changes necessary. So Chris, it sounds like the antibody automation platform announcement today fits with what you've been saying for the last couple of years. >>So the question is, what's next? Where does the Ansible need to mature and expand and you know, what, what are users asking for that Ansible is not doing today? So a couple things. Um, they did okay, but not fantastic at infrastructure modeling. Ansible. They did okay, but not amazing at what we call comprehension, which is making a call as to, you know, using AI and machine learning to make a call and what the infrastructure layers should look like. To be Frank, no one did really well in that one. So not too, not too bad on that. Um, and the other thing is they need to improve slightly. Is there integration story? They actually have a really good one. You see all the folks that are here. Um, it's just, it's, it's just as hair away from being the best. They're not quite there yet. So, and when, again, when I mean integrations, I don't mean having a laundry list of vendors you work with. >>I mean actually working with them to build code and you saw that this morning where there's the best, uh, right now surprisingly is VMware, but for you Morris built that relationship off for a long time. Um, they work right alongside Microsoft and Google and all these folks to build the code together in the industry. Uh, I think the darkest source of all is probably, and it remains to be seen if they can actually do something that is HashiCorp. Um, Terraform is an interesting player in this entire space. I actually included them in our wave on infrastructure automation platforms and you can argue is it even an automation platform? Quite frankly. Um, uh, I think HashiCorp itself was trying to figure out exactly what it is. But the bottom line is it's got tremendous Mindshare and it works well. So I think that if you watch, if you see the strategy going forward and look at, you know, what they're putting their investments into, they could become a really serious damaging player in this space. Chris Gardner, thanks for coming on the cube, sharing your insights and your research at Forrester forced wave. Check it out. Just came out a couple of months ago. Uh, infrastructure automation platforms. Q three 2019. Chris Gardner, the author here in the Q, breaking it down. I'm John furrier. There's too many men. We'll be back with more after the short break. Thank you.

>> Narrator: From Berlin, Germany, it's theCUBE (relaxing music) covering DataWorks Summit Europe 2018. (relaxing music) Brought to you by Hortonworks. (quieting music) >> Well, hello and welcome to theCUBE. We're here at DataWorks Summit 2018 in Berlin, Germany, and it's been a great show. Who we have now is we have IBM. Specifically we have Dave McDonnell of IBM, and we're going to be talkin' with him for the next 10 minutes or so about... Dave, you explain. You are in storage for IBM, and IBM of course is a partner of Hortonworks who are of course the host of this show. So Dave, have you been introduced, give us your capacity or roll at IBM. Discuss the partnership of Hortonworks, and really what's your perspective on the market for storage systems for Big Data right now and going forward? And what kind of work loads and what kind of requirements are customers coming to you with for storage systems now? >> Okay, sure, so I lead alliances for the storage business unit, and Hortonworks, we actually partner with Hortonworks not just in our storage business unit but also with our analytics counterparts, our power counterparts, and we're in discussions with many others, right? Our partner organization services and so forth. So the nature of our relationship is quite broad compared to many of our others. We're working with them in the analytics space, so these are a lot of these Big Data Data Lakes, BDDNA a lot of people will use as an acronym. These are the types of work loads that customers are using us both for. >> Mm-hmm. >> And it's not new anymore, you know, by now they're well past their first half dozen applications. We've got customers running hundreds of applications. These are production applications now, so it's all about, "How can I be more efficient? "How can I grow this? "How can I get the best performance and scalability "and ease of management to deploy these "in a way that's manageable?" 'cause if I have 400 production applications, that's not off in any corner anymore. So that's how I'd describe it in a nutshell. >> One of the trends that we're seeing at Wikibon, of course I'm the lead analyst for Big Data Analytics at Wikibon under SiliconANGLE Media, we're seeing a trend in the marketplace towards I wouldn't call them appliances, but what I would call them is workload optimized hardware software platforms so they can combine storage with compute and are optimized for AI and machine learning and so forth. Is that something that you're hearing from customers, that they require those built-out, AI optimized storage systems, or is that far in the future or? Give me a sense for whether IBM is doing anything in that area and whether that's on your horizon. >> If you were to define all of IBM in five words or less, you would say "artificial intelligence and cloud computing," so this is something' >> Yeah. that gets a lot of thought in Mindshare. So absolutely we hear about it a lot. It's a very broad market with a lot of diverse requirements. So we hear people asking for the Converged infrastructure, for Appliance solutions. There's of course Hyper Converged. We actually have, either directly or with partners, answers to all of those. Now we do think one of the things that customers want to do is they're going to scale and grow in these environments is to take a software-defined strategy so they're not limited, they're not limited by hardware blocks. You know, they don't want to have to buy processing power and spend all that money on it when really all they need is more data. >> Yeah. >> There's pros and cons to the different (mumbles). >> You have power AI systems, I know that, so that's where they're probably heading, yeah. >> Yes, yes, yes. So of course, we have packages that we've modeled in AI. They feed off of some of the Hortonworks data lakes that we're building. Of course we see a lot of people putting these on new pieces of infrastructure because they don't want to put this on their production applications, so they're extracting data from maybe a Hortonworks data lake number one, Hortonworks data lake number two, some of the EDWs, some external data, and putting that into the AI infrastructure. >> As customers move their cloud infrastructures towards more edge facing environments, or edge applications, how are storage requirements change or evolving in terms of in the move to edge computing. Can you give us a sense for any sort of trends you're seeing in that area? >> Well, if we're going to the world of AI and cognitive applications, all that data that I mighta thrown in the cloud five years ago I now, I'm educated enough 'cause I've been paying bills for a few years on just how expensive it is, and if I'm going to be bringing that data back, some of which I don't even know I'm going to be bringing back, it gets extremely expensive. So we see a pendulum shift coming back where now a lot of data is going to be on host, ah sorry, on premise, but it's not going to stay there. They need the flexibility to move it here, there, or everywhere. So if it's going to come back, how can we bring customers some of that flexibility that they liked about the cloud, the speed, the ease of deployment, even a consumption based model? These are very big changes on a traditional storage manufacturer like ourselves, right? So that's requiring a lot of development in software, it's requiring a lot of development in our business model, and one of the biggest thing you hear us talk about this year is IBM Cloud Private, which does exactly that, >> Right. and it gives them somethin' they can work with that's flexible, it's agile, and allows you to take containerized based applications and move them back and forth as you please. >> Yeah. So containerized applications. So if you can define it for our audience, what is a containerized application? You talk about Docker and orchestrate it through Kubernetes and so forth. So you mentioned Cloud Private. Can you bring us up to speed on what exactly Cloud Private is and in terms of the storage requirements or storage architecture within that portfolio? >> Oh yes, absolutely. So this is a set of infrastructure that's optimized for on-premise deployment that gives you multi-cloud access, not just IBM Cloud, Amazon Web Services, Microsoft Azure, et cetera, and then it also gives you multiple architectural choices basically wrapped by software to allow you to move those containers around and put them where you want them at the right time at the right place given the business requirement at that hour. >> Now is the data storager persisted in the container itself? I know that's fairly difficult to do in a Docker environment. How do ya handle persistence of data for containerized applications within your architecture? >> Okay, some of those are going to be application specific. It's the question of designing the right data management layer depending on the application. So we have software intelligence, some of it from open source, some of which we add on top of open source to bring some of the enterprise resilience and performance needed. And of course, you have to be very careful if the biggest trend in the world is unstructured data. Well, okay fine, it's a lot of sensor data. That's still fairly easy to move around. But once we get into things like medical images, lots of video, you know, HD video, 4K video, those are the things which you have to give a lot of thought to how to do that. And that's why we have lots of new partners that we work with the help us with edge cloud, which gives that on premise-like performance in really a cloud-like set up. >> Here's a question out of left field, and you may not have the answer, but I would like to hear your thoughts on this. How has Blockchain, and IBM's been making significant investments in blockchain technology database technology, how is blockchain changing the face of the storage industry in terms of customers' requirements for a storage systems to manage data in distributed blockchains? Is that something you're hearing coming from customers as a requirement? I'm just tryin' to get a sense for whether that's, you know, is it moving customers towards more flash, towards more distributed edge-oriented or edge deployed storage systems? >> Okay, so yes, yes, and yes. >> Okay. So all of a sudden, if you're doing things like a blockchain application, things become even more important than they are today. >> Yeah. >> Okay, so you can't lose a transaction. You can't have a storage going down. So there's a lot more care and thought into the resiliency of the infrastructure. If I'm, you know, buying a diamond from you, I can't accept the excuse that my $100,000 diamond, maybe that's a little optimistic, my $10,000 diamond or yours, you know, the transaction's corrupted because the data's not proper. >> Right. >> Or if I want my privacy, I need to be assured that there's good data governance around that transaction, and that that will be protected for a good 10, 20, and 30 years. So it's elevating the importance of all the infrastructure to a whole different level. >> Switching our focus slightly, so we're here at DataWorks Summit in Berlin. Where are the largest growth markets right now for cloud storage systems? Is it Apache, is it the North America, or where are the growth markets in terms of regions, in terms of vertical industries right now in the marketplace for enterprise grade storage systems for big data in the cloud? >> That's a great question, 'cause we certainly have these conversations globally. I'd say the place where we're seeing the most activity would be the Americas, we see it in China. We have a lot of interesting engagements and people reaching out to us. I would say by market, you can also point to financial services in more than those two regions. Financial services, healthcare, retail, these are probably the top verticals. I think it's probably safe to assume, and we can the federal governments also have a lot of stringent requirements and, you know, requirements, new applications around the space as well. >> Right. GDPR, how is that impacting your customers' storage requirements. The requirement for GDPR compliance, is that moving the needle in terms of their requirement for consolidated storage of the data that they need to maintain? I mean obviously there's a security, but there's just the sheer amount of, there's a leading to consolidation or centralization of storage, of customer data, that would seem to make it easier to control and monitor usage of the data. Is it making a difference at all? >> It's making a big difference. Not many people encrypt data today, so there's a whole new level of interest in encryption at many different levels, data at rest, data in motion. There's new levels of focus and attention on performance, on the ability for customers to get their arms around disparate islands of data, because now GDPR is not only a legal requirement that requires you to be able to have it, but you've also got timelines which you're expected to act on a request from a customer to have your data removed. And most of those will have a baseline of 30 days. So you can't fool around now. It's not just a nice to have. It's an actual core part of a business requirement that if you don't have a good strategy for, you could be spending tens of millions of dollars in liability if you're not ready for it. >> Well Dave, thank you very much. We're at the end of our time. This has been Dave McDonnell of IBM talking about system storage and of course a big Hortonworks partner. We are here on day two of the DataWorks Summit, and I'm James Kobielus of Wikibon SiliconANGLE Media, and have a good day. (upbeat music)