Breaking Analysis: Amping it up with Frank Slootman
>> From theCUBE studios in Palo Alto in Boston, bringing you data-driven insights from the cube and ETR, this is Breaking Analysis with Dave Vellante. >> Organizations have considerable room to improve their performance without making expensive changes to their talent, their structure, or their fundamental business model. You don't need a slew of consultants to tell you what to do. You already know. What you need is to immediately ratchet up expectations, energy, urgency, and intensity. You have to fight mediocrity every step of the way. Amp it up and the results will follow. This is the fundamental premise of a hard-hitting new book written by Frank Slootman, CEO of Snowflake, and published earlier this year. It's called "Amp It Up, Leading for Hypergrowth "by Raising Expectations, Increasing Urgency, "and Elevating Intensity." Hello and welcome to this week's Wikibon CUBE Insights, powered by ETR. At Snowflake Summit last month, I was asked to interview Frank on stage about his new book. I've read it several times. And if you haven't read it, you should. Even if you have read it, in this Breaking Analysis, we'll dig deeper into the book and share some clarifying insights and nuances directly from Slootman himself from my one-on-one conversation with him. My first question to Slootman was why do you write this book? Okay, it's kind of a common throwaway question. And how the heck did you find time to do it? It's fairly well-known that a few years ago, Slootman put up a post on LinkedIn with the title Amp It Up. It generated so much buzz and so many requests for Frank's time that he decided that the best way to efficiently scale and share his thoughts on how to create high-performing companies and organizations was to publish a book. Now, he wrote the book during the pandemic. And I joked that they must not have Netflix in Montana where he resides. In a pretty funny moment, he said that writing the book was easier than promoting it. Take a listen. >> Denise, our CMO, you know, she just made sure that this process wasn't going to. It was more work for me to promote this book with all these damn podcasts and other crap, than actually writing the book, you know. And after a while, I was like I'm not doing another podcast. >> Now, the book gives a lot of interesting background information on Slootman's career and what he learned at various companies that he led and participated in. Now, I'm not going to go into most of that today, which is why you should read the book yourself. But Slootman, he's become somewhat of a business hero to many people, myself included. Leaders like Frank, Scott McNealy, Jayshree Ullal, and my old boss, Pat McGovern at IDG, have inspired me over the years. And each has applied his or her own approach to building cultures and companies. Now, when Slootman first took over the reins at Snowflake, I published a Breaking Analysis talking about Snowflake and what we could expect from the company now that Slootman and CFO Mike Scarpelli were back together. In that post, buried toward the end, I referenced the playbook that Frank used at Data Domain and ServiceNow, two companies that I followed quite closely as an analyst, and how it would be applied at Snowflake, that playbook if you will. Frank reached out to me afterwards and said something to the effect of, "I don't use playbooks. "I am a situational leader. "Playbooks, you know, they work in football games. "But in the military, they teach you "situational leadership." Pretty interesting learning moment for me. So I asked Frank on the stage about this. Here's what he said. >> The older you get, the more experience that you have, the more you become a prisoner of your own background because you sort of think in terms of what you know as opposed to, you know, getting outside of what you know and trying to sort of look at things like a five-year-old that has never seen this before. And then how would you, you know, deal with it? And I really try to force myself into I've never seen this before and how do I think about it? Because at least they're very different, you know, interpretations. And be open-minded, just really avoid that rinse and repeat mentality. And you know, I've brought people in from who have worked with me before. Some of them come with me from company to company. And they were falling prey to, you know, rinse and repeat. I would just literally go like that's not what we want. >> So think about that for a moment. I mean, imagine coming in to lead a new company and forcing yourself and your people to forget what they know that works and has worked in the past, put that aside and assess the current situation with an open mind, essentially start over. Now, that doesn't mean you don't apply what has worked in the past. Slootman talked to me about bringing back Scarpelli and the synergistic relationship that they have and how they build cultures and the no BS and hard truth mentality they bring to companies. But he bristles when people ask him, "What type of CEO are you?" He says, "Do we have to put a label on it? "It really depends on the situation." Now, one of the other really hard-hitting parts of the book was the way Frank deals with who to keep and who to let go. He uses the Volkswagen tagline of drivers wanted. He says in his book, in companies there are passengers and there are drivers, and we want drivers. He said, "You have to figure out really quickly "who the drivers are and basically throw the wrong people "off the bus, keep the right people, bring in new people "that fit the culture and put them "in the right seats on the bus." Now, these are not easy decisions to make. But as it pertains to getting rid of people, I'm reminded of the movie "Moneyball." Art Howe, the manager of the Oakland As, he refused to play Scott Hatteberg at first base. So the GM, Billy Bean played by Brad Pitt says to Peter Brand who was played by Jonah Hill, "You have to fire Carlos Pena." Don't learn how to fire people. Billy Bean says, "Just keep it quick. "Tell him he's been traded and that's it." So I asked Frank, "Okay, I get it. "Like the movie, when you have the wrong person "on the bus, you just have to make the decision, "be straightforward, and do it." But I asked him, "What if you're on the fence? "What if you're not completely sure if this person "is a driver or a passenger, if he or she "should be on the bus or not on the bus? "How do you handle that?" Listen to what he said. >> I have a very simple way to break ties. And when there's doubt, there's no doubt, okay? >> When there's doubt, there's no doubt. Slootman's philosophy is you have to be emphatic and have high conviction. You know, back to the baseball analogy, if you're thinking about taking the pitcher out of the game, take 'em out. Confrontation is the single hardest thing in business according to Slootman but you have to be intellectually honest and do what's best for the organization, period. Okay, so wow, that may sound harsh but that's how Slootman approaches it, very Belichickian if you will. But how can you amp it up on a daily basis? What's the approach that Slootman takes? We got into this conversation with a discussion about MBOs, management by objective. Slootman in his book says he's killed MBOs at every company he's led. And I asked him to explain why. His rationale was that individual MBOs invariably end up in a discussion about relief of the MBO if the person is not hitting his or her targets. And that detracts from the organizational alignment. He said at Snowflake everyone gets paid the same way, from the execs on down. It's a key way he creates focus and energy in an organization, by creating alignment, urgency, and putting more resources into the most important things. This is especially hard, Slootman says, as the organization gets bigger. But if you do approach it this way, everything gets easier. The cadence changes, the tempo accelerates, and it works. Now, and to emphasize that point, he said the following. Play the clip. >> Every meeting that you have, every email, every encounter in the hallway, whatever it is, is an opportunity to amp things up. That's why I use that title. But do you take that opportunity? >> And according to Slootman, if you don't take that opportunity, if you're not in the moment, amping it up, then you're thinking about your golf game or the tennis match that's going on this weekend or being out on your boat. And to the point, this approach is not for everyone. You're either built for it or you're not. But if you can bring people into the organization that can handle this type of dynamic, it creates energy. It becomes fun. Everything moves faster. The conversations are exciting. They're inspiring. And it becomes addictive. Now let's talk about priorities. I said to Frank that for me anyway, his book was an uncomfortable read. And he was somewhat surprised by that. "Really," he said. I said, "Yeah. "I mean, it was an easy read but uncomfortable "because over my career, I've managed thousands of people, "not tens of thousands but thousands, "enough to have to take this stuff very seriously." And I found myself throughout the book, oh, you know, on the one hand saying to myself, "Oh, I got that right, good job, Dave." And then other times, I was thinking to myself, "Oh wow, I probably need to rethink that. "I need to amp it up on that front." And the point is to Frank's leadership philosophy, there's no one correct way to approach all situations. You have to figure it out for yourself. But the one thing in the book that I found the hardest was Slootman challenged the reader. If you had to drop everything and focus on one thing, just one thing, for the rest of the year, what would that one thing be? Think about that for a moment. Were you able to come up with that one thing? What would happen to all the other things on your priority list? Are they all necessary? If so, how would you delegate those? Do you have someone in your organization who can take those off your plate? What would happen if you only focused on that one thing? These are hard questions. But Slootman really forces you to think about them and do that mental exercise. Look at Frank's body language in this screenshot. Imagine going into a management meeting with Frank and being prepared to share all the things you're working on that you're so proud of and all the priorities you have for the coming year. Listen to Frank in this clip and tell me it doesn't really make you think. >> I've been in, you know, on other boards and stuff. And I got a PowerPoint back from the CEO and there's like 15 things. They're our priorities for the year. I'm like you got 15, you got none, right? It's like you just can't decide, you know, what's important. So I'll tell you everything because I just can't figure out. And the thing is it's very hard to just say one thing. But it's really the mental exercise that matters. >> Going through that mental exercise is really important according to Slootman. Let's have a conversation about what really matters at this point in time. Why does it need to happen? And does it take priority over other things? Slootman says you have to pull apart the hairball and drive extraordinary clarity. You could be wrong, he says. And he admits he's been wrong on many things before. He, like everyone, is fearful of being wrong. But if you don't have the conversation according to Slootman, you're already defeated. And one of the most important things Slootman emphasizes in the book is execution. He said that's one of the reasons he wrote "Amp It Up." In our discussion, he referenced Pat Gelsinger, his former boss, who bought Data Domain when he was working for Joe Tucci at EMC. Listen to Frank describe the interaction with Gelsinger. >> Well, one of my prior bosses, you know, Pat Gelsinger, when they acquired Data Domain through EMC, Pat was CEO of Intel. And he quoted Andy Grove as saying, 'cause he was Intel for a long time when he was younger man. And he said no strategy is better than its execution, which if I find one of the most brilliant things. >> Now, before you go changing your strategy, says Slootman, you have to eliminate execution as a potential point of failure. All too often, he says, Silicon Valley wants to change strategy without really understanding whether the execution is right. All too often companies don't consider that maybe the product isn't that great. They will frequently, for example, make a change to sales leadership without questioning whether or not there's a product fit. According to Slootman, you have to drive hardcore intellectual honesty. And as uncomfortable as that may be, it's incredibly important and powerful. Okay, one of the other contrarian points in the book was whether or not to have a customer success department. Slootman says this became really fashionable in Silicon Valley with the SaaS craze. Everyone was following and pattern matching the lead of salesforce.com. He says he's eliminated the customer service department at every company he's led which had a customer success department. Listen to Frank Slootman in his own words talk about the customer success department. >> I view the whole company as a customer success function. Okay, I'm customer success, you know. I said it in my presentation yesterday. We're a customer-first organization. I don't need a department. >> Now, he went on to say that sales owns the commercial relationship with the customer. Engineering owns the technical relationship. And oh, by the way, he always puts support inside of the engineering department because engineering has to back up support. And rather than having a separate department for customer success, he focuses on making sure that the existing departments are functioning properly. Slootman also has always been big on net promoter score, NPS. And Snowflake's is very high at 72. And according to Slootman, it's not just the product. It's the people that drive that type of loyalty. Now, Slootman stresses amping up the big things and even the little things too. He told a story about someone who came into his office to ask his opinion about a tee shirt. And he turned it around on her and said, "Well, what do you think?" And she said, "Well, it's okay." So Frank made the point by flipping the situation. Why are you coming to me with something that's just okay? If we're going to do something, let's do it. Let's do it all out. Let's do it right and get excited about it, not just check the box and get something off your desk. Amp it up, all aspects of our business. Listen to Slootman talk about Steve Jobs and the relevance of demanding excellence and shunning mediocrity. >> He was incredibly intolerant of anything that he didn't think of as great. You know, he was immediately done with it and with the person. You know, I'm not that aggressive, you know, in that way. I'm a little bit nicer, you know, about it. But I still, you know, I don't want to give into expediency and mediocrity. I just don't, I'm just going to fight it, you know, every step of the way. >> Now, that story was about a little thing like some swag. But Slootman talked about some big things too. And one of the major ways Snowflake was making big, sweeping changes to amp up its business was reorganizing its go-to-market around industries like financial services, media, and healthcare. Here's some ETR data that shows Snowflake's net score or spending momentum for key industry segments over time. The red dotted line at 40% is an indicator of highly elevated spending momentum. And you can see for the key areas shown, Snowflake is well above that level. And we cut this data where responses were greater, the response numbers were greater than 15. So not huge ends but large enough to have meaning. Most were in the 20s. Now, it's relatively uncommon to see a company that's having the success of Snowflake make this kind of non-trivial change in the middle of steep S-curve growth. Why did they make this move? Well, I think it's because Snowflake realizes that its data cloud is going to increasingly have industry diversity and unique value by industry, that ecosystems and data marketplaces are forming around industries. So the more industry affinity Snowflake can create, the stronger its moat will be. It also aligns with how the largest and most prominent global system integrators, global SIs, go to market. This is important because as companies are transforming, they are radically changing their data architecture, how they think about data, how they approach data as a competitive advantage, and they're looking at data as specifically a monetization opportunity. So having industry expertise and knowledge and aligning with those customer objectives is going to serve Snowflake and its ecosystems well in my view. Slootman even said he joined the board of Instacart not because he needed another board seat but because he wanted to get out of his comfort zone and expose himself to other industries as a way to learn. So look, we're just barely scratching the surface of Slootman's book and I've pulled some highlights from our conversation. There's so much more that I can share just even from our conversation. And I will as the opportunity arises. But for now, I'll just give you the kind of bumper sticker of "Amp It Up." Raise your standards by taking every opportunity, every interaction, to increase your intensity. Get your people aligned and moving in the same direction. If it's the wrong direction, figure it out and course correct quickly. Prioritize and sharpen your focus on things that will really make a difference. If you do these things and increase the urgency in your organization, you'll naturally pick up the pace and accelerate your company. Do these things and you'll be able to transform, better identify adjacent opportunities and go attack them, and create a lasting and meaningful experience for your employees, customers, and partners. Okay, that's it for today. Thanks for watching. And thank you to Alex Myerson who's on production and he manages the podcast for Breaking Analysis. Kristin Martin and Cheryl Knight help get the word out on social and in our newsletters. And Rob Hove is our EIC over at Silicon Angle who does some wonderful and tremendous editing. Thank you all. Remember, all these episodes are available as podcasts. Wherever you listen, just search Breaking Analysis podcast. I publish each week on wikibon.com and siliconangle.com. And you can email me at david.vellante@siliconangle.com or DM me @dvellante or comment on my LinkedIn posts. And please do check out etr.ai for the best survey data in enterprise tech. This is Dave Vellante for theCUBE Insights, powered by ETR. Thanks for watching. Be well. And we'll see you next time on Breaking Analysis. (upbeat music)
SUMMARY :
insights from the cube and ETR, And how the heck did than actually writing the book, you know. "But in the military, they teach you And you know, I've brought people in "on the bus, you just And when there's doubt, And that detracts from the Every meeting that you have, And the point is to Frank's And I got a PowerPoint back from the CEO And one of the most important things the most brilliant things. According to Slootman, you have to drive Okay, I'm customer success, you know. and even the little things too. going to fight it, you know, and he manages the podcast
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Frank Slootman, Snowflake | Snowflake Summit 2022
>>Hi, everybody. Welcome back to Caesars in Las Vegas. My name is Dave ante. We're here with the chairman and CEO of snowflake, Frank Luman. Good to see you again, Frank. Thanks for coming on. Yeah, >>You, you as well, Dave. Good to be with you. >>No, it's, it's awesome to be, obviously everybody's excited to be back. You mentioned that in your, in your keynote, the most amazing thing to me is the progression of what we're seeing here in the ecosystem and of your data cloud. Um, you wrote a book, the rise of the data cloud, and it was very cogent. You talked about network effects, but now you've executed on that. I call it the super cloud. You have AWS, you know, I use that term, AWS. You're building on top of that. And now you have customers building on top of your cloud. So there's these layers of value that's unique in the industry. Was this by design >>Or, well, you know, when you, uh, are a data clouding, you have data, people wanna do things, you know, with that data, they don't want to just, you know, run data operations, populate dashboards, you know, run reports pretty soon. They want to build applications and after they build applications, they wanna build businesses on it. So it goes on and on and on. So it, it drives your development to enable more and more functionality on that data cloud. Didn't start out that way. You know, we were very, very much focused on data operations, then it becomes application development and then it becomes, Hey, we're developing whole businesses on this platform. So similar to what happened to Facebook in many, in many ways, you know, >>There was some confusion I think, and there still is in the community of, particularly on wall street, about your quarter, your con the consumption model I loved on the earnings call. One of the analysts asked Mike, you know, do you ever consider going to a subscription model? And Mike got cut him off, then let finish. No, that would really defeat the purpose. Um, and so there's also a narrative around, well, maybe snowflake, consumption's easier to dial down. Maybe it's more discretionary, but I, I, I would say this, that if you're building apps on top of snowflake and you're actually monetizing, which is a big theme here, now, your revenue is aligned, you know, with those cloud costs. And so unless you're selling it for more, you know, than it costs more than, than you're selling it for, you're gonna dial that up. And that is the future of, I see this ecosystem in your company. Is that, is that fair? You buy that. >>Yeah, it, it is fair. Obviously the public cloud runs on a consumption model. So, you know, you start looking all the layers of the stack, um, you know, snowflake, you know, we have to be a consumption model because we run on top of other people's, uh, consumption models. Otherwise you don't have alignment. I mean, we have conversations, uh, with people that build on snowflake, um, you know, they have trouble, you know, with their financial model because they're not running a consumption model. So it's like square pack around hole. So we all have to align ourselves. So that's when they pay a dollar, you know, a portion goes to, let's say, AWS portion goes to the snowflake of that dollar. And the portion goes to whatever the uplift is, application value, data value, whatever it is to that goes on top of that. So the whole dollar, you know, gets allocated depending on whose value at it. Um, we're talking about. >>Yeah, but you sell value. Um, so you're not a SaaS company. Uh, at least I don't look at you that that way I I've always felt like the SAS pricing model is flawed because it's not aligned with customers. Right. If you, if you get stuck with orphaned licenses too bad, you know, pay us. >>Yeah. We're, we're, we're obviously a SaaS model in the sense that it is software as a service, but it's not a SaaS model in the sense that we don't sell use rights. Right. And that's the big difference. I mean, when you buy, you know, so many users from, you know, Salesforce and ServiceNow or whoever you have just purchased the right, you know, for so many users to use that software for this period of time, and the revenue gets recognized, you know, radically, you know, one month at a time, the same amount. Now we're not that different because we still do a contract the exact same way as SA vendor does it, but we don't recognize the revenue radically. We recognize the revenue based on the consumption, but over the term of the contract, we recognize the entire amount. It just is not neatly organized in these monthly buckets. >>You know? So what happens if they underspend one quarter, they have to catch up by the end of the, the term, is that how it works or is that a negotiation or it's >>The, the, the spending is a totally, totally separate from the consumption itself, you know, because you know how they pay for the contract. Let's say they do a three year contract. Um, you know, they, they will probably pay for that, you know, on an annual basis, you know, that three year contract. Um, but it's how they recognize their expenses for snowflake and how we recognize the revenue is based on what they actually consume. But it's not like you're on demand where you can just decide to not use it. And then I don't have any cost, but over the three year period, you know, all of that, you know, uh, needs to get consumed or they expire. And that's the same way with Amazon. If I don't consume what I buy from Amazon, I still gotta pay for it. You know, so, >>Well, you're right. Well, I guess you could buy by the drink, but it's way, way more expensive and nobody really correct. Does that, so, yep. Okay. Phase one, better simpler, you know, cloud enterprise data warehouse, phase two, you introduced the, the data cloud and, and now we're seeing the rise of the data cloud. What, what does phase three look like >>Now? Phase, phase three is all about applications. Um, and we've just learned, uh, you know, from the beginning that people were trying to do this, but we weren't instrumental at all to do it. So people would ODBC, you know, JDBC drivers just uses as database, right? So the entire application would happen outside, you know, snowflake, we're just a database. You connect to the database, you know, you read or right data, you know, you do data, data manipulations. And then the application, uh, processing all happens outside of snowflake. Now there's issues with that because we start to exfil trade data, meaning that we started to take data out of snowflake and, and put it, uh, in other places. Now there's risk for that. There's operational risk, there's governance, exposure, security issues, you know, all this kind of stuff. And the other problem is, you know, data gets Reed. >>It proliferates. And then, you know, data science tests are like, well, I, I need that data to stay in one place. That's the whole idea behind the data cloud. You know, we have very big infrastructure clouds. We have very big application clouds and then data, you know, sort of became the victim there and became more proliferated and more segment. And it's ever been. So all we do is just send data to the work all day. And we said, no, we're gonna enable the work to get to the data. And the data that stays in more in place, we don't have latency issue. We don't have data quality issues. We don't have lineage issues. So, you know, people have responded very, very well to the data cloud idea, like, yeah, you know, as an enterprise or an institution, you know, I'm the epicenter of my own data cloud because it's not just my own data. >>It's also my ecosystem. It's the people that I have data networking relationships with, you know, for example, you know, take, you know, uh, an investment bank, you know, in, in, in, in New York city, they send data to fidelity. They send data to BlackRock. They send data to, you know, bank of New York, all the regulatory clearing houses, all on and on and on, you know, every night they're running thousands, tens of thousands, you know, of jobs pushing that data, you know, out there. It just, and they they're all on snowflake already. So it doesn't have to be this way. Right. So, >>Yes. So I, I asked the guys before, you know, last week, Hey, what, what would you ask Frank? Now? You might remember you came on, uh, our program during COVID and I was asking you how you're dealing with it, turn off the news. And it was, that was cool. And I asked you at the time, you know, were you ever, you go on Preem and you said, look, I'll never say never, but it defeats the purpose. And you said, we're not gonna do a halfway house. Actually, you were more declarative. We're not doing a halfway house, one foot in one foot out. And then the guy said, well, what about that Dell deal? And that pure deal that you just did. And I, I think I know the answer, but I want to hear from you did a customer come to you and say, get you in the headlock and say, you gotta do this. >>Or it did happen that way. Uh, it, uh, it started with a conversation, um, you know, via with, uh, with Michael Dell. Um, it was supposed to be just a friendly chat, you know, Hey, how's it going? And I mean, obviously Dell is the owner of data, the main, or our first company, you know? Um, but it's, it, wasn't easy for, for Dell and snowflake to have a conversation because they're the epitome of the on-premise company and we're the epitome of a cloud company. And it's like, how, what do we have in common here? Right. What can we talk about? But, you know, Michael's a very smart, uh, engaging guy, you know, always looking for, for opportunity. And of course they decided we're gonna hook up our CTOs, our product teams and, you know, explore, you know, somebody's, uh, ideas and, you know, yeah. We had some, you know, starts and restarts and all of that because it's just naturally, you know, uh, not an easy thing to conceive of, but, you know, in the end it was like, you know what? >>It makes a lot of sense. You know, we can virtualize, you know, Dell object storage, you know, as if it's, you know, an S three storage, you know, from Amazon and then, you know, snowflake in its analytical processing. We'll just reference that data because to us, it just looks like a file that's sitting on, on S3. And we have, we have such a thing it's called an external table, right. That's, that's how we basically, it projects, you know, a snowflake, uh, semantic and structural model, you know, on an external object. And we process against it exactly the same way as if it was an internal, uh, table. So we just extended that, um, you know, with, um, with our storage partners, like Dell and pure storage, um, for it to happen, you know, across a network to an on-prem place. So it's very elegant and it, it, um, it becomes an, an enterprise architecture rather than just a cloud architecture. And I'm, I just don't know what will come of it. And, but I've already talked to customers who have to have data on premises just can't go anywhere because they process against it, you know, where it originates, but there are analytical processes that wanna reference attributes of that data. Well, this is what we'll do that. >>Yeah. I'm, it is interesting. I'm gonna ask Dell if I were them, I'd be talking to you about, Hey, I'm gonna try to separate compute from storage on prem and maybe do some of the, the work there. I don't even know if it's technically feasible. It's, I'll ask OI. But, um, but, but, but to me, that's an example of your extending your ecosystem. Um, so you're talking now about applications and that's an example of increasing your Tam. I don't know if you ever get to the edge, you know, we'll see, we're not quite quite there yet, but, um, but as you've said before, there's no lack of market for you. >>Yeah. I mean, obviously snowflake it it's, it's Genesis was reinventing database management in, in a cloud computing environment, which is so different from a, a machine environment or a cluster environment. So that's why, you know, we're, we're, we're not a, a fit for a machine centric, uh, environment sort of defeats the purpose of, you know, how we were built. We, we are truly a native solution. Most products, uh, in the clouds are actually not cloud native. You know, they, they originated the machine environments and you still see that, you know, almost everything you see in the cloud by the way is not cloud native, our generation of applications. They only run the cloud. They can only run the cloud. They are cloud native. They don't know anything else, >>You know? Yeah, you're right. A lot of companies would just wrap something in wrap their stack in Kubernetes and throw it into the cloud and say, we're in the cloud too. And you basically get, you just shifted. It >>Didn't make sense. Oh. They throw it in the container and run it. Right. Yeah. >>So, okay. That's cool. But what does that get you that doesn't change your operational model? Um, so coming back to software development and what you're doing in, in that regard, it seems one of the things we said about Supercloud is in order to have a Supercloud, you gotta have an ecosystem, you gotta have optionality. Hence you're doing things like Apache iceberg, you know, you said today, well, we're not sure where it's gonna go, but we offering options. Uh, but, but my, my question is, um, as it pertains to software developments specifically, how do you, so one of the things we said, sorry, I've lost my train there. One of the things we said is you have to have a super PAs in order to have a super cloud ecosystem, PAs layer. That's essentially what you've introduced here. Is it not a platform for our application development? >>Yeah. I mean, what happens today? I mean, how do you enable a developer, you know, on snowflake, without the developer, you know, reading the, the files out of snowflake, you know, processing, you know, against that data, wherever they are, and then putting the results set, God knows where, right. And that's what happens today. It's the wild west it's completely UN uncovered, right? And that's the reason why lots of enterprises will not allow Python anything anywhere near, you know, their enterprise data. We just know that, uh, we also know it from streamlet, um, or the acquisition, um, large acquisition that we made this year because they said, look, you know, we're, we have a lot of demand, you know, uh, in the Python community, but that's the wild west. That's not the enterprise grade high trust, uh, you know, corporate environment. They are strictly segregated, uh, today. >>Now do some, do these, do these things sometimes dribble up in the enterprise? Yes, they do. And it's actually intolerable the risk that enterprises, you know, take, you know, with things being UN uncovered. I mean the whole snowflake strategy and promises that you're in snowflake, it is a, an absolute enterprise grade environment experience. And it's really hard to do. It takes enormous investment. Uh, but that is what you buy from us. Just having Python is not particularly hard. You know, we can do that in a week. This has taken us years to get it to this level, you know, of, of, you know, governance, security and, and, you know, having all the risks around exfiltration and so on, really understood and dealt with. That's also why these things run in private previews and public previews for so long because we have to squeeze out, you know, everything that may not have been, you know, understood or foreseen, you know, >>So there are trade offs of, of going into this snowflake cloud, you get all this great functionality. Some people might think it's a walled garden. How, how would you respond to that? >>Yeah. And it's true when you have a, you know, a snowflake object, like a snowflake, uh, table only snowflake, you know, runs that table. And, um, you know, that, that is, you know, it's very high function. It's very sort of analogous to what apple did, you know, they have very high functioning, but you do have to accept the fact that it's, that it's not, uh, you know, other, other things in apple cannot, you know, get that these objects. So this is the reason why we introduce an open file format, you know, like, like iceberg, uh, because what iceberg effectively does is it allows any tool, uh, you know, to access that particular object. We do it in such a way that a lot of the functionality of snowflake, you know, will address the iceberg format, which is great because it's, you're gonna get much more function out of our, you know, iceberg implementation than you would get from iceberg on its own. So we do it in a very high value addeds, uh, you know, manner, but other tools can still access the same object in a read to write, uh, manner. So it, it really sort of delivers the original, uh, promise of the data lake, which is just like, Hey, I have all these objects tools come and go. I can use what I want. Um, so you get, you get the best of both worlds for the most part. >>Have you reminds me a little bit of VMware? I mean, VMware's a software mainframe, it's just better than >>Doing >>It on your own. Yep. Um, one of the other hallmarks of a cloud company, and you guys clearly are a cloud company is startups and innovation. Um, now of course you see that in, in the, in the ecosystem, uh, and maybe that's the answer to my question, but you guys are kind of whale hunters, <laugh> your customers are, tend to be bigger. Uh, is the, is the innovation now the extension of that, the ecosystem is that by design. >>Oh, um, you know, we have a enormous, uh, ISV following and, um, we're gonna have a whole separate conference like this, by the way, just for, yeah. >>For developers. I hope you guys will up there too. Yeah. Um, you know, the, the reason that, that the ISV strategy is very important for, you know, for, for, for, for many reasons, but, you know, ISVs are the people that are really going to unlock a lot of the value and a lot of the promise of data, right? Because you, you can never do that on your own. And the problem has been that for ISVs, it is so expensive and so difficult to build a product that can be used because the entire enterprise platform infrastructure needs to be built by somebody, you know, I mean, are you really gonna run infrastructure, database, operations, security, compliance, scalability, economics. How do you do that as a software company where really you only have your, your domain expertise that you want to deliver on a platform. You don't wanna do all these things. >>First of all, you don't know how to do it, how to do it well. Um, so it is much easier, much faster when there is already platform to actually build done in the world of clout that just doesn't, you know, exist. And then beyond that, you know, okay, fine building. It is sort of step one. Now I gotta sell it. I gotta market it. So how do I do that? Well, in the snowflake community, you have already market <laugh>, there's thousands and thousands of customers that are also on self lake. Okay. So their, their ability to consume that service that you just built, you know, they can search it, they can try it, they can test it and decide whether they want to consume it. And then, you know, we can monetize it. So all they have to do is cash the check. So the net effecti of it is we drastically lowered the barriers to entry into the world, you know, of software, you know, two men or two women in a dog, and a handful of files can build something that then can be sold, sort of to, for software developers. >>I wrote a piece 2012 after the first reinvent. And I, you know, and I, and I put a big gorilla on the front page and I said, how do you compete with Amazon gorilla? And then one of my answers was you build data ecosystems and you verticalize, and that's, that's what you're doing >>Here. Yeah. There certain verticals that are farther along than others, uh, obviously, but for example, in financial, uh, which is our largest vertical, I mean, the, the data ecosystem is really developing hardcore now. And that's, that's because they so rely on those relationships between all the big financial institutions and entities, regulatory, you know, clearing houses, investment bankers, uh, retail banks, all this kind of stuff. Um, so they're like, it becomes a no brainer. The network affects kick in so strongly because they're like, well, this is really the only way to do it. I mean, if you and I work in different companies and we do, and we want to create a secure, compliant data network and connection between us, I mean, it would take forever to get our lawyers to agree that yeah, it's okay. <laugh> right now, it's like a matter of minutes to set it up. If we're both on snowflake, >>It's like procurement, do they, do you have an MSA yeah. Check? And it just sail right through versus back and forth and endless negotiations >>Today. Data networking is becoming core ecosystem in the world of computing. You know, >>I mean, you talked about the network effects in rise of the data cloud and correct. Again, you know, you, weren't the first to come up with that notion, but you are applying it here. Um, I wanna switch topics a little bit. I, when I read your press releases, I laugh every time. Cause this says no HQ, Bozeman. And so where, where do you, I think I know where you land on, on hybrid work and remote work, but what are your thoughts on that? You, you see Elon the other day said you can't work for us unless you come to the office. Where, where do you stand? >>Yeah. Well, the, well, the, the first aspect is, uh, we really wanted to, uh, separate from the idea of a headquarters location, because I feel it's very antiquated. You know, we have many different hubs. There's not one place in the world where all the important people are and where we make all the important positions, that whole way of thinking, uh, you know, it is obsolete. I mean, I am where I need to be. And it it's many different places. It's not like I, I sit in this incredible place, you know, and that's, you know, that's where I sit and everybody comes to me. No, we are constantly moving around and we have engineering hubs. You know, we have your regional, uh, you know, headquarters for, for sales. Obviously we have in Malaysia, we have in Europe, you know? And, um, so I wanted to get rid of this headquarters designation. >>And, you know, the, the, the other issue obviously is that, you know, we were obviously in California, but you know, California is, is no longer, uh, the dominant place of where we are resident. I mean, 40% of our engineering people are now in be Washington. You know, we have hundreds of people in Poland where people, you know, we are gonna have very stressed location in Toronto. Um, yeah. Obviously our customers are, are everywhere, right? So this idea that, you know, everything is happening in, in one state is just, um, you know, not, not correct. So we wanted to go to no headquarters. Of course the SCC doesn't let you do that. Um, because they want, they want you to have a street address where the government can send you a mail and then it becomes, the question is, well, what's an acceptable location. Well, it has to be a place where the CEO and the CFO have residency by hooker, by crook. >>That happened to be in Bozeman Montana because Mike and I are both, it was not by design. We just did that because we were, uh, required to, you know, you know, comply with government, uh, requirements, which of course we do, but that's why it, it says what it says now on, on the topic of, you know, where did we work? Um, we are super situational about it. It's not like, Hey, um, you know, everybody in the office or, or everybody is remote, we're not categorical about it. Depends on the function, depends on the location. Um, but everybody is tethered to an office. Okay. In words, everybody has a relationship with an office. There's, there's almost nobody, there are a few exceptions of people that are completely remote. Uh, but you know, if you get hired on with snowflake, you will always have an office affiliation and you can be called into the office by your manager. But for purpose, you know, a meeting, a training, an event, you don't get called in just to hang out. And like, the office is no longer your home away from home. Right. And we're now into hotel, right? So you don't have a fixed place, you know? So >>You talked in your keynote a lot about last question. I let you go customer alignment, obviously a big deal. I have been watching, you know, we go to a lot of events, you'll see a technology company tell a story, you know, about their widget or whatever it was their box. And then you'll see an outcome and you look at it and you shake your head and say, well, that the difference between this and that is the square root of zero, right. When you talk about customer alignment today, we're talking about monetizing data. Um, so that's a whole different conversation. Um, and I, I wonder if you could sort of close on how that's different. Um, I mean, at ServiceNow, you transformed it. You know, I get that, you know, data, the domain was okay, tape, blow it out, but this is a, feels like a whole new vector or wave of growth. >>Yeah. You know, monetizing, uh, data becomes sort of a, you know, a byproduct of having a data cloud you all of a sudden, you know, become aware of the fact that, Hey, Hey, I have data and be that data might actually be quite valuable to parties. And then C you know, it's really easy to then, you know, uh, sell that and, and monetize that. Cause if it was hard, forget it, you know, I don't have time for it. Right. But if it's relatively, if it's compliant, it's relatively effortless, it's pure profit. Um, I just want to reference one attribute, two attributes of what you have, by the way, you know, uh, hedge funds have been into this sort of thing, you know, for a long time, because they procure data from hundreds and hundreds of sources, right. Because they're, they are the original data scientists. >>Um, but the, the bigger thing with data is that a lot of, you know, digital transformation is, is, is finally becoming real. You know, for years it was arm waving and conceptual and abstract, but it's becoming real. I mean, how do we, how do we run a supply chain? You know, how do we run, you know, healthcare, um, all these things are become are, and how do we run cyber security? They're being redefined as data problems and data challenges. And they have data solutions. So that's right. Data strategies are insanely important because, you know, if, if the solution is through data, then you need to have, you know, a data strategy, you know, and in our world, that means you have a data cloud and you have all the enablement that allows you to do that. But, you know, hospitals, you know, are, are saying, you know, data science is gonna have a bigger impact on healthcare than life science, you know, in the coming, whatever, you know, 10, 20 years, how do you enable that? >>Right. I, I have conversations with, with, with hospital executives are like, I got generations of data, you know, clinical diagnostic, demographic, genomic. And then I, I am envisioning these predictive outcomes over here. I wanna be able to predict, you know, once somebody's gonna get what disease and you know, what I have to do about it, um, how do I do that? <laugh> right. The day you go from, uh, you know, I have a lot of data too. I have these outcomes and then do me a miracle in the middle, in the middle of somewhere. Well, that's where we come in. We're gonna organize ourselves and then unpack thats, you know, and then we, we work, we through training models, you know, we can start delivering some of these insights, but the, the promise is extraordinary. We can change whole industries like pharma and, and, and healthcare. Um, you know, 30 effects of data, the economics will change. And you know, the societal outcomes, you know, um, quality of life disease, longevity of life is quite extraordinary. Supply chain management. That's all around us right >>Now. Well, there's a lot of, you know, high growth companies that were kind of COVID companies, valuations shot up. And now they're trying to figure out what to do. You've been pretty clear because of what you just talked about, the opportunities enormous. You're not slowing down, you're amping it up, you know, pun intended. So Frank Luman, thanks so much for coming on the cube. Really appreciate your time. >>My pleasure. >>All right. And thank you for watching. Keep it right there for more coverage from the snowflake summit, 2022, you're watching the cube.
SUMMARY :
Good to see you again, Frank. You have AWS, you know, I use that term, AWS. you know, with that data, they don't want to just, you know, run data operations, populate dashboards, One of the analysts asked Mike, you know, do you ever consider going to a subscription model? with people that build on snowflake, um, you know, they have trouble, you know, with their financial model because bad, you know, pay us. you know, so many users from, you know, Salesforce and ServiceNow or whoever you have just purchased the they, they will probably pay for that, you know, on an annual basis, you know, that three year contract. Phase one, better simpler, you know, cloud enterprise data warehouse, You connect to the database, you know, you read or right data, you know, you do data, data manipulations. like, yeah, you know, as an enterprise or an institution, you know, I'm the epicenter of you know, for example, you know, take, you know, uh, an investment bank, you know, in, you know, were you ever, you go on Preem and you said, look, I'll never say never, but it defeats the purpose. just naturally, you know, uh, not an easy thing to conceive of, but, you know, You know, we can virtualize, you know, Dell object storage, you know, I don't know if you ever get to the edge, you know, we'll see, we're not quite quite there yet, So that's why, you know, we're, And you basically get, you just shifted. Oh. They throw it in the container and run it. you know, you said today, well, we're not sure where it's gonna go, but we offering options. you know, on snowflake, without the developer, you know, reading the, the files out of snowflake, And it's actually intolerable the risk that enterprises, you know, take, So there are trade offs of, of going into this snowflake cloud, you get all this great functionality. uh, you know, other, other things in apple cannot, you know, get that these objects. Um, now of course you see that Oh, um, you know, we have a enormous, uh, ISV following and, be built by somebody, you know, I mean, are you really gonna run infrastructure, you know, of software, you know, two men or two women in a dog, and a handful of files can build you know, and I, and I put a big gorilla on the front page and I said, how do you compete with Amazon gorilla? regulatory, you know, clearing houses, investment bankers, uh, retail banks, It's like procurement, do they, do you have an MSA yeah. Data networking is becoming core ecosystem in the world of computing. Again, you know, It's not like I, I sit in this incredible place, you know, and that's, And, you know, the, the, the other issue obviously is that, you know, we were obviously in California, We just did that because we were, uh, required to, you know, you know, I have been watching, you know, we go to a lot of events, you'll see a technology company tell And then C you know, you know, a data strategy, you know, and in our world, that means you have a data cloud and you have all the enablement that thats, you know, and then we, we work, we through training models, you know, you know, pun intended. And thank you for watching.
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Frank Slootman & Anita Lynch v4 720p
>> Hello everybody. And welcome back to, theCUBE coverage of the Snowflake Data Cloud Summit 2020. We're tracking the rise of the Data Cloud, and fresh off the keynotes here, Frank Slootman, the Chairman and CEO of Snowflake and Anita Lynch, the Vice President of data governance at Disney streaming services. Folks Welcome. >> Thank you >> Thanks for having us Dave. >> Anita Disney plus awesome. You know, we signed up early, watched all the Marvel movies, Hamilton, the new Pixar movie soul. I haven't gotten it to the Mandalorian yet, your favorite. But really appreciate you guys coming on. Let me start with Frank. I'm glad you're putting forth this vision around the Data Cloud, because I never liked the term enterprise data warehouse. What you're doing is so different from the sort of that legacy world that I've known all these years. But start with why the Data Cloud? What problems are you trying to solve? And maybe some of the harder challenges you're seeing. >> Yeah, you know, we have a, we've come a long way in terms of workload execution. Right? In terms of scale and performance, and concurrent execution. We've really taken the lid off, sort of the physical constraints that have existed on these type of operations. But there's one problem that we're not yet solving, and that is the siloing and bunkering of data. And essentially, data is locked in applications, it's locked in data centers, it's locked in cloud, cloud regions. Incredibly hard for data science teams to really unlock the true value of data, when you can't address patterns that exist across data sets. So where we perpetuate a status we've had for forever since the beginning of computing. If we don't start to crack that problem now we have that opportunity. But the notion of a Data Cloud is like basically saying, "Look folks, we have to start on siloing and unlocking the data, and bring it into a place, where we can access it across all these perimeters, and boundaries that have historically existed. It's very much a step level function. Like the customers have always looked at things, one workload at a time, that mentality really has to go. You really have to have a Data Cloud mentality, as well as a workload orientation towards managing data. >> Anita, it was great hearing your role at Disney and in your keynote, and the work you're doing, the governance work. and you're serving a great number of stakeholders, enabling things like data sharing. You got really laser focused on trust, compliance, privacy. This idea of a data clean room is really interesting. Maybe you can expand on some of these initiatives here, and share what you're seeing as some of the biggest challenges to success, and of course, the opportunities that you're unlocking. >> Sure. In my role leading data governance, it's really critical to make sure that all of our stakeholders not only know what data is available and accessible to them. They can also understand really easily and quickly, whether or not the data that they're using is for the appropriate use case. And so that's a big part of how we scale data governance, and a lot of the work that we would normally have to do manually is actually done for us through the data clean rooms. >> Thank you for that. I wonder if you could talk a little bit more about the role of data and how your data strategy has evolved and maybe discuss some of the things that Frank mentioned about data silos. And I mean, obviously you can relate to that having been in the data business for a while, but I wonder if you can elucidate on that. >> Sure. I mean, data complexities are going to evolve over time in any traditional data architecture simply because you often have different teams at different periods and time trying to analyze and gather data across a whole lot of different sources. And the complexity that just arises out of that is due to the different needs of specific stakeholders. There are time constraints and quite often, it's not always clear how much value they're going to be able to extract from the data at the outset. So what we've tried to do to help break down those silos is allow individuals to see upfront how much value they're going to get from the data by knowing that it's trustworthy right away. By knowing that it's something that they can use in their specific use case right away. And by ensuring that essentially as they're continuing to kind of scale the use cases that they're focused on, they're no longer required to make multiple copies of the data, do multiple steps to reprocess the data. And that makes all the difference in the world. >> Yeah, for sure. I'm a copy Creek because it'd be the silent killer. Frank I followed you for a number of years, you're a big thinker, you and I have had a lot of conversations about the near-term, mid-term and long-term, I wonder if you could talk about, in your keynote you're talking about eliminating silos and connecting across data sources. Which is really powerful concept but really only if people are willing and able to connect and collaborate. Where do you see that happening? Maybe what are some of the blockers there? >> Well, there's certainly a natural friction there. I still remember when we first started to talk to, Salesforce, you know, they had discovered that we were a top three destination of Salesforce data and they were wondering why that was, and the reason is of course, that people take Salesforce data push it to snowflake because they want to overlay it with what data outside of Salesforce. Whether it's Adobe or any other marketing dataset. And then they want to run very highly scaled processes on it. But the reflexes in the world of SaaS is always like no, we're an Island, we're a planet down to ourselves. Everybody needs to come with us, as opposed to we go to a different platform to run these types of processes. It's no different for the public cloud vendor. They didn't only, they have massive moats around their storage to really prevent data from leaving their orbit. So there is natural friction in terms for this to happen. But on the other hand there is an enormous need. We can't deliver on the power and potential of data unless we allow it to come together. Snowflake is the platform that allows that to happen. We were pleased with our relationship with Salesforce because they did appreciate why this was important and why this was necessary. And we think, other parts of the industry will gradually come around to it as well. So the idea of a Data Cloud has really come, right. When people are recognizing why this matters now. It's not going to happen overnight. It is a step while will function a very big change in mentality and orientation. >> Yeah. It's almost as though the the SaaS suffocation of our industry sort of repeated some of the application silos and you build a hardened top around it, all the processes are hardened around it and okay, here we go. And you're really trying to break that, aren't you? >> Yep, exactly. >> Anita, again, I want to come back to this notion of governance. It's so it's so important. It's the first role in your title and it really underscores the importance of this. You know, Frank was just talking about some of the hurdles and this is a big one. I mean, we saw this in the early days of big data where governance was just afterthought. It was like bolted on the kind of wild wild West. I'm interested in your governance journey. And maybe you can share a little bit about what role snowflake has played there in terms of supporting that agenda and kind of what's next on that journey. >> Sure. Well, I've led data teams in numerous ways over my career. This is the first time that I've actually had the opportunity to focus on governance and what it's done is allowed for my organization to scale much more rapidly. And that's so critically important for our overall strategy as a company. >> Well, I mean, a big part of what you were talking about at least my inference in your talk was really that the business folks didn't have to care about, you know, wonder about they cared about it, but they don't have to wonder about, and about the privacy concerns, et cetera. You've taken care of all that it's sort of transparent to them. Is that right?| >> Yea That's right absolutely. So we focus on ensuring compliance across all of the different regions where we operate. We also partner very heavily with our legal and information security teams. They're critical to ensuring that we're able to do this. we don't do it alone. But governance includes not just the compliance and the privacy, it's also about data access, and it's also about ensuring data quality. And so all of that comes together under the governance umbrella. I also lead teams that focus on things like instrumentation, which is how we collect data. We focus on the infrastructure and making sure that we've architected for scale and all of these are really important components of our strategy. >> I got a...So I have a question maybe each of you can answer. I sort of see this, our industry moving from products, to then, to platforms and platforms even evolving into ecosystems. And then there's this ecosystem of data. You guys both talked a lot about data sharing but maybe Frank, you can start, Anita you can add on to Frank's answer. You're obviously both passionate about the use of data and trying to do so in a responsible way. That's critical but it's also going to have business impact. Frank, where's this passion come from on your side. And how are you putting into action in your own organization? >> Well, you know I'm really going to date myself here, but many, many years ago, I saw the first glimpse of multidimensional databases that were used for reporting really on IBM mainframes. And it was extraordinarily difficult. We didn't even have the words back then in terms of data warehouses and business. All these terms didn't exist. People just knew that they wanted to have a more flexible in way of reporting and being able to pivot data dimensionally and all these kinds of things. And I just bought whatever this predates windows 3.1, which really, set off the whole sort of graphical, way of dealing with systems which there's now a whole generations of people that don't know any different right? So I've lived the pain of this problem and sort of had a front row seat to watching this transpire over a very long period of time. And that's one of the reasons, why I'm here, because I finally seen, a glimpse of, I also, as an industry fully, fully just unleashing and unlocking to potential. We're now in a place where the technology is ahead of people's ability to harness it. Which we've never been there before. It was always like, we wanted to do things that technology wouldn't let us. It's different now. I mean, people are just, their heads are spinning with what's now possible, which is why you see markets evolve, very rapidly right now we were talking earlier about how you can't take past definitions and concepts and apply them to what's going on in the world. because the world's changing right in front of your eyes right now. >> So Anita maybe you could add on to what Frank just said and share some of the business impacts and outcomes that are notable since you've really applied your your love of data and maybe, maybe touch on, on culture. Data culture, any words of wisdom for folks in the audience who might be thinking about embarking on a Data Cloud journey, similar to what you've been on. >> Yeah sure. I think for me, I fell in love with technology first and then I fell in love with data. And I fell in love with data because of the impact that data can have on both the business and the technology strategy. And so it's sort of that nexus, between all three. And in terms of my career journey and some of the impacts that I've seen. I mean, I think with the advent of the cloud, before, well, how do I say that. Before the cloud actually became so prevalent and such a common part of the strategy that's required it was so difficult, you know, so painful. It took so many hours to actually be able to calculate the volumes of data that we had. Now we have that accessibility, and then on top of it, with the snowflake Data Cloud it's much more performance oriented from a cost perspective because you don't have multiple copies of the data, or at least you don't have to have multiple copies of the data. And I think moving beyond some of the traditional mechanisms for for measuring business impact, has only been possible with the volumes of data that we have available to us today. And it's just, it's phenomenal to see the speed at which we can operate. And really, truly understand our customer's interests and their preferences and then tailor the experiences that they really want and deserve for them. It's, been a great feeling to get to this point in time. >> That's fantastic. So, Frank, I got to ask you this. So in your spare time you decided to write a book, I'm loving it. I don't have a signed copy so I'm going to have to send it back and have you sign it. But, and you're, I love the inside baseball. It's just awesome. So really appreciate that. So, but why did you decide to write a book? >> Well, there were a couple of reasons, obviously we thought of as an interesting tale to tell for anybody, who is interested in what's going on, how did this come about? Who are the characters behind the scenes and all this stuff. But from a business standpoint because this is such a step function it's so non incremental, we felt like, we really needed quite a bit of real estate to really lay out what the full narrative and context is. And, we thought, the books titled the "Rise of the Data Cloud." That's exactly what it is. And we're trying to make the case for that mindset, that mentality, that strategy because all of us, I think as an industry, were at risk of, persisting, perpetuating where we've been since the beginning of computing. So we're really trying to make a pretty forceful case for a look. There's an enormous opportunity out there but there's some choices you have to make along the way. >> Guys, we got to leave it there. Frank, I know you and I are going to talk again Anita, I hope we have a chance to meet face to face and talk in theCUBE live someday. You're phenomenal guests and what a great story. Thank you both for coming on. And thank you for watching. Keep it right there. You're watching the, Snowflake Data Cloud Summit, on theCUBE.
SUMMARY :
and fresh off the keynotes here, And maybe some of the harder and that is the siloing and of course, the opportunities and a lot of the work and maybe discuss some of the things And that makes all the and able to connect and collaborate. But on the other hand some of the application It's the first role in your title This is the first time that and about the privacy concerns, et cetera. of the different regions where we operate. passionate about the use And that's one of the reasons, of the business impacts and outcomes and some of the impacts that I've seen. I love the inside baseball. "Rise of the Data Cloud." And thank you for watching.
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Frank Slootman Dave Vellante Cube Conversation
>>from the Cube Studios in Palo Alto in Boston, connecting with thought leaders all around >>the world. This is a cute conversation high, but this is Day Volonte. And as you know, we've been tracking the next generation of clouds. Sometimes we call it Cloud to two point. Frank's Lukman is here to really unpack this with me. Frank. Great to see you. Thanks for coming on. >>Yeah, you as well. They could see it >>s o obviously hot off your AIPO A lot of buzz around that. Uh, that's fine. We could we could talk about that, but I really want to talk about the future. What? Before we get off the I p o. That was something you told me when you're CEO service. Now you said, hey, we're priced to perfection, so it looks like snowflakes gonna be priced to perfection. It's a marathon, though. You You made that clear. I presume it's not any different here for you. Yeah, >>well, I think you know the service now. Journey was different in the sense that we were kind of under the underdogs, and people sort of discovered over the years the full potential of the company and I think there's stuff like they pretty much discovered a day. One. It's a little bit more, More sometimes it's nice to be an underdog. Were a bit of an over dog in this, uh, this particular scenario, but, you know, it is what it is, Andre. You know, it's all about execution delivering the results, delivering on our vision, Uh, you know, being great with our customers. And, uh, hopefully the chips will fall where they where they may. At that point, >>yeah, you're you're You're a poorly kept secret at this point, Frank. After a while, I wanted, you know, I've got some excerpts of your book that that I've been reading. And, of course, I've been following your career since the two thousands. You're off sailing. You mentioned in your book that you were kind of retired. You were done, and then you get sucked back in now. Why? I mean, are you in this for the sport? What's the story here? >>Uh, actually, that that's not a bad way of characterizing it. I think I am in that, uh, you know, for the sport, uh, you know the only way to become the best version of yourself is to be to be under the gun and, uh, you know, every single day. And that's that's certainly what we are. It sort of has its own rewards building great products, building great companies, regardless off you know what the spoils. Maybe it has its own rewards. And I It's hard for people like us to get off the field and, you know, hang it up. So here we are. >>You know, you're putting forth this vision now the data cloud, which obviously it's good marketing, but I'm really happy because I don't like the term Enterprise Data Warehouse. I don't think it reflects what you're trying to accomplish. E D. W. It's slow on Lee. A few people really know how to use it. The time value of data is gone by the time you know, your business is moving faster than the data in the D. W. And it really became a savior because of Sarbanes Oxley. That's really what it came a reporting mechanism. So I've never seen What you guys are doing is is e d w. So I want you to talk about the data cloud. I want to get into the to the vision a little bit and maybe challenge you on a couple things so our audience can better understand it. Yes. So >>the notion of a data cloud is is actually, uh, you know, type of cloud that we haven't had. I mean, data has been been fragmented and locked up in a million different places in different clouds. Different cloud regions, obviously on premise, um, And for data science teams, you know, they're trying thio drive analysis across datasets, which is incredibly hard, Which is why you know, a lot of this resorts to, you know, programming on bond things of that sort of. ITT's hardly scalable because the data is not optimized. The economics are not optimized. There's no governance model and so on. But a data cloud is actually the ability thio loosely couple and lightly Federated uh, data, regardless of where it is. So it doesn't have scale limitations or performance limitations. Uh, the way traditional data warehouses have had it. So we really have a fighting chance off really killing the silos and unlocking the bunkers and allowing the full promise of data sciences and ml On day I thio really happen. I mean, a lot of lot of the analysis that happens on data is on the single data set because it's just too damn hard, you know, to drive analysis across multiple data sets. And, you know, when we talk to our customers, they have very precise designs on what they're trying to do. They say, Look, we are trying to discover, you know, through through through deep learning You know what the patterns are that lead to transactions. You know, whether it's if you're streaming company. Maybe it's that you're signing up for a channel or you're buying a movie or whatever it is. What is the pattern you know, of data points that leads us to that desired outcome. Once you have a very accurate description of the data relationships, you know that results in that outcome, you can then search for it and scale it, you know, tens of million times over. That's what digital enterprises do, right? So in order to discover these patterns enriched the data to the point where the patterns become incredibly predictive. Uh, that's that's what snowflake is formed, right? But it requires a completely Federated Data mo because you're not gonna find a data pattern in the in the single data set per se right? So that's that's what it's all about. I mean, the outcomes of a data cloud are very, very closely related to the business outcomes that the user is seeking, right? It's not some infrastructure process. It has a very remote relationship with business outcome. This is very, very closely related. >>So it doesn't take a brain surgeon to look at the Trillion Years Club. And so I could see that I could see the big you know, trillion dollars apple $2 trillion market cap companies. They got data at the core, whereas most companies most incumbents. Yeah, it might be a bottling plant that the core, some manufacturing or some other processes they put, they put data around it in these silos. It seems like you're trying toe really? Bring that innovation and put data at the core. And you've got an architecture to do that. You talk about your multi cluster shared storage architecture. You mentioned you mentioned data sharing it. Will this, in your opinion, enable, for instance, incumbents to do what a lot of the startups were able to do with the cloud days? I mean they got access to data centers, which they they couldn't have before the cloud you're trying to do with something similar with data. >>Yeah, so So, you know, obviously there's no doubt that the cloud is a critical enabler. This wouldn't be happening. Uh, you know what? I was at the same time, the trails that have been blessed by the likes of Facebook and Google. Uh, e the reason those enterprises are so extraordinary valuable is is because of what they know. Uh, you know, through data and how they can monetize what they know through data. But that is now because that power is now becoming available, you know, to every single enterprise out there. Right, Because the data platform, the underlying cloud capabilities, we are now delivering that to anybody who wants it. Now, you still need to have strong date engineering data science capabilities. It's not like falling off a log, but fundamentally, those capabilities are now, you know, broadly accessible in the marketplace. >>So we're talking upfront about some of the differences between what you've done earlier in your career. Like I said, you're the worst kept secret, you know, Data domain. I would say it was sort of somewhat of a niche market. You you blew it up until it was very disruptive, but it was somewhat limited in what could be done. Uh, and and maybe some of that limitation, you know, wouldn't have occurred if you stay the price, uh, independent company service. Now you mop the table up because you really had no competition there, Not the case here. You you've got some of the biggest competitors in the world, so talk about that. And what gives you confidence that you can continue to dominate, >>But, you know, it's actually interesting that you bring up these companies. I mean, data. The man was a scenario where we were constrained on market and literally we were a data backup company. As you recall, we needed to move into backup software. Need to move the primary storage. While we knew it, we couldn't execute on it because it took tremendous resource is which, back in the day, it was much harder than one of this right now. So we ended up selling the company to E M. C and and now part of Dell. But way short, uh, we're left with some trauma from that experience, Uh, that, you know, why couldn't we, you know, execute on that transformation? So coming to service now, we were extremely. I'm certainly need personally, extremely attuned to the challenges that we have endured in our prior company. One of the reasons why you saw service now break out at scale at tremendous growth rights is because of what we have learned from the prior journey. We're not gonna ever get caught again in a situation where we could not sustain our markets and sustain our growth. So if service I was very much the execution model was very much a reaction to what we had encountered in the prior company. Now coming into snowflake totally different deal. Because not only is there's a large market, this is a developing market. I think you've pointed out in some of your broadcasting that this market is very much in flux on the reason is that you know, technology is now capable of doing things for for people and enterprises that they could never do before. So people are spending way mawr resource is than they ever thought possible on these new capability. So you can't think in terms of static markets and static data definitions, it means nothing. Okay, These things are so in transition right now, it's very difficult for people you know to to scope that the scale of this opportunity. >>Yeah. I wanna understand you're thinking around and, you know, I've written about the TAM, and can Snowflake grow into its valuation and the way I drew it, I said, Okay, you got data Lakes and you got Enterprise Data Warehouse. That's pretty well understood. But I called it data as a service to cover the closest analogy to your data cloud. And then even beyond that, when you start bringing in the edge and real time data, uh, talk about how you're thinking about that, Tam. And what what you have to do to participate. You have toe, you know, bring adjacent capabilities, ISAT this read data sharing that will get you there. In other words, you're not like a transaction system. You hear people talking about converge databases, you hear? Talk about real time inference at the edge that today anyway, isn't what snowflake is about. Does that vision of data sharing and the data cloud does that allow you to participate in that massive, multi $100 billion tam that that I laid out and probably others as well. >>Yeah, well, it is always difficult. Thio defined markets based on historical concept that probably not gonna apply whole lot for much longer. I mean, the way we think of it is that data is the beating heart of the digital enterprise on, uh, you know, digital enterprises today. What do you look at? People against the car door dash or so on. Um, they were built from the ground up to be digital on the prices and data Is the beating heart off their operation Data operations is their manufacturing, if you will, um, every other enterprise out there is is working very hard to become digital or part digital and is going to learn to develop data platforms like what we're talking about here to data Cloud Azaz. Well, as the expertise in terms of data engineering and data scientist to really fully become a digital enterprise, right. So, you know, we view data as driving operations off the digital enterprise. That's really what it iss right data, and it's completely data driven. And there's no people involved. People are developing and supporting the process. But in the execution, it is end to end. Data driven. Being that data is the is the signal that initiates the process is technol assess. Their there being a detective, and then they fully execute the entire machinery probe Problematic machinery, if you will, um, you know, of the processes that have been designed, for example, you know, I may fit a certain pattern. You know, that that leads to some transactional context. But I've not fully completed that pattern until I click on some Lincoln. And all of a sudden proof I have become, you know, a prime prospect system, the text that in the real time and then unleashes Oh, it's outreach and capabilities to get me to transact me. You and I are experiencing this every day. You know, when we're when we're online, you just may not fully re election. That's what's happening behind the scenes. That's really what this is all about. So and so to me, this is sort of the new online transaction processing is enter and, uh, you know, data digital. Uh, no process that is continually acquiring, analyzing and acting on data. >>Well, you've talked about the time time value of of data. It loses value over time. And to the extent that you can actually affect decisions, maybe before you lose the customer before you lose the patient even even more importantly or before you lose the battle. Uh, there's all kinds of, you know, mental models that you can apply this. So automation is a key part of that. And then again, I think a lot of people like you said, if you just try to look at historical markets, you can't really squint through those and apply them. You really have toe open up your mind and think about the new possibilities. And so I could see your your component of automation. I I see what's happening in the r P. A space and and I could see See these this massive opportunities Thio really change society, change business, your last thoughts. >>There's just there's just no scenario that I can envision where data is not completely core in central to a digital enterprise, period. >>Yeah, I think I really do think, Frank, your your your Your vision is misunderstood somewhat. I think people say Okay. Hey, we'll bet on salute men Scarpelli the team. That's great to do that. But I think this is gonna unfold in a way that people may be having predicted that maybe you guys, yourselves and your founders, you know, haven't have aren't able to predict as well. But you've got that good, strong architectural philosophy that you're pursuing and it just kind of feels right, doesn't it? >>You know, I mean, one of the 100 conversations and, uh, you know, things is the one of the reasons why we also wrote our book. You know, the rights of the data cloud is to convey to the marketplace that this is not an incremental evolution, that this is not sort of building on the past. There is a real step function here on the way to think about it is that typically enterprises and institutions will look at a platform like snowflakes from a workload context. In other words, I have this business. I have this workload. This is very much historically defined, by the way. And then they benchmark us, you know, against what they're what they're already doing on some legacy platform. And they decided, like, Yeah, this is a good fit. We're gonna put Snowflake here. Maybe there, but it's still very workload centric, which means that we are essentially perpetuating the mentality off the past. Right? We were doing it. Wanna work, load of the time We're creating the new silos and the new bunkers of data in the process. And we're really not approaching this with level of vision that the data science is really required to drive maximum benefit from data. So our arguments and this is this is not an easy arguments is to say, toc IOS on any other sea level person that wants to listen to that look, you know, just thinking about, you know, operational context and operational. Excellent. It's like we have toe have a platform that allows us unfettered access to the data that, you know, we may need to, you know, bring the analytical power to right. If you have to bring in political power to a diversity of data sets, how are we going to do that right? The data lives in, like, 500 different places. It's just not possible, right, other than with insane amounts of programming and complexity, and then we don't have the performance, and we don't have to economics, and we don't have the governance and so on. So you really want to set yourself up with a data cloud so that you can unleash your data science, uh, capabilities, your machine learning your deep learning capabilities, aan den, you really get the full throttle advantage. You know of what the technology can do if you're going to perpetuate the silo and bunkering of data by doing it won't work. Load of the time. You know, 5, 10 years from now, we're having the same conversation we've been having over the last 40 years, you know? >>Yeah. Operationalize ing your data is gonna require busting down those those silos, and it's gonna require something like the data cloud to really power that to the next decade and beyond. Frank's movement Thanks so much for coming in. The Cuban helping us do a preview here of what's to come. >>You bet, Dave. Thanks. >>All right. Thank you for watching. Everybody says Dave Volonte for the Cube will see you next time
SUMMARY :
And as you know, we've been tracking the next generation of clouds. Yeah, you as well. Before we get off the I p o. That was something you told me when you're CEO service. this particular scenario, but, you know, it is what it is, Andre. I wanted, you know, I've got some excerpts of your book that that I've been reading. uh, you know, for the sport, uh, you know the only way to become the best version of yourself is to it. The time value of data is gone by the time you know, your business is moving faster than the data is on the single data set because it's just too damn hard, you know, to drive analysis across And so I could see that I could see the big you know, trillion dollars apple Uh, you know, through data and how they can monetize what Uh, and and maybe some of that limitation, you know, wouldn't have occurred if you stay the price, Uh, that, you know, why couldn't we, you know, execute on and the data cloud does that allow you to participate in that massive, And all of a sudden proof I have become, you know, a prime prospect system, Uh, there's all kinds of, you know, mental models that you completely core in central to a digital enterprise, period. maybe you guys, yourselves and your founders, you know, haven't have aren't able to predict as well. You know, I mean, one of the 100 conversations and, uh, you know, things and it's gonna require something like the data cloud to really power that to the next Everybody says Dave Volonte for the Cube will see you next time
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Frank Slootman & Anita Lynch FIX v2
>>Hello, buddy. And welcome back to the cubes. Coverage of Snowflake Data Cloud Summer 2020. We're tracking the rise of the data cloud and fresh off the keynotes. Hear Frank's Luqman, the chairman and CEO of Snowflake, and Anita Lynch, the vice president of data governance at Disney Streaming Services. Folks. Welcome E Need a Disney plus. Awesome. You know, we signed up early. Watched all the Marvel movies. Hamilton, the new Pixar movie Soul. I haven't gotten to the man DeLorean yet. Your favorite, but I really appreciate you guys coming on. Let me start with Frank. I'm glad you're putting forth this vision around the data cloud because I never liked the term Enterprise Data Warehouse. What you're doing is is so different from the sort of that legacy world that I've known all these years. But start with why the data cloud? What problems are you trying to solve? And maybe some of the harder challenges you're seeing? >>Yeah. You know, we have We've come a long way in terms of workload, execution, right? In terms of scale and performance and concurrent execution. We really taking the lid off. Sort of the physical constraints that that have existed on these types of operations. But there's one problem, uh, that were not yet, uh solving. And that is the silo ing and bunkering of data essentially in the data is locked in applications. It's locked in data centers. It's locked in cloud cloud regions incredibly hard for for data science teams to really unlock the true value of data when you when you can address patterns that that exists across data set. So we're perpetuate, uh, status we've had for for ever since the beginning off computing. If we don't start Thio, crack that problem now we have that opportunity. But the notion of a data cloud is like basically saying, Look, folks, you know, we we have to start inside, lowing and unlocking the data on bring it into a place where we can access it. Uh, you know, across all these parameters and boundaries that have historically existed, it's very much a step level function. Customers have always looked at things won't workload at that time. That mentality really has to go. You really have to have a data club mentality as well as a workload orientation towards towards managing data. >>Anita is great here in your role at Disney and you're in your keynote and the work you're doing the governance work and you're you're serving a great number of stakeholders, enabling things like data sharing. You got really laser focused on trust, compliance, privacy. This idea of a data clean room is really interesting. You know, maybe you can expand on some of these initiatives here and share what you're seeing as some of the biggest challenges to success. And, of course, the opportunities that you're unlocking. >>Sure, I mean, in my role leading data to governance, it's really critical to make sure that all of our stakeholders not only know what data is available and accessible to them, they can also understand really easily and quickly whether or not the data that they're using is for the appropriate use case. And so that's a big part of how we scale data governance. And a lot of the work that we would normally have to do manually is actually done for us through the data Clean rooms. >>Thank you for that. I wonder if you could talk a little bit more about the role of data and how your data strategy has evolved and maybe discuss some of the things that Frank mentioned about data silos. And I mean, obviously you can relate to that having been in the data business for a while, but I wonder if you could elucidate on that. >>Sure, I mean data complexities air going to evolve over time in any traditional data architecture. Er, simply because you often have different teams at different periods in time trying thio, analyze and gather data across Ah, whole lot of different sources. And the complexity that just arises out of that is due to the different needs of specific stakeholders, their time constraints. And quite often, um, it's not always clear how much value they're gonna be able to extract from the data at the outset. So what we've tried to do to help break down the silos is allow individuals to see up front how much value they're going to get from the data by knowing that it's trustworthy right away. By knowing that it's something that they can use in their specific use case right away, and by ensuring that essentially, as they're continuing to kind of scale, the use cases that they're focused on their no longer required Thio make multiple copies of the data, do multiple steps to reprocess the data. And that makes all the difference in the world, >>for sure. I mean, copy creep, because it be the silent killer. Frank, I've followed you for a number of years. Your big thinker. You and I have had a lot of conversations about the near term midterm and long term. I wonder if you could talk about you know, when you're Kino. You talk about eliminating silos and connecting across data sources, which really powerful concept. But really only if people are willing and able to connect and collaborate. Where do you see that happening? Maybe What are some of the blockers there? >>Well, there's there's certainly, ah, natural friction there. I still remember when we first started to talk to to Salesforce, you know, they had discovered that we were top three destination off sales first data, and they were wondering why that was. And the reason is, of course, that people take salesforce data, push it to snowflake because they wanna overlay it with what data? Outside of Salesforce, you know, whether it's adobe or any other marketing data set and then they want to run very highly skilled processes, you know, on it. But the reflexes in the world of SAS is always like, No, we're an island were planning down to ourselves. Everybody needs to come with us as opposed to we We go, you know, to a different platform to run these type of processes. It's no different for the for the public club. Better day didn't mean they have, you know, massive moats around there. Uh, you know, their stories to, you know, really prevent data from from leaving their their orbit. Eso there is natural friction in, uh, in terms off for this to happen. But on the other hand, you know, there is an enormous need, you know, we can't deliver on on the power and potential of data unless we allow it to come together. Uh, snowflake is the platform that allows that to happen. Uh, you know, we were pleased with our relationship with Salesforce because they did appreciate you know why this was important and why this was necessary. And we think you know, other parts of the industry will gradually come around to it as well. So the the idea of a data cloud has really come, right? Uh, people are recognizing, you know, why does this matter now? It's not gonna happen overnight. There's a step global function of very big change in mentality and orientation. >>Yeah. It's almost as though the SAS ification of our industry sort of repeated some of the application silos and you build a hardened top around it. All the processes are hard around. OK, here we go. And you're really trying to break that, aren't you? Yeah, Exactly. Anita. Again, I wanna come back to this notion of governance. It's so it's so important. It's the first role in your title, and it really underscores the importance of this. Um, you know, Frank was just talking about some of the hurdles, and this is this is a big one. I mean, we saw this in the early days of big data. Where governance was this after thought it was like, bolted on kind of wild, Wild West. I'm interested in your governance journey. And maybe you could share a little bit about what role snowflake has played there in terms of supporting that agenda. Bond. Kind of What's next on that journey? >>Sure. Well, you know, I've I've led data teams in a numerous, uh, in numerous ways over my career. This is the first time that I've actually had the opportunity to focus on governance. And what it's done is allowed for my organization to scale much more rapidly. And that's so critically important for our overall strategy as a company. >>Well, I mean a big part of what you were talking about. At least my inference in your talk was really that the business folks didn't have to care about, you know, wonder about they cared about it. But they're not the wonder about and and about the privacy, the concerns, etcetera. You've taken care of all that. It's sort of transparent to them. Is that >>yeah, right. That's right. Absolutely So we focus on ensuring compliance across all of the different regions where we operate. We also partner very heavily with our legal and information security teams. They're critical to ensuring, you know, that were ableto do this. We don't we don't do it alone. But governance includes not just, you know, the compliance and the privacy. It's also about data access, and it's also about ensuring data quality. And so all of that comes together under the governance umbrella. I also lead teams that focus on things like instrumentation, which is how we collect data. We focus on the infrastructure and making sure that we've architected for scale and all of these air really important components of our strategy. >>I got. So I have a question. Maybe each of you can answer. I I sort of see this our industry moving from, you know, products toe, then two platforms and platforms, even involving into ecosystems. And then there's this ecosystem of data. You guys both talked a lot about data sharing, But maybe Frank, you could start in Anita. You can add on to Frank's answer. You're obviously both both passionate about the use of data and trying to do so in a responsible way. That's critical, but it's also gonna have business impact. Frank, where's this passion come from? On your side. And how are you putting in tow action in your own organization? >>Well, you know, I'm really gonna date myself here, but, you know, uh, many, many years ago, uh, I saw the first glimpse off, uh, multidimensional databases that were used for reporting really on IBM mainframes on git was extraordinarily difficult. We didn't even have the words back then in terms of data, warehouses and all these terms didn't exist. People just knew that they wanted to have, um, or flexible way of reporting and being able Thio pivot data dimensionally and all these kinds of things. And I just whatever this predates, you know, Windows 3.1, which really set off the whole sort of graphical in a way of dealing with systems which there's not a whole generations of people that don't know any different, Right? So I I've lived the pain off. This problem on sort of had a front row seat to watching this this transpire over a very long period of time. And that's that's one of the reasons you know why I'm here. Because I finally seen a glimpse off. You know, I also as an industry fully fully just unleashing and unlocking the potential were not in a place where the technology is ahead of people's ability to harness it right, which we've never been there before, right? It was always like we wanted to do things that technology wouldn't let us. It's different now. I mean, people are just heads are spinning with what's now possible, which is why you see markets evolved very rapidly right now. We were talking earlier about how you can't take, you know, past definitions and concepts and apply them to what's going on the world. The world's changing right in front of your eyes right now. >>Sonita. Maybe you could add on to what Frank just said and share some of the business impacts and and outcomes that are notable since you're really applied your your love of data and maybe maybe touch on culture, data, culture, any words of wisdom for folks in the audience who might be thinking about embarking on a data cloud journey similar to what you've been on? >>Yeah, sure, I think for me. I fell in love with technology first, and then I fell in love with data, and I fell in love with data because of the impact the data can have on both the business and the technology strategy. And so it's sort of that nexus, you know, between all three and in terms of my career journey and some of the impacts that I've seen. I mean, I think with the advent of the cloud you know before. Well, how do I say that before the cloud actually became, you know, so prevalent and such a common part of the strategy that's required It was so difficult, you know, so painful. It took so many hours to actually be able to calculate, you know, the volumes of data that we had. Now we have that accessibility, and then on top of it with the snowflake data cloud, it's much more performance oriented from a cost perspective because you don't have multiple copies of the data, or at least you don't have toe have multiple copies of the data. And I think moving beyond some of the traditional mechanisms for for measuring business impact has has only been possible with the volumes of data that we have available to us today. And it's just it's phenomenal to see the speed at which we can operate and really, truly understand our customers, interests and their preferences, and then tailor the experiences that they really want and deserve for them. Um, it's it's been a great feeling. Thio, get to this point in time. >>That's fantastic. So, Frank, I gotta ask you if you're still in your spare time. You decided to write a book? I'm loving it. Um, I don't have a signed copy, so I'm gonna have to send it back and have you sign it. But your love, the inside baseball, it's just awesome. Eso really appreciate that. So but why did you decide to write a book? >>Well, there were a couple of reasons. Obviously, uh, we thought it was an interesting tale to tell for anybody who's interested in, you know what's going on. How did this come about, You know, where the characters behind the scenes and all this kind of stuff. But, you know, from a business standpoint, because this is such a step function, it's so non incremental. We felt like, you know, we really needed quite a bit of real estate to really lay out what the full narrative in context is on. Do you know, we thought books titled The Rise of the Data Cloud. That's exactly what it iss. And we're trying to make the case for that mindset, that mentality, that strategy. Uh, because all of us, you know, I think it's an industry were risk off, you know, persisting, perpetuating. Uh, you know, where we've been since the beginning off computing. So we're really trying to make a pretty forceful case for Look, there's an enormous opportunity out there. The different choices you have to make along the way. >>Guys, we got to leave it there. Frank. I know you and I are gonna talk again. Anita. I hope we have a chance to meet face to face and and talking the Cube live someday. You're phenomenal guests. And what a great story. Thank you both for coming on. Thank you. All right, you're welcome. And keep it right there, buddy. We'll be back for the next guest right after this short break and we're clear. All right. Not bad.
SUMMARY :
And maybe some of the harder challenges you're seeing? But the notion of a data cloud is like basically saying, Look, folks, you know, You know, maybe you can expand on some of these initiatives here and share what you're seeing as some of the biggest And a lot of the work that we would normally have to do manually is actually done for And I mean, obviously you can relate to that having been in the data business for a while, And that makes all the difference in the world, I wonder if you could talk about you And we think you know, other parts of the industry will gradually come around to it as well. And maybe you could share a little bit about what role snowflake has played there This is the first time that I've actually had the opportunity was really that the business folks didn't have to care about, you know, not just, you know, the compliance and the privacy. And how are you putting in tow action in your own organization? And I just whatever this predates, you know, Windows 3.1, Maybe you could add on to what Frank just said and share some of the business impacts able to calculate, you know, the volumes of data that we had. Um, I don't have a signed copy, so I'm gonna have to send it back and have you sign it. Uh, because all of us, you know, I think it's an industry were I know you and I are gonna talk again.
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Frank Slootman & Anita Lynch V1
>> Hello everybody and welcome back to the cubes coverage of the Snowflake Data Cloud Summit 2020. We're tracking the rise of the Data Cloud, and fresh off the keynotes here, Frank Slootman, the chairman and CEO of Snowflake and Anita Lynch, the vice president of Data Governance at Disney Streaming Services. Folks, welcome. >> Thank you Thanks for having us, Dave, >> I need a Disney plus awesome. You know, we signed up early, watched all the Marvel movies, Hamilton, the new Pixar Movie saw, I haven't gotten into the Mandalorian yet, your favorite, but, (woman laughing) really appreciate you guys coming on. Let me start with Frank. I'm glad you're putting forth this vision around the data cloud, because I never liked the term Enterprise Data Warehouse, what you're doing is so different from the sort of that legacy world that I've known all these years, but start with why the Data Cloud, what problems are you trying to solve? And maybe some of the harder challenges you're seeing. >> Yeah I know, you know we've come a long way in terms of workload execution, right? In terms of scale and performance, you know, concurrent execution, we really taken the lid off sort of the physical constraints that have existed on these types of operations. But there's one problem, that we're not yet solving. And that is the siloing and bunkering of data. And especially in a data is locked in application it is locked data centers, is locked in cloud regions, incredibly hard for data science teams to really, you know, unlock the true value of data. When you can address patterns that exist across a data set. So we're perpetuate, a status we've had forever since the beginning of computing. If we don't start to crack that problem now we have that opportunity. But the notion of a Data Cloud is like basically saying, look folks, you know, we have to start unsiloing and unlocking the data, and bring it into a place, you know, where we can access it, you know, across all these parameters and boundaries that have historically existed. It's very much a step level function. Now the customers have always looked at things one workload at a time, that mentality really has to go. You really have to have a Data Cloud mentality, as well as a workload orientation towards managing data. >> Anita was great hearing your role at Disney, and your keynote, and the work you're doing, the governance work, and you're serving a great number of stakeholders, enabling things like data sharing, you got really laser focused on trust, compliance, privacy. Is this idea of a data clean room is really interesting. You maybe you can expand on some of these initiatives here and share what you're seeing as some of the biggest challenges to success. And of course, the opportunities that you're unlocking. >> Sure. I mean, in my role, leading Data Governance, it's really critical to make sure that all of our stakeholders, not only know what data is available and accessible to them, they can also understand really easily and quickly, whether or not the data that they're using is for the appropriate use case. And so, that's a big part of how we scale data governance, and a lot of the work that we would normally have to do manually, is actually done for us through the data clean rooms. >> Thank you for that. I wonder if you could talk a little bit more about the role of data and how your data strategy has evolved and maybe discuss some of the things that Frank mentioned about data silos, and obviously you can relate to that, having been in the data business for awhile, but wonder if you can elucidate on that. >> Sure. I mean, data complexities are going to evolve over time in any traditional data architecture, simply because you often have different teams at different periods in time, trying to analyze and gather data across a whole lot of different sources. And the complexity that just arises out of that, is, due to the different needs of specific stakeholders. There are time constraints, and quite often it's not always clear, how much value they're going to be able to extract from the data at the outset. So what we've tried to do to help break down those silos, is, allow individuals to see upfront how much value they're going to get from the data, by knowing that it's trustworthy right away . By knowing that it's something that they can use in their specific use case right away. And by ensuring that essentially, as they're continuing to kind of scale the use cases that they're focused on, they're no longer required to make multiple copies of the data, do multiple steps to reprocess the data. And that makes all the difference in the world. >> Yeah, for sure. I mean copy creek, cause it'd be the silent killer. Frank I followed you for a number of years. You're a big thinker. You and I have had a lot of conversations about the near term, mid term and long term. I wonder if you could talk about, you know, when your keynote, you talked about eliminating silos, and connecting across data sources, which really powerful concept, but it really only, if people are willing and able to connect and collaborate, where do you see that happening? Maybe what are some of the blockers there? >> Well, there's certainly a natural friction there. I still remember when we first started to talk to Salesforce, you know, they had, discovered that we were a top three destination of Salesforce data and they were wondering, you know, why that was? And the reason is of course that people take Salesforce data, push it to Snowflake, because they want to overlay it with data outside of Salesforce. You know what it is Adobe or any 6other marketing dataset. And then they want to run very highly skilled processes, you know, on it. But the reflexes in the world of SAS, is always like, no, we're an Island, we're a planet onto ourselves. Everybody needs to come with us as opposed to, we go to a different platform to run these types of processes. It's no different for thee public cloud vendor. They did only, they have, you know, massive moats around, you know, their storage to, you know, to really prevent data from leaving their orbit. So there is natural friction in terms of for this to happen. But on the other hand, you know, there is an enormous need, you know, we can't deliver on the power and potential of data, unless we allow it to come together. Snowflake is the platform that allows that to happen. You know, we were pleased with our relationship with Salesforce because they did appreciate, you know, why this was important and why this was necessary. And we think, you know, other parts of the industry will gradually come around to it as well. So the idea of a Data Cloud has really come. Right, people are recognizing, you know, why does this matters now. It's not going to happen overnight. It is a step what will function a very big change in mentality and orientation. You know? >> Yeah. It's almost as though the sussification of our industry sort of repeated some of the application silos, and build a heart on to and all the processes of(mummers) Okay, here we go. And you're really trying to break that aren't you? >> Yep, exactly. >> Anita, again, I want to come back to this notion of governance. It's so important. It's the first rule in your title, and it really underscores the importance of this. You know, Frank was just talking about some of the hurdles and this is a big one. I mean we saw this in the early days of big data where governance was this afterthought. It was like bolted on kind of wild west. I'm interested in your governance journey. And maybe you can share a little bit about what role Snowflake has played there in terms of supporting that agenda, and kind of what's next on that journey. >> Sure. Well, you know, I've led data teams, in numerous ways over my career, this is the first time, that I've actually had the opportunity to focus on governance. And what it's done, is allowed for my organization to scale much more rapidly. And that's so critically important for our overall strategy as a company. >> Well, I mean, a big part of what you were talking about, at least my inference in your talk, was really that the business folks didn't have to care about, your wonder about they cared about it, but they don't have to wonder about, and about the privacy concerns, et cetera, you've taken care of all that. It's sort of transparent to them. >> Yeah, that's right. Absolutely. So we focus on ensuring compliance across all of the different regions where we operate. We also partner very heavily with our legal and information security teams. They're critical, to ensuring you know, that we're able to do this. We don't do it alone. But governance includes not just, you know, the compliance and the privacy. It's also about data access. And it's also about ensuring data quality. And so all of that comes together under the governance umbrella. I also lead teams that focus on things like instrumentation, which is how we collect data, we focus on the infrastructure, and making sure that we've architected for scale , and all of these are really important components of our strategy. >> So I have a question maybe each of you can answer it. I sort of see this, our industry moving from products to then, to the platforms and platforms even evolving into ecosystems. And then there's this ecosystem of data. You guys both talked a lot about data sharing, but, but maybe Frank, you can start and Anita you can add onto Frank's answer. You obviously both passionate about the use of data and trying to do so in a responsible way, that's critical, but it's also going to have business impact. Frank, where's this passion come from on your side? And how are you putting into action in your own organization? >> Well, you know, I'm really going to date myself here, but you know many years ago, you know, I saw the first glimpse of multidimensional databases that were used for reporting really on IBM mainframes. And it was extraordinarily difficult. We didn't even have the words back then in terms of data, warehouses and business, all these terms didn't exist. People just knew that they want to have a more flexible way of reporting and being able to pivot data, dimensionally, all these kinds of things. And I just by whatever this predates, you know, windows 3.1, which really, you know, set off the whole sort of graphical, you know, way of dealing with systems, which there's not whole generations of people that don't know any different. Right? So I've lived the pain of this problem, and sort of had a front row seat, to watching this transpire over a very long period of time. And that's one of the reasons, you know, why I'm here because I finally seen, you know, a glimpse of, you know, I also, as an industry fully, just unleashing and unlocking the potential. We're not at a place where the technology is ahead of people's ability to harness it. Right. Which we'd never been there before. Right. It was always like we wanted to do things and technology wouldn't let us, it's different now. I mean, people are just, heads are spinning with what's now possible, which is why you see Marcus evolve, you know, very rapidly right now, we were talking earlier about how you can't take, you know, past definitions and concepts and apply them to what's going on in the world. The world's changing right in front of your eyes right now, >> So Anita maybe you could add on to what Frank just said and share some of the business impacts, and outcomes that are notable since you've really applied your love of data and maybe touch culture, data culture. Any words of wisdom for folks in the audience who might be thinking about embarking on a Data Cloud journey, similar to what you've been on. >> Yeah Sure. I think for me, I fell in love with technology first, and then I fell in love with data and I fell in love with data because of the impact that data can have, on both the business, and the technology strategy. And so it's sort of that nexus between all three. And in terms of my career journey and some of the impacts that I've seen. I think with the advent of the Cloud, you know, before, well, how do I say this? Before the cloud actually became so prevalent and such a common part of the strategy that's required, it was so difficult, you know, so painful. It took so many hours to actually, be able to calculate, you know, the volumes of data that we had. Now we have that accessibility. And then on top of it, with the Snowflake Data Cloud, it's much more performance oriented from a cost perspective because you don't have multiple copies of the data, or at least you don't have to have multiple copies of the data. And I think, moving beyond some of the traditional mechanisms for measuring business impact, has only been possible with the volumes of data that we have available to us today. And it's just, it's phenomenal to see the speed at which we can operate and really, truly understand our customer's interests and their preferences, and then tailor the experiences that they really want and deserve for them. It's been a great feeling to get to this point in time. >> That's fantastic. So, Frank, I got to ask you to do so in your spare time you decided to write a book am loving it. I have a signed copy, so I'm going to have to send it back and have you sign it. But, and I love the inside baseball. It's just awesome. So really appreciate that. So, but why did you decide to write a book? >> Well, there were a couple of reasons. Obviously we thought it was an interesting tale to tell for anybody, you know, who is interested in, you know, what's going on? How did this come about? You know, or the characters behind the scenes and all this kind of stuff. But, you know, from a business standpoint, you know, because this is such a step function, it's so non incremental, we felt like we really needed quite a bit of real estate to really lay out, what the full narrative and context is. And, you know, we thought, you know, books titled the rise of the Data Cloud. That's exactly what it is. And we're trying to make the case for that mindset, that mentality, that strategy, because all of us, you know, I think as an industry we're at risk of, you know, persisting, perpetuating, you know, where we've been since the beginning of computing. So we're really trying to make a pretty forceful case for look, you know, there's an enormous opportunity out there, but there's some choices you have to make along the way. >> Guys, we got to leave it there. Frank. I know you and I are going to talk again, Anita, I hope we have a chance to meet face to face and in the cube live someday, your phenomenal guest and what a great story. Thank you both for coming on. Thanks Dave, >> Thank you >> You're welcome to keep it right there, buddy. We'll be back with the next guest right after this short break. (upbeat music)
SUMMARY :
of the Snowflake Data Cloud Summit 2020. And maybe some of the harder to really, you know, of the biggest challenges to success. and a lot of the work that and obviously you can relate to that, And that makes all the talk about, you know, But on the other hand, you know, of the application silos, of the hurdles and this is a big one. that I've actually had the opportunity of what you were talking about, to ensuring you know, each of you can answer it. And that's one of the reasons, you know, and share some of the business impacts, it was so difficult, you know, so painful. I got to ask you to do to tell for anybody, you know, I know you and I We'll be back with the next guest right
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Frank Slootman, Snowflake | CUBE Conversation, April 2020
(upbeat music) >> Narrator: From theCUBE Studios in Palo Alto and Boston, connecting with thought leaders all around the world, this is theCUBE Coversation. >> All right everybody, this is Dave Vellante and welcome to this special CUBE Conversation. I first met Frank Slootman in 2007 when he was the CEO of Data Domain. Back then he was the CEO of a disruptive company and still is. Data Domain, believe or not back then, was actually replacing tape drives as the primary mechanism for backup. Yes, believe it or not, it used to be tape. Fast forward several years later, I met Frank again at VMworld when he had become the CEO of ServiceNow. At the time ServiceNow was a small company, about 100 plus million dollars. Frank and his team took that company to 1.2 billion. And Gartner, at the time of IPO said "you know, this doesn't make sense. "It's a small market, it's a very narrow help desk market, "it's maybe a couple billion dollars." The vision of Slootman and his team was to really expand the total available market and execute like a laser. Which they did and today, ServiceNow a very, very successful company. Snowflake first came into my line of sight in 2015 when SiliconANGLE wrote an article, "Why Snowflake is Better "Than Amazon Redshift, Re-imagining Data". Well last year Frank Slootman joined Snowflake, another disruptive company. And he's here today to talk about how Snowflake is really participating in this COVID-19 crisis. And I really want to share some of Frank's insights and leadership principles, Frank great to see you, thanks for coming on. >> Yeah, thanks for having us Dave. >> So when I first reported earlier this year on Snowflake and shared some data with the community, you reached back out to me and said "Dave, I want to just share with you. "I am not a playbook CEO, I am a situational CEO. "This is what I learned in the military." So Frank, this COVID-19 situation was thrown at you, it's a black swan, what was your first move as a leader? >> Well, my first move is let's not overreact. Take a deep breath. Let's really examine what we know. Let's not jump to conclusions, let's not try to project things that we're not capable of projecting. That's hard because we tend to have sort of levels of certainty about what's going to happen in the week, in the next month and so on and all of a sudden that's out of the window. It creates enormous anxiety with people. So in other words you got to sort of reset to okay, what do we know, what can we do, what do we control? And not let our minds sort of go out of control. So I talk to our people all the time about maintain a sense of normalcy, focus on the work, stay in the moment and by the way, turn the newsfeed off, right, because the hysteria you get fed through the media is really not helpful, right? So just cool down and focus on what we still can do. And then I think then everybody takes a deep breath and we just go back to work. I mean, we're in this mode now for three weeks and I can tell you, I'm on teleconferencing calls, whatever, eight, nine hours a day. Prospects, customers, all over the world. Pretty much what I was doing before except I'm not traveling right now. So it's not, >> Yeah, so it sounds clear-- >> Not that different than what it was before. (laughs) >> It sounds very Bill Belichickian, you know? >> Yeah. >> Focus on those things of which you can control. When you were running ServiceNow I really learned it from you and of course Mike Scarpelli, your then and current CFO about the importance of transparency. And I'm interested in how you're communicating, it sounds like you're doing some very similar things but have you changed the way in which you've communicated to your team, your internal employees at all? >> We're communicating much more. Because we can no longer rely on sort of running into people here, there and everywhere. So we have to be much more purposeful about communications. For example, I mean I send an email out to the entire company on Monday morning. And it's kind of a bunch of anecdotes. Just to bring the connection back, the normalcy. It just helps people get connected back to the mothership and like well, things are still going on. We're still talking in the way we always used to be. And that really helps and I also, I check in with people a lot more, I ask all of our leadership to constantly check in with people because you can't assume that everybody is okay, you can't be out of sight, out of mind. So we need to be more purposeful in reaching out and communicating with people than we were previously. >> And a lot of people obviously concerned about their jobs. Have you sort of communicated, what have you communicated to employees about layoffs? I mean, you guys just did a large raise just before all this, your timing was kind of impeccable. But what have you communicated in that regard? >> I've said, there's no layoffs on our radar, number one. Number two, we are hiring. And number three is we have a higher level of scrutiny on the hires that we're making. And I am very transparent. In other words I tell people look, I prioritize the roles that are closest to the direct train of the business. Right, it's kind of common sense. But I wanted to make sure that this is how we're thinking about it. There are some roles that are more postponable than others. I'm hiring in engineering without any reservation because that is the long term strategic interest of the company. One the sales side, I want to know that sales leaders know how to convert to yields, that we're not just sort of bringing capacity online. And the leadership is not convinced or confident that they can convert to yield. So there's a little bit finer level of scrutiny on the hiring. But by and large, it's not that different. There's this saying out there that we should suspend all non-essential spending and hiring, I'm like you should always do that. Right? I mean what's different today? (both laugh) If it's non-essential, why do it, right? So all of this comes back to this is probably how we should operate anyways, yep. >> I want to talk a little bit about the tech behind Snowflake. I'm very sensitive when CEOs come on my program to make sure that we're not, I'm not trying to bait CEOs into ambulance chasing, that's not what it's about. But I do want to share with our community kind of what's new, what's changed and how companies like Snowflake are participating in this crisis. And in particular, we've been reporting for awhile, if you guys bring up that first slide. That the innovation in the industry is really no longer about Moore's Law. It's really shifted. There's a new, what we call an innovation cocktail in the business and we've collected all this data over the last 10 years. With Hadoop and other distributed data and now we have Edge Data, et cetera, there's this huge trove of data. And now AI is becoming real, it's becoming much more economical. So applying machine intelligence to this data and then the Cloud allows us to do this at scale. It allows us to bring in more data sources. It brings an agility in. So I wonder if you could talk about sort of this premise and how you guys fit. >> Yeah, I would start off by reordering the sequence and saying Cloud's number one. That is foundational. That helps us bring scale to data that we never had to number two, it helps us bring computational power to data at levels we've never had before. And that just means that queries and workloads can complete orders of magnitude faster than they ever could before. And that introduces concepts like the time value of data, right? The faster you get it, the more impactful and powerful it is. I do agree, I view AI as sort of the next generation of analytics. Instead of using data to inform people, we're using data to drive processes and businesses directly, right? So I'm agreeing obviously with these strengths because we're the principal beneficiaries and drivers of these platforms. >> Well when we talked about earlier this year about Snowflake, we really brought up the notion that you guys were one of the first if not the first. And guys, bring back Frank, I got to see him. (Frank chuckles) One of the first to really sort of separate the notion of being able to scale, compute independent of storage. And that brought not only economics but it brought flexibility. So you've got this Cloud-native database. Again, what caught my attention in that Redshift article we wrote is essentially for our audience, Redshift was based on ParAccel. Amazon did a great job of really sort of making that a Cloud database but it really wasn't born in the Cloud and that's sort of the advantage of Snowflake. So that architectural approach is starting to really take hold. So I want to give an example. Guys if you bring up the next chart. This is an example of a system that I've been using since early January when I saw this COVID come out. Somebody texted me this. And it's the Johns Hopkins dataset, it's awesome. It shows you, go around the map, you can follow it, it's pretty close to real time. And it's quite good. But the problem is, all right thank you guys. The problem is that when I started to look at, I wanted to get into sort of a more granular view of the counties. And I couldn't do that. So guys bring up the next slide if you would. So what I did was I searched around and I found a New York Times GitHub data instance. And you can see it in the top left here. And basically it was a CSV. And notice what it says, it says we can't make this file beautiful and searchable because it's essentially too big. And then I ran into what you guys are doing with Star Schema, Star Schema's a data company. And essentially you guys made the notion that look, the Johns Hopkins dataset as great as it is it's not sort of ready for analytics, it's got to be cleaned, et cetera. And so I want you to talk about that a little bit. Guys, if you could bring Frank back. And share with us what you guys have done with Star Schema and how that's helping understand COVID-19 and its progression. >> Yeah, one of the really cool concepts I've felt about Snowflake is what we call the data sharing architecture. And what that really means is that if you and I both have Snowflake accounts, even though we work for different institutions, we can share data optics, tables, schema, whatever they are with each other. And you can process against that in place if they are residing in a local, to your own platform. We have taken that concept from private also to public. So that data providers like Star Schema can list their datasets, because they're a data company, so obviously it's in their business interest to allow this data to be profiled and to be accessible by the Snowflake community. And this data is what we call analytics ready. It is instantly accessible. It is also continually updated, you have to do nothing. It's augmented with incremental data and then our Snowflake users can just combine this data with supply chain, with economic data, with internal operating data and so on. And we got a very strong reaction from our customer base because they're like "man, you're saving us weeks "if not months just getting prepared to start to do an al, let alone doing them." Right? Because the data is analytics ready and they have to do literally nothing. I mean in other words if they ask us for it in the morning, in the afternoon they'll be running workloads again. Right, and then combining it with their own data. >> Yeah, so I should point out that that New York Times GitHub dataset that I showed you, it's a couple of days behind. We're talking here about near realtime, or as close as realtime as you can get, is that right? >> Yep. Yeah, every day it gets updated. >> So the other thing, one of the things we've been reporting, and Frank I wondered if you could comment on this, is this new emerging workloads in the Cloud. We've been reporting on this for a couple of years. The first generation of Cloud was IS, was really about compute, storage, some database infrastructure. But really now what we're seeing is these analytic data stores where the valuable data is sitting and much of it is in the Cloud and bringing machine intelligence and data science capabilities to that, to allow for this realtime or near realtime analysis. And that is a new, emerging workload that is really gaining a lot of steam as these companies try to go to this so-called digital transformation. Your comments on that. >> Yeah, we refer to that as the emergence or the rise of the data Cloud. If you look at the Cloud landscape, we're all very familiar with the infrastructure clouds. AWS and Azure and GCP and so on, it's just massive storage and servers. And obviously there's data locked in to those infrastructure clouds as well. We've been familiar for it for 10, 20 years now with application clouds, notably Salesforce but obviously Workday, ServiceNow, SAP and so on, they also have data in them, right? But now you're seeing that people are unsiloing the data. This is super important. Because as long as the data is locked in these infrastructure clouds, in these application clouds, we can't do the things that we need to do with it, right? We have to unsilo it to allow the scale of querying and execution against that data. And you don't see that any more clear that you do right now during this meltdown that we're experiencing. >> Okay so I learned long ago Frank not to argue with you but I want to push you on something. (Frank laughs) So I'm not trying to be argumentative. But one of those silos is on-prem. I've heard you talk about "look, we're a Cloud company. "We're Cloud first, we're Cloud only. "We're not going to do an on-prem version." But some of that data lives on-prem. There are companies out there that are saying "hey, we separate compute and storage too, "we run in the Cloud. "But we also run on-prem, that's our big differentiator." Your thoughts on that. >> Yeah, we burnt the ship behind us. Okay, we're not doing this endless hedging that people have done for 20 years, sort of keeping a leg in both worlds. Forget it, this will only work in the public Cloud. Because this is how the utility model works, right? I think everybody is coming to this realization, right? I mean excuses are running out at this point. We think that it'll, people will come to the public Cloud a lot sooner than we will ever come to the private Cloud. It's not that we can't run on a private cloud, it just diminishes the potential and the value that we bring. >> So as sort of mentioned in my intro, you have always been at the forefront of disruption. And you think about digital transformation. You know Frank we go to all of these events, it used to be physical and now we're doing theCUBE digital. And so everybody talks about digital transformation. CEOs get up, they talk about how they're helping their customers move to digital. But the reality is is when you actually talk to businesses, there was a lot of complacency. "Hey, this isn't really going to happen in my lifetime" or "we're doing pretty well." Or maybe the CEO might be committed but it doesn't necessarily trickle down to the P&L managers who have an update. One of the things that we've been talking about is COVID-19 is going to accelerate that digital transformation and make it a mandate. You're seeing it obviously in retail play out and a number of other industries, supply chains are, this has wreaked havoc on supply chains. And so there's going to be a rethinking. What are your thoughts on the acceleration of digital transformation? >> Well obviously the crisis that we're experiencing is obviously an enormous catalyst for digital transformation and everything that that entails. And what that means and I think as a industry we're just victims of inertia. Right, I mean haven't understood for 20 years why education, both K through 12 but also higher ed, why they're so brick and mortar bound and the way they're doing things, right? And we could massively scale and drop the cost of education by going digital. Now we're forced into it and everybody's like "wow, "this is not bad." You're right, it isn't, right but we haven't so the economics, the economic imperative hasn't really set in but it is now. So these are all great things. Having said that, there are also limits to digital transformation. And I'm sort of experiencing that right now, being on video calls all day. And oftentimes people I've never met before, right? There's still a barrier there, right? It's not like digital can replace absolutely everything. And that is just not true, right? I mean there's some level of filter that just doesn't happen when you're digital. So there's still a need for people to be in the same place. I don't want to sort of over rotate on this concept, that like okay, from here on out we're all going to be on the wires, that's not the way it will be. >> Yeah, be balanced. So earlier you made a comment, that "we should never "be spending on non-essential items". And so you've seen (Frank laughs) back in 2008 you saw the Rest in Peace good times, you've seen the black swan memos that go out. I assume that, I mean you're a very successful investor as well, you've done a couple of stints in the VC community. What are you seeing in the Valley in regard to investments, will investments continue, will we continue to feed innovation, what's your sense of that? Well this is another wake up call. Because in Silicon Valley there's way too much money. There's certainly a lot of ideas but there's not a lot of people that can execute on it. So what happens is a lot of things get funded and the execution is either no good or it's just not a valid opportunity. And when you go through a downturn like this you're finding out that those businesses are not going to make it. I mean when the tide is running out, only the strongest players are going to survive that. It's almost a natural selection process that happens from time to time. It's not necessarily a bad thing because people get reallocated. I mean Silicon Valley is basically one giant beehive, right? I mean we're constantly repurposing money and people and talent and so on. And that's actually good because if an idea is not worth in investing in, let's not do it. Let's repurpose those resources in places where it has merit, where it has viability. >> Well Frank, I want to thank you for coming on. Look, I mean you don't have to do this. You could've retired long, long ago but having leaders like you in place in these times of crisis, but even when in good times to lead companies, inspire people. And we really appreciate what you do for companies, for your employees, for your customers and certainly for our community, so thanks again, I really appreciate it. >> Happy to do it, thanks Dave. >> All right and thank you for watching everybody, Dave Vellante for theCUBE, we will see you next time. (upbeat music)
SUMMARY :
this is theCUBE Coversation. And I really want to share some of Frank's insights and said "Dave, I want to just share with you. So in other words you got to sort of reset to okay, Not that different than what it was before. I really learned it from you and of course Mike Scarpelli, I ask all of our leadership to constantly check in But what have you communicated in that regard? So all of this comes back to this is probably how and how you guys fit. And that just means that queries and workloads And then I ran into what you guys are doing And what that really means is that if you and I or as close as realtime as you can get, is that right? Yeah, every day it gets updated. and much of it is in the Cloud And you don't see that any more clear that you do right now Okay so I learned long ago Frank not to argue with you and the value that we bring. But the reality is is when you actually talk And I'm sort of experiencing that right now, And when you go through a downturn like this And we really appreciate what you do for companies, Dave Vellante for theCUBE, we will see you next time.
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Frank Slootman, ServiceNow - ServiceNow Knowledge 2016 - #Know16 - #theCUBE
>> live from Las Vegas. It's the cute covering knowledge sixteen Brought to you by service. Now here your host, Dave Alon and Jeffrey >> College sixteen everybody hashtag no. Sixteen. Check out crowd chat dot net slash No. Sixteen. Gonna crowd check going on. Frank's Luminous here is the president and CEO and not so invisible Hand of service now at the helm. Frank, it's great to see you again. Always looked so nice. Job on the keynote this morning. Eleven thousand plus right, actually closer to twelve thousand. About twenty registrations tweeted out again today. M c world was ten thousand this year. So you're bigger than the M C world, at least in attendance. Imagine what it's going to be when you're a twenty four billion dollars company with. But anyway, congratulations. Thank you. Great to see you again. So yeah. So you must feel good about where you were at the financial analyst meeting yesterday. You laid out the vision you guys were on track for sixteen. Still focused on four billion dollars by twenty twenty. We know a lot can happen between now and twenty twenty, but you gotta be feeling pretty good about the tam expansion the product portfolio. The customer acceptance. Give us the update. >> Yeah, way to feel good. I laid out yesterday for the capital markets. Folk folks are framework. Phase one was R R R zero to one hundred. Uh, that was really when we were startup, Fred Laddie was CEO of the company. It was reaching escape velocity. The night came in in two thousand eleven that was faced to, and we're really focused on scale on discipline and really delivering on the promise that have been created. And the company went from one hundred million two billion dollars last year. But now you know, we're we've entered phase three and face tree is a billion to four billion and we're changing. We're changing from a single product single mark, a single channel company to one that's multi products, multi channel and multi market. And it's a transition. We're not assuming that lather rinse repeat is going to take care of it. So we're raising ourselves to another level. We're questioning what we're doing just to keep things, keep everybody on their tell us >> and your keynote this morning to talk about the states. The first greatest yaar pcrm oracle ASAP. and the second greatest state popularized the course by by sales force. Others before salesforce boost sales force Really one and you guys are laying out a vision for a service management across the enterprise, and you touch deeply into those other estates described that strategy and how it's going to affect customers going forward. >> Yeah, our deep belief is that the way we made its work is going to change under the influence ofthe technology. And what's possible? Has it been that long that we sort of got wire to our in boxes and email became our reactive reflects of way off doing things right? There was a time before e mail. Well, there will be a time after e mail as well. A lot of work is going to be defined into work flows. And then the reason is we don't need to reinvent the wheel over and over and over again. Every single time we do something you know when we define work flows, we had the opportunity Teo plant for work. We have the opportunity to motto Orc, we can analyze work. We can figure out what it cost. We can figure out how well we're doing These are This is where efficiency comes from. Essentially, companies will become clouds. They will all becomes, offer companies right, and they all are going to start to manage themselves like that. So the future of rolls and enterprises and institution and jobs, it's less about being into processes that will be in terms of defining and building the process and then managed in the process. These are these are profound fundamental transformations how we >> work. And you spoke on the Kino to about kind of the different point of view within engagement model when you come from and some type of background versus some of the other interaction. Specifically contrast ing serum, Um, in the way that engagement method works. Versace somewhere. Yeah. You solved the problem. Help a person get up off the floor. I love your I followed that. I can't get up example, but then really get to the root cause. And now you know the good position you're in. As that methodology moves beyond just the chorus people, two people doing it functions in all different roles. >> This this this, this our heritage. We've always taking the service management model. It's basically an engagement model an engineering model because we need to do recalls analysis. Why are we talking in the first place and then to fix and change model? It's a holistic process if you just haven't engaged a model that's not that satisfying because we're just trying to relieve the pain of the moment. But we're not prosecuting general line cost. And even if we knew the underlying cause, we're doing nothing about it. And people keep coming back with the same problem over and over again. So it's not so much about just managing the quality, the service. It's about managing the underlying quality off the core product that we're providing, whether that probably product for that product is in service. >> So a few years ago, I said, I thought you were on a collision course with sales force, and you kind of bristled at that and say, I know we're just doing our thing, but you're Tam is now so large. I mean, you're good, becoming a very large software company. You're in rarified air, so essentially everybody's, you know, I'm gonna have you in their line of sites. That's good. In the other hand, you know, it's an interesting position to be in. So what? Your thoughts on that from >> industry landscape. It's a huge market. You know, we're not super fixated on a confrontation with this player, that player. But we have philosophical conviction that doing customer service, you know our way is the right way to do that. And with things moving to Coyote Internet Oh, thanks, it's becoming way more important. It's not enough to say, Hey, my device is not working, you know? Can I reset the device? Can I see what's going on by straight? People have to become way smarter a za function off the software technology that we have just saying Well, you know, take you call and try to figure out what's going on right? And these days, you're already when you have a conductivity problem with tea for your WiFi service and so on, they can already already tell you, you know, what the hell thiss off your device and what what the problem domain really is. We're going to go way further in that direction. I mean, somebody shows of the refrigerators busted somebody shows up at your door. That person knows nothing, right until they literally open the door and they start looking around right. That's going to change because they will already know. And they'LL have to write parts with them, right if parts are actually involved or they can fix it remotely. So that's desk for service models are moving >> well, your tent, You're celebrating your tent in tenth year anniversary now, and the interesting thing about service now is used. You started in it. You call them your peeps. Your fundamental assumption is that it is touching everything in making that bet That has been a tailwind fear. It's quite a bit different than some of the other software companies that you see going >> down. So he's not just touching everything. It is everything that >> sass cos a cloud of Takeda mean more sass Company's coming out of general business. Then there is the technology business. Do you see that trend? >> I think, by the way, salesforce. I commend them for this vision. They've always said every company becomes this offer company that is absolutely and profoundly true. We're all becoming clouds, Um, and we're literally, you know, running as hard as we can, uh, to catch that ball downfield. You know what? This is about >> you guys have built an incredibly viable business now with riel mo mentum. So as you look forward to next ten years, talk about sort of that vision that you see of service management going beyond I t into other functions of the company as well as growing the ecosystem. >> Yeah, so no, our vision and our approach is about looking at work, right? We're not managing records. Whether it's HR or financial records. It's not about the record. It's about the work. If you take a company like sales first, they're focused on the customer. We're focused on the service. The service is the unit of work. So we have a unique focus on zooming in on that unit of work and structuring, defining and managing that. So to us, everything looks like a service at every application, every task, every request. Everything we do has a beginning and an end. And as an opportunity for structuring, automating, analyzing, monitoring all those candle thanks. So our future world, you know, we'll still have email, but so much of what we do in the day to day basis will be structured in systems and by the way, our life is consumers were already living that way. He just don't notice it because that's natural. I mean, uber is a structure of workflow. Even Facebook, in many ways, is that way. Making a reservation is the structural work flow. Ordering something at Amazon structure workflow and it's lights out lightspeed sort of world is trying to go. >> And if you think about growing this company to the to the next phase lots going on, you making acquisitions, you're bringing in a new town. The ecosystem is really an interesting item here because we saw Accenture Pickup Cloud Sherpas this year. We saw fruition and CSC And so you're seeing the big guys now take notice. That's gotta make you feel great. Talk about the ecosystem a little bit, >> Yeah, it's definitely in on inflection in our world when people are not just saying put me in coach, you know I can do this, but they're starting to, you know, put out real capital on buying companies. Now. There's numbers behind service now, and we're not just on an opportunistic thing in their business, but we're an ongoing business on dare doubling down. They're not. There will be many acquisitions off a lot of our service partners and also our technology partner. So we have a hundred seventy partners here. This is really good because we don't want our customers to sort of feel like I'm dependent on service now for everything. We want them to have many choices, not just in deployment partners, but also technology integrations. No value at its offer products. They shouldn't be depending on you for everything on us. >> In terms of emanate, it's been selective. I mean, you know, you know, we see these larger legacy cos they live off of ebony because they can't innovate you guys doing a lot of innovation internally. But But take a minute to talk about Emma and the particular we're interested in how you integrate cos you don't bolt on to the platform, you essentially re platform. You rewrite talk about that a little bit? >> Yes. Are our eminent strategy has been focused on talent and technology. Tellem builds the technology. Technology without the talent is not very useful. You know, in the short time you'LL run out of gas on that so it's always the combination of the people and what they have built that you correct We don't integrate technology that we acquire, we take it apart and we re implement it on our platform. That is a core core commitment that we make to our customer base, that we are not going to saddle you with the problems you've had for the last thirty years, where you are constantly testing and retesting integrations between this assets versus that assets and have whole steps dedicated to sort of keep the patchwork operable. We take that on right. You don't have to worry about it. You turn on the service, it will work with everything else on. Our customers early on, recognized that we were different in that regard. It's very expensive. It's very time consuming. But when we go to buy an asset and a talent pool, we first look at Cannes, where you re platform it's and secondly, does the technical team that comes with it. I want to do that because if somehow there they're not bought in on that strategy, we don't want to go there >> right. I want to shift gears a little bit and talk about your customers. You guys have a very special relationship with your customers and David on the Q. We go to a lot of shows, and there are few people at that elicit the excitement within the room like Fred does when he comes on stage, you know, and we talk a lot about when the founder's still involved in the company. It's really important that I still remember the first time I saw the cakes and twenty thirteen like, What does it do with the cakes and still Crispo post on lengthen five cakes a day? I think he just doesn't follow him. You'LL see cakes from all OVER the WORLD What do you are hearing from your customers? As you guys go to this next phase because you've had a really special relationship, we've gone beyond just when when Fred was running it, you've taken it to a billion. Now you're going to four. What kind of feedback and engagement we haven't out in the field. Don't talk to customers all, >> you know. Yeah, I do a lot. We're very intensely customer phasing company, just just culturally, but we're incredibly dedicated to their success, the way we believe that the value of our company is sort of summed up in the aggregate in terms of how strongly a customers feel about us. Forget all the financial metro. It's how strongly customers feel about you is the ultimate value off your your franchise. The cakes. It's a celebration. One service now goals life. It is. People feel like we let him out of jail. I mean, they have. Pignon goes with the name of the product that they're replacing. Haven't >> seen the >> way, So it's it's what they go from one generation or two generations ago into, Ah, very modern, transformational, empowering, platform. Empowering thing is really important because they are now in charge, right? They're able to make changes on a daily basis. Before they could do nothing. They were dependent on bunch of people that they could never get access to, to make changes for them. It all goes away right, that that's the essence off. But what service now provides >> thiss concept of love, this customer discussion? Because I love initiatives that born in the customer, I think Siam was one of those. I think it came out of Europe. I'm not exactly sure talk about Siam what it is and how it relates to your business. >> Siam feels to us a little bit like the next installment on my tail, sort of the evolution ofthe vital because it's not just service management. It's service, integration and management. But they had a very, very precise definition and framework around what we did. What I till. It's also what we're doing. The Siam were really expanding the scope and sort of adapting it to a much broader context because we think Siam you take its narrow definition very useful, very productive. And we have lots of customers that are pursuing a Siam strategy. But we're saying what semen says, which is now we're going to reorganize our entire enterprise in terms ofthe our service assets, anything that produces the service. But it's an organization or a system or a group of people, whatever it is, as well as everybody that has toe have access to the service. And those were not just people. They're also systems. So they re conceptualize one of this to be an enterprise, very visionary and very, very transformational. You won't recognize enterprise is an institution in the future. There'll be so different that people won't no longer be on in the inside of the process. They will be on the outside of the process, right? Jobs are changing. It's gonna have profound. If one says there will be lots of jobs, well, there will be new jobs and a lot of the old jobs. You know, they're going to go by the wayside >> and, you know, you're obviously in Silicon Valley, and I know there's a lot of work being done about. This is probably not the way we're going to communicate in the future. You guys, this theme of a new way to work today in your keynote, you talked about I ot You threw that buzz word out there and you said, I know before you start rolling your eyes and you guys have a play actually, in I o t again As Jeff said, we go to a lot of these conferences. You hear the similar thing? Digital transformation. I ot your play on aisle is around wearables and really driving some platform innovation to your wrist you have the watch on is that I had guys announced a wearable today, I said, I think I just I tweeted. I think that service now just announced Well, I watch aware a bone some things that we did. And so what's that all about? >> Well, we we've been able Teo, deliver services on watch ever since. Yeah, watch came out because we're a platform. We've been able to do this literally from day one. We're just tryingto inspire our customers to figure out How do you really use a watch? Right? Warm of the struggles that Apple has where the watch is, What's the killer app? It's not replacing Fitbit. You know that that z not enough, right? What's the most killer app for a wearable? And we think you're really time and predictive business metrics. You know, at a glance, because that's where this gramophone you really have to, you know, work to device. This is at a glance, right? And we are really tryingto get to this real time predictive mode off doing things because it's just so much more productive. But as I said in the rap over the keynote right, there's a lot of sizzle people lost watches and *** bang stuff. What enables toe watch. And that's really what we think Apple needs. You know, Forest tries used what enables that watch to become a productive business device, and it's the underlying repository of data that's continually being updated. That's what makes the watch powerful. >> So how did this come about you guys? You obviously like you said you had apse for the watch Your you enable that. But it wasn't good enough for you just didn't fit the use case well enough. But he said, Hey, let's go build it. >> Yeah, there is. There is a design aspect to it. And, you know, it is you heard during the keynote whether people do typically, you know, we're just shrink down to you. I from the bigger form factor to watch. And that's always the first generation >> and my phone on a watch. And >> everybody goes like, Well, that's not it. So and then we go back to the drawing board and we really, really think through the usability off that form factor, which is so tiny >> one of things about knowledge is the content from the customers. So I want to ask you how you spend your time here. Yesterday was a financial analyst meeting. Today you're in the general session and the keynotes. You got a CEO event going on. You had a partner event going on. How do you know. Is there there three francs? >> No, it's, uh it's it's no I I couldn't be more thrilled. We have so much going on at this conference in in years to come. You know that we'LL be vertical Industry conference is going on because we see that as the next evolution next phase of our evolution is that vertical ization is happening already because we have someone e big customers and single verticals. Whether it's financials and pharma retail, those folks can get so much benefit from associating with their counterparts in the same line of business, especially when the value of moves from it to broader enterprise that becomes very pertinent. So we're worked over in the middle of figuring out how to sort of enable ourselves We've enabled ourselves as a multi product organization. That was the whole face three transition. But the vertical ization is something that sort of next in our revolution. >> I mentioned my last question for eventual Silicon Valley. Obviously you're part of of of really set of rising stars and your butchery. You know, Scott decent and saw him the other day seen Cem Riel innovations coming at the same time, hearing a lot of these Caesar. Real nervous. You don't sound nervous. You sound really hopeful. What's your What's your outlook for? >> You know, your situation. We had our financial analyst yesterday, and you know that the capital markets crowd is very nervous. All of us are trying to decide on my in or out, and some things they do both before noon. Uh, I can't run a company that way. Most of the decisions that we make on a daily basis are not with a quarterly oriented. They go on for years and years, so I can't get that excited. You know, about the second floor of the business on a very short term basis, we know were lashed to the mast. We're going to go down with the ship. Were committed, were not interrupt. We're in. We're completely in. So our mindset is that we're just We're fine to be on the ship in running us, right? In January, the capital market sold is off. And in April that came back in were the same company, right? There was no reason to be that excited either to the downside or the upside. Right? This this a marathon companies get billed over long periods of time. >> Yeah, you don't seem like you're on that ninety days shot. Claws clock. Of course, it helps when you have a great customer base together. You got a great team. Frank's Lumen. Thanks so much for first of all, for having us at knowledge, we love this event. It's one of our favorites. And thanks for coming. It's >> great beer. Thank you. >> Alright, keep right, everybody. We'Ll be back with our next guest right after this is the cue. We're alive. Service now. Knowledge. Sixteen. Right back. It's always fun to come back to the cube because
SUMMARY :
sixteen Brought to you by service. You laid out the vision you guys were on track for sixteen. But now you know, we're we've entered phase three and face tree is a billion to four billion management across the enterprise, and you touch deeply into those other estates described Yeah, our deep belief is that the way we made its work is And now you know the good position you're in. So it's not so much about just managing the quality, the service. In the other hand, you know, I mean, somebody shows of the refrigerators busted somebody shows up at your door. It's quite a bit different than some of the other software companies that you see going It is everything that Do you see that trend? We're all becoming clouds, Um, and we're literally, you know, running as hard as we can, So as you look forward to next ten years, talk about sort of that vision that you see of It's not about the record. And if you think about growing this company to the to the next phase lots going on, me in coach, you know I can do this, but they're starting to, you know, put out real capital I mean, you know, you know, out of gas on that so it's always the combination of the people and what they have built that you correct We don't integrate and David on the Q. We go to a lot of shows, and there are few people at that elicit the It's how strongly customers feel about you is the ultimate value It all goes away right, that that's the essence off. Because I love initiatives that born in the context because we think Siam you take its narrow definition very useful, This is probably not the way we're going to communicate in the future. You know, at a glance, because that's where this gramophone you really have to, you know, You obviously like you said you had apse for the watch Your I from the bigger form factor to And So and then we go back to the drawing board and we really, So I want to ask you how you spend your time here. is that vertical ization is happening already because we have someone e big Scott decent and saw him the other day seen Cem Riel innovations coming at the same time, Most of the decisions that we make on a daily basis Yeah, you don't seem like you're on that ninety days shot. Thank you. always fun to come back to the cube because
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Frank Slootman | ServiceNow Knowledge15
David it's just gonna call in like basically live feel more nos Vegas Nevada execute again it's the 10 covering knowledge 15 brought to you by service now hello everyone welcome to the cube this is our flagship program we go out to the events in the correct the city okla noise I'm John furry the founder silicon they enjoy my coach Dave vellante co-founder Wikibon org and networks I to be in Las Vegas live for three days of wall-to-wall coverage of service now's no 15 knowledge 15 hashtag no 15 go to the crowd chat / no 15 join the conversation our first guest is Frank's lubin president/ceo source now great to see you again thanks for having us thanks much absolutely the keynote was great i mean in the world's changing IT cloud vmware's had an announcement about native apps on the cloud customers are changing business models are changing talk about what you get to do house that you had a big stock drop in the past week and value is that a sentiment of the of the of the Wall Street dynamic products what is it about the business right now with clouds specifically the business model for your customers it's flywheel the SAS models what's what's going on what's your take on all that flying cloud companies and obviously well I ought to got a lot of the high we're one of them you know we're priced to perfection right and that's that's not an easy place to be for for for anybody and you know we're not really focused on that it's this is a marathon every quarter is one mile marker he can't get too excited about you know one versus the other we're really pacing ourselves your building you know an enterprise that's going to be here for for a long time and our focus is not just on modernizing what what people are doing it's focusing on transforming what people are doing and the emphasis that we place on everything as a service structure workflow approaches getting away from message oriented ways of doing things like email is enormous sea change right there is there's over 100 million PDFs out their forms that people have to download and fill out what somebody else then has to scan and reenter right the world is ripe for this type of innovation the technology is here all we need to do is apply it the start okay so I said when I talked yesterday and I said any successful 12 billion dollar valuation company's going to have a day like friday but I've noticed post the financial analyst discussion yesterday things have calmed down a little bit so who knows maybe it's a buying opportunity I wanted to tie it into the TAM expansion that we've seen when you first took this company public everybody looked at it as a very small niche and it took you and Mike scarpelli and others a while to sort of educate Wall Street on the size of the potential and we're now starting to see that come to fruition you guys talk about expanding into the business side and now you're doing it you talk about going into mobile you talk about you know new innovations at the SMB why is it that you're so successful at executing at what you're doing is that the platform is that the people is that the customers I wonder if you could describe that a little bit what's the magic formula are fundamentally a platform company we that was not always well understood even before I joined the company and I talked to Fred Lunney the founder we were very well aware of the opportunity to expand just dramatically beyond the boundaries of the initial application set which was the IGM set of applications it's just how to do that right when you peel away the veneer the rhetoric the nomenclature you know what you see is a workflow an orchestration platform this is so broadly applicable right what these knowledge conferences are all about is to show people what is possible on this platform and you know all we have to do is take the horse to water soda drink and then you know they go on their own right this is a place where people come to get inspired platform and if you seen from some of the examples that we had on stage this morning and people are not tackling crm applications what service now you know why there's really nothing there's really no boundaries in terms of service management for us to tackle workflows and orchestrations like that right so the world is your oyster II and there's really no place that we we can go with this platform all we got to do is empower and energize the audience that you have here and the fact that they show up in such huge numbers as evidence that were we're succeeding at that right good all the events it's the same kind of theme Internet of Things Big Data have paced are changing clouds and innovator what is it about the cloud and your platform and your customers in terms of the business models what is it about the innovation that's going on right without business must change what specifically can you highlight and get some example because you have a lot of customers we were just talking that the cubbies are sending dozens of people here this event it's not just a boondoggle there's some real work getting done so there's a huge transformation see what is it about the business model now that's changing what are you guys doing turn on your platform this conference is called knowledge for a reason people come here to get knowledge right that's right the labs and training and all this kind of stuff but the most important thing to understand about service now what we did with the individuals really lowered the skills profile and the skill demands to be able to access this level of functional and we really did that by an order of magnitude this wasn't just a platform for programmers people that really have procedural programming skills we really took that out of the equation and people have Excel style skills people will understand the rows and columns and data types that's enough to know to be able to go up okay now what happens in that process we empower very large groups of people in our case IT people to basically take control back over this platform you know in Prior generations of this class of software they were always dependent very small we were people that weren't very accessible and very expensive to do thanks for them how they're doing that is what has unleashed explosion creativity let's talk a little bit about your keynote everything as a service was your big theme EAS sort of acronym what is everything is the service number one second question is is there an analogue to vm sprawl is there a potential for server sprawl what do you what are you telling customers about that are they asking you questions but start with what does everything is a service what does that mean everything is what service means taking work work in the sense the repeatable activities things we do over and over again digging it out of the realm of messaging email text phone and putting it into structure workflow we essentially invent that dress as once without best practices really tune and optimize that process and every single time we do that activity we do it exactly the same way and we enforce the business rules the logic upfront stupid enough to thinking like I always is the silly example an organization I lose my security badge or I mangled in the door I need a new on what do I do well you know I Massey Hill I just asked my admin you figure it out okay but everybody else starts roaming the halls like where do i go to go to the front desk maybe you know that thing employees have to have a place to go for their service needs whatever it is HR related facilities related maybe have a parking issue and you should be able to search navigate themselves to a place where they can make a request and then that request is no different than sending a package through fedex or ordering something on amazon information it's now following you you don't have to go and chase it anymore right oh there's a big inversion of how we work i mean we often target service now but we're changing how we work because we're going we're getting away from the structure messaging woman be structure workflow that's what everything is a service is about regard to aquino but so second part of I want to talk about that is my question is there a dark side to that is there a risk of just too many services service sprawl or do you have service for that is there an app for that yeah talk about that logo the obviously during our keynote we actually spoke explicitly to that point because you're concerning your race is legitimate people are saying hey you know DevOps is great you know empowering all these groups to publish their own services that's great but now I'm going to lose control I'm going to lose visibility and we'll lose accountability i'm going to have compliance security problems and so on what we do is you know we actually maintain the transparency the visibility and the control while people are doing things so it doesn't become the Wild West that we've had in Prior generations of software >> Frank talk about what you're seeing in big data honestly you know we didn't cover that space this doesn't seem to be its own little market but certainly medupe to some stuff going on but companies are looking at Big Data certainly in data as it advantaged in some of the things whether it's IT and or an apple agents what's your vision and what is what our customers doing with the day how's the NIT date is great and everyone's the service date is enabler you look at that and how do you find your customs look at it are very transactionally intense but so our systems they're not data rich in the sense that we deal with enormous volumes of data so it's a little bit of a different model and during the keynote what I talked about it's not like they what's hiding your data we can't figure out what's going on the data by structuring the data right what big data tries to do they're trying to figure out what's going on in unstructured data really really hard to do we structure the data so hence it's very very easy for us to analyze the dashboard exactly what's going on but our focus is not so much on big data it's on real time data the real time dimension is something that is going to become huge because people are demanding real-time information is just not interesting to look at data it's 12 24 hours old and because we are sitting on life data the ability to represent it so you can see your business in action right that is insanely exciting for for executives and managers network magic was hot in the old days with the network little but now the way date is got that same kind of paradigm where you have active data passive data and by melding together they can create values that mean we the CIO that we talked to they what you mean by real time today yeah I said look where I want to get you there's one my office just wall-to-wall LED panels and I want to see every every pocket of activity I want to see it executing in real time whether it's good better and different setting threshold seeing exceptions and says I want to be it's like watching the stock market I want to watch my my business that way and that is what we're going to focus on very different from data oceans and data legs and all this kind of stuff we've already structured the data we're not going to have the problem of big data the three of us started our careers without email and it was amazing productivity bump into our lives when we got email but now email is this productivity killer you talked about it in your keynote you guys did a survey is that basically forty percent of a time is spent on admin tasks and employees time I know judge doesn't manage I'll give your calculation i saw was manager with just even you know higher salaries but so how much of that can you actually reduce and what a customer is actually doing around that well it can be reduced by orders of magnitude you can't make it go away I mean people have needs but being able to make those needs fully automated very intuitive very productive it's absolutely possible right I mean 42 days a week almost half time on tasks that have nothing to do or your job is absurd I think this is almost a dirty little secret of business death we have invested in everything except our own internal workplace productivity right we're stuck in the 1980s if not the 1970s and who's going to put on that mantle write it and we're always trying to drive IT to take on that mantle because who else CEOs typically are focused about revenue right image presentation right coo CFO's those are the people that should be driving the internal productivity challenge sorry just that we just haven't made any progress there in decades and the acceleration now is a significant I start guy an email Facebook say I just finally gave my blackberry you mentioned iPhone and your kita he's still using the blackberry I was like that's actually a great scandalous blog post opportunity but are you mentioned iphone in your keynote moment of this is changing the world certainly edge of the network smartphones and we also hear from customers want to be more Apple night so what's your what were you hearing from customers and they say I don't want to be like the 80s and 90s I want to be more like Apple meaning kind of like the iPhone and the innovation that they bring what they brought to that or you guys been using uber as an example or open table as an example that's that modern vibe for the customer what are they trying to get to in an environment what's their outcome what are you hearing customers the first aspect is the series experience itself in other words what does would like to do what you want to get done essentially we're transactional platform we're not a hanging around platform like a social system we twitter has no no point no purpose it's just nice to shoot things out into the ether and help somebody sees it our systems are not like that it's about performing a unit of work something very specific about the beginning it doesn't end and there's things that happen in between the result it's very different that way uber is also a transactional app I want to hail a cab I need a ride opentable is transactional act I want a reservation there's a very specific end point to that unit of work and this is where technology can be incredibly helpful to get you there faster i use the Gulf example you know fewer strokes is better right and as people want they want have grubert a lot and I find that user experience my blowing compared to trying to call or or hail account it's cheaper and it scales incredibly well right but if wherever you are or whenever you are it seems to be there's cars around this quite impressive App Store like model the enterprise has been kicked around for a while is that service cataloging uber shows the real-time aspect of services needs you know demand in real time but in the back-end service catalog that more apples to the apple store at the back end its lights out light speed right in other words it's just like Amazon right everything is the speed of light until I got to pick something off the shelf the real world kicks in and i have to ship something the same thing same thing with fedex I mean the information processing aspect of FedEx is what makes fedex special in fact that they have planes and trucks you know it is not what your user experience focuses on yeah you got minimal exposure to that you are you're on your way to a billion dollars here shortly you've laid out a plan for four billion by the league 2020 correct with the the financial analyst a lot of people say well one of these guys going to make money you have indicated before you you're right now after scale after growth and what if you could address that um we actually were profitable are you sure I mean we were you could make a lot more money if you want to do but you're going for growth I should have clarified that question better you guys can be wildly profitable if you skip down and just reach over office we've always said and by the way you know one of the things that that our business model really focuses on is making sure that the cash equation really work so on a cash flow basis we're doing extraordinarily well because it's a subscription model you know the profitability equation is a little squishy it's more accounting them than economic which is why the focus on cash our investors focus on growth in the next thing to focus is on this cash right and after they get generally accounting representation of our at some point the law of large numbers kicks in and that's really maybe out in the business out a target model yesterday I was we put updated for the financial analyst shows you exactly where the leverage is coming from transparent supplies for peace I want to let's do a great job of that very drill into on the he said amazon amazon does a great job executing and near a great executors and certainly proven that we do successful with the company but they're constantly innovating the new product announcements debÃa new announcements is that the new competitive advantage scale and stickiness through rapidly iteration of new features is that this is just a one-off outlier with amazon you see no price it be more like that's one of them  you see that with Tesla they've changed the car industry there's constant updates to the cars right a changes of driving experience and that that model of rapid iteration is really the new normal you know back to the real time thing it gets really boring when you get an update every 18 months you think we don't tolerate those kind of time friends anymore and lag is not a good ending our but I you know software gotta ask you a final question I know you getting we're getting a puppy you get very busy schedule thanks to spend the time with us as well I'll see you had a your competitive sailor and following your career right outside sirs now you got a boat for the nuchal hand you mentioned data ocean data legs big big fan of data ocean I want you to share perspective from what you've learned sailing and being successful winning and sailing with how to navigate an idea this as a c-level executive or a CEO CIO or some of the trenches what lessons can sail in your experience is sailing and running service now what would you share with the folks out there as they try to look at their transitional transformation I teach transformation the others there's a lot of analogs if you will between sailing and business because it's this multi-dimensional game that we play you know in sailing it's about technology it's about how great your crew is it's I'll get your boat is it's the weather is what the competition is doing all those things you have in business so people always want to write it yourselves he's like another you know another another brutal contest township and that's that's all true it's very multi-dimensional and finding your high leverage entry point because you know it's very easy to do super business super busy and business and really not move the dial right so understanding where leverage exists what opportunities are that's really the art form I Frank great to have I know you're busy to getting them getting of the big nokia pricing the president/ceo of service now here live in Las Vegas is to Cuba railroad next guest live in three days wall-to-wall coverage here at no.15 join the conversation crowd chef net / no 15 right now
SUMMARY :
the new normal you know back to the real
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Frank Slootman | ServiceNow Knowledge14
but cube at servicenow knowledge 14 is sponsored by service now here are your hosts Dave vellante and Jeff trick here we go hi buddy we're back this is Dave vellante with Jeff freak this is the cube we go out to the events we extract the signal from the noise we have a crowd chatting on its crowd chat / no 14 so check that out put your tweets in crouch at awesome engagement app Frank's Lupin is here president CEO of service now Frank it's it's a pleasure to have you back on the cube great to see again great to be here thanks things how you feeling I'm feeling great no I got that keynote got the keynote out this morning you had the financial analyst in yesterday had the industry analyst and they're working you hard absolutely it's a circus yeah so your keynote this morning was great I was right up front they have a nice spot for the industry analyst so appreciate that take good notes but one of the themes that you struck was really hit home to me because you talked about transforming IT from essentially a cost center into a value producer and how service now is at the heart of that and and how the role of the CIO is changing so one of you could sort of summarize and talk a little bit about how you see the role of IT and generally in the CIO specifically changing and what role service now plays in that transformation yeah just just to give a little bit on macro context right that's sort of the worst of all scenarios that we see out there where I t is essentially viewed as as a commodity as a utility and as a result you know people don't see much impact I just want to get a cheaper cheaper cheaper and they want to cut more costs out of the infrastructure and staffing levels and so on and actually is just an organization that we're tolerating because I guess we have to have email and Internet access and all that sort of thing now you go looking into broader world around what technology has done to change business right what amazon has done based on their technology platform what we've seen an online banking you know what we're seeing an online education there's just just incredible examples of innovation using technologies now aighty hasn't done that for their own enterprises they happen in some instances are some some really great examples out there where I t did impacted business but by and large IT is not viewed as to go to people that know how to bring technology into business you know in a way that that really turns the tables on the competition do some mind-blowing things i always ask CIOs when i when i meet him and says what have you done in the last 12 months that really blew people's minds or in terms of applying technology to business problems right and they start sort of thinking like i'll actually it is surely nothing i can think of well that's probably you know a question you should be asking yourself all the time right if it's not when lightning in a bottle when it's not the sort of thing that sort of lights up the whole enterprise like we won't do it is we have to do this that excitement then you're shooting too low and you know in general I find the the cost obsession and IT is an indication that we're not looking for the opportunity and I think that's that that's it that's a damn shame or we're here to change that well you talked about panning for gold was that proposed here in California and it's also a propellant you your company is smoking hot and you know your your commonly associated with the likes of workday and Salesforce and sponsor must be very very proud of that but also there's gold and then RIT shops right there's goal than those organizations that's not being being mined and and you know I think you talk about your penetration is what twenty percent of your your target your global 2000 where we have footprint in about eighteen percent of the enterprises that we think are relevant and appropriate to us but within those eighteen percent you know we were probably a third saturated so so very early innings for service now even though we've achieved considerable scale and very high growth at that scale so when you go into one of your accounts can you discern actual that actual value production vision that you set forth can you see it can you touch it can you you know to this to a skeptic a prospectus yeah Frank that sounds good but can you actually sort of provide proof points yeah managing surface is just essential in terms of economizing and saving money and here's why no I'll give you some some very pedestrian examples that we've seen in real life and the human resources department and probably get the example because I t everybody sort understands how to how the game works right HR organizations historically have not had service models they have that email and phones and so on the problem just called somebody as a result that was a huge amount of work that preoccupied the HR organization that nobody knew what people were working on and the staffing grew and grew and grew to deal with the growing volume of ink wires and problems and changes and so on until they have systems service models and they have reporting and analytics that showed them what was consuming their time once you know that you can put initiatives in place to start dealing with the underlying causes that are driving that work I have seen HR organizations dwindle their staffing by 50% just by understanding what of this day we're working on right that's what service management is all about instead of just delivering service you're managing and once that quarter drops by the way IT organizations they get this in space right because you know large enterprises they got fifty hundred thousand one hundred fifty thousand instance flowing to their organization a month it's a huge consumer of resource right if you go to these other service domains and you see very similar things this layer of software really optimizes that resource well the way they attack it oftentimes is human resource doesn't that scare a lot of prospects away when they hear oh wow near cup service now and they're going to replace all these these people it's a it's a good question actually wrote a blog post about it recently as well there is no doubt that in the economy at large we're going to see massive substitution from people to systems why because the technology is here and the economic imperative is here it's very much a societal and social question but you know here's the thing see alternative you know are we going to try and stop it and not do it it's going to happen the markets are going to run their course what needs to happen is that we adjust you know for example you know in education we have a lot of teachers right what's going to happen to teachers when education is delivered through online streaming well teachers gobble you want to become crooklyn developers in other words evolve and change in their roles because education is going online slowly but let's go into why because the format the service experience is that much better it scales that much better in step much more economical than what we currently have well you said today in your key note that the system is broken you know I'm having to put four kids through school I appreciate a nudge there to the educational system why did it take so long I mean these are the IT guys ease of the technology guys in the organization they're there to deliver value why did it take so long for this kind of transformational yeah wave Steve Jobs has been the late Steve Jobs been quoted many times people don't know what they want until I show it to him and that's sort of what we're doing we're showing it to him that's what we did this morning we're showing people what they can aspire to that's what we're here for we're trying to stimulate inspire motivate give people a sense of mission right as opposed to keeping the lights on managing crises running around with your hair on fire that's not a very attractive you know a view to half of your organization and what you do all day right yeah so I have it struck again by your keynote the Affordable Care Act affectionately known as Obamacare they not the government not a customer of yours or what's the scoop oh no they could you have helped with had problem we could have for sure but then again many people cook that for the foot of people then software and technology they look at something like that yeah last night I set a dinner with Adam infrastructure for Kaiser Permanente and they had a certainly know the problems of open enrollment that a massive scale and certainly we didn't want to trivialize the problem it is really really hard to need to operate the service like that at the scale that that they need to but there is no doubt that you know we don't need any new core technology to build systems like that I mean the technology exists the skills exists sure that I want to walk better than so let's talk about your business a little bit this year third year now right since you've joined service now exactly three years this week yeah so let's sort of break that down but when you when you join service now that the discussion was around and you talked about this yesterday the the whole team and everybody was looking at help desk saying wow how can these these these values be justified and of course you blew that away and now people are beginning to understand that it's interesting to note that data domain you sold the company i think for what 2.5 billion the entire market is is now greater than the market that it replaced interesting that's right the market was three billion it's now I according obviously bigger than three billion and growing yeah you know so that's kind of interesting now that's a much more confined market you know you talked about the tons of the team they're being finite you always knew it was finite here it's different you guys have started to sort of fine tune your tam analysis and communicate that it's still hard because you just don't know the how people are going to use your software they're finding new ways but the team and I took a stab and I came up with 30 billion but it was a top-down it wasn't a bottom up and it was I had to get the blog post out so it's kind of a back of the napkin but still it's very very large clearly a multiple of the IT service management market so I wonder if you could talk about sort of the the evolution of your thinking in terms of the market opportunity with service now were you always sort of where we are today or that have to evolve over time now it has evolved I'd say dramatically obviously the expansion from what used to be called help desk management to IT service management basically you know exploded the market at least 5-fold and they were licensing five to ten times as many people on our system now for itsm purposes then we used to and in the mid 90s during to help desk area because back then all we did was licensed people ever physically on the help desk right people that would take phone calls and emails and so on now really everybody in the IT organization is an actor and a participant in the workflow of service management you may be a DBA maybe a network engineer you're going to get when an incident comes in or a problem is defined you're going to be part of that workflow right so that Dad expansion was not understood early on but beyond that services is everything is everywhere and services everything and every physical and even non physical assets have service models around them so once you start looking forward you see it absolutely everywhere you know I don't know what's a few billion among friends you know I know all that the numbers are but this is heavily transformational I think one of the things that people struggle with they're looking for a line of sight right in our company like workday is viewed very possibly why because they're seeing them take dollar for dollar market evaluation away from companies that they can identify recipe in Oracle and so on feels very credible to gamma that's 250 billion dollars or mark oh I can see those guys from work the Oracle Sapa okay take a chunk out of their eyes I know you go look at service now you need to have more imagination there's this great court from Arthur Schopenhauer that I showed you yesterday which said you know you know takedowns to hit a target that nobody else can hit but it takes genius to hit a target on nobody else can see right it's transformational right what worked it does is modern with what service now does this transformation is fundamentally different so when you came on to service now I presume your focus was putting in the infrastructure and the process is to make sure that you could scale just having watched you in your career you're you're big on growth and yeah you're pretty aggressive so so take us through sort of you know where you sort of started and what the emphasis was and and where it is now be clearly you're investing in sales and marketing you're investing in AP I didn't know this the substantial number of global 2000 companies in asia-pacific so that's another so how is that I mean break that down into maybe one or two or three sort of segments of your attention and effort there there's sort of you can sort of split up in two major stages or phases the first phase you know when when I took over the helm of the company was very much focused on operationalizing stabilizing scale being able to deliver what we're already doing in a consistent and predictable manner and that was not a minor task because because the company had grown so fast but hadn't been able to basically catch itself in terms of bill into business building the organization underneath its business so that preoccupied us tremendously the whole thing about cloud is is not like there's a lot of people you know running around out there to actually no clout that understand clot that can build clouds and how many people do you know that I've actually done this because there's you know three years ago I mean they were far and few we actually recruited people that have built the original cloud of ebay because those guys were pioneers they have solved a lot of the problems associated with cloud early on we saw a lot of people that understood data centers the cloud this is almost in verse two data centers the mentality that you need to to run them davos phase one before us and we sort of got through that you know about you know a year and a half ago for sure about a year ago and we started to shift gears you know really from the operational infrastructure concentration that we've had to really trying to drive strategically the business towards enterprise service management they're really expanding the addressable market way beyond where we had been before we were going to market until i see i l-look itsm replacement you have to do it you're sitting on 10 15 20 year old software it's crappy it's got to go fine we're going to do that right but we want to give you this much bigger perspective managing service in the enterprise and you know make that a mission that you can own as a CEO and drive throughout your organization over a period of years and a lot of our customers have road maps that are 24 36 months and it shows you all the things they're going to knock off over that period of time and all the different you know parksley enterprises to sell is its engineering its market yourself so on yes okay so Tam expansion and now obviously accessing that to him we hire in a lot of sales people and go to market I was struck walking around the exhibit hall last night because you just announced app creator I think last year yep knowledge I was struck by you know that the booth down there with the number of apps I mean it's just astounding where that's going wouldn't have predicted you know some of them that I that I saw so that's obviously part of the the tam expansion as well I wonder if we could talk about the importance of a single system of record in order to achieve that vision because it's not always easy right politically people want to keep data in their own little silos so how does that work you can't force it in because it sort of just happen organically how critical is that to your success I mean when you have applications or services that relate to each other like for example you know this morning we showed in a demo I think we're sure like seven or eight different applications in the course of one demonstration the reason that is a single system of record matters so much when you do that is all these apps need to be aware of each other right when your when your staff in the projects you need to look at the resource management well that resource management relates to the skill requirements as well the skills that are available right what you don't want is these apps living in their own universes with their own data moss your own database because now you have to start the hack integrations between them to make any sense out of that and that's the world we lived and that's been the bane of software existence for for so long the ServiceNow said I'm not going to do that okay every application that relates to any other application they're going to be operating on exactly the same data model and by the way you see that throughout our platform right when you bring up an asset in the CMDB like a server or a rather or Santa whatever it is you'll be able to see all the other data artifacts throughout the platform like instantly problem of changes in projects and tasks that relate to that particular asset there's nobody else that can do that right and we provide the 360-degree visibility that makes application development so compelling because you know all the users are already defined the system you don't even have to get started with that you only define users once right you reuse all that and all the other artifacts already exists so you get this data gravitas that the more data that is there to richer the application with almond environment becomes yeah we talked about this too at the analyst meeting about the relationship to your M&A strategy you've got to be selective it's got to fit in to that single system of record does that however limit your choices in rule absolute limit our choices but you know this is the commitment from an architectural standpoint that we make us that we're not going to repeat what legacy vendors have done is I mean you know 50 apps whole stand along to hack integrations between them as I said that's the world our customers want to leave behind because it was just horrible former from an efficiency standpoint after a while all you people do is managing the operability of the patchwork plethora of assets that they have they're not doing anything productive and in our world they don't they do none of that right they're not upgrading software because it's the clouds you know we do that and they're not hacking integrations between apps because there is no constant of integration on service not with all the apps are aware through a shared data model so is there still plenty of M&A opportunity for you out there though I mean your stocks up I know it's off a little bit lately which I think it's really healthy I'm happy about that nice little breather but still you know you've made great progress adding value you can obviously use your stock as acquisition card co there's still plenty of opportunities for you notice there's absolutely tons of opportunities again in a day you know software infrastructure is it's very similar and very common between application itself for us to bring an application into our user interface framework I mean they have to have a user interface framework of some sort right so whether we replace what they have with ours with a replace the data structure we replace the underlying cloud we can do all those things right the question is is there going to be hard is it going to be expensive is it going to be time-consuming or maybe not as much and that will influence how attractive we are to the asset all right Frank we're way over on time but I could go forever i mean really appreciate you coming on CX for having us here it's really fantastic event all right keep it right to everybody we're back with our next guest this is the cube we're live from moscone right back
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Frank Slootman | ServiceNow Knowledge13
this one minute I'm here with my co-host Jeff Frick who we just fresh off of the AWS summit the Amazon event Jeff and I covered that and we're here at knowledge 13 now this conference is all about the notion of going from IT as a service organization changing high teas mantra from no to now that really is the theme of this conference and we're here with Frank's luton who's the president and CEO of service now Frank welcome back to the cube thanks good to be here that's good to see you again we had you on that vm world is great story when we first introduced service now to our community you just fresh off the keynote fantastic keynote by the way thank you you had strong themes i mentioned the from no to now you talked about itu gave a little little tongue-in-cheek joke about the line outside the the rmv the Registry of Motor Vehicles and that's sort of the the idea is you guys are transforming IT from an organization that is trying to manage demand push off demand saying no we'll get it in six months it'll cost you five million dollars to one that really is redesigning IT processes around the globe so first of all welcome back congratulations how do you feel after that keynote I have to work a lot of energy in that room and it was electrifying it was awesome well one of the one of the guys in the panel stopped when you had asking the question I think was the guy from NY yes he said even stop you looked at the audience said i love this crowd that was a great crowd we gave a little goop out to the audience so talk about from know to now how'd you come up with that theme and you know give us a little color behind you know it's it's actually not easy for for us to communicate about service now desk to to lay people in sight unless you have lived in sight I t you just most people don't even know what I t really does on the day-to-day basis right so we've lived a fairly insular existence because you know everybody knows what sales people do and to some degree about HR doesn't finance people but I t it's a bit of a you know a bit of a mystery to what most folks do right but most people do know however is that the service experience with IT has been and challenging what's all we say I mean it's been you know sort of a service experience where if you have to ask the answer was going to be no right because IT organizations have been super preoccupied with infrastructure rapid change in the infrastructure for the last 30 40 years nothing ever set still long enough for us to really master the architecture and the platforms are really stabilizing mature our systems and they have to keep moving so you get pretty cranky it's back to your organization having to live that kind of life so their their their reputation for service has not been stellar and I love making the joke during the keynote their ranking right down there with legal in the basement you know of the corporate enterprise you know so well so talk a little bit about sort of how you guys you know go into an organism's you start with the IT organization right in helping them sort of automated processes connect all these different processes but you've been through your platform expanding out to other parts of the organization the irony is that I T which is the most technology savvy organization in the price as the least management sophistication in terms of managing their own activity which you know I duck to the CIO of a very large consumer gets company he said where does she make her son it's inexcusable right here here we are running milk that going in dollar budgets and staffs with tens of thousands of people and we're running it on spreadsheets email excel project management tools this is ridiculous right we don't have real information in near real time and show that we can drive our business as opposed to being driven by it right i key executives have a tendency to run from one crisis to another with their hair on fire and that's sort of the mental model and a note of now message is about out of a get these people out of this you know reactive crisis mode to where they become full-blown business partners and they start you know bring your guide to enterprise and in a very transformative way or they become the people that bring innovation to the enterprise you know here's so much Frank about shadow I teach my colleague Jeff Frick and I were at the AWS some of the few weeks and you see a lot of these cloud companies you mentioned your keynote Salesforce the salespeople workday talk to HR people they sort n run IT certainly amazon is the poster child for shadow IT but you know Jeff we have that sort of notion where IT people are not the center of the new cloud universe but that's different for service now yes it's very different but the other thing brought up amazon your keynote and how they've kind of fine what kind of a user expectation experiences with an application on the web a level of service a level of delivery and then you've got AWS its kind of the girl child of shadow IT but you guys are coming in really as the enabler to let the internal IT guys actually have the tools to compete with with guys trying to go around it really exact with delivery platform I mean we're trying to turn the tables here right because the entire history of IT is one big end around righty the many computer was an end-around of the glasshouse client-server was really pcs you know dribbling into departmental environments suffer as a service was an incredible end around people in there didn't realize it was seeping into the enterprise right now things like 80 lbs now infrastructure right is actually finding its way so we're saying look you know worthy Enterprise IT cloud company right we are going to empower and enable IT to be driving rather than just being driven and being taken over and run over by by events because that's what's been happening here's the goodness IT can start withdrawing and getting out of the business of infrastructure which is what they've been doing forever infrastructure is very challenging pretty soon that's going to be somebody else's problem right infrastructure goes behind the cooking all you have to do is in network connection so that means that the role of IT is moving from you know keeping the lights on to you know we're going to be the people who are experts at defining structuring and automating service relationships and so does relationship management I mean at this and I make a joke about you know your hole in the inbox of email you know it's full of basically service relationships that are unstructured and unlimited and undefined right right and there is this incredible opportunity to go aptet with record-keeping workflow systems and that's what we want to enable and empower IT to do right we had to give you a quick example actually very interesting we talked to our one of our very large retail customers and the supply chain office unbeknownst to us went to IT and said hey we want to build this app what should we use and Ikey said no you should try and do that on service now what's the app a supply chain office in a retail environment what they do is they take requests all day long stores distribution centers suppliers and they're rebalancing you know product right place right time right right product and they were doing that everybody running spreadsheets and emails and people constantly calling what's the update on my request and they decide no we're going to go to a record-keeping workflow system and from the moment you know they started using that system all of a sudden they had full visibility to a what the volume was of issues that was coming in but the nature of the volume was how well they were doing on their SOS relative to their storage and distribution centers and they were able to structurally go after you know the things that were a constant them grief because they just didn't know right so very simply in very short period of time you know they transformed themselves from the supply chain all those Devils running around like a chicken with his head cut off the people that were actually driving to supply chain now now supply chain management in the retail organization it's super mission-critical right because their results are directly impacted by having right product right time right place simple example where we moving from email and Excel to a record-keeping workflow system any impact with literally within 30 40 days is enormous yeah you hear that a lot of people just using Excel using email we talked to we talking some customers last night we talked to some perspective customers that were in so to check it out and they were big Lotus no shop and is describing sort of the difficulties and challenges of it you will sign them up I can almost see it but the other thing so so this notion of your customer base is very powerful in fact I tweeted out I said the service now has a sick logo basis and we said is that a typo said no sick like that sick touchdown catch it isn't good yeah sick is it good but I mean which I we hear from land o lakes Red Hat metropcs KPM nor Brent I mean just on and on and on at Facebook Intel google or customers what are some other favorite customer stories you hear a lot of the same themes Frank you know we used to use spreadsheets with using email or reliant on all these disparate processes bringing them all together getting some some other you know favorite stories of yours for customers I I relayed a bunch of him on stage this morning right beasties it's just extraordinary to me the the corporate America I mean you mentioned some of them but you know the people we had on stage you know AIG you know coca-cola company's general electric demand this is United States Army right and they owe is yeah New York Stock Exchange eli lilly big pharmaceuticals bristol-myers squibb they all have the same set of issues they have a completely fractured fragmented sprawled acti environment right and here's the interesting history we have not had CIOs that long you know I T used to report into a division next sag or a regional exact and there really wasn't one person that was responsible for running IT throughout the global enterprise because it was just a decentralized function by the way example when you in Europe yeah I ray mighty and I certainly wasn't IT guy stuff and by the way it wasn't my priority either you know it was just by the way that's for some of the history you know comes from so CIO comes in and they are now charged with you're going to run this thing they're not running anything they're being run by it right so until you get to global IT processes I mean City another you know big name they set to as rogue global bank that we don't have global IT right it is the inefficiency and the lack of ability to drive and manage is unacceptable for these very sophisticated large institutions it's embarrassing really you know yeah I mean you really can't go global as a come you can't scale your business not having all these surprises so to me it's about global scaling and it's about the business value of both having ITB accountable but also have the metrics and the visibility to be able to demonstrate the value to the organization you see i SAT with our executive sponsor from bristol-myers squibb last night and she said i got data and i got it in real time and i know it's good so I'm not putting my service providers on their heels you know before they were you know everything was you know in the realm of you know interpretation and fuzzy fuzzy right and now it's like I have data and I'm driving and I'm changing behavior right so the empowering effective it has mighty organizations it's just stomach right I thought that empowering note that came up in your keynote was interesting how the IT organizations themselves and their presentation now to their internal customers are looking more like a company you know they're they're being cute there yeah I'm taking branding they're there they're not just button pushers in and as you said you know infrastructure operators they are trying to be contributors to the business and keeping some this automobile shade of nail them to it's even stronger than now yes they want to be contributors to the business but they want to be the playmakers they wanted me to go to guys give me the ball you know that that's where we want to you know take itt there that people that really understand how to change how work gets done the enterprise I thought you characterize the dwelling experience in IT people have been running from crisis to crisis and they need to be more proactive so talk about how your system allows them to be more proactive well it's all about going from a message oriented environment to a system or an a message or environment is the one way l know it's email it's text you know it's voice right that doesn't work because you know we're just talking right systems have the ability to drive behavior because you know every time you send an email you should think to yourself could i create a service request instead right because a service request has a defined data ship it goes into a database it gets assigned you know in a workflow operation it has metrics around it if it doesn't get responded to a certain amount of time it gets accelerated to the escalator to the next level or management right so the process is defined structure to automate it is going to run its course right whether you know people are participating in it or not with this great example one of our customers equinix delilah or Brian Lily's here actually is a CIO and he said they will sell funny you know we have a system that all my life cycle application where our developers check-in fixes and enhancement to a particular software release for an application and he says because they know to work flows is completely structured an automated everybody knows that they don't get their fixes enhancement in by a certain time poof the dashboards pop the higher-ups see you know who's behind and who's not and that the threat alone of the transparency and visibility that the process introduces causes everybody there run harder right so people won't have to run around with the whip like where are you you know the process is driving is like a hamster on a treadmill you know so Freki used amazon as an example of the user experience that you know you covet as a CEO of this company and you believe you're your customer base desires at the back end also when you talk about companies like Amazon and Facebook and Google they are super highly automated you also talked about lights out automation yeah now normally IT organizations are managed now they're managed by humans they're not highly automated are you are you seeing your customers able to get to that sort of vision that you're talking about that lights-out automation almost like the hyperscale guys you know it's a super important custody I said during the cleanup or were overstaffed and under automated NIT we have reams of people on staff any large financial institutions have tens of thousands of people on staff they're bigger than any technology company right why is that it's because things are very laborious laborious and manual right the processes that they run require so many touch points I mean one of the things that we always tell our customers when you can reimplement these processes do not take your legacy forward because your legacy is very manual you remember the inbox in the outbox when we have physical in boxes and other boxes and now we know we have our laptop why do we have an inbox and outbox right does this message really this cross why are you even involved in this process right so we have to invert the process it's not like wouldn't it be nice for you to be involved in this process there'd better be a very good reason for you to touch this process because the moment you touch it you know we're going from the speed of light to you know the speed of the dirt road that Franco so service now is really in a rocket ship right now and you've demonstrated you've got a track record of being able to be sometimes call jump three myself throwing gasoline on the fire you look very good at that you got 1,600 customers you're growing like crazy but you're under penetrated in your target which is the global 2000 you're only fourteen percent penetrated in the global 2000 so get a long way to go in this journey we're very excited to be you know covering this event really appreciate you guys having us here Frank's loot Minh will give you the last word and then we'll wrap you know this is actually one of the great things that we are so on the front hood and they're penetrated because our investors are like wow you've got a lot of runway you know considering the size company that we we already are and you know the rate of monetization of our business is is extraordinarily I in other words the share of wallet that service now represents and the enterprise is so much larger than people had ever considered or thought because it was not an existing category that was fully metastasized and visible it's new it's emergent it is really transforming how people you know look at technology and process automation and so on now we're gonna be here all week covering knowledge we've got it we're going to double-click on so how is it that service now is able to deliver this cloud functionality the secret is in the single system of record the CMDB and that is not a trivial thing to do we didn't talk about that with Frankie could talk about it but we don't want to steal you know the name of thunder yeah fred muddies going to be on RNA Justin who's the CTO we're going to go deep into sort of how service now actually accomplishes this architecture Lee what their vision is so Frank thanks very much for spending so much time I know you're busy you got to run but appreciate you coming on terrific thanks for having me alright thanks for watching everybody keep it right there we'll be right back with more we're live from Las Vegas ServiceNow knowledge we'll be right back this is the Q cute baby rock and roll
**Summary and Sentiment Analysis are not been shown because of improper transcript**
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Frank Slootman - VMworld 2012 - theCUBE
>> wait. >> Okay, We're back. Live a V M. World twenty twelve. I'm John for the founder's silicon angle dot com. This is the Cube silicon angle dot TV's flagship telecast. We go out to the events and extracted signal from the noise CEOs, entrepreneurs, analysts, marketing people, developers, whoever has the signal, we want extract that share that with you. We have a special guest today. Frank's Leutnant is a sea of service. Now again, I'm John Furry. I'm joined my co host >> of Dave Alonso, a wicked bond dog. Frank, Last time we saw Europe on the stage, you had these glasses on the hat. Remember that, Elwood? So, uh, welcome to the Cube. First time on Thank you. Too many of'Em worlds. I'm sure. A little different angle now. Yeah, Service now. Very exciting. Just went public solving a big problem on DH. Added again? Yes. So tell us. How do you feel? >> That's interesting. A lot of people ask me, how did you end up in, you know, in a in an application software tap a category you spent all this time in storage. The reality is that most of my life, you know, being in the application, development, dusting and system management. So this is actually close to my wheelhouse. Stories was actually a pretty good diversion for me. Careerwise >> service now, relatively, you know, not not a household name but solving that problem. Really, There's no system of record for i t. What activities air doing? Whether it's finance, it's whether it's application portfolio project portfolio. You guys were attacking that whole nut with a software service model. I mean, it used to be a lot of point tools to do that. And you guys seem to be having a lot of success bringing that all to the cloud. >> Yeah, the irony is, is that you look at all the corporate functions, you know, finance, sales, marketing HR, I sort of ranks, you know, last or near last in terms of management sophistication, right compared to the other functional areas, because the most mighty organization have to show for themselves. They helped US management system for their work. For right now, they are to keep track of what's running in their their operation, and that service model is typical of infrastructure providers. Right? You see it, you know, with tell coast like looking t you see it with power. You tell these, like PG and E their infrastructure providers first and the service model. It is not particularly compelling, right? So what we tried to dio it's really take it from a D M V style service model standing in line waiting to be helped. Do you want this more like amazon dot com, where I help myself, It's into it. If it's online, it's productive. It's where I want to go. Teo to make requests as well. Let's receive service >> So you're selling primarily to the organization. Who you sell to in the theory is that the CEO is that the project management offices all the above >> as the servicers management is a very well defined center of responsibility in i t organization. So there's always a group of people who is in charge of that that disciplined. They're easy to find, But CEOs are always involved, and the reason is these air very high profile system rollout because everybody in it is an actor or participant, the workflow as well as the broader employee population, the enterprise, touchy systems, So you better believe that people are sensitive about this being a successful practical and it looks more like a neo system. Dan. It does an infrastructure type system >> without the AARP complexity of it. >> Yes, it's it's a mixed >> metaphor, but so So here are your roughly a hundred fifty million dollar company, you know, annualized, you nice market. >> Either way, we've we've guided to about two. Thirty five, >> thirty five this year. Okay, Great. That's >> want to make sure that their investors don't get >> background. We're sorry about that. Es to thirty five, which is why your market cap about three point six billion. I think >> way had about ninety eight percent growth and buildings in the last quarter. So the high growth, obviously it's what drives >> what's driving that. So how big is the business that you guys playing? What's your tan? >> So we think that the tam just for the narrow definition around service management is a is a multi billion dollar opportunity Because of the nature ofthe work flows, we're also expanding into the operations management area. Right? This is this is where HP lives and BMC and IBM and CIA with these very large open view Tivoli Well, because their work flows between services system management are all becoming integrator that used to be suffered spheres. Not anymore. >> And that's an enormous market. >> It i d. C. Thanks. It's about a thirteen fourteen doing dollar market, and then you have the platform is a service opportunity because our customers have just gone wild, building all kinds of spoke applications on a platform just because they could. So >> you kind of betting on the intersection of systems management, operations, management >> and the platform. >> Okay, and it's kind of jump ball, really, with the dynamic of the cloud coming in, isn't it? In terms of the competitive, it's >> Ah, it's interesting because we look another assassin categories like HR marketing. You see a whole host of players you're looking in our category on the only breakout play there has been serviced now way have predominately compete against legacy vendors, people that I just mentioned. So >> you've got some experience doing that I want >> I want to ask you about the discipline side of the market. You guys are public companies, so yeah, you're out there is all exposed and then talk about some of the product directions because out yesterday they were really showcasing the vision within VM where old way a new way, a access APS infrastructure. You know the classic in the old way. New Way, Modern era. We've been calling it in your world. You're actually replacing some pretty old stuff. I mean, I remember back in the late eighties, early nineties health testing people had that's headsets on and, you know, homegrown software developers and quit a lot of this legacy kind of mindset. So first question is, Is that true? Is there still that much baggage in that services business? From an infrastructure standpoint? And the second part, the question is, what's the new stuff that's really disrupting the market? So in the new way, what is the key features that that's happening in the services industry? >> So, you know, I already started to allude to it, right. So you want to evolve that service model from that help death centric DNP style of service experience to one that's on the line looks more consumer style. You know, the way we've learned from Apple and Yahoo and Google and people like that help yourself. If you have a problem at home with your apple TV, you're really gonna try and call Apple know you're going to go online and you find years of communities you get Teo answers ten times faster, that weight and then following these needy old models the way you reference there is an awful lot of that still living in the world off because they're focuses infrastructure, not service. That's change it, right? I mean, CEOs, I read somewhere, have a shelf life of about eighteen months, right? There's incredible impatience and dissatisfaction with how that function is running. It's costing too much money in the service is not exactly to to write home about. People are really ready to move their service malls. >> The largest answer was, Just hire someone else to do it. That was the outsourcing boom, right? So that's still brought problems, right? Legacy. So how is that still in play? So if the notion is okay, outsource it, and then the outsources has some warts on it that's got to be tweaked. What's the new version? Because you know amazon dot com and you know this new environment availability, instant access, the information we don't service etcetera is that changing it >> way believed that the move to cloud computing is really going to change the role of the CIA, all right, because infrastructure is going to become something that's behind Courtney, and it's becoming less of an infrastructure centric job. CEOs and T organizations become Mohr service engineering organizations, people that understand work flows. People understand how to automate work, flows right out. And, you know, I know how to run a database or a network or, you know, all the security dimensions and so on because we're just breaking as an industry. There just isn't enough competency and skill sets for everybody to be confident at the level that we need to be at structure. It's not scaling, right. It's sort of the way telephone switching centers were in the nineteen fifties >> means one of those things to with the CIA. Attention, I'LL get to that later. But now, with big data in real time analytics is more pressure on the service delivery side. As a business driver, you seeing that pressure as well, or is it more? We just gotta fix it now. I got to do it >> Well, nighty organizations in the lift from one crisis to the next, completely event driven, you know we haven't out its were all over it. Trying to restore service on DH. You know, we sort of live that life day in, day out. But I've never changes right So waken get ahead of this game. You know, if we start structuring, you know, the interaction model that we have with our users how we communicate with them. I mean, simple things, right when you were, you haven't out it. It would be helpful if we were able to pull status. You know, every twenty minutes us to what? What we're doing, What's going on. Right? But having infrastructure be ableto push data out? No, like that. Most organizations don't do that. They live pretty much in the dark, >> so share with our audience out there. That's watching. We have a lot of professionals and data scientists and analyst type audience that we've that we've that follows. Looking angle with Yvonne on DH. Some CEOs as well on early adopters share the folks out there. The pitch, How bad is it that their environment and how easy is it to change? It is just a norther. A magnitude sense of is a turnkey. How do you guys roll in? What's he engagement look like? It's not as hard as the things that most people might have the opinion. I don't want to get just ugly. It's painful or is it not painful? Is it quick pop now? Is it like how fast a roll in and out the infrastructure that you >> the's are extraordinarily sticky systems the system that were that we replace >> your systems of the old systems. >> The old systems are on the reason that they've been around for ten, fifteen years. They're very difficult to replace. And if you look at our girls, that's certainly testament to our compelling. The value proposition has been people have said, you know, a pain is becoming unbearable and be the view of the promised Land is looking pretty good, right? So there's both an incentive to change and to move, and secondly, there is something to move towards that is this compelling inspiring. And it really is going to change my game right, because now we tell people said, Look, if you just tryingto get to a snazzier, more modern help desk, we're not your guy, okay? Because we don't find out a compelling vision of the world. We wantto wholesale transform how you deliver service just >> take us to some of those cats you were talking before you came on about your growth tripling inside. But talk about a zoo company, which is a whole nother conversation. We could talk about it yet you have expertise in, but talk more about the customer deployments. You got some fresh funding with the AIPO. You're geared up. You go out to the market place. What are the conversations like, What are some of the stats and one of the conversation with the CIA? >> Well, the CIA is obviously are interested, first and foremost of the transformation of the service model, right? I mean, we have to get Teo service experience that's more reminiscent of people experience on the consumer side. Now we typically have to do that, that an economic equation that's very similar to what they're having right now. They're not interested in spend more. They just want to get completely refreshed, you know, platform for similar amounts of money that they're already spending because Versace, you know, we're not just taking the software, not off the after after table. We're also taking the entire infrastructure, all the operating staff, everything it takes to run that environment becomes ours, right? It's no longer in the I T department, so that looks pretty compelling to them. >> How about some of the numbers in terms of uptake with customers recently? What's the growth rate was? Can you share some numbers? >> Way have about twelve hundred price customers? We had about one hundred twenty seven the last quarter. That's that is a huge number of customers. Tio Tio ad we have. Most of our focus is on global two thousand enterprises. We have about two hundred thirty global two thousand enterprises, and they're all you know who's who names that, that people recognize Starting up Ticket's been been strong. We're running very, very hard to make sure that we have two services infrastructure. Both there's people and infrastructure to be able to accommodate that. >> Well, I'm excited to interview you because I want to ask you kind of more of a personal question. And although we just met for the first time here, your name's been kicked around as kind of a maverick operational executive who knows how to scale organization. So we're in kind of living in an era where the business value focused, whether startups and has been a lot of talk about, you know, the Facebook idea, the young kids under thirty running a billion dollar market gap, companies trying to actually move from hyped to real scale. And Palmer. It's made a comment yesterday kind of dissing Facebook of in terms of the value proposition relative to say, you know, bm where. But the question I want to ask you is, um, what's your success model for scaling an organization on DH for the younger execs out there? And for people who don't know you just chairs up on the camera? What's your philosophy as the repeatable sales, lower cost leverage model? I mean variety of different kind of ingredients. What's the Franks Lukman formula for success and scaling? Bringing a product to market and growing it? >> Well, the first order of business for for a start up venture of any sort is growth. I find that a lot of people come on a business school in trying to balance girl for profitability. Um, that mentality makes no sense to me, right? It's economics. Before accounting, accounting becomes the bastardization of economics, we run our ventures cash on booking their economic concepts, not accounting constructs, right people are trying to show profit prematurely when they can invest that money to grow. We tripled our head count over the last year. We got very far over our skis. No, we're burning a hole in our gas pals but were very clear with investors that look, we are still increasing our productivity for head. Why, when we apply to resource is to grow this franchise Growth expands our multiples, expands valuation. That's what everybody is in the business for, so so sort of summarize. Knowing your question. Most people hold back on growth, and they don't really know why they're not all out trying to drive growth and the reason that growth is so important. You need to be a breakout player. Nobody wants to be the in between player. That's neither fish nor fowl and doesn't become a dominant entity into space that it wants to be in >> and have the financing in the dry powder behind you that you were a venture capital Greylock, which no something into about investing. So that's also important part right? >> Well, you don't. That's why I said to you manage on cash you managed on bookings. Those are the economics in the business essentially, >> and you've been looking up, have some really good finances behind you, trust you who get the concepts and that's key well, continue in the right >> way went public. We also explain to investors Look, this is what we're trying to do, and this is what we need you to buy into. Otherwise, find somebody else's talk. So >> what is the going public affect? You know the perception amongst the CEO's when you chose to list on the way we had them on earlier this week? But how is that affected? The brand perception? >> That was the whole reason for us to go public, right? We didn't need to cash liquidity. Obviously, it's good for employees and investors when I pose fundamentally a branding event. You know, I used the analogy. We went from playing on Saturday to playing on Sunday. You know, all of a sudden you know you're transparent, you know, all the all the thud that gets spread about you by competition. People cannot punch you up on Iand. See what the truth is around your balance sheet. You know how abot your last quarter was? It's been three. I po was tremendous for us from a branding standpoint, >> and you've been known Teo have a reputation of really getting the product in this case, the service, right? And then really getting aggressive on the sales side. Can you talk about what you've done in the sales side? I know you've aggressively hired. >> Yeah, we You know, as I said, we tripled our head count. We went from three shells. Reasons to twelve insight. One year we spread out all over Europe today. This is a ground war. You need an army to fight it. This is not Facebook. We cannot sign up annoying people in a week. It is a business that runs over the ground so you cannot scale and drive growth business unless you have two people to run it. >> And you're selling belly to belly. That right? Absolutely. So you know, >> we're going through the front door of the elevator >> way. Okay, We're getting the hook here. We're getting hooked, but I have to quit final questions. One is just put a plug out there for service's angle dot com that Silicon Angles separate publication. We launched last year, thanks to E m. C. For helping us sponsor that but really dedicated to the new era of services. And there is some disruption. We're excited to cover you guys, so I just wanted to say Go, go check out sources angle. So Franklin asked two questions. One. What's the big disruption in the services business that most people aren't getting right now? General, you know, man and tech on the street, not the insider inside the ropes. So that's the first question. The second question. What's your goals for the year? For the business? >> Well, the interesting thing about the services business is how it's one of these areas that is sort of the least automated. Write. It runs on the concept of institutional knowledge. Phone conversations, informal communications, email and the frontier in service management is that those become software automated structure processes that is not just happening in I t able sticks. It's happening everywhere, right? What do you want to request? Food. You know, from the hotel you knew what a Virgin America, right? You know, request from your seat, something that's just, you know, on an example of how >> that's the story, you know, debate about that. >> That's how it's gonna go, right? So services it's going to become, really that I call the service fabric right? Essentially how thes processes get conducted. So we're super excited because our platform sits right in the middle of that trend and we're going to try and make that trend. >> It's eleven. Platform to the economics are fantastic and no real customs agents were brought up exactly so good margins. >> And it's just >> like the stock immediately. >> It's much more scalable in the district. Disintermediation. You know, all the all the manual effort goes into this. >> Okay, so now I know your public CEO and everything now, so you really can't be as wild as you could have you a private. But what's the outlook for year? Your personal goals for the year >> Wait, given guns from or get one quarter for years. So check with your favorite analysts. >> Okay? Growth is on the horizon. Congratulations. Frank's been great to have your leadership in the Cube. Thank you. Time Cuban great to have you. This is silicon angle dot coms. The cube will be right back with our next guest, Cynthia Stoddard from Netapp CIA, Another CIA. We're gonna get into the trenches and hear about the transformation again. We'LL be right back
SUMMARY :
This is the Cube silicon angle dot TV's flagship telecast. Frank, Last time we saw Europe on the stage, you had these glasses on the hat. most of my life, you know, being in the application, development, dusting and system management. service now, relatively, you know, not not a household name but Yeah, the irony is, is that you look at all the corporate functions, you know, finance, sales, is that the project management offices all the above as the broader employee population, the enterprise, touchy systems, So you better believe that you know, annualized, you nice market. Either way, we've we've guided to about two. That's Es to thirty five, which is why your market cap about three point six So the high growth, So how big is the business that you guys playing? of the nature ofthe work flows, we're also expanding into the It's about a thirteen fourteen doing dollar market, and then you have the platform is a service You see a whole host of players you're looking in our category on the only breakout play there So in the new way, what is the key features that that's happening in the services needy old models the way you reference there is an awful lot of that still living So if the notion is okay, And, you know, I know how to run a database or a network or, you know, all the security dimensions is more pressure on the service delivery side. Well, nighty organizations in the lift from one crisis to the next, completely event driven, Is it like how fast a roll in and out the infrastructure that you The old systems are on the reason that they've been around for ten, fifteen years. take us to some of those cats you were talking before you came on about your growth tripling inside. We're also taking the entire infrastructure, all the operating staff, everything it takes to run that environment becomes We have about two hundred thirty global two thousand enterprises, and they're all you know who's who names But the question I want to ask you is, um, what's your success model Well, the first order of business for for a start up venture of any sort is and have the financing in the dry powder behind you that you were a venture capital Greylock, Those are the economics in the business essentially, We also explain to investors Look, this is what we're trying to do, and this is what we need you to buy into. all of a sudden you know you're transparent, you know, all the all the thud that gets spread about the service, right? It is a business that runs over the ground so you cannot scale and So you know, We're excited to cover you guys, You know, from the hotel you knew what a Virgin excited because our platform sits right in the middle of that trend and we're going to try and make that trend. Platform to the economics are fantastic and no real customs agents were brought up exactly so You know, all the all the manual effort Your personal goals for the year So check with your favorite analysts. Growth is on the horizon.
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Phil Kippen, Snowflake, Dave Whittington, AT&T & Roddy Tranum, AT&T | | MWC Barcelona 2023
(gentle music) >> Narrator: "TheCUBE's" live coverage is made possible by funding from Dell Technologies, creating technologies that drive human progress. (upbeat music) >> Hello everybody, welcome back to day four of "theCUBE's" coverage of MWC '23. We're here live at the Fira in Barcelona. Wall-to-wall coverage, John Furrier is in our Palo Alto studio, banging out all the news. Really, the whole week we've been talking about the disaggregation of the telco network, the new opportunities in telco. We're really excited to have AT&T and Snowflake here. Dave Whittington is the AVP, at the Chief Data Office at AT&T. Roddy Tranum is the Assistant Vice President, for Channel Performance Data and Tools at AT&T. And Phil Kippen, the Global Head Of Industry-Telecom at Snowflake, Snowflake's new telecom business. Snowflake just announced earnings last night. Typical Scarpelli, they beat earnings, very conservative guidance, stocks down today, but we like Snowflake long term, they're on that path to 10 billion. Guys, welcome to "theCUBE." Thanks so much >> Phil: Thank you. >> for coming on. >> Dave and Roddy: Thanks Dave. >> Dave, let's start with you. The data culture inside of telco, We've had this, we've been talking all week about this monolithic system. Super reliable. You guys did a great job during the pandemic. Everything shifting to landlines. We didn't even notice, you guys didn't miss a beat. Saved us. But the data culture's changing inside telco. Explain that. >> Well, absolutely. So, first of all IoT and edge processing is bringing forth new and exciting opportunities all the time. So, we're bridging the world between a lot of the OSS stuff that we can do with edge processing. But bringing that back, and now we're talking about working, and I would say traditionally, we talk data warehouse. Data warehouse and big data are now becoming a single mesh, all right? And the use cases and the way you can use those, especially I'm taking that edge data and bringing it back over, now I'm running AI and ML models on it, and I'm pushing back to the edge, and I'm combining that with my relational data. So that mesh there is making all the difference. We're getting new use cases that we can do with that. And it's just, and the volume of data is immense. >> Now, I love ChatGPT, but I'm hoping your data models are more accurate than ChatGPT. I never know. Sometimes it's really good, sometimes it's really bad. But enterprise, you got to be clean with your AI, don't you? >> Not only you have to be clean, you have to monitor it for bias and be ethical about it. We're really good about that. First of all with AT&T, our brand is Platinum. We take care of that. So, we may not be as cutting-edge risk takers as others, but when we go to market with an AI or an ML or a product, it's solid. >> Well hey, as telcos go, you guys are leaning into the Cloud. So I mean, that's a good starting point. Roddy, explain your role. You got an interesting title, Channel Performance Data and Tools, what's that all about? >> So literally anything with our consumer, retail, concenters' channels, all of our channels, from a data perspective and metrics perspective, what it takes to run reps, agents, all the way to leadership levels, scorecards, how you rank in the business, how you're driving the business, from sales, service, customer experience, all that data infrastructure with our great partners on the CDO side, as well as Snowflake, that comes from my team. >> And that's traditionally been done in a, I don't mean the pejorative, but we're talking about legacy, monolithic, sort of data warehouse technologies. >> Absolutely. >> We have a love-hate relationship with them. It's what we had. It's what we used, right? And now that's evolving. And you guys are leaning into the Cloud. >> Dramatic evolution. And what Snowflake's enabled for us is impeccable. We've talked about having, people have dreamed of one data warehouse for the longest time and everything in one system. Really, this is the only way that becomes a reality. The more you get in Snowflake, we can have golden source data, and instead of duplicating that 50 times across AT&T, it's in one place, we just share it, everybody leverages it, and now it's not duplicated, and the process efficiency is just incredible. >> But it really hinges on that separation of storage and compute. And we talk about the monolithic warehouse, and one of the nightmares I've lived with, is having a monolithic warehouse. And let's just go with some of my primary, traditional customers, sales, marketing and finance. They are leveraging BSS OSS data all the time. For me to coordinate a deployment, I have to make sure that each one of these units can take an outage, if it's going to be a long deployment. With the separation of storage, compute, they own their own compute cluster. So I can move faster for these people. 'Cause if finance, I can implement his code without impacting finance or marketing. This brings in CI/CD to more reality. It brings us faster to market with more features. So if he wants to implement a new comp plan for the field reps, or we're reacting to the marketplace, where one of our competitors has done something, we can do that in days, versus waiting weeks or months. >> And we've reported on this a lot. This is the brilliance of Snowflake's founders, that whole separation >> Yep. >> from compute and data. I like Dave, that you're starting with sort of the business flexibility, 'cause there's a cost element of this too. You can dial down, you can turn off compute, and then of course the whole world said, "Hey, that's a good idea." And a VC started throwing money at Amazon, but Redshift said, "Oh, we can do that too, sort of, can't turn off the compute." But I want to ask you Phil, so, >> Sure. >> it looks from my vantage point, like you're taking your Data Cloud message which was originally separate compute from storage simplification, now data sharing, automated governance, security, ultimately the marketplace. >> Phil: Right. >> Taking that same model, break down the silos into telecom, right? It's that same, >> Mm-hmm. >> sorry to use the term playbook, Frank Slootman tells me he doesn't use playbooks, but he's not a pattern matcher, but he's a situational CEO, he says. But the situation in telco calls for that type of strategy. So explain what you guys are doing in telco. >> I think there's, so, what we're launching, we launched last week, and it really was three components, right? So we had our platform as you mentioned, >> Dave: Mm-hmm. >> and that platform is being utilized by a number of different companies today. We also are adding, for telecom very specifically, we're adding capabilities in marketplace, so that service providers can not only use some of the data and apps that are in marketplace, but as well service providers can go and sell applications or sell data that they had built. And then as well, we're adding our ecosystem, it's telecom-specific. So, we're bringing partners in, technology partners, and consulting and services partners, that are very much focused on telecoms and what they do internally, but also helping them monetize new services. >> Okay, so it's not just sort of generic Snowflake into telco? You have specific value there. >> We're purposing the platform specifically for- >> Are you a telco guy? >> I am. You are, okay. >> Total telco guy absolutely. >> So there you go. You see that Snowflake is actually an interesting organizational structure, 'cause you're going after verticals, which is kind of rare for a company of your sort of inventory, I'll say, >> Absolutely. >> I don't mean that as a negative. (Dave laughs) So Dave, take us through the data journey at AT&T. It's a long history. You don't have to go back to the 1800s, but- (Dave laughs) >> Thank you for pointing out, we're a 149-year-old company. So, Jesse James was one of the original customers, (Dave laughs) and we have no longer got his data. So, I'll go back. I've been 17 years singular AT&T, and I've watched it through the whole journey of, where the monolithics were growing, when the consolidation of small, wireless carriers, and we went through that boom. And then we've gone through mergers and acquisitions. But, Hadoop came out, and it was going to solve all world hunger. And we had all the aspects of, we're going to monetize and do AI and ML, and some of the things we learned with Hadoop was, we had this monolithic warehouse, we had this file-based-structured Hadoop, but we really didn't know how to bring this all together. And we were bringing items over to the relational, and we were taking the relational and bringing it over to the warehouse, and trying to, and it was a struggle. Let's just go there. And I don't think we were the only company to struggle with that, but we learned a lot. And so now as tech is finally emerging, with the cloud, companies like Snowflake, and others that can handle that, where we can create, we were discussing earlier, but it becomes more of a conducive mesh that's interoperable. So now we're able to simplify that environment. And the cloud is a big thing on that. 'Cause you could not do this on-prem with on-prem technologies. It would be just too cost prohibitive, and too heavy of lifting, going back and forth, and managing the data. The simplicity the cloud brings with a smaller set of tools, and I'll say in the data space specifically, really allows us, maybe not a single instance of data for all use cases, but a greatly reduced ecosystem. And when you simplify your ecosystem, you simplify speed to market and data management. >> So I'm going to ask you, I know it's kind of internal organizational plumbing, but it'll inform my next question. So, Dave, you're with the Chief Data Office, and Roddy, you're kind of, you all serve in the business, but you're really serving the, you're closer to those guys, they're banging on your door for- >> Absolutely. I try to keep the 130,000 users who may or may not have issues sometimes with our data and metrics, away from Dave. And he just gets a call from me. >> And he only calls when he has a problem. He's never wished me happy birthday. (Dave and Phil laugh) >> So the reason I asked that is because, you describe Dave, some of the Hadoop days, and again love-hate with that, but we had hyper-specialized roles. We still do. You've got data engineers, data scientists, data analysts, and you've got this sort of this pipeline, and it had to be this sequential pipeline. I know Snowflake and others have come to simplify that. My question to you is, how is that those roles, how are those roles changing? How is data getting closer to the business? Everybody talks about democratizing business. Are you doing that? What's a real use example? >> From our perspective, those roles, a lot of those roles on my team for years, because we're all about efficiency, >> Dave: Mm-hmm. >> we cut across those areas, and always have cut across those areas. So now we're into a space where things have been simplified, data processes and copying, we've gone from 40 data processes down to five steps now. We've gone from five steps to one step. We've gone from days, now take hours, hours to minutes, minutes to seconds. Literally we're seeing that time in and time out with Snowflake. So these resources that have spent all their time on data engineering and moving data around, are now freed up more on what they have skills for and always have, the data analytics area of the business, and driving the business forward, and new metrics and new analysis. That's some of the great operational value that we've seen here. As this simplification happens, it frees up brain power. >> So, you're pumping data from the OSS, the BSS, the OKRs everywhere >> Everywhere. >> into Snowflake? >> Scheduling systems, you name it. If you can think of what drives our retail and centers and online, all that data, scheduling system, chat data, call center data, call detail data, all of that enters into this common infrastructure to manage the business on a day in and day out basis. >> How are the roles and the skill sets changing? 'Cause you're doing a lot less ETL, you're doing a lot less moving of data around. There were guys that were probably really good at that. I used to joke in the, when I was in the storage world, like if your job is bandaging lungs, you need to look for a new job, right? So, and they did and people move on. So, are you able to sort of redeploy those assets, and those people, those human resources? >> These folks are highly skilled. And we were talking about earlier, SQL hasn't gone away. Relational databases are not going away. And that's one thing that's made this migration excellent, they're just transitioning their skills. Experts in legacy systems are now rapidly becoming experts on the Snowflake side. And it has not been that hard a transition. There are certainly nuances, things that don't operate as well in the cloud environment that we have to learn and optimize. But we're making that transition. >> Dave: So just, >> Please. >> within the Chief Data Office we have a couple of missions, and Roddy is a great partner and an example of how it works. We try to bring the data for democratization, so that we have one interface, now hopefully know we just have a logical connection back to these Snowflake instances that we connect. But we're providing that governance and cleansing, and if there's a business rule at the enterprise level, we provide it. But the goal at CDO is to make sure that business units like Roddy or marketing or finance, that they can come to a platform that's reliable, robust, and self-service. I don't want to be in his way. So I feel like I'm providing a sub-level of platform, that he can come to and anybody can come to, and utilize, that they're not having to go back and undo what's in Salesforce, or ServiceNow, or in our billers. So, I'm sort of that layer. And then making sure that that ecosystem is robust enough for him to use. >> And that self-service infrastructure is predominantly through the Azure Cloud, correct? >> Dave: Absolutely. >> And you work on other clouds, but it's predominantly through Azure? >> We're predominantly in Azure, yeah. >> Dave: That's the first-party citizen? >> Yeah. >> Okay, I like to think in terms sometimes of data products, and I know you've mentioned upfront, you're Gold standard or Platinum standard, you're very careful about personal information. >> Dave: Yeah. >> So you're not trying to sell, I'm an AT&T customer, you're not trying to sell my data, and make money off of my data. So the value prop and the business case for Snowflake is it's simpler. You do things faster, you're in the cloud, lower cost, et cetera. But I presume you're also in the business, AT&T, of making offers and creating packages for customers. I look at those as data products, 'cause it's not a, I mean, yeah, there's a physical phone, but there's data products behind it. So- >> It ultimately is, but not everybody always sees it that way. Data reporting often can be an afterthought. And we're making it more on the forefront now. >> Yeah, so I like to think in terms of data products, I mean even if the financial services business, it's a data business. So, if we can think about that sort of metaphor, do you see yourselves as data product builders? Do you have that, do you think about building products in that regard? >> Within the Chief Data Office, we have a data product team, >> Mm-hmm. >> and by the way, I wouldn't be disingenuous if I said, oh, we're very mature in this, but no, it's where we're going, and it's somewhat of a journey, but I've got a peer, and their whole job is to go from, especially as we migrate from cloud, if Roddy or some other group was using tables three, four and five and joining them together, it's like, "Well look, this is an offer for data product, so let's combine these and put it up in the cloud, and here's the offer data set product, or here's the opportunity data product," and it's a journey. We're on the way, but we have dedicated staff and time to do this. >> I think one of the hardest parts about that is the organizational aspects of it. Like who owns the data now, right? It used to be owned by the techies, and increasingly the business lines want to have access, you're providing self-service. So there's a discussion about, "Okay, what is a data product? Who's responsible for that data product? Is it in my P&L or your P&L? Somebody's got to sign up for that number." So, it sounds like those discussions are taking place. >> They are. And, we feel like we're more the, and CDO at least, we feel more, we're like the guardians, and the shepherds, but not the owners. I mean, we have a role in it all, but he owns his metrics. >> Yeah, and even from our perspective, we see ourselves as an enabler of making whatever AT&T wants to make happen in terms of the key products and officers' trade-in offers, trade-in programs, all that requires this data infrastructure, and managing reps and agents, and what they do from a channel performance perspective. We still ourselves see ourselves as key enablers of that. And we've got to be flexible, and respond quickly to the business. >> I always had empathy for the data engineer, and he or she had to service all these different lines of business with no business context. >> Yeah. >> Like the business knows good data from bad data, and then they just pound that poor individual, and they're like, "Okay, I'm doing my best. It's just ones and zeros to me." So, it sounds like that's, you're on that path. >> Yeah absolutely, and I think, we do have refined, getting more and more refined owners of, since Snowflake enables these golden source data, everybody sees me and my organization, channel performance data, go to Roddy's team, we have a great team, and we go to Dave in terms of making it all happen from a data infrastructure perspective. So we, do have a lot more refined, "This is where you go for the golden source, this is where it is, this is who owns it. If you want to launch this product and services, and you want to manage reps with it, that's the place you-" >> It's a strong story. So Chief Data Office doesn't own the data per se, but it's your responsibility to provide the self-service infrastructure, and make sure it's governed properly, and in as automated way as possible. >> Well, yeah, absolutely. And let me tell you more, everybody talks about single version of the truth, one instance of the data, but there's context to that, that we are taking, trying to take advantage of that as we do data products is, what's the use case here? So we may have an entity of Roddy as a prospective customer, and we may have a entity of Roddy as a customer, high-value customer over here, which may have a different set of mix of data and all, but as a data product, we can then create those for those specific use cases. Still point to the same data, but build it in different constructs. One for marketing, one for sales, one for finance. By the way, that's where your data engineers are struggling. >> Yeah, yeah, of course. So how do I serve all these folks, and really have the context-common story in telco, >> Absolutely. >> or are these guys ahead of the curve a little bit? Or where would you put them? >> I think they're definitely moving a lot faster than the industry is generally. I think the enabling technologies, like for instance, having that single copy of data that everybody sees, a single pane of glass, right, that's definitely something that everybody wants to get to. Not many people are there. I think, what AT&T's doing, is most definitely a little bit further ahead than the industry generally. And I think the successes that are coming out of that, and the learning experiences are starting to generate momentum within AT&T. So I think, it's not just about the product, and having a product now that gives you a single copy of data. It's about the experiences, right? And now, how the teams are getting trained, domains like network engineering for instance. They typically haven't been a part of data discussions, because they've got a lot of data, but they're focused on the infrastructure. >> Mm. >> So, by going ahead and deploying this platform, for platform's purpose, right, and the business value, that's one thing, but also to start bringing, getting that experience, and bringing new experience in to help other groups that traditionally hadn't been data-centric, that's also a huge step ahead, right? So you need to enable those groups. >> A big complaint of course we hear at MWC from carriers is, "The over-the-top guys are killing us. They're riding on our networks, et cetera, et cetera. They have all the data, they have all the client relationships." Do you see your client relationships changing as a result of sort of your data culture evolving? >> Yes, I'm not sure I can- >> It's a loaded question, I know. >> Yeah, and then I, so, we want to start embedding as much into our network on the proprietary value that we have, so we can start getting into that OTT play, us as any other carrier, we have distinct advantages of what we can do at the edge, and we just need to start exploiting those. But you know, 'cause whether it's location or whatnot, so we got to eat into that. Historically, the network is where we make our money in, and we stack the services on top of it. It used to be *69. >> Dave: Yeah. >> If anybody remembers that. >> Dave: Yeah, of course. (Dave laughs) >> But you know, it was stacked on top of our network. Then we stack another product on top of it. It'll be in the edge where we start providing distinct values to other partners as we- >> I mean, it's a great business that you're in. I mean, if they're really good at connectivity. >> Dave: Yeah. >> And so, it sounds like it's still to be determined >> Dave: Yeah. >> where you can go with this. You have to be super careful with private and for personal information. >> Dave: Yep. >> Yeah, but the opportunities are enormous. >> There's a lot. >> Yeah, particularly at the edge, looking at, private networks are just an amazing opportunity. Factories and name it, hospital, remote hospitals, remote locations. I mean- >> Dave: Connected cars. >> Connected cars are really interesting, right? I mean, if you start communicating car to car, and actually drive that, (Dave laughs) I mean that's, now we're getting to visit Xen Fault Tolerance people. This is it. >> Dave: That's not, let's hold the traffic. >> Doesn't scare me as much as we actually learn. (all laugh) >> So how's the show been for you guys? >> Dave: Awesome. >> What're your big takeaways from- >> Tremendous experience. I mean, someone who doesn't go outside the United States much, I'm a homebody. The whole experience, the whole trip, city, Mobile World Congress, the technologies that are out here, it's been a blast. >> Anything, top two things you learned, advice you'd give to others, your colleagues out in general? >> In general, we talked a lot about technologies today, and we talked a lot about data, but I'm going to tell you what, the accelerator that you cannot change, is the relationship that we have. So when the tech and the business can work together toward a common goal, and it's a partnership, you get things done. So, I don't know how many CDOs or CIOs or CEOs are out there, but this connection is what accelerates and makes it work. >> And that is our audience Dave. I mean, it's all about that alignment. So guys, I really appreciate you coming in and sharing your story in "theCUBE." Great stuff. >> Thank you. >> Thanks a lot. >> All right, thanks everybody. Thank you for watching. I'll be right back with Dave Nicholson. Day four SiliconANGLE's coverage of MWC '23. You're watching "theCUBE." (gentle music)
SUMMARY :
that drive human progress. And Phil Kippen, the Global But the data culture's of the OSS stuff that we But enterprise, you got to be So, we may not be as cutting-edge Channel Performance Data and all the way to leadership I don't mean the pejorative, And you guys are leaning into the Cloud. and the process efficiency and one of the nightmares I've lived with, This is the brilliance of the business flexibility, like you're taking your Data Cloud message But the situation in telco and that platform is being utilized You have specific value there. I am. So there you go. I don't mean that as a negative. and some of the things we and Roddy, you're kind of, And he just gets a call from me. (Dave and Phil laugh) and it had to be this sequential pipeline. and always have, the data all of that enters into How are the roles and in the cloud environment that But the goal at CDO is to and I know you've mentioned upfront, So the value prop and the on the forefront now. I mean even if the and by the way, I wouldn't and increasingly the business and the shepherds, but not the owners. and respond quickly to the business. and he or she had to service Like the business knows and we go to Dave in terms doesn't own the data per se, and we may have a entity and really have the and having a product now that gives you and the business value, that's one thing, They have all the data, on the proprietary value that we have, Dave: Yeah, of course. It'll be in the edge business that you're in. You have to be super careful Yeah, but the particularly at the edge, and actually drive that, let's hold the traffic. much as we actually learn. the whole trip, city, is the relationship that we have. and sharing your story in "theCUBE." Thank you for watching.
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theCUBE's New Analyst Talks Cloud & DevOps
(light music) >> Hi everybody. Welcome to this Cube Conversation. I'm really pleased to announce a collaboration with Rob Strechay. He's a guest cube analyst, and we'll be working together to extract the signal from the noise. Rob is a long-time product pro, working at a number of firms including AWS, HP, HPE, NetApp, Snowplow. I did a stint as an analyst at Enterprise Strategy Group. Rob, good to see you. Thanks for coming into our Marlboro Studios. >> Well, thank you for having me. It's always great to be here. >> I'm really excited about working with you. We've known each other for a long time. You've been in the Cube a bunch. You know, you're in between gigs, and I think we can have a lot of fun together. Covering events, covering trends. So. let's get into it. What's happening out there? We're sort of exited the isolation economy. Things were booming. Now, everybody's tapping the brakes. From your standpoint, what are you seeing out there? >> Yeah. I'm seeing that people are really looking how to get more out of their data. How they're bringing things together, how they're looking at the costs of Cloud, and understanding how are they building out their SaaS applications. And understanding that when they go in and actually start to use Cloud, it's not only just using the base services anymore. They're looking at, how do I use these platforms as a service? Some are easier than others, and they're trying to understand, how do I get more value out of that relationship with the Cloud? They're also consolidating the number of Clouds that they have, I would say to try to better optimize their spend, and getting better pricing for that matter. >> Are you seeing people unhook Clouds, or just reduce maybe certain Cloud activities and going maybe instead of 60/40 going 90/10? >> Correct. It's more like the 90/10 type of rule where they're starting to say, Hey I'm not going to get rid of Azure or AWS or Google. I'm going to move a portion of this over that I was using on this one service. Maybe I got a great two-year contract to start with on this platform as a service or a database as a service. I'm going to unhook from that and maybe go with an independent. Maybe with something like a Snowflake or a Databricks on top of another Cloud, so that I can consolidate down. But it also gives them more flexibility as well. >> In our last breaking analysis, Rob, we identified six factors that were reducing Cloud consumption. There were factors and customer tactics. And I want to get your take on this. So, some of the factors really, you got fewer mortgage originations. FinTech, obviously big Cloud user. Crypto, not as much activity there. Lower ad spending means less Cloud. And then one of 'em, which you kind of disagreed with was less, less analytics, you know, fewer... Less frequency of calculations. I'll come back to that. But then optimizing compute using Graviton or AMD instances moving to cheaper storage tiers. That of course makes sense. And then optimize pricing plans. Maybe going from On Demand, you know, to, you know, instead of pay by the drink, buy in volume. Okay. So, first of all, do those make sense to you with the exception? We'll come back and talk about the analytics piece. Is that what you're seeing from customers? >> Yeah, I think so. I think that was pretty much dead on with what I'm seeing from customers and the ones that I go out and talk to. A lot of times they're trying to really monetize their, you know, understand how their business utilizes these Clouds. And, where their spend is going in those Clouds. Can they use, you know, lower tiers of storage? Do they really need the best processors? Do they need to be using Intel or can they get away with AMD or Graviton 2 or 3? Or do they need to move in? And, I think when you look at all of these Clouds, they always have pricing curves that are arcs from the newest to the oldest stuff. And you can play games with that. And understanding how you can actually lower your costs by looking at maybe some of the older generation. Maybe your application was written 10 years ago. You don't necessarily have to be on the best, newest processor for that application per se. >> So last, I want to come back to this whole analytics piece. Last June, I think it was June, Dev Ittycheria, who's the-- I call him Dev. Spelled Dev, pronounced Dave. (chuckles softly) Same pronunciation, different spelling. Dev Ittycheria, CEO of Mongo, on the earnings call. He was getting, you know, hit. Things were starting to get a little less visible in terms of, you know, the outlook. And people were pushing him like... Because you're in the Cloud, is it easier to dial down? And he said, because we're the document database, we support transaction applications. We're less discretionary than say, analytics. Well on the Snowflake earnings call, that same month or the month after, they were all over Slootman and Scarpelli. Oh, the Mongo CEO said that they're less discretionary than analytics. And Snowflake was an interesting comment. They basically said, look, we're the Cloud. You can dial it up, you can dial it down, but the area under the curve over a period of time is going to be the same, because they get their customers to commit. What do you say? You disagreed with the notion that people are running their calculations less frequently. Is that because they're trying to do a better job of targeting customers in near real time? What are you seeing out there? >> Yeah, I think they're moving away from using people and more expensive marketing. Or, they're trying to figure out what's my Google ad spend, what's my Meta ad spend? And what they're trying to do is optimize that spend. So, what is the return on advertising, or the ROAS as they would say. And what they're looking to do is understand, okay, I have to collect these analytics that better understand where are these people coming from? How do they get to my site, to my store, to my whatever? And when they're using it, how do they they better move through that? What you're also seeing is that analytics is not only just for kind of the retail or financial services or things like that, but then they're also, you know, using that to make offers in those categories. When you move back to more, you know, take other companies that are building products and SaaS delivered products. They may actually go and use this analytics for making the product better. And one of the big reasons for that is maybe they're dialing back how many product managers they have. And they're looking to be more data driven about how they actually go and build the product out or enhance the product. So maybe they're, you know, an online video service and they want to understand why people are either using or not using the whiteboard inside the product. And they're collecting a lot of that product analytics in a big way so that they can go through that. And they're doing it in a constant manner. This first party type tracking within applications is growing rapidly by customers. >> So, let's talk about who wins in that. So, obviously the Cloud guys, AWS, Google and Azure. I want to come back and unpack that a little bit. Databricks and Snowflake, we reported on our last breaking analysis, it kind of on a collision course. You know, a couple years ago we were thinking, okay, AWS, Snowflake and Databricks, like perfect sandwich. And then of course they started to become more competitive. My sense is they still, you know, compliment each other in the field, right? But, you know, publicly, they've got bigger aspirations, they get big TAMs that they're going after. But it's interesting, the data shows that-- So, Snowflake was off the charts in terms of spending momentum and our EPR surveys. Our partner down in New York, they kind of came into line. They're both growing in terms of market presence. Databricks couldn't get to IPO. So, we don't have as much, you know, visibility on their financials. You know, Snowflake obviously highly transparent cause they're a public company. And then you got AWS, Google and Azure. And it seems like AWS appears to be more partner friendly. Microsoft, you know, depends on what market you're in. And Google wants to sell BigQuery. >> Yeah. >> So, what are you seeing in the public Cloud from a data platform perspective? >> Yeah. I think that was pretty astute in what you were talking about there, because I think of the three, Google is definitely I think a little bit behind in how they go to market with their partners. Azure's done a fantastic job of partnering with these companies to understand and even though they may have Synapse as their go-to and where they want people to go to do AI and ML. What they're looking at is, Hey, we're going to also be friendly with Snowflake. We're also going to be friendly with a Databricks. And I think that, Amazon has always been there because that's where the market has been for these developers. So, many, like Databricks' and the Snowflake's have gone there first because, you know, Databricks' case, they built out on top of S3 first. And going and using somebody's object layer other than AWS, was not as simple as you would think it would be. Moving between those. >> So, one of the financial meetups I said meetup, but the... It was either the CEO or the CFO. It was either Slootman or Scarpelli talking at, I don't know, Merrill Lynch or one of the other financial conferences said, I think it was probably their Q3 call. Snowflake said 80% of our business goes through Amazon. And he said to this audience, the next day we got a call from Microsoft. Hey, we got to do more. And, we know just from reading the financial statements that Snowflake is getting concessions from Amazon, they're buying in volume, they're renegotiating their contracts. Amazon gets it. You know, lower the price, people buy more. Long term, we're all going to make more money. Microsoft obviously wants to get into that game with Snowflake. They understand the momentum. They said Google, not so much. And I've had customers tell me that they wanted to use Google's AI with Snowflake, but they can't, they got to go to to BigQuery. So, honestly, I haven't like vetted that so. But, I think it's true. But nonetheless, it seems like Google's a little less friendly with the data platform providers. What do you think? >> Yeah, I would say so. I think this is a place that Google looks and wants to own. Is that now, are they doing the right things long term? I mean again, you know, you look at Google Analytics being you know, basically outlawed in five countries in the EU because of GDPR concerns, and compliance and governance of data. And I think people are looking at Google and BigQuery in general and saying, is it the best place for me to go? Is it going to be in the right places where I need it? Still, it's still one of the largest used databases out there just because it underpins a number of the Google services. So you almost get, like you were saying, forced into BigQuery sometimes, if you want to use the tech on top. >> You do strategy. >> Yeah. >> Right? You do strategy, you do messaging. Is it the right call by Google? I mean, it's not a-- I criticize Google sometimes. But, I'm not sure it's the wrong call to say, Hey, this is our ace in the hole. >> Yeah. >> We got to get people into BigQuery. Cause, first of all, BigQuery is a solid product. I mean it's Cloud native and it's, you know, by all, it gets high marks. So, why give the competition an advantage? Let's try to force people essentially into what is we think a great product and it is a great product. The flip side of that is, they're giving up some potential partner TAM and not treating the ecosystem as well as one of their major competitors. What do you do if you're in that position? >> Yeah, I think that that's a fantastic question. And the question I pose back to the companies I've worked with and worked for is, are you really looking to have vendor lock-in as your key differentiator to your service? And I think when you start to look at these companies that are moving away from BigQuery, moving to even, Databricks on top of GCS in Google, they're looking to say, okay, I can go there if I have to evacuate from GCP and go to another Cloud, I can stay on Databricks as a platform, for instance. So I think it's, people are looking at what platform as a service, database as a service they go and use. Because from a strategic perspective, they don't want that vendor locking. >> That's where Supercloud becomes interesting, right? Because, if I can run on Snowflake or Databricks, you know, across Clouds. Even Oracle, you know, they're getting into business with Microsoft. Let's talk about some of the Cloud players. So, the big three have reported. >> Right. >> We saw AWSs Cloud growth decelerated down to 20%, which is I think the lowest growth rate since they started to disclose public numbers. And they said they exited, sorry, they said January they grew at 15%. >> Yeah. >> Year on year. Now, they had some pretty tough compares. But nonetheless, 15%, wow. Azure, kind of mid thirties, and then Google, we had kind of low thirties. But, well behind in terms of size. And Google's losing probably almost $3 billion annually. But, that's not necessarily a bad thing by advocating and investing. What's happening with the Cloud? Is AWS just running into the law, large numbers? Do you think we can actually see a re-acceleration like we have in the past with AWS Cloud? Azure, we predicted is going to be 75% of AWS IAS revenues. You know, we try to estimate IAS. >> Yeah. >> Even though they don't share that with us. That's a huge milestone. You'd think-- There's some people who have, I think, Bob Evans predicted a while ago that Microsoft would surpass AWS in terms of size. You know, what do you think? >> Yeah, I think that Azure's going to keep to-- Keep growing at a pretty good clip. I think that for Azure, they still have really great account control, even though people like to hate Microsoft. The Microsoft sellers that are out there making those companies successful day after day have really done a good job of being in those accounts and helping people. I was recently over in the UK. And the UK market between AWS and Azure is pretty amazing, how much Azure there is. And it's growing within Europe in general. In the states, it's, you know, I think it's growing well. I think it's still growing, probably not as fast as it is outside the U.S. But, you go down to someplace like Australia, it's also Azure. You hear about Azure all the time. >> Why? Is that just because of the Microsoft's software state? It's just so convenient. >> I think it has to do with, you know, and you can go with the reasoning they don't break out, you know, Office 365 and all of that out of their numbers is because they have-- They're in all of these accounts because the office suite is so pervasive in there. So, they always have reasons to go back in and, oh by the way, you're on these old SQL licenses. Let us move you up here and we'll be able to-- We'll support you on the old version, you know, with security and all of these things. And be able to move you forward. So, they have a lot of, I guess you could say, levers to stay in those accounts and be interesting. At least as part of the Cloud estate. I think Amazon, you know, is hitting, you know, the large number. Laws of large numbers. But I think that they're also going through, and I think this was seen in the layoffs that they were making, that they're looking to understand and have profitability in more of those services that they have. You know, over 350 odd services that they have. And you know, as somebody who went there and helped to start yet a new one, while I was there. And finally, it went to beta back in September, you start to look at the fact that, that number of services, people, their own sellers don't even know all of their services. It's impossible to comprehend and sell that many things. So, I think what they're going through is really looking to rationalize a lot of what they're doing from a services perspective going forward. They're looking to focus on more profitable services and bringing those in. Because right now it's built like a layer cake where you have, you know, S3 EBS and EC2 on the bottom of the layer cake. And then maybe you have, you're using IAM, the authorization and authentication in there and you have all these different services. And then they call it EMR on top. And so, EMR has to pay for that entire layer cake just to go and compete against somebody like Mongo or something like that. So, you start to unwind the costs of that. Whereas Azure, went and they build basically ground up services for the most part. And Google kind of falls somewhere in between in how they build their-- They're a sort of layer cake type effect, but not as many layers I guess you could say. >> I feel like, you know, Amazon's trying to be a platform for the ecosystem. Yes, they have their own products and they're going to sell. And that's going to drive their profitability cause they don't have to split the pie. But, they're taking a piece of-- They're spinning the meter, as Ziyas Caravalo likes to say on every time Snowflake or Databricks or Mongo or Atlas is, you know, running on their system. They take a piece of the action. Now, Microsoft does that as well. But, you look at Microsoft and security, head-to-head competitors, for example, with a CrowdStrike or an Okta in identity. Whereas, it seems like at least for now, AWS is a more friendly place for the ecosystem. At the same time, you do a lot of business in Microsoft. >> Yeah. And I think that a lot of companies have always feared that Amazon would just throw, you know, bodies at it. And I think that people have come to the realization that a two pizza team, as Amazon would call it, is eight people. I think that's, you know, two slices per person. I'm a little bit fat, so I don't know if that's enough. But, you start to look at it and go, okay, if they're going to start out with eight engineers, if I'm a startup and they're part of my ecosystem, do I really fear them or should I really embrace them and try to partner closer with them? And I think the smart people and the smart companies are partnering with them because they're realizing, Amazon, unless they can see it to, you know, a hundred million, $500 million market, they're not going to throw eight to 16 people at a problem. I think when, you know, you could say, you could look at the elastic with OpenSearch and what they did there. And the licensing terms and the battle they went through. But they knew that Elastic had a huge market. Also, you had a number of ecosystem companies building on top of now OpenSearch, that are now domain on top of Amazon as well. So, I think Amazon's being pretty strategic in how they're doing it. I think some of the-- It'll be interesting. I think this year is a payout year for the cuts that they're making to some of the services internally to kind of, you know, how do we take the fat off some of those services that-- You know, you look at Alexa. I don't know how much revenue Alexa really generates for them. But it's a means to an end for a number of different other services and partners. >> What do you make of this ChatGPT? I mean, Microsoft obviously is playing that card. You want to, you want ChatGPT in the Cloud, come to Azure. Seems like AWS has to respond. And we know Google is, you know, sharpening its knives to come up with its response. >> Yeah, I mean Google just went and talked about Bard for the first time this week and they're in private preview or I guess they call it beta, but. Right at the moment to select, select AI users, which I have no idea what that means. But that's a very interesting way that they're marketing it out there. But, I think that Amazon will have to respond. I think they'll be more measured than say, what Google's doing with Bard and just throwing it out there to, hey, we're going into beta now. I think they'll look at it and see where do we go and how do we actually integrate this in? Because they do have a lot of components of AI and ML underneath the hood that other services use. And I think that, you know, they've learned from that. And I think that they've already done a good job. Especially for media and entertainment when you start to look at some of the ways that they use it for helping do graphics and helping to do drones. I think part of their buy of iRobot was the fact that iRobot was a big user of RoboMaker, which is using different models to train those robots to go around objects and things like that, so. >> Quick touch on Kubernetes, the whole DevOps World we just covered. The Cloud Native Foundation Security, CNCF. The security conference up in Seattle last week. First time they spun that out kind of like reinforced, you know, AWS spins out, reinforced from reinvent. Amsterdam's coming up soon, the CubeCon. What should we expect? What's hot in Cubeland? >> Yeah, I think, you know, Kubes, you're going to be looking at how OpenShift keeps growing and I think to that respect you get to see the momentum with people like Red Hat. You see others coming up and realizing how OpenShift has gone to market as being, like you were saying, partnering with those Clouds and really making it simple. I think the simplicity and the manageability of Kubernetes is going to be at the forefront. I think a lot of the investment is still going into, how do I bring observability and DevOps and AIOps and MLOps all together. And I think that's going to be a big place where people are going to be looking to see what comes out of CubeCon in Amsterdam. I think it's that manageability ease of use. >> Well Rob, I look forward to working with you on behalf of the whole Cube team. We're going to do more of these and go out to some shows extract the signal from the noise. Really appreciate you coming into our studio. >> Well, thank you for having me on. Really appreciate it. >> You're really welcome. All right, keep it right there, or thanks for watching. This is Dave Vellante for the Cube. And we'll see you next time. (light music)
SUMMARY :
I'm really pleased to It's always great to be here. and I think we can have the number of Clouds that they have, contract to start with those make sense to you And, I think when you look in terms of, you know, the outlook. And they're looking to My sense is they still, you know, in how they go to market And he said to this audience, is it the best place for me to go? You do strategy, you do messaging. and it's, you know, And I think when you start Even Oracle, you know, since they started to to be 75% of AWS IAS revenues. You know, what do you think? it's, you know, I think it's growing well. Is that just because of the And be able to move you forward. I feel like, you know, I think when, you know, you could say, And we know Google is, you know, And I think that, you know, you know, AWS spins out, and I think to that respect forward to working with you Well, thank you for having me on. And we'll see you next time.
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Breaking Analysis: Enterprise Technology Predictions 2023
(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)
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insights from the Cube and ETR, do for the community, Dave, good to see you. actually come back to me if you would. It just stays at the top. the most aggressive to cut. that have the most to lose What's the primary method still leads the way, you know, So in addition to what we're seeing here, And so I actually thank you I went through it for you. I'm going to ask you to explain and they're certainly not going to get it to you in a zero trust way. So all of that is the One is just the number of So come back to me in 12 So 52% of the ETR survey amount of money on the Metaverse and also in the data prep tools. the cloud expands to the biggest shock to me "Ah, it's, you know, really and Fastly is their really the folks said, you know, for a home in the enterprise, Yeah, and I got to be honest, in the community, you know, and I don't know if that's the right move and the vertical axis is shared net score. So that's really what you want Well, the way they compete So that's, you know, One of the problems, if and that's going to be obviously even Oracle is going to scale down. and the data pipelines and that, you know, Been a nuts three I love the fact I know you were really is so much data at ETR. and we'll see you next time
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Dilip Kumar, AWS Applications | AWS re:Invent 2022
(lively music) >> Good afternoon and welcome back to beautiful Las Vegas, Nevada, where we're here live from the show floor, all four days of AWS re:Invent. I'm Savannah Peterson, joined with my co-host Dave Vellante. Dave, how you doing? >> Good. Beautiful and chilly Las Vegas. Can't wait to get back to New England where it's warm. >> Balmy, New England this time of year in December. Wow, Dave, that's a bold statement. I am super excited about the conversation that we're going to be having next. And, you know, I'm not even going to tee it up. I just want to bring Dilip on. Dilip, thank you so much for being here. How you doing? >> Savannah, Dave, thank you so much. >> Hey, Dilip. >> Excited to be here. >> It's joy to have you. So, you have been working at Amazon for about 20 years. >> Almost. Almost. >> Yes. >> Feels like 20, 19 1/2. >> Which is very exciting. You've had a lot of roles. I'm going to touch on some of them, but you just came over to AWS from the physical retail side. Talk to me about that. >> Yup, so I've been to Amazon for 19 1/2 years. Done pricing, supply chain. I was Jeff Bezos technical advisor for a couple years. >> Casual name drop. >> Casual name drop. >> Savannah: But a couple people here for that name before. >> Humble brag, hashtag. And then I, for the last several years, I was leading our physical retail initiatives. We just walk out Amazon One, bringing convenience to physical spaces. And then in August, with like as those things were getting a lot of traction and we were selling to third parties, we felt that it would be better suited in AWS. And, but along with that, there was also another trend that's been brewing, which is, you know, companies have loved building on AWS. They love the infrastructure services, but increasingly, they're also asking us to build applications that are higher up in the stack. Solving key, turnkey business problems. Just walk out Amazon One or examples of that, Amazon Connect. We just recently announced supply chain, so now there's a bevy interesting services all coming together, higher up in the stack for customers. So it's an exciting time. >> It was interesting that you're able to, you know, transfer from that retail. I mean, normally, in historically, if you're within an industry, retail, manufacturing, automotive whatever. You were kind as locked in a little bit. >> Dilip: Siloed a little bit. Yeah, yeah, yeah. >> Because they had their own, your own value chain. And I guess, data has changed that maybe, that you can traverse now. >> Yeah, if you think about the things that we did, even when we were in retail, the tenants was less about the industries and more about how can we bring convenience to physical spaces? The fact that you don't like to wait in line is no more like likely, you know, five years from now than it is today. So, it's a very durable tenant, but it's equally applicable whether you're in a grocery store, a convenience store, a stadium, an airport. So it actually transcends any, and like supply chain, think of supply chain. Supply chain isn't, you know, targeted to any one particular industry. It has broad applicability. So these things are very, you know, horizontally applicable. >> Anything that makes my life easier, I'm down. >> Savannah: We're all here for the easy button. We've been talking about it a bit this week. I'm in. And the retail store, I mean, I'm in San Francisco. I've had the experience of going through. Very interesting and seamless journey, honestly. It's very exciting. So tell us a little bit more about the applications group at AWS. >> Yup. So as I said, you know, we are, the applications group is a combination of several services. You know, we have communication developer services, which is the ability to add simple email service or video and embed video, voice chat using a chime SDK. In a higher up in the stack, we are taking care of things that IT administrators have to deal with where you can provision an entire desktop with the workspaces or provide a femoral access to it. And then as you go up even higher up in the stack, you have productivity applications like AWS Wicker, which we just did GA, you know, last week in AWS Clean Rooms which we announced as a service in preview. And then you have, you know, Connect, which is our cloud contact center, AWS supply chain. Just walk out Amazon One, it just feels like we're getting started. >> Just a couple things going on. >> So, clean rooms. Part of the governance play, part of data sharing. Can you explain, you know, we were talking offline, but I remember back in the disk drive days. We were in a clean room, they'd show you the clean room, you couldn't go near it unless you had a hazmat suit on. So now you're applying that to data. Explain that concept. >> Yeah, so the companies across, you know, financial services or healthcare, advertising, they all want to be able to combine and pull together data`sets with their partners in order to get these collaborative insights. The problem is either the data's fragmented, it's siloed or you have, you know, data governance issues that's preventing them from sharing. And the key requirement is that they want to be able to share this data without exposing any of the underlying data. Clean rooms are always emerged as a solution to that, but the problem with that is that they're hard to maintain. They're expensive. You have to write complex privacy queries. And if you make a mistake, you risk exposing the same data that you've been, you know, studiously trying to protect. >> Trying to protect. >> You know, take advertising as an industry, as an example. You know, advertisers care about, is my ad effective? But it turns out that if you're an advertiser and let's say you're a Nike or some other advertiser and your pop, you know, you place an ad on the website. Well, you want to stop showing the ad to people who have already purchased the product. However, people who purchased the product,- >> Savannah: It happens all the time. >> that purchasing data is not accessible to them easily. But if you could combine those insights, you know, the publishers benefit, advertisers benefits. So AWS Clean Rooms is that service that allows you very easily to be able to collaborate with a group of folks and then be able to gain these collaborative insights. >> And the consumers benefit. I mean, how many times you bought, you search it. >> It happens all the time. >> They know. And like, I just bought that guys, you know? >> Yeah, no, exactly. >> Four weeks. >> And I'm like, you don't need to serve me that, you know? And we understand the marketing backend. And it's just a waste of money and energy and resources. I mean, we're talking about sustainability as well. I don't think supply chain has ever had a hotter moment than it's had the last two and a half years. Tell me more about the announcement. >> Yup, so super excited about this. As you know, as you said, supply chains have always been very critical and very core for companies. The pandemic exacerbated it. So, ours way of sort of thinking about supply chains is to say that, you know, companies have taken, over the years many, like dozens, like millions and millions of dollars of investment in building their own supply chains. But the problem with supply chains is that the reason that they're not as functional as they could be is because of the lack of visibility. Because they're strung together very many disparate systems, that lack of visibility affects agility. And so, our approach in it was to say that, well, if we could have folks use their existing supply chain what can we do to improve the investment on the ROI of what they're getting? By creating a layer on top of it, that provides them that insights, connects all of these disparate data and then provides them insights to say, well, you know, here's where you overstock, here's where you under stock. You know, this is the, you know, the carbon emission impact of being able to transfer something. So like rather without requiring people to re-platform, what's the way that we can add value in it? And then also build upon Amazon's, you know, years of supply chain experience, to be able to build these predictive analytics for customers. >> So, that's a good, I like that you started with the why. >> Yes. >> Right now, what is it? It's an abstraction layer and then you're connecting into different data points. >> Yes, that's correct. >> Injecting ML. >> Feel like you can pick in, like if you think about supply chain, you can have warehouse management systems, order management systems. It could be in disparate things. We use ML to be able to bring all of this disparate data in and create our unified data lake. Once you have that unified data lake, you can then run an insights layer on top of it to be able to say, so that as the data changes, supply chain is not a static thing. Data's constantly changing. As the data's changing, the data lake now reflects the most up-to-date information. You can have alerts and insights set up on it to say that, what are the kinds of things that you're interested in? And then more importantly, supply chain and agility is about communication. In order to be able to make certain things happen, you need to be able to communicate, you need to make sure that everyone's on the same page. And we allow for a lot of the communication and collaboration tools to be built within this platform so that you're not necessarily leaving to go and toggle from one place to the other to solve your problems. >> And in the pie chart of how people spend their time, they're spending a lot less time communicating and being proactive. >> That's correct. >> And getting ahead of the curve. They're spending more time trying to figure out actually what's going on. >> Yes. >> And that's the problem that you're going to solve. >> Well, and it ensures that the customer at the other end of that supply chain experience is going to have their expectations managed in terms of when their good might get there or whatever's going to happen. >> Exactly. >> I feel like that expectation management has been such a big part of it. Okay, I just have to ask because I'm very curious. What was it like advising Jeff? >> Quite possibly the best job that I've ever had. You know, he's a fascinating individual. >> Did he pay you to say that? >> Nope. But I would've, like, I would've done it for like, it's remarkable seeing how he thinks and his approach to problem solving. It is, you know, you could be really tactical and go very deep. You could be extremely strategic. And to be able to sort of move effortlessly between those two is a unique skill. I learned a lot. >> Yeah, absolutely. So what made you want to evolve your career at Amazon after that? 'Cause I see on your LinkedIn, you say, it was the best job you ever had. With curiosity? >> Yeah, so one of the things, so the role is designed for you to be able to transition to something new. >> Savannah: Oh, cool. >> So after I finished that role, we were just getting into our foray with physical stores. And the idea between physical stores is that, you and I as consumers, we all have a lot of choices for physical stores. You know, there's a lot of options, there's a lot of formats. And so the last thing we wanted to do is come up with another me too offering. So, our approach was that what can we do to improve convenience in physical stores? That's what resulted in just walk out to Amazon Go. That's what resulted in Amazon One, which is another in a fast, convenient, contactless way to pay using the power of your palm. And now, what started in Amazon retail is now expanded to several third parties in, you know, stadiums, convention centers, airports. >> Airport, I just had, was in the Houston airport and got to do a humanless checkout. >> Dilip: Exactly. >> And actually in Honolulu a couple weeks ago as well too. Yeah, so we're going to see more and more of this. >> Yes. >> So what Amazon, I think has over a million employees. A lot of those are warehouse employees. But what advice would you give to somebody who's somewhere inside of Amazon, maybe they're on AWS, maybe they're Amazon. What advice would you give somebody inside that's maybe, you know, hey, I've been at this job for five, six years, three, four years, whatever it is. I want to do something else. And there's so much opportunity inside Amazon, right? What would you advise them? >> My single advice, which is actually transferable and I use it for myself is choose something that makes you a little uncomfortable. >> Dave: Get out of your comfort zone. >> It's like, you got to do that. It's like, it's not the easiest thing to hear, but it's also the most satisfying. Because almost every single time that I've done it for myself, it's resulted in like, you don't really know what the answer is. You don't really know exactly where you're going to end up, but the process and the journey through it, if you experience a little bit of discomfort constantly, it makes you non complacent. It makes you sort of not take the job, sort of in a stride. You have to be on it to do it. So that's the advice that I would give anyone. >> Yeah, that's good. So something that's maybe adjacent and maybe not completely foreign to you, but also something that, you know, you got to go dig a little bit and learn. >> You're planning a career change over here, Dave? >> No, I know a lot of people in Amazon are like, hey, I'm trying to figure out what I want to do next. I mean, I love it here. I live by the LPS, you know, but, and there's so much to choose from. >> It is, you know, when I joined in 2003, there were so many things that we were sort of doing today. None of those existed. It's a fascinating company. And the evolution, you could be in 20 different places and the breadth of the kinds of things that, you know, the Amazon experience provides is timeless. It's fascinating. >> And, you know, you look at a company like Amazon, and, you know, it's so amazing. You look at this ecosystem. I've been around- >> Even a show floor. >> I've been around a lot of time. And the show floor says it all. But I've seen a lot of, you know, waves. And each subsequent wave, you know, we always talk about how many companies were in the Fortune 1000 and aren't anymore. And, but the leaders, you know, survive and they thrive. And I think it's fascinating to try to better understand the culture that enables that. You know, you look at a company like Microsoft that was irrelevant and then came back. You know, even IBM was on death store for a while and they come back and so they. And so, but Amazon just feels, you know, at the moment you feel like, "Oh wow, nothing can stop this machine." 'Cause everybody's trying to disrupt Amazon and then, you know, only the paranoid survive, all that stuff. But it's not like, past is not prologue, all right? So that's why I asked these questions. And you just said that a lot of the services today that although the ideas didn't even exist, I mean, walkout. I mean, that's just amazing. >> I think one of the things that Amazon does really well culturally is that they create the single threaded leadership. They give people focus. If you have to get something done, you have to give people focus. You can't distract them with like seven different things and then say that, oh, by the way, your eighth job is to innovate. It just doesn't work that way. It's like it's hard. Like it can be- >> And where were the energy come from that? >> Exactly. And so giving people that single threaded focus is super important. >> Frank Slootman, the CEO of Snowflake, has a great quote. He wrote on his book. He said, "If you got 14 priorities, you got none." And he asks,- >> Well said. >> he challenges people. If you had to give up everything and do only one thing for the next 365 days, what would that be? It's a really hard question to answer. >> I feel like as we're around New Year's resolution times. I mean when we thinking about that, maybe we can all share our one thing. So, Dilip, you've been with the the applications team for five months. What's coming up next? >> Well, as I said, you know, it feels like it's still day one for applications. If you think about the things, the news that we introduced and the several services that we introduced, it has applicability across a variety of horizontal industries. But then we're also feeling that there's considerable vertical applications that can be built for specific things. Like, it could be in advertising, it could be in financial services, it could be in manufacturing. The opportunities are endless. I think the notion of people wanting applications higher up in the stack and a little more turnkey solutions is also, it's not new for us, but it's also new and creative too. You know, AWS has traditionally been doing. >> So again, this relates to what we were sort of talking about before. And maybe, this came from Jazzy or maybe it came from Bezos. But you hear a lot, it's okay to be misunderstood or if we were misunderstood for a long time. So when people hear up the stack, they think, when you think about apps, you know, in the last 10 years it was taking on-prem and bringing it into the cloud. Okay, you saw that with CREM, email, CRM, service management, you know, data warehouses, et cetera. Amazon is thinking about this in a different way. It's like you're looking at the world saying, okay, how can we improve whatever? Workflows, people's lives, doing something that's not been done before? And that seems to be the kind of applications that you guys are thinking about building. >> Yeah. >> And that's unique. It's not just, okay, we're going to take something on-prem put it in the cloud. Been there, done that. That S-curve is sort of flattening now. But there's a new S-curve which is completely new workflows and innovations and processes that we really haven't thought about yet. Or you're thinking about, I presume. >> Yeah. Having said that, I'd also like to sort of remind folks that when you consider the, you know, the entire spend, the portion of workloads that are running in the cloud is a teeny tiny fraction. It's like less than 5%, like 4% or something like that. So it's a very, there's still plenty of things that can sort of move to the cloud. But you're right that there is another trend of where in the stack and the types of applications that you can provide as well. >> Yeah, new innovation that haven't well thought of yet. >> So, Dilip, we have a new tradition here on theCUBE at re:Invent. Where we're looking for your 30 minute Instagram reel, your hot take, biggest key theme, either for you, your team, or just general vibe from the show. >> General vibe from the show. Well, 19 1/2 years at Amazon, this is actually my first re:Invent, believe it or not. This is my, as a AWS employee now, as re:Invent with like launching services. So that's the first. I've been to re:Invent before, but as an attendee rather than as a person who's, you know, a contributing number of the workforce. >> Working actually? >> If you will. >> Actually doing your job. >> And so I'm just amazed at the energy and the breadth. And the, you know, from the partners to the customers to the diversity of people who are coming here from everywhere. I had meetings from people in New Zealand. Like, you know, the UK, like customers are coming at us from like very many different places. And it's fascinating for me to see. It's new for me as well given, you know, some of my past experience. But this is a, it's been a blast. >> People are pumped. >> People are pumped. >> They can't believe the booth traffic. Not only that quality. >> Right. All of our guests have talked about that. >> Like, yeah, you know, we're going to throw half of these leads away, but they're saying no, I'm having like really substantive conversations with business people. This is, I think, my 10th re:Invent. And the first one was mostly developers. And I'm like, what are you talking about? And, you know, so. Now it's a lot more business people, a lot of developers too. >> Yeah. >> It's just. >> The community really makes it. Dilip, thank you so much for joining us today on theCube. >> Thank you for having me. >> You're fantastic. I could ask you a million questions. Be sure and tell Jeff that we said hi. >> Will do. >> Savannah: Next time you guys are hanging out. And thank all of you. >> You want to go into space? >> Yeah. Yes, yes, absolutely. I'm perhaps the most space obsessed on the show. And with that, we will continue our out of this world coverage shortly from fabulous Las Vegas where we are at AWS re:Invent. It is day four with Dave Vellante. I'm Savannah Peterson and you're watching theCUBE, the leader in high tech coverage. (lively music)
SUMMARY :
Dave, how you doing? Beautiful and chilly Las Vegas. And, you know, I'm not So, you have been working at Almost. but you just came over to AWS Yup, so I've been to here for that name before. that's been brewing, which is, you know, able to, you know, transfer Dilip: Siloed a little bit. that you can traverse now. is no more like likely, you know, Anything that makes And the retail store, I have to deal with where you Can you explain, you know, And if you make a mistake, you showing the ad to people that allows you very easily And the consumers benefit. that guys, you know? to serve me that, you know? is to say that, you know, I like that you started and then you're connecting like if you think about supply chain, And in the pie chart of And getting ahead of the curve. And that's the problem Well, and it ensures that I feel like that expectation management Quite possibly the best It is, you know, you So what made you want for you to be able to And so the last thing we wanted to do and got to do a humanless checkout. And actually in Honolulu a But what advice would you give to somebody that makes you a little uncomfortable. It's like, you got to do that. but also something that, you know, I live by the LPS, you know, but, And the evolution, you could And, you know, you look And, but the leaders, you If you have to get something done, And so giving people that He said, "If you got 14 If you had to give up the the applications team you know, it feels like that you guys are thinking about building. put it in the cloud. that you can provide as well. Yeah, new innovation that So, Dilip, we have a new tradition here you know, a contributing And the, you know, from the They can't believe the booth traffic. All of our guests And I'm like, what are you talking about? Dilip, thank you so much for I could ask you a million questions. you guys are hanging out. I'm perhaps the most space
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Day 4 Keynote Analysis | AWS re:Invent 2022
(upbeat music) >> Good morning everybody. Welcome back to Las Vegas. This is day four of theCUBE's wall-to-wall coverage of our Super Bowl, aka AWS re:Invent 2022. I'm here with my co-host, Paul Gillin. My name is Dave Vellante. Sanjay Poonen is in the house, CEO and president of Cohesity. He's sitting in as our guest market watcher, market analyst, you know, deep expertise, new to the job at Cohesity. He was kind enough to sit in, and help us break down what's happening at re:Invent. But Paul, first thing, this morning we heard from Werner Vogels. He was basically given a masterclass on system design. It reminded me of mainframes years ago. When we used to, you know, bury through those IBM blue books and red books. You remember those Sanjay? That's how we- learned back then. >> Oh God, I remember those, Yeah. >> But it made me think, wow, now you know IBM's more of a systems design, nobody talks about IBM anymore. Everybody talks about Amazon. So you wonder, 20 years from now, you know what it's going to be. But >> Well- >> Werner's amazing. >> He pulled out a 24 year old document. >> Yup. >> That he had written early in Amazon's evolution about synchronous design or about essentially distributed architectures that turned out to be prophetic. >> His big thing was nature is asynchronous. So systems are asynchronous. Synchronous is an illusion. It's an abstraction. It's kind of interesting. But, you know- >> Yeah, I mean I've had synonyms for things. Timeless architecture. Werner's an absolute legend. I mean, when you think about folks who've had, you know, impact on technology, you think of people like Jony Ive in design. >> Dave: Yeah. >> You got to think about people like Werner in architecture and just the fact that Andy and the team have been able to keep him engaged that long... I pay attention to his keynote. Peter DeSantis has obviously been very, very influential. And then of course, you know, Adam did a good job, you know, watching from, you know, having watched since I was at the first AWS re:Invent conference, at time was President SAP and there was only a thousand people at this event, okay? Andy had me on stage. I think I was one of the first guest of any tech company in 2011. And to see now this become like, it's a mecca. It's a mother of all IT events, and watch sort of even the transition from Andy to Adam is very special. I got to catch some of Ruba's keynote. So while there's some new people in the mix here, this has become a force of nature. And the last time I was here was 2019, before Covid, watched the last two ones online. But it feels like, I don't know 'about what you guys think, it feels like it's back to 2019 levels. >> I was here in 2019. I feel like this was bigger than 2019 but some people have said that it's about the same. >> I think it was 60,000 versus 50,000. >> Yes. So close. >> It was a little bigger in 2019. But it feels like it's more active. >> And then last year, Sanjay, you weren't here but it was 25,000, which was amazing 'cause it was right in that little space between Omicron, before Omicron hit. But you know, let me ask you a question and this is really more of a question about Amazon's maturity and I know you've been following them since early days. But the way I get the question, number one question I get from people is how is Amazon AWS going to be different under Adam than it was under Andy? What do you think? >> I mean, Adam's not new because he was here before. In some senses he knows the Amazon culture from prior, when he was running sales and marketing prior. But then he took the time off and came back. I mean, this will always be, I think, somewhat Andy's baby, right? Because he was the... I, you know, sent him a text, "You should be really proud of what you accomplished", but you know, I think he also, I asked him when I saw him a few weeks ago "Are you going to come to re:Invent?" And he says, "No, I want to leave this to be Adam's show." And Adam's going to have a slightly different view. His keynotes are probably half the time. It's a little bit more vision. There was a lot more customer stories at the beginning of it. Taking you back to the inspirational pieces of it. I think you're going to see them probably pulling up the stack and not just focused in infrastructure. Many of their platform services are evolved. Many of their, even application services. I'm surprised when I talk to customers. Like Amazon Connect, their sort of call center type technologies, an app layer. It's getting a lot. I mean, I've talked to a couple of Fortune 500 companies that are moving off Ayer to Connect. I mean, it's happening and I did not know that. So it's, you know, I think as they move up the stack, the platform's gotten more... The data centric stack has gotten, and you know, in the area we're working with Cohesity, security, data protection, they're an investor in our company. So this is an important, you know, both... I think tech player and a partner for many companies like us. >> I wonder the, you know, the marketplace... there's been a big push on the marketplace by all the cloud companies last couple of years. Do you see that disrupting the way softwares, enterprise software is sold? >> Oh, for sure. I mean, you have to be a ostrich with your head in the sand to not see this wave happening. I mean, what's it? $150 billion worth of revenue. Even though the growth rates dipped a little bit the last quarter or so, it's still aggregatively between Amazon and Azure and Google, you know, 30% growth. And I think we're still in the second or third inning off a grand 1 trillion or 2 trillion of IT, shifting not all of it to the cloud, but significantly faster. So if you add up all of the big things of the on-premise world, they're, you know, they got to a certain size, their growth is stable, but stalling. These guys are growing significantly faster. And then if you add on top of them, platform companies the data companies, Snowflake, MongoDB, Databricks, you know, Datadog, and then apps companies on top of that. I think the move to the Cloud is inevitable. In SaaS companies, I don't know why you would ever implement a CRM solution on-prem. It's all gone to the Cloud. >> Oh, it is. >> That happened 15 years ago. I mean, begin within three, five years of the advent of Salesforce. And the same thing in HR. Why would you deploy a HR solution now? You've got Workday, you've got, you know, others that are so some of those apps markets are are just never coming back to an on-prem capability. >> Sanjay, I want to ask you, you built a reputation for being able to, you know, forecast accurately, hit your plan, you know, you hit your numbers, you're awesome operator. Even though you have a, you know, technology degree, which you know, that's a two-tool star, multi-tool star. But I call it the slingshot economy. This is like, I mean I've seen probably more downturns than anybody in here, you know, given... Well maybe, maybe- >> Maybe me. >> You and I both. I've never seen anything like this, where where visibility is so unpredictable. The economy is sling-shotting. It's like, oh, hurry up, go Covid, go, go go build, build, build supply, then pull back. And now going forward, now pulling back. Slootman said, you know, on the call, "Hey the guide, is the guide." He said, "we put it out there, We do our best to hit it." But you had CrowdStrike had issues you know, mid-market, ServiceNow. I saw McDermott on the other day on the, on the TV. I just want to pay, you know, buy from the guy. He's so (indistinct) >> But mixed, mixed results, Salesforce, you know, Octa now pre-announcing, hey, they're going to be, or announcing, you know, better visibility, forward guide. Elastic kind of got hit really hard. HPE and Dell actually doing really well in the enterprise. >> Yep. >> 'Course Dell getting killed in the client. But so what are you seeing out there? How, as an executive, do you deal with such poor visibility? >> I think, listen, what the last two or three years have taught us is, you know, with the supply chain crisis, with the surge that people thought you may need of, you know, spending potentially in the pandemic, you have to start off with your tech platform being 10 x better than everybody else. And differentiate, differentiate. 'Cause in a crowded market, but even in a market that's getting tougher, if you're not differentiating constantly through technology innovation, you're going to get left behind. So you named a few places, they're all technology innovators, but even if some of them are having challenges, and then I think you're constantly asking yourselves, how do you move from being a point product to a platform with more and more services where you're getting, you know, many of them moving really fast. In the case of Roe, I like him a lot. He's probably one of the most savvy operators, also that I respect. He calls these speedboats, and you know, his core platform started off with the firewall network security. But he's built now a very credible cloud security, cloud AI security business. And I think that's how you need to be thinking as a tech executive. I mean, if you got core, your core beachhead 10 x better than everybody else. And as you move to adjacencies in these new platforms, have you got now speedboats that are getting to a point where they are competitive advantage? Then as you think of the go-to-market perspective, it really depends on where you are as a company. For a company like our size, we need partners a lot more. Because if we're going to, you know, stand on the shoulders of giants like Isaac Newton said, "I see clearly because I stand on the shoulders giants." I need to really go and cultivate Amazon so they become our lead partner in cloud. And then appropriately Microsoft and Google where I need to. And security. Part of what we announced last week was, last month, yeah, last couple of weeks ago, was the data security alliance with the biggest security players. What was I trying to do with that? First time ever done in my industry was get Palo Alto, CrowdStrike, Wallace, Tenable, CyberArk, Splunk, all to build an alliance with me so I could stand on their shoulders with them helping me. If you're a bigger company, you're constantly asking yourself "how do you make sure you're getting your, like Amazon, their top hundred customers spending more with that?" So I think the the playbook evolves, and I'm watching some of these best companies through this time navigate through this. And I think leadership is going to be tested in enormously interesting ways. >> I'll say. I mean, Snowflake is really interesting because they... 67% growth, which is, I mean, that's best in class for a company that's $2 billion. And, but their guide was still, you know, pretty aggressive. You know, so it's like, do you, you know, when it when it's good times you go, "hey, we can we can guide conservatively and know we can beat it." But when you're not certain, you can't dial down too far 'cause your investors start to bail on you. It's a really tricky- >> But Dave, I think listen, at the end of the day, I mean every CEO should not be worried about the short term up and down in the stock price. You're building a long-term multi-billion dollar company. In the case of Frank, he has, I think I shot to a $10 billion, you know, analytics data warehousing data management company on the back of that platform, because he's eyeing the market that, not just Teradata occupies today, but now Oracle occupies or other databases, right? So his tam as it grows bigger, you're going to have some of these things, but that market's big. I think same with Palo Alto. I mean Datadog's another company, 75% growth. >> Yeah. >> At 20% margins, like almost rule of 95. >> Amazing. >> When they're going after, not just the observability market, they're eating up the sim market, security analytics, the APM market. So I think, you know, that's, you look at these case studies of companies who are going from point product to platforms and are steadily able to grow into new tams. You know, to me that's very inspiring. >> I get it. >> Sanjay: That's what I seek to do at our com. >> I get that it's a marathon, but you know, when you're at VMware, weren't you looking at the stock price every day just out of curiosity? I mean listen, you weren't micromanaging it. >> You do, but at the end of the day, and you certainly look at the days of earnings and so on so forth. >> Yeah. >> Because you want to create shareholder value. >> Yeah. >> I'm not saying that you should not but I think in obsession with that, you know, in a short term, >> Going to kill ya. >> Makes you, you know, sort of myopically focused on what may not be the right thing in the long term. Now in the long arc of time, if you're not creating shareholder value... Look at what happened to Steve Bomber. You needed Satya to come in to change things and he's created a lot of value. >> Dave: Yeah, big time. >> But I think in the short term, my comments were really on the quarter to quarter, but over a four a 12 quarter, if companies are growing and creating profitable growth, they're going to get the valuation they deserve. >> Dave: Yeah. >> Do you the... I want to ask you about something Arvind Krishna said in the previous IBM earnings call, that IT is deflationary and therefore it is resistant to the macroeconomic headwinds. So IT spending should actually thrive in a deflation, in a adverse economic climate. Do you think that's true? >> Not all forms of IT. I pay very close attention to surveys from, whether it's the industry analysts or the Morgan Stanleys, or Goldman Sachs. The financial analysts. And I think there's a gluc in certain sectors that will get pulled back. Traditional view is when the economies are growing people spend on the top line, front office stuff, sales, marketing. If you go and look at just the cloud 100 companies, which are the hottest private companies, and maybe with the public market companies, there's way too many companies focused on sales and marketing. Way too many. I think during a downsizing and recession, that's going to probably shrink some, because they were all built for the 2009 to 2021 era, where it was all about the top line. Okay, maybe there's now a proposition for companies who are focused on cost optimization, supply chain visibility. Security's been intangible, that I think is going to continue to an investment. So I tell, listen, if you are a tech investor or if you're an operator, pay attention to CIO priorities. And right now, in our business at Cohesity, part of the reason we've embraced things like ransomware protection, there is a big focus on security. And you know, by intelligently being a management and a security company around data, I do believe we'll continue to be extremely relevant to CIO budgets. There's a ransomware, 20 ransomware attempts every second. So things of that kind make you relevant in a bank. You have to stay relevant to a buying pattern or else you lose momentum. >> But I think what's happening now is actually IT spending's pretty good. I mean, I track this stuff pretty closely. It's just that expectations were so high and now you're seeing earnings estimates come down and so, okay, and then you, yeah, you've got the, you know the inflationary factors and your discounted cash flows but the market's actually pretty good. >> Yeah. >> You know, relative to other downturns that if this is not a... We're not actually not in a downturn. >> Yeah. >> Not yet anyway. It may be. >> There's a valuation there. >> You have to prepare. >> Not sales. >> Yeah, that's right. >> When I was on CNBC, I said "listen, it's a little bit like that story of Joseph. Seven years of feast, seven years of famine." You have to prepare for potentially your worst. And if it's not the worst, you're in good shape. So will it be a recession 2023? Maybe. You know, high interest rates, inflation, war in Russia, Ukraine, maybe things do get bad. But if you belt tightening, if you're focused in operational excellence, if it's not a recession, you're pleasantly surprised. If it is one, you're prepared for it. >> All right. I'm going to put you in the spot and ask you for predictions. Expert analysis on the World Cup. What do you think? Give us the breakdown. (group laughs) >> As my... I wish India was in the World Cup, but you can't get enough Indians at all to play soccer well enough, but we're not, >> You play cricket, though. >> I'm a US man first. I would love to see one of Brazil, or Argentina. And as a Messi person, I don't know if you'll get that, but it would be really special for Messi to lead, to end his career like Maradonna winning a World Cup. I don't know if that'll happen. I'm probably going to go one of the Latin American countries, if the US doesn't make it far enough. But first loyalty to the US team, and then after one of the Latin American countries. >> And you think one of the Latin American countries is best bet to win or? >> I don't know. It's hard to tell. They're all... What happens now at this stage >> So close, right? >> is anybody could win. >> Yeah. You just have lots of shots of gold. I'm a big soccer fan. It could, I mean, I don't know if the US is favored to win, but if they get far enough, you get to the finals, anybody could win. >> I think they get Netherlands next, right? >> That's tough. >> Really tough. >> But... The European teams are good too, but I would like to see US go far enough, and then I'd like to see Latin America with team one of Argentina, or Brazil. That's my prediction. >> I know you're a big Cricket fan. Are you able to follow Cricket the way you like? >> At god unearthly times the night because they're in Australia, right? >> Oh yeah. >> Yeah. >> I watched the T-20 World Cup, select games of it. Yeah, you know, I'm not rapidly following every single game but the World Cup games, I catch you. >> Yeah, it's good. >> It's good. I mean, I love every sport. American football, soccer. >> That's great. >> You get into basketball now, I mean, I hope the Warriors come back strong. Hey, how about the Warriors Celtics? What do we think? We do it again? >> Well- >> This year. >> I'll tell you what- >> As a Boston Celtics- >> I would love that. I actually still, I have to pay off some folks from Palo Alto office with some bets still. We are seeing unprecedented NBA performance this year. >> Yeah. >> It's amazing. You look at the stats, it's like nothing. I know it's early. Like nothing we've ever seen before. So it's exciting. >> Well, always a pleasure talking to you guys. >> Great to have you on. >> Thanks for having me. >> Thank you. Love the expert analysis. >> Sanjay Poonen. Dave Vellante. Keep it right there. re:Invent 2022, day four. We're winding up in Las Vegas. We'll be right back. You're watching theCUBE, the leader in enterprise and emerging tech coverage. (lighthearted soft music)
SUMMARY :
When we used to, you know, Yeah. So you wonder, 20 years from now, out to be prophetic. But, you know- I mean, when you think you know, watching from, I feel like this was bigger than 2019 I think it was 60,000 But it feels like it's more active. But you know, let me ask you a question So this is an important, you know, both... I wonder the, you I mean, you have to be a ostrich you know, others that are so But I call it the slingshot economy. I just want to pay, you or announcing, you know, better But so what are you seeing out there? I mean, if you got core, you know, pretty aggressive. I think I shot to a $10 billion, you know, like almost rule of 95. So I think, you know, that's, I seek to do at our com. I mean listen, you and you certainly look Because you want to Now in the long arc of time, on the quarter to quarter, I want to ask you about And you know, by intelligently But I think what's happening now relative to other downturns It may be. But if you belt tightening, to put you in the spot but you can't get enough Indians at all But first loyalty to the US team, It's hard to tell. if the US is favored to win, and then I'd like to see Latin America the way you like? Yeah, you know, I'm not rapidly I mean, I love every sport. I mean, I hope the to pay off some folks You look at the stats, it's like nothing. talking to you guys. Love the expert analysis. in enterprise and emerging tech coverage.
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Breaking Analysis: Snowflake caught in the storm clouds
>> From the CUBE Studios in Palo Alto in Boston, bringing you data driven insights from the Cube and ETR. This is Breaking Analysis with Dave Vellante. >> A better than expected earnings report in late August got people excited about Snowflake again, but the negative sentiment in the market is weighed heavily on virtually all growth tech stocks and Snowflake is no exception. As we've stressed many times the company's management is on a long term mission to dramatically simplify the way organizations use data. Snowflake is tapping into a multi hundred billion dollar total available market and continues to grow at a rapid pace. In our view, Snowflake is embarking on its third major wave of innovation data apps, while its first and second waves are still bearing significant fruit. Now for short term traders focused on the next 90 or 180 days, that probably doesn't matter. But those taking a longer view are asking, "Should we still be optimistic about the future of this high flyer or is it just another over hyped tech play?" Hello and welcome to this week's Wiki Bond Cube Insights powered by ETR. Snowflake's Quarter just ended. And in this breaking analysis we take a look at the most recent survey data from ETR to see what clues and nuggets we can extract to predict the near term future in the long term outlook for Snowflake which is going to announce its earnings at the end of this month. Okay, so you know the story. If you've been investor in Snowflake this year, it's been painful. We said at IPO, "If you really want to own this stock on day one, just hold your nose and buy it." But like most IPOs we said there will be likely a better entry point in the future, and not surprisingly that's been the case. Snowflake IPOed a price of 120, which you couldn't touch on day one unless you got into a friends and family Delio. And if you did, you're still up 5% or so. So congratulations. But at one point last year you were up well over 200%. That's been the nature of this volatile stock, and I certainly can't help you with the timing of the market. But longer term Snowflake is targeting 10 billion in revenue for fiscal year 2028. A big number. Is it achievable? Is it big enough? Tell you what, let's come back to that. Now shorter term, our expert trader and breaking analysis contributor Chip Simonton said he got out of the stock a while ago after having taken a shot at what turned out to be a bear market rally. He pointed out that the stock had been bouncing around the 150 level for the last few months and broke that to the downside last Friday. So he'd expect 150 is where the stock is going to find resistance on the way back up, but there's no sign of support right now. He said maybe at 120, which was the July low and of course the IPO price that we just talked about. Now, perhaps earnings will be a catalyst, when Snowflake announces on November 30th, but until the mentality toward growth tech changes, nothing's likely to change dramatically according to Simonton. So now that we have that out of the way, let's take a look at the spending data for Snowflake in the ETR survey. Here's a chart that shows the time series breakdown of snowflake's net score going back to the October, 2021 survey. Now at that time, Snowflake's net score stood at a robust 77%. And remember, net score is a measure of spending velocity. It's a proprietary network, and ETR derives it from a quarterly survey of IT buyers and asks the respondents, "Are you adopting the platform new? Are you spending 6% or more? Is you're spending flat? Is you're spending down 6% or worse? Or are you leaving the platform decommissioning?" You subtract the percent of customers that are spending less or churning from those that are spending more and adopting or adopting and you get a net score. And that's expressed as a percentage of customers responding. In this chart we show Snowflake's in out of the total survey which ranges... The total survey ranges between 1,200 and 1,400 each quarter. And the very last column... Oh sorry, very last row, we show the number of Snowflake respondents that are coming in the survey from the Fortune 500 and the Global 2000. Those are two very important Snowflake constituencies. Now what this data tells us is that Snowflake exited 2021 with very strong momentum in a net score of 82%, which is off the charts and it was actually accelerating from the previous survey. Now by April that sentiment had flipped and Snowflake came down to earth with a 68% net score. Still highly elevated relative to its peers, but meaningfully down. Why was that? Because we saw a drop in new ads and an increase in flat spend. Then into the July and most recent October surveys, you saw a significant drop in the percentage of customers that were spending more. Now, notably, the percentage of customers who are contemplating adding the platform is actually staying pretty strong, but it is off a bit this past survey. And combined with a slight uptick in planned churn, net score is now down to 60%. That uptick from 0% and 1% and then 3%, it's still small, but that net score at 60% is still 20 percentage points higher than our highly elevated benchmark of 40% as you recall from listening to earlier breaking analysis. That 40% range is we consider a milestone. Anything above that is actually quite strong. But again, Snowflake is down and coming back to churn, while 3% churn is very low, in previous quarters we've seen Snowflake 0% or 1% decommissions. Now the last thing to note in this chart is the meaningful uptick in survey respondents that are citing, they're using the Snowflake platform. That's up to 212 in the survey. So look, it's hard to imagine that Snowflake doesn't feel the softening in the market like everyone else. Snowflake is guiding for around 60% growth in product revenue against the tough compare from a year ago with a 2% operating margin. So like every company, the reaction of the street is going to come down to how accurate or conservative the guide is from their CFO. Now, earlier this year, Snowflake acquired a company called Streamlit for around $800 million. Streamlit is an open source Python library and it makes it easier to build data apps with machine learning, obviously a huge trend. And like Snowflake, generally its focus is on simplifying the complex, in this case making data science easier to integrate into data apps that business people can use. So we were excited this summer in the July ETR survey to see that they added some nice data and pick on Streamlit, which we're showing here in comparison to Snowflake's core business on the left hand side. That's the data warehousing, the Streamlit pieces on the right hand side. And we show again net score over time from the previous survey for Snowflake's core database and data warehouse offering again on the left as compared to a Streamlit on the right. Snowflake's core product had 194 responses in the October, 22 survey, Streamlit had an end of 73, which is up from 52 in the July survey. So significant uptick of people responding that they're doing business in adopting Streamlit. That was pretty impressive to us. And it's hard to see, but the net scores stayed pretty constant for Streamlit at 51%. It was 52% I think in the previous quarter, well over that magic 40% mark. But when you blend it with Snowflake, it does sort of bring things down a little bit. Now there are two key points here. One is that the acquisition seems to have gained exposure right out of the gate as evidenced by the large number of responses. And two, the spending momentum. Again while it's lower than Snowflake overall, and when you blend it with Snowflake it does pull it down, it's very healthy and steady. Now let's do a little pure comparison with some of our favorite names in this space. This chart shows net score or spending velocity in the Y-axis, an overlap or presence, pervasiveness if you will, in the data set on the X-axis. That red dotted line again is that 40% highly elevated net score that we like to talk about. And that table inserted informs us as to how the companies are plotted, where the dots set up, the net score, the ins. And we're comparing a number of database players, although just a caution, Oracle includes all of Oracle including its apps. But we just put it in there for reference because it is the leader in database. Right off the bat, Snowflake jumps out with a net score of 64%. The 60% from the earlier chart, again included Streamlit. So you can see its core database, data warehouse business actually is higher than the total company average that we showed you before 'cause the Streamlit is blended in. So when you separate it out, Streamlit is right on top of data bricks. Isn't that ironic? Only Snowflake and Databricks in this selection of names are above the 40% level. You see Mongo and Couchbase, they know they're solid and Teradata cloud actually showing pretty well compared to some of the earlier survey results. Now let's isolate on the database data platform sector and see how that shapes up. And for this analysis, same XY dimensions, we've added the big giants, AWS and Microsoft and Google. And notice that those three plus Snowflake are just at or above the 40% line. Snowflake continues to lead by a significant margin in spending momentum and it keeps creeping to the right. That's that end that we talked about earlier. Now here's an interesting tidbit. Snowflake is often asked, and I've asked them myself many times, "How are you faring relative to AWS, Microsoft and Google, these big whales with Redshift and Synapse and Big Query?" And Snowflake has been telling folks that 80% of its business comes from AWS. And when Microsoft heard that, they said, "Whoa, wait a minute, Snowflake, let's partner up." 'Cause Microsoft is smart, and they understand that the market is enormous. And if they could do better with Snowflake, one, they may steal some business from AWS. And two, even if Snowflake is winning against some of the Microsoft database products, if it wins on Azure, Microsoft is going to sell more compute and more storage, more AI tools, more other stuff to these customers. Now AWS is really aggressive from a partnering standpoint with Snowflake. They're openly negotiating, not openly, but they're negotiating better prices. They're realizing that when it comes to data, the cheaper that you make the offering, the more people are going to consume. At scale economies and operating leverage are really powerful things at volume that kick in. Now Microsoft, they're coming along, they obviously get it, but Google is seemingly resistant to that type of go to market partnership. Rather than lean into Snowflake as a great partner Google's field force is kind of fighting fashion. Google itself at Cloud next heavily messaged what they call the open data cloud, which is a direct rip off of Snowflake. So what can we say about Google? They continue to be kind of behind the curve when it comes to go to market. Now just a brief aside on the competitive posture. I've seen Slootman, Frank Slootman, CEO of Snowflake in action with his prior companies and how he depositioned the competition. At Data Domain, he eviscerated a company called Avamar with their, what he called their expensive and slow post process architecture. I think he actually called it garbage, if I recall at one conference I heard him speak at. And that sort of destroyed BMC when he was at ServiceNow, kind of positioning them as the equivalent of the department of motor vehicles. And so it's interesting to hear how Snowflake openly talks about the data platforms of AWS, Microsoft, Google, and data bricks. I'll give you this sort of short bumper sticker. Redshift is just an on-prem database that AWS morphed to the cloud, which by the way is kind of true. They actually did a brilliant job of it, but it's basically a fact. Microsoft Excel, a collection of legacy databases, which also kind of morphed to run in the cloud. And even Big Query, which is considered cloud native by many if not most, is being positioned by Snowflake as originally an on-prem database to support Google's ad business, maybe. And data bricks is for those people smart enough to get it to Berkeley that love complexity. And now Snowflake doesn't, they don't mention Berkeley as far as I know. That's my addition. But you get the point. And the interesting thing about Databricks and Snowflake is a while ago in the cube I said that there was a new workload type emerging around data where you have AWS cloud, Snowflake obviously for the cloud database and Databricks data for the data science and EML, you bring those things together and there's this new workload emerging that's going to be very powerful in the future. And it's interesting to see now the aspirations of all three of these platforms are colliding. That's quite a dynamic, especially when you see both Snowflake and Databricks putting venture money and getting their hooks into the loyalties of the same companies like DBT labs and Calibra. Anyway, Snowflake's posture is that we are the pioneer in cloud native data warehouse, data sharing and now data apps. And our platform is designed for business people that want simplicity. The other guys, yes, they're formidable, but we Snowflake have an architectural lead and of course we run in multiple clouds. So it's pretty strong positioning or depositioning, you have to admit. Now I'm not sure I agree with the big query knockoffs completely. I think that's a bit of a stretch, but snowflake, as we see in the ETR survey data is winning. So in thinking about the longer term future, let's talk about what's different with Snowflake, where it's headed and what the opportunities are for the company. Snowflake put itself on the map by focusing on simplifying data analytics. What's interesting about that is the company's founders are as you probably know from Oracle. And rather than focusing on transactional data, which is Oracle's sweet spot, the stuff they worked on when they were at Oracle, the founder said, "We're going to go somewhere else. We're going to attack the data warehousing problem and the data analytics problem." And they completely re-imagined the database and how it could be applied to solve those challenges and reimagine what was possible if you had virtually unlimited compute and storage capacity. And of course Snowflake became famous for separating the compute from storage and being able to completely shut down compute so you didn't have to pay for it when you're not using it. And the ability to have multiple clusters hit the same data without making endless copies and a consumption/cloud pricing model. And then of course everyone on the planet realized, "Wow, that's a pretty good idea." Every venture capitalist in Silicon Valley has been funding companies to copy that move. And that today has pretty much become mainstream in table stakes. But I would argue that Snowflake not only had the lead, but when you look at how others are approaching this problem, it's not necessarily as clean and as elegant. Some of the startups, the early startups I think get it and maybe had an advantage of starting later, which can be a disadvantage too. But AWS is a good example of what I'm saying here. Is its version of separating compute from storage was an afterthought and it's good, it's... Given what they had it was actually quite clever and customers like it, but it's more of a, "Okay, we're going to tier to storage to lower cost, we're going to sort of dial down the compute not completely, we're not going to shut it off, we're going to minimize the compute required." It's really not true as separation is like for instance Snowflake has. But having said that, we're talking about competitors with lots of resources and cohort offerings. And so I don't want to make this necessarily all about the product, but all things being equal architecture matters, okay? So that's the cloud S-curve, the first one we're showing. Snowflake's still on that S-curve, and in and of itself it's got legs, but it's not what's going to power the company to 10 billion. The next S-curve we denote is the multi-cloud in the middle. And now while 80% of Snowflake's revenue is AWS, Microsoft is ramping up and Google, well, we'll see. But the interesting part of that curve is data sharing, and this idea of data clean rooms. I mean it really should be called the data sharing curve, but I have my reasons for calling it multi-cloud. And this is all about network effects and data gravity, and you're seeing this play out today, especially in industries like financial services and healthcare and government that are highly regulated verticals where folks are super paranoid about compliance. There not going to share data if they're going to get sued for it, if they're going to be in the front page of the Wall Street Journal for some kind of privacy breach. And what Snowflake has done is said, "Put all the data in our cloud." Now, of course now that triggers a lot of people because it's a walled garden, okay? It is. That's the trade off. It's not the Wild West, it's not Windows, it's Mac, it's more controlled. But the idea is that as different parts of the organization or even partners begin to share data that they need, it's got to be governed, it's got to be secure, it's got to be compliant, it's got to be trusted. So Snowflake introduced the idea of, they call these things stable edges. I think that's the term that they use. And they track a metric around stable edges. And so a stable edge, or think of it as a persistent edge is an ongoing relationship between two parties that last for some period of time, more than a month. It's not just a one shot deal, one a done type of, "Oh guys shared it for a day, done." It sent you an FTP, it's done. No, it's got to have trajectory over time. Four weeks or six weeks or some period of time that's meaningful. And that metric is growing. Now I think sort of a different metric that they track. I think around 20% of Snowflake customers are actively sharing data today and then they track the number of those edge relationships that exist. So that's something that's unique. Because again, most data sharing is all about making copies of data. That's great for storage companies, it's bad for auditors, and it's bad for compliance officers. And that trend is just starting out, that middle S-curve, it's going to kind of hit the base of that steep part of the S-curve and it's going to have legs through this decade we think. And then finally the third wave that we show here is what we call super cloud. That's why I called it multi-cloud before, so it could invoke super cloud. The idea that you've built a PAS layer that is purpose built for a specific objective, and in this case it's building data apps that are cloud native, shareable and governed. And is a long-term trend that's going to take some time to develop. I mean, application development platforms can take five to 10 years to mature and gain significant adoption, but this one's unique. This is a critical play for Snowflake. If it's going to compete with the big cloud players, it has to have an app development framework like Snowpark. It has to accommodate new data types like transactional data. That's why it announced this thing called UniStore last June, Snowflake a summit. And the pattern that's forming here is Snowflake is building layer upon layer with its architecture at the core. It's not currently anyway, it's not going out and saying, "All right, we're going to buy a company that's got to another billion dollars in revenue and that's how we're going to get to 10 billion." So it's not buying its way into new markets through revenue. It's actually buying smaller companies that can complement Snowflake and that it can turn into revenue for growth that fit in to the data cloud. Now as to the 10 billion by fiscal year 28, is that achievable? That's the question. Yeah, I think so. Would the momentum resources go to market product and management prowess that Snowflake has? Yes, it's definitely achievable. And one could argue to $10 billion is too conservative. Indeed, Snowflake CFO, Mike Scarpelli will fully admit his forecaster built on existing offerings. He's not including revenue as I understand it from all the new stuff that's in the pipeline because he doesn't know what it's going to look like. He doesn't know what the adoption is going to look like. He doesn't have data on that adoption, not just yet anyway. And now of course things can change quite dramatically. It's possible that is forecast for existing businesses don't materialize or competition picks them off or a company like Databricks actually is able in the longer term replicate the functionality of Snowflake with open source technologies, which would be a very competitive source of innovation. But in our view, there's plenty of room for growth, the market is enormous and the real key is, can and will Snowflake deliver on the promises of simplifying data? Of course we've heard this before from data warehouse, the data mars and data legs and master data management and ETLs and data movers and data copiers and Hadoop and a raft of technologies that have not lived up to expectations. And we've also, by the way, seen some tremendous successes in the software business with the likes of ServiceNow and Salesforce. So will Snowflake be the next great software name and hit that 10 billion magic mark? I think so. Let's reconnect in 2028 and see. Okay, we'll leave it there today. I want to thank Chip Simonton for his input to today's episode. Thanks to Alex Myerson who's on production and manages the podcast. Ken Schiffman as well. Kristin Martin and Cheryl Knight help get the word out on social media and in our newsletters. And Rob Hove is our Editor in Chief over at Silicon Angle. He does some great editing for us. Check it out for all the news. Remember all these episodes are available as podcasts. Wherever you listen, just search Breaking Analysis podcast. I publish each week on wikibon.com and siliconangle.com. Or you can email me to get in touch David.vallante@siliconangle.com. DM me @dvellante or comment on our LinkedIn post. And please do check out etr.ai, they've got the best survey data in the enterprise tech business. This is Dave Vellante for the CUBE Insights, powered by ETR. Thanks for watching, thanks for listening and we'll see you next time on breaking analysis. (upbeat music)
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David Flynn Supercloud Audio
>> From every ISV to solve the problems. You want there to be tools in place that you can use, either open source tools or whatever it is that help you build it. And slowly over time, that building will become easier and easier. So my question to you was, where do you see you playing? Do you see yourself playing to ISVs as a set of tools, which will make their life a lot easier and provide that work? >> Absolutely. >> If they don't have, so they don't have to do it. Or you're providing this for the end users? Or both? >> So it's a progression. If you go to the ISVs first, you're doomed to starved before you have time for that other option. >> Yeah. >> Right? So it's a question of phase, the phasing of it. And also if you go directly to end users, you can demonstrate the power of it and get the attention of the ISVs. I believe that the ISVs, especially those with the biggest footprints and the most, you know, coveted estates, they have already made massive investments at trying to solve decentralization of their software stack. And I believe that they have used it as a hook to try to move to a software as a service model and rope people into leasing their infrastructure. So if you look at the clouds that have been propped up by Autodesk or by Adobe, or you name the company, they are building proprietary makeshift solutions for decentralizing or hybrid clouding. Or maybe they're not even doing that at all and all they're is saying hey, if you want to get location agnosticness, then what you should just, is just move into our cloud. >> Right. >> And then they try to solve on the background how to decentralize it between different regions so they can have decent offerings in each region. But those who are more advanced have already made larger investments and will be more averse to, you know, throwing that stuff away, all of their makeshift machinery away, and using a platform that gives them high performance parallel, low level file system access, while at the same time having metadata-driven, you know, policy-based, intent-based orchestration to manage the diffusion of data across a decentralized infrastructure. They are not going to be as open because they've made such an investment and they're going to look at how do they monetize it. So what we have found with like the movie studios who are using us already, many of the app they're using, many of those software offerings, the ISVs have their own cloud that offers that software for the cloud. But what we got when I asked about this, 'cause I was dealt specifically into this question because I'm very interested to know how we're going to make that leap from end user upstream into the ISVs where I believe we need to, and they said, look, we cannot use these software ISV-specific SAS clouds for two reasons. Number one is we lose control of the data. We're giving it to them. That's security and other issues. And here you're talking about we're doing work for Disney, we're doing work for Netflix, and they're not going to let us put our data on those software clouds, on those SAS clouds. Secondly, in any reasonable pipeline, the data is shared by many different applications. We need to be agnostic as to the application. 'Cause the inputs to one application, you know, the output for one application provides the input to the next, and it's not necessarily from the same vendor. So they need to have a data platform that lets them, you know, go from one software stack, and you know, to run it on another. Because they might do the rendering with this and yet, they do the editing with that, and you know, et cetera, et cetera. So I think the further you go up the stack in the structured data and dedicated applications for specific functions in specific verticals, the further up the stack you go, the harder it is to justify a SAS offering where you're basically telling the end users you need to park all your data with us and then you can run your application in our cloud and get this. That ultimately is a dead end path versus having the data be open and available to many applications across this supercloud layer. >> Okay, so-- >> Is that making any sense? >> Yes, so if I could just ask a clarifying question. So, if I had to take Snowflake as an example, I think they're doing exactly what you're saying is a dead end, put everything into our proprietary system and then we'll figure out how to distribute it. >> Yeah. >> And and I think if you're familiar with Zhamak Dehghaniis' data mesh concept. Are you? >> A little bit, yeah. >> But in her model, Snowflake, a Snowflake warehouse is just a node on the mesh and that mesh is-- >> That's right. >> Ultimately the supercloud and you're an enabler of that is what I'm hearing. >> That's right. What they're doing up at the structured level and what they're talking about at the structured level we're doing at the underlying, unstructured level, which by the way has implications for how you implement those distributed database things. In other words, implementing a Snowflake on top of Hammerspace would have made building stuff like in the first place easier. It would allow you to easily shift and run the database engine anywhere. You still have to solve how to shard and distribute at the transaction layer above, so I'm not saying we're a substitute for what you need to do at the app layer. By the way, there is another example of that and that's Microsoft Office, right? It's one thing to share that, to have a file share where you can share all the docs. It's something else to have Word and PowerPoint, Excel know how to allow people to be simultaneously editing the same doc. That's always going to happen in the app layer. But not all applications need that level of, you know, in-app decentralization. You know, many of them, many workflows are pipelined, especially the ones that are very data intensive where you're doing drug discovery or you're doing rendering, or you're doing machine learning training. These things are human in the loop with large stages of processing across tens of thousands of cores. And I think that kind of data processing pipeline is what we're focusing on first. Not so much the Microsoft Office or the Snowflake, you know, parking a relational database because that takes a lot of application layer stuff and that's what they're good at. >> Right. >> But I think... >> Go ahead, sorry. >> Later entrance in these markets will find Hammerspace as a way to accelerate their work so they can focus more narrowly on just the stuff that's app-specific, higher level sharing in the app. >> Yes, Snowflake founders-- >> I think it might be worth mentioning also, just keep this confidential guys, but one of our customers is Blue Origin. And one of the things that we have found is kind of the point of what you're talking about with our customers. They're needing to build this and since it's not commercially available or they don't know where to look for it to be commercially available, they're all building themselves. So this layer is needed. And Blue is just one of the examples of quite a few we're now talking to. And like manufacturing, HPC, research where they're out trying to solve this problem with their own scripting tools and things like that. And I just, I don't know if there's anything you want to add, David, but you know, but there's definitely a demand here and customers are trying to figure out how to solve it beyond what Hammerspace is doing. Like the need is so great that they're just putting developers on trying to do it themselves. >> Well, and you know, Snowflake founders, they didn't have a Hammerspace to lean on. But, one of the things that's interesting about supercloud is we feel as though industry clouds will emerge, that as part of company's digital transformations, they will, you know, every company's a software company, they'll begin to build their own clouds and they will be able to use a Hammerspace to do that. >> A super pass layer. >> Yes. It's really, I don't know if David's speaking, I don't want to speak over him, but we can't hear you. May be going through a bad... >> Well, a regional, regional talks that make that possible. And so they're doing these render farms and editing farms, and it's a cloud-specific to the types of workflows in the median entertainment world. Or clouds specifically to workflows in the chip design world or in the drug and bio and life sciences exploration world. There are large organizations that are kind of a blend of end users, like the Broad, which has their own kind of cloud where they're asking collaborators to come in and work with them. So it starts to even blur who's an end user versus an ISV. >> Yes. >> Right? When you start talking about the massive data is the main gravity is to having lots of people participate. >> Yep, and that's where the value is. And that's where the value is. And this is a megatrend that we see. And so it's really important for us to get to the point of what is and what is not a supercloud and, you know, that's where we're trying to evolve. >> Let's talk about this for a second 'cause I want to, I want to challenge you on something and it's something that I got challenged on and it has led me to thinking differently than I did at first, which Molly can attest to. Okay? So, we have been looking for a way to talk about the concept of cloud of utility computing, run anything anywhere that isn't addressed in today's realization of cloud. 'Cause today's cloud is not run anything anywhere, it's quite the opposite. You park your data in AWS and that's where you run stuff. And you pretty much have to. Same with with Azure. They're using data gravity to keep you captive there, just like the old infrastructure guys did. But now it's even worse because it's coupled back with the software to some degree, as well. And you have to use their storage, networking, and compute. It's not, I mean it fell back to the mainframe era. Anyhow, so I love the concept of supercloud. By the way, I was going to suggest that a better term might be hyper cloud since hyper speaks to the multidimensionality of it and the ability to be in a, you know, be in a different dimension, a different plane of existence kind of thing like hyperspace. But super and hyper are somewhat synonyms. I mean, you have hyper cars and you have super cars and blah, blah, blah. I happen to like hyper maybe also because it ties into the whole Hammerspace notion of a hyper-dimensional, you know, reality, having your data centers connected by a wormhole that is Hammerspace. But regardless, what I got challenged on is calling it something different at all versus simply saying, this is what cloud has always meant to be. This is the true cloud, this is real cloud, this is cloud. And I think back to what happened, you'll remember, at Fusion IO we talked about IO memory and we did that because people had a conceptualization of what an SSD was. And an SSD back then was low capacity, low endurance, made to go military, aerospace where things needed to be rugged but was completely useless in the data center. And we needed people to imagine this thing as being able to displace entire SAND, with the kind of capacity density, performance density, endurance. And so we talked IO memory, we could have said enterprise SSD, and that's what the industry now refers to for that concept. What will people be saying five and 10 years from now? Will they simply say, well this is cloud as it was always meant to be where you are truly able to run anything anywhere and have not only the same APIs, but you're same data available with high performance access, all forms of access, block file and object everywhere. So yeah. And I wonder, and this is just me throwing it out there, I wonder if, well, there's trade offs, right? Giving it a new moniker, supercloud, versus simply talking about how cloud is always intended to be and what it was meant to be, you know, the real cloud or true cloud, there are trade-offs. By putting a name on it and branding it, that lets people talk about it and understand they're talking about something different. But it also is that an affront to people who thought that that's what they already had. >> What's different, what's new? Yes, and so we've given a lot of thought to this. >> Right, it's like you. >> And it's because we've been asked that why does the industry need a new term, and we've tried to address some of that. But some of the inside baseball that we haven't shared is, you remember the Web 2.0, back then? >> Yep. >> Web 2.0 was the same thing. And I remember Tim Burners Lee saying, "Why do we need Web 2.0? "This is what the Web was always supposed to be." But the truth is-- >> I know, that was another perfect-- >> But the truth is it wasn't, number one. Number two, everybody hated the Web 2.0 term. John Furrier was actually in the middle of it all. And then it created this groundswell. So one of the things we wrote about is that supercloud is an evocative term that catalyzes debate and conversation, which is what we like, of course. And maybe that's self-serving. But yeah, HyperCloud, Metacloud, super, meaning, it's funny because super came from Latin supra, above, it was never the superlative. But the superlative was a convenient byproduct that caused a lot of friction and flack, which again, in the media business is like a perfect storm brewing. >> The bad thing to have to, and I think you do need to shake people out of their, the complacency of the limitations that they're used to. And I'll tell you what, the fact that you even have the terms hybrid cloud, multi-cloud, private cloud, edge computing, those are all just referring to the different boundaries that isolate the silo that is the current limited cloud. >> Right. >> So if I heard correctly, what just, in terms of us defining what is and what isn't in supercloud, you would say traditional applications which have to run in a certain place, in a certain cloud can't run anywhere else, would be the stuff that you would not put in as being addressed by supercloud. And over time, you would want to be able to run the data where you want to and in any of those concepts. >> Or even modern apps, right? Or even modern apps that are siloed in SAS within an individual cloud, right? >> So yeah, I guess it's twofold. Number one, if you're going at the high application layers, there's lots of ways that you can give the appearance of anything running anywhere. The ISV, the SAS vendor can engineer stuff to have the ability to serve with low enough latency to different geographies, right? So if you go too high up the stack, it kind of loses its meaning because there's lots of different ways to make due and give the appearance of omni-presence of the service. Okay? As you come down more towards the platform layer, it gets harder and harder to mask the fact that supercloud is something entirely different than just a good regionally-distributed SAS service. So I don't think you, I don't think you can distinguish supercloud if you go too high up the stack because it's just SAS, it's just a good SAS service where the SAS vendor has done the hard work to give you low latency access from different geographic regions. >> Yeah, so this is one of the hardest things, David. >> Common among them. >> Yeah, this is really an important point. This is one of the things I've had the most trouble with is why is this not just SAS? >> So you dilute your message when you go up to the SAS layer. If you were to focus most of this around the super pass layer, the how can you host applications and run them anywhere and not host this, not run a service, not have a service available everywhere. So how can you take any application, even applications that are written, you know, in a traditional legacy data center fashion and be able to run them anywhere and have them have their binaries and their datasets and the runtime environment and the infrastructure to start them and stop them? You know, the jobs, the, what the Kubernetes, the job scheduler? What we're really talking about here, what I think we're really talking about here is building the operating system for a decentralized cloud. What is the operating system, the operating environment for a decentralized cloud? Where you can, and that the main two functions of an operating system or an operating environment are the process scheduler, the thing that's scheduling what is running where and when and so forth, and the file system, right? The thing that's supplying a common view and access to data. So when we talk about this, I think that the strongest argument for supercloud is made when you go down to the platform layer and talk of it, talk about it as an operating environment on which you can run all forms of applications. >> Would you exclude--? >> Not a specific application that's been engineered as a SAS. (audio distortion) >> He'll come back. >> Are you there? >> Yeah, yeah, you just cut out for a minute. >> I lost your last statement when you broke up. >> We heard you, you said that not the specific application. So would you exclude Snowflake from supercloud? >> Frankly, I would. I would. Because, well, and this is kind of hard to do because Snowflake doesn't like to, Frank doesn't like to talk about Snowflake as a SAS service. It has a negative connotation. >> But it is. >> I know, we all know it is. We all know it is and because it is, yes, I would exclude them. >> I think I actually have him on camera. >> There's nothing in common. >> I think I have him on camera or maybe Benoit as saying, "Well, we are a SAS." I think it's Slootman. I think I said to Slootman, "I know you don't like to say you're a SAS." And I think he said, "Well, we are a SAS." >> Because again, if you go to the top of the application stack, there's any number of ways you can give it location agnostic function or you know, regional, local stuff. It's like let's solve the location problem by having me be your one location. How can it be decentralized if you're centralizing on (audio distortion)? >> Well, it's more decentralized than if it's all in one cloud. So let me actually, so the spectrum. So again, in the spirit of what is and what isn't, I think it's safe to say Hammerspace is supercloud. I think there's no debate there, right? Certainly among this crowd. And I think we can all agree that Dell, Dell Storage is not supercloud. Where it gets fuzzy is this Snowflake example or even, how about a, how about a Cohesity that instantiates its stack in different cloud regions in different clouds, and synchronizes, however magic sauce it does that. Is that a supercloud? I mean, so I'm cautious about having too strict of a definition 'cause then only-- >> Fair enough, fair enough. >> But I could use your help and thoughts on that. >> So I think we're talking about two different spectrums here. One is the spectrum of platform to application-specific. As you go up the application stack and it becomes this specific thing. Or you go up to the more and more structured where it's serving a specific application function where it's more of a SAS thing. I think it's harder to call a SAS service a supercloud. And I would argue that the reason there, and what you're lacking in the definition is to talk about it as general purpose. Okay? Now, that said, a data warehouse is general purpose at the structured data level. So you could make the argument for why Snowflake is a supercloud by saying that it is a general purpose platform for doing lots of different things. It's just one at a higher level up at the structured data level. So one spectrum is the high level going from platform to, you know, unstructured data to structured data to very application-specific, right? Like a specific, you know, CAD/CAM mechanical design cloud, like an Autodesk would want to give you their cloud for running, you know, and sharing CAD/CAM designs, doing your CAD/CAM anywhere stuff. Well, the other spectrum is how well does the purported supercloud technology actually live up to allowing you to run anything anywhere with not just the same APIs but with the local presence of data with the exact same runtime environment everywhere, and to be able to correctly manage how to get that runtime environment anywhere. So a Cohesity has some means of running things in different places and some means of coordinating what's where and of serving diff, you know, things in different places. I would argue that it is a very poor approximation of what Hammerspace does in providing the exact same file system with local high performance access everywhere with metadata ability to control where the data is actually instantiated so that you don't have to wait for it to get orchestrated. But even then when you do have to wait for it, it happens automatically and so it's still only a matter of, well, how quick is it? And on the other end of the spectrum is you could look at NetApp with Flexcache and say, "Is that supercloud?" And I would argue, well kind of because it allows you to run things in different places because it's a cache. But you know, it really isn't because it presumes some central silo from which you're cacheing stuff. So, you know, is it or isn't it? Well, it's on a spectrum of exactly how fully is it decoupling a runtime environment from specific locality? And I think a cache doesn't, it stretches a specific silo and makes it have some semblance of similar access in other places. But there's still a very big difference to the central silo, right? You can't turn off that central silo, for example. >> So it comes down to how specific you make the definition. And this is where it gets kind of really interesting. It's like cloud. Does IBM have a cloud? >> Exactly. >> I would say yes. Does it have the kind of quality that you would expect from a hyper-scale cloud? No. Or see if you could say the same thing about-- >> But that's a problem with choosing a name. That's the problem with choosing a name supercloud versus talking about the concept of cloud and how true up you are to that concept. >> For sure. >> Right? Because without getting a name, you don't have to draw, yeah. >> I'd like to explore one particular or bring them together. You made a very interesting observation that from a enterprise point of view, they want to safeguard their store, their data, and they want to make sure that they can have that data running in their own workflows, as well as, as other service providers providing services to them for that data. So, and in in particular, if you go back to, you go back to Snowflake. If Snowflake could provide the ability for you to have your data where you wanted, you were in charge of that, would that make Snowflake a supercloud? >> I'll tell you, in my mind, they would be closer to my conceptualization of supercloud if you can instantiate Snowflake as software on your own infrastructure, and pump your own data to Snowflake that's instantiated on your own infrastructure. The fact that it has to be on their infrastructure or that it's on their, that it's on their account in the cloud, that you're giving them the data and they're, that fundamentally goes against it to me. If they, you know, they would be a pure, a pure plate if they were a software defined thing where you could instantiate Snowflake machinery on the infrastructure of your choice and then put your data into that machinery and get all the benefits of Snowflake. >> So did you see--? >> In other words, if they were not a SAS service, but offered all of the similar benefits of being, you know, if it were a service that you could run on your own infrastructure. >> So did you see what they announced, that--? >> I hope that's making sense. >> It does, did you see what they announced at Dell? They basically announced the ability to take non-native Snowflake data, read it in from an object store on-prem, like a Dell object store. They do the same thing with Pure, read it in, running it in the cloud, and then push it back out. And I was saying to Dell, look, that's fine. Okay, that's interesting. You're taking a materialized view or an extended table, whatever you're doing, wouldn't it be more interesting if you could actually run the query locally with your compute? That would be an extension that would actually get my attention and extend that. >> That is what I'm talking about. That's what I'm talking about. And that's why I'm saying I think Hammerspace is more progressive on that front because with our technology, anybody who can instantiate a service, can make a service. And so I, so MSPs can use Hammerspace as a way to build a super pass layer and host their clients on their infrastructure in a cloud-like fashion. And their clients can have their own private data centers and the MSP or the public clouds, and Hammerspace can be instantiated, get this, by different parties in these different pieces of infrastructure and yet linked together to make a common file system across all of it. >> But this is data mesh. If I were HPE and Dell it's exactly what I'd be doing. I'd be working with Hammerspace to create my own data. I'd work with Databricks, Snowflake, and any other-- >> Data mesh is a good way to put it. Data mesh is a good way to put it. And this is at the lowest level of, you know, the underlying file system that's mountable by the operating system, consumed as a real file system. You can't get lower level than that. That's why this is the foundation for all of the other apps and structured data systems because you need to have a data mesh that can at least mesh the binary blob. >> Okay. >> That hold the binaries and that hold the datasets that those applications are running. >> So David, in the third week of January, we're doing supercloud 2 and I'm trying to convince John Furrier to make it a data slash data mesh edition. I'm slowly getting him to the knothole. I would very much, I mean you're in the Bay Area, I'd very much like you to be one of the headlines. As Zhamak Dehghaniis going to speak, she's the creator of Data Mesh, >> Sure. >> I'd love to have you come into our studio as well, for the live session. If you can't make it, we can pre-record. But you're right there, so I'll get you the dates. >> We'd love to, yeah. No, you can count on it. No, definitely. And you know, we don't typically talk about what we do as Data Mesh. We've been, you know, using global data environment. But, you know, under the covers, that's what the thing is. And so yeah, I think we can frame the discussion like that to line up with other, you know, with the other discussions. >> Yeah, and Data Mesh, of course, is one of those evocative names, but she has come up with some very well defined principles around decentralized data, data as products, self-serve infrastructure, automated governance, and and so forth, which I think your vision plugs right into. And she's brilliant. You'll love meeting her. >> Well, you know, and I think.. Oh, go ahead. Go ahead, Peter. >> Just like to work one other interface which I think is important. How do you see yourself and the open source? You talked about having an operating system. Obviously, Linux is the operating system at one level. How are you imagining that you would interface with cost community as part of this development? >> Well, it's funny you ask 'cause my CTO is the kernel maintainer of the storage networking stack. So how the Linux operating system perceives and consumes networked data at the file system level, the network file system stack is his purview. He owns that, he wrote most of it over the last decade that he's been the maintainer, but he's the gatekeeper of what goes in. And we have leveraged his abilities to enhance Linux to be able to use this decentralized data, in particular with decoupling the control plane driven by metadata from the data access path and the many storage systems on which the data gets accessed. So this factoring, this splitting of control plane from data path, metadata from data, was absolutely necessary to create a data mesh like we're talking about. And to be able to build this supercloud concept. And the highways on which the data runs and the client which knows how to talk to it is all open source. And we have, we've driven the NFS 4.2 spec. The newest NFS spec came from my team. And it was specifically the enhancements needed to be able to build a spanning file system, a data mesh at a file system level. Now that said, our file system itself and our server, our file server, our data orchestration, our data management stuff, that's all closed source, proprietary Hammerspace tech. But the highways on which the mesh connects are actually all open source and the client that knows how to consume it. So we would, honestly, I would welcome competitors using those same highways. They would be at a major disadvantage because we kind of built them, but it would still be very validating and I think only increase the potential adoption rate by more than whatever they might take of the market. So it'd actually be good to split the market with somebody else to come in and share those now super highways for how to mesh data at the file system level, you know, in here. So yeah, hopefully that answered your question. Does that answer the question about how we embrace the open source? >> Right, and there was one other, just that my last one is how do you enable something to run in every environment? And if we take the edge, for example, as being, as an environment which is much very, very compute heavy, but having a lot less capability, how do you do a hold? >> Perfect question. Perfect question. What we do today is a software appliance. We are using a Linux RHEL 8, RHEL 8 equivalent or a CentOS 8, or it's, you know, they're all roughly equivalent. But we have bundled and a software appliance which can be instantiated on bare metal hardware on any type of VM system from VMware to all of the different hypervisors in the Linux world, to even Nutanix and such. So it can run in any virtualized environment and it can run on any cloud instance, server instance in the cloud. And we have it packaged and deployable from the marketplaces within the different clouds. So you can literally spin it up at the click of an API in the cloud on instances in the cloud. So with all of these together, you can basically instantiate a Hammerspace set of machinery that can offer up this file system mesh. like we've been using the terminology we've been using now, anywhere. So it's like being able to take and spin up Snowflake and then just be able to install and run some VMs anywhere you want and boom, now you have a Snowflake service. And by the way, it is so complete that some of our customers, I would argue many aren't even using public clouds at all, they're using this just to run their own data centers in a cloud-like fashion, you know, where they have a data service that can span it all. >> Yeah and to Molly's first point, we would consider that, you know, cloud. Let me put you on the spot. If you had to describe conceptually without a chalkboard what an architectural diagram would look like for supercloud, what would you say? >> I would say it's to have the same runtime environment within every data center and defining that runtime environment as what it takes to schedule the execution of applications, so job scheduling, runtime stuff, and here we're talking Kubernetes, Slurm, other things that do job scheduling. We're talking about having a common way to, you know, instantiate compute resources. So a global compute environment, having a common compute environment where you can instantiate things that need computing. Okay? So that's the first part. And then the second is the data platform where you can have file block and object volumes, and have them available with the same APIs in each of these distributed data centers and have the exact same data omnipresent with the ability to control where the data is from one moment to the next, local, where all the data is instantiate. So my definition would be a common runtime environment that's bifurcate-- >> Oh. (attendees chuckling) We just lost them at the money slide. >> That's part of the magic makes people listen. We keep someone on pin and needles waiting. (attendees chuckling) >> That's good. >> Are you back, David? >> I'm on the edge of my seat. Common runtime environment. It was like... >> And just wait, there's more. >> But see, I'm maybe hyper-focused on the lower level of what it takes to host and run applications. And that's the stuff to schedule what resources they need to run and to get them going and to get them connected through to their persistence, you know, and their data. And to have that data available in all forms and have it be the same data everywhere. On top of that, you could then instantiate applications of different types, including relational databases, and data warehouses and such. And then you could say, now I've got, you know, now I've got these more application-level or structured data-level things. I tend to focus less on that structured data level and the application level and am more focused on what it takes to host any of them generically on that super pass layer. And I'll admit, I'm maybe hyper-focused on the pass layer and I think it's valid to include, you know, higher levels up the stack like the structured data level. But as soon as you go all the way up to like, you know, a very specific SAS service, I don't know that you would call that supercloud. >> Well, and that's the question, is there value? And Marianna Tessel from Intuit said, you know, we looked at it, we did it, and it just, it was actually negative value for us because connecting to all these separate clouds was a real pain in the neck. Didn't bring us any additional-- >> Well that's 'cause they don't have this pass layer underneath it so they can't even shop around, which actually makes it hard to stand up your own SAS service. And ultimately they end up having to build their own infrastructure. Like, you know, I think there's been examples like Netflix moving away from the cloud to their own infrastructure. Basically, if you're going to rent it for more than a few months, it makes sense to build it yourself, if it's at any kind of scale. >> Yeah, for certain components of that cloud. But if the Goldman Sachs came to you, David, and said, "Hey, we want to collaborate and we want to build "out a cloud and essentially build our SAS system "and we want to do that with Hammerspace, "and we want to tap the physical infrastructure "of not only our data centers but all the clouds," then that essentially would be a SAS, would it not? And wouldn't that be a Super SAS or a supercloud? >> Well, you know, what they may be using to build their service is a supercloud, but their service at the end of the day is just a SAS service with global reach. Right? >> Yeah. >> You know, look at, oh shoot. What's the name of the company that does? It has a cloud for doing bookkeeping and accounting. I forget their name, net something. NetSuite. >> NetSuite. NetSuite, yeah, Oracle. >> Yeah. >> Yep. >> Oracle acquired them, right? Is NetSuite a supercloud or is it just a SAS service? You know? I think under the covers you might ask are they using supercloud under the covers so that they can run their SAS service anywhere and be able to shop the venue, get elasticity, get all the benefits of cloud in the, to the benefit of their service that they're offering? But you know, folks who consume the service, they don't care because to them they're just connecting to some endpoint somewhere and they don't have to care. So the further up the stack you go, the more location-agnostic it is inherently anyway. >> And I think it's, paths is really the critical layer. We thought about IAS Plus and we thought about SAS Minus, you know, Heroku and hence, that's why we kind of got caught up and included it. But SAS, I admit, is the hardest one to crack. And so maybe we exclude that as a deployment model. >> That's right, and maybe coming down a level to saying but you can have a structured data supercloud, so you could still include, say, Snowflake. Because what Snowflake is doing is more general purpose. So it's about how general purpose it is. Is it hosting lots of other applications or is it the end application? Right? >> Yeah. >> So I would argue general purpose nature forces you to go further towards platform down-stack. And you really need that general purpose or else there is no real distinguishing. So if you want defensible turf to say supercloud is something different, I think it's important to not try to wrap your arms around SAS in the general sense. >> Yeah, and we've kind of not really gone, leaned hard into SAS, we've just included it as a deployment model, which, given the constraints that you just described for structured data would apply if it's general purpose. So David, super helpful. >> Had it sign. Define the SAS as including the hybrid model hold SAS. >> Yep. >> Okay, so with your permission, I'm going to add you to the list of contributors to the definition. I'm going to add-- >> Absolutely. >> I'm going to add this in. I'll share with Molly. >> Absolutely. >> We'll get on the calendar for the date. >> If Molly can share some specific language that we've been putting in that kind of goes to stuff we've been talking about, so. >> Oh, great. >> I think we can, we can share some written kind of concrete recommendations around this stuff, around the general purpose, nature, the common data thing and yeah. >> Okay. >> Really look forward to it and would be glad to be part of this thing. You said it's in February? >> It's in January, I'll let Molly know. >> Oh, January. >> What the date is. >> Excellent. >> Yeah, third week of January. Third week of January on a Tuesday, whatever that is. So yeah, we would welcome you in. But like I said, if it doesn't work for your schedule, we can prerecord something. But it would be awesome to have you in studio. >> I'm sure with this much notice we'll be able to get something. Let's make sure we have the dates communicated to Molly and she'll get my admin to set it up outside so that we have it. >> I'll get those today to you, Molly. Thank you. >> By the way, I am so, so pleased with being able to work with you guys on this. I think the industry needs it very bad. They need something to break them out of the box of their own mental constraints of what the cloud is versus what it's supposed to be. And obviously, the more we get people to question their reality and what is real, what are we really capable of today that then the more business that we're going to get. So we're excited to lend the hand behind this notion of supercloud and a super pass layer in whatever way we can. >> Awesome. >> Can I ask you whether your platforms include ARM as well as X86? >> So we have not done an ARM port yet. It has been entertained and won't be much of a stretch. >> Yeah, it's just a matter of time. >> Actually, entertained doing it on behalf of NVIDIA, but it will absolutely happen because ARM in the data center I think is a foregone conclusion. Well, it's already there in some cases, but not quite at volume. So definitely will be the case. And I'll tell you where this gets really interesting, discussion for another time, is back to my old friend, the SSD, and having SSDs that have enough brains on them to be part of that fabric. Directly. >> Interesting. Interesting. >> Very interesting. >> Directly attached to ethernet and able to create a data mesh global file system, that's going to be really fascinating. Got to run now. >> All right, hey, thanks you guys. Thanks David, thanks Molly. Great to catch up. Bye-bye. >> Bye >> Talk to you soon.
SUMMARY :
So my question to you was, they don't have to do it. to starved before you have I believe that the ISVs, especially those the end users you need to So, if I had to take And and I think Ultimately the supercloud or the Snowflake, you know, more narrowly on just the stuff of the point of what you're talking Well, and you know, Snowflake founders, I don't want to speak over So it starts to even blur who's the main gravity is to having and, you know, that's where to be in a, you know, a lot of thought to this. But some of the inside baseball But the truth is-- So one of the things we wrote the fact that you even have that you would not put in as to give you low latency access the hardest things, David. This is one of the things I've the how can you host applications Not a specific application Yeah, yeah, you just statement when you broke up. So would you exclude is kind of hard to do I know, we all know it is. I think I said to Slootman, of ways you can give it So again, in the spirit But I could use your to allowing you to run anything anywhere So it comes down to how quality that you would expect and how true up you are to that concept. you don't have to draw, yeah. the ability for you and get all the benefits of Snowflake. of being, you know, if it were a service They do the same thing and the MSP or the public clouds, to create my own data. for all of the other apps and that hold the datasets So David, in the third week of January, I'd love to have you come like that to line up with other, you know, Yeah, and Data Mesh, of course, is one Well, you know, and I think.. and the open source? and the client which knows how to talk and then just be able to we would consider that, you know, cloud. and have the exact same data We just lost them at the money slide. That's part of the I'm on the edge of my seat. And that's the stuff to schedule Well, and that's the Like, you know, I think But if the Goldman Sachs Well, you know, what they may be using What's the name of the company that does? NetSuite, yeah, Oracle. So the further up the stack you go, But SAS, I admit, is the to saying but you can have a So if you want defensible that you just described Define the SAS as including permission, I'm going to add you I'm going to add this in. We'll get on the calendar to stuff we've been talking about, so. nature, the common data thing and yeah. to it and would be glad to have you in studio. and she'll get my admin to set it up I'll get those today to you, Molly. And obviously, the more we get people So we have not done an ARM port yet. because ARM in the data center I think is Interesting. that's going to be really fascinating. All right, hey, thanks you guys.
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Day 2 Wrap Up | CrowdStrike Fal.Con 2022
(upbeat music) >> Okay, we're back to wrap up Fal.con 2022 CrowdStrike's customer event. You're watching theCUBE. My name is Dave Vellante. My co-host, Dave Nicholson, is on injured reserve today, so I'm solo. But I wanted to just give the audience a census to some of my quick takeaways. Really haven't given a ton of thought on this. We'll do review after we check out the videos and the transcripts, and do what we do at SiliconANGLE and theCUBE. I'd say the first thing is, look CrowdStrike continues to expand it's footprint. And, it's adding the identity module, through the preempt acquisition. Working very closely with managed service providers, MSPs, managed security service providers. Having an SMB play. So CrowdStrike has 20,000 customers. I think it could, it could 10X that, you know, over some period of time. As I've said earlier, it's on a path by mid-decade to be a 5 billion company, in terms of revenue. At the macro level, security is somewhat, I'd say it's less discretionary than some other investments. You know, you can, you can probably hold off buying a new storage device. You can maybe clean that up. You know, you might be able to hold off on some of your analytics, but at the end of the day, security is not completely non-discretionary. It's competing. The CISO is competing with other budgets. Okay? So it's, while it's less discretionary, it is still, you know, not an open checkbook for the CISO. Now, having said that, from CrowdStrike standpoint it has an excellent opportunity to consolidate tools. It's one of the biggest problems in the security business Go to Optiv and check out their security taxonomy. It'll make your eyes bleed. There's so many tools and companies that are really focused on one specialization. But really, what CrowdStrike can do with its 22 modules, to say, hey, we can give you ROI and consolidate those. And not only is it risk reduction, it's lowering the labor cost and labor intensity, so you can focus on other areas and free up the biggest problem that CISOs have. It's the lack of enough talent. So, really strong business value and value proposition. A lot of that is enabled by the architecture. We've talked about this. You can check out my breaking analysis that I dropped last weekend, on CrowdStrike. And, you know, can it become a generational company. But it's really built on a cloud-native architecture. George Kurtz and company, they shunned having an on-premise architecture. Much like Snowflake Frank Slootman has said, we're not doing a halfway house. We're going to put all our resources on a cloud-native architecture. The lightweight agent that allows them to add new modules and collect more data, and scale out. The purpose-built threat graph and and time series database, and asset graph that they've built. And very strong use of AI, to not only stop known malware, but stop unknown malware. Identify threats. Do that curation. And really, you know, support the SecOp teams. Product wise, I think the big three takeaways, and there were others, but the big three for me is EDR extending into XDR. You know, X is the extending for, in really, the core of endpoint detection and response, extending that further. Well, it seems to be a big buzzword these days. CrowdStrike, I think, is very focused on making a more complete, a holistic offering, beyond endpoint. And I think it's going to do very well in that space. They're not alone. There are others. It's a very competitive space. The second is identity. Through the acquisition of Preempt. CrowdStrike building that identity module. Partnering with leaders like Okta, to really provide that sort of, treating identity, if you will, as an endpoint. And then sort of Humio is now Falcon Log Scale. Bringing together, you know, the data and the observability piece, and the security piece, is kind of the three big product trends that I saw. I think the last point I'll make, before we wrap, is the ecosystem. The ecosystem here is good. It reminds me, I said, a number of times this week, of ServiceNow in 2013 I think the difference is, CrowdStrike has an SMB play it can go after many more customers, and actually have an even broader platform. And I think it can accelerate its ecosystem faster than ServiceNow was able to do that. I mean, it's got to be, sort of, an open and collaborative sort of ecosystem. You know, ServiceNow is kind of, more of, a one-way street. And I think the other piece of that ecosystem, that we see evolving, into IOT, into the operations technology and critical infrastructure. Which is so important, because critical infrastructure of nations is so vulnerable. We're seeing this in the Ukraine. Security is a key component now of any warfare. And going forward, it's always going to be a key component. Nation states are going to go after trust, or secure infrastructure, or critical infrastructure. Try to disable that and disrupt that. So securing those operation assets is going to be very critical. Not just the refrigerator and the coffee maker, but really going after those critical infrastructures. (chuckles) Getting asked to break. And the last thing I'll say, is the developer platform. We heard from ML that, the opportunity that's there, to build out a PaaS layer, super PaaS layer, if you will, so that developers can add value. I think if that happens, this ecosystem, which is breaking down, will explode. This is Dave Vellante, wrapping up at CrowdStrike, Fal.con 2022, Fal.con 2022. Go to SiliconAngle.com, for all the news. Check out theCUBE.net. You'll see these videos on demand and many others. Check out (indistinct).com for all the research. And look for where we'll be next. Of course, re:Invent is the big fall event, but there are many others in between. Thanks for watching. We're out. (music plays out)
SUMMARY :
is kind of the three big
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George Kurtz, CrowdStrike | CrowdStrike Fal.Con 2022
(upbeat music) >> Welcome back to The Cube's coverage of Fal.Con 22. I'm Dave Vellante with Dave Nicholson. This is day one of our coverage. We had the big keynotes this morning. Derek Jeter was one of the keynotes. We have a big Yankee fan here: George Kurtz is the co-founder and CEO of CrowdStrike. George, thanks for coming on The Cube. >> It's great to be here. >> Boston fan, you know, I tweeted out Derek Jeter. He broke my heart many times, but I can't hate on Jeter. You got to have respect for the guy. >> Well, I still remember I was in Japan when Boston was down you know, by three games and came back to win. So I've got my own heartbreak as well. >> It did heal some wounds, but it almost changed the rivalry, you know? I mean, >> Yeah. >> Once, it's kind of neutralized it, you know? It's just not as interesting. I mean, I'm a season ticket holder. I go to all the games and Yankee games are great. A lot of it used to be, you would never walk into Fenway park with, you know pin stripes, when today there's as many Yankee fans as there are... >> I know. >> Boston fans. Anyway, at Fenway, I mean. >> Yeah. >> Why did you start CrowdStrike? >> Biggest thing for me was to really change the game in how people were looking at security. And at my previous company, I think a lot of people were buying security and not getting the outcome that they wanted. Not- I got acquired by a company, not my first company. So, to be clear, and before I started CrowdStrike, I was in the antivirus world, and they were spending a lot of money with antivirus vendors but not getting the outcome I thought they should achieve, which is to stop the breach, not just stop malware. And for me, security should be outcome based not sort of product based. And the biggest thing for us was how could we create the sales force of security that was focused on getting the right outcome: stopping the breach. >> And the premise, I've seen it, the unstoppable breach is a myth. No CSOs don't live by that mantra, but you do. How are you doing on that journey? >> Well I think, look, there's no 100% of anything in security, but what we've done is really created a platform that's focused on identifying and stopping breaches as well as now, extending that out into helping IT identify assets and their hygiene and basically providing more visibility into IT assets. So, we talked about the convergence of that. Maybe we'll get into it, but. >> Dave Vellante: Sure. >> We're doing pretty well. And from our standpoint, we've got a lot of customers, almost 20,000, that rely on us day to day to help stop the breach. >> Well, and when you dig into the CrowdStrike architecture, what's so fascinating is, you know, Dave, we've talked about this: agent bad. Well, not necessarily, if you can have a lightweight agent that can scale and support a number of modules, then you can consolidate all these point tools out there. You talked about in your keynote, your pillars, workloads, which really end points >> Right. >> ID, which we're going to talk about. Identity data and network security. You're not a network security specialist, >> Right. >> But the other three, >> Yes. >> You're knocking down. >> Yeah. >> You guys went deep into that today. Talk about that. >> We did, most folks are going to know us for endpoint and Cloud workload protection and visibility. We did an acquisition almost two years to the day on preempt. And that was our identity play, identity threat protection and detection. And that really turned out to be a smart move, because it's the hottest topic right now. If you look at all the breaches over the last couple years, it's all identity based. Big, big talking points in our keynotes today. >> Dave Vellante: Right. >> And then the third area is on data, and data is really the you know, the new currency that people trade in. So how do you identify and protect endpoints and workloads? How do you tie that together with identity, as well as understanding how you connect the dots and the data and where data flows? And that's really been our focus and we continue to deliver on that for customers. >> And you've had a real dogma, I'll call it, about Cloud Native. I've had this conversation with Frank Slootman, "No we're not going to do a halfway house." You, I think, said it really well today. I think it was you who said it. If you've got On-Prem and Cloud, you got two code bases, >> George Kurtz: Right. >> That you got to maintain. >> That's it, yeah. >> And that means you're taking away resources from one or the other. >> That's exactly right. And what a lot of our competitors have done is they started On-Prem as an AV vendor, and then they took what they had and they basically put it in a Cloud instance called a Cloud, which doesn't really scale. And then, you know, where they need to, they basically still keep their On-Prem, and that just diffuses your engineering team. And most of the On-Prem stuff doesn't even have the features of what they're trying to offer from the Cloud. So either you're Cloud Native or you're not. You can't be halfway. >> But it doesn't mean that you can't include and ingest On-Prem data- >> Well, absolutely. >> into your platform, and that's what I think most people just some reason don't seem to understand. >> Well our agents run wherever. They certainly run On-Prem. >> Dave Vellante: Right. Right. >> And they run in the Cloud, they run wherever. But the crowd in the CrowdStrike is the fact that we can crowdsource this threat information at scale into our threat graph, which gives us unique insight, 7 trillion events per week. And you can't do that if you're not Cloud Native. And that crowd gives the, we call, community immunity. We see all kinds of attacks across 176 different countries. That benefit accrues to all of our customers. >> But how do you envision and maintain and preserve a lightweight agent that can support so many modules? As you do more acquisitions and you knock down new areas and bring in new functionality, go after things like operations technology, how is it that you're able to keep that agent lightweight? >> Well, we started as a platform company, meaning that the whole idea was we're going to build a lightweight agent. First iteration had no security capabilities. It was collect data, get it into a common data architecture or threat graph, in one spot. And then once we had the data then we applied AI to it and we created different workflows. So, the first incarnation was get data into the Cloud at scale. And that still holds true today. So if you think about why we can actually have all these different modules without an impact on the performance, it's we collect data one time. It's a threat data, you know? We're not collecting user data, but threat data collection mechanism. Once we have all that data, then we can slice and dice and create other modules. So the new modules never have to even touch the agent 'cause we've already collected the data. >> I'm going to just keep going, Dave, unless you shove your way in. >> No, no, go ahead. No, no, no. I'm waiting to pounce. >> But okay, so, I think, George, but George, I need to ask you about a comment that you made about we're not just shoving it into a data lake. But you are collecting all the data. Can you explain that nuance? >> Yeah. So there's a difference between a collect and forward agent. It means they just collect a bunch of data. They'll probably store it in a lot of space on the endpoint. It's slow and cumbersome, and then they'll forward it up into another data lake. So you have no context going into no context. Our agent is a smart agent, which actually allows us to always track the context of all these processes in what's happening on the endpoint. And it's a mini graph, meaning we keep track of the relationships. And as we ship that contextual information to the Cloud, we never lose that context. And then it goes into the bigger graph database, always with the same level of context. So, we keep the context of each individual workload or endpoint, and then across the Cloud, we have the context of all of those put together. It's massive. And that allows us to create different insights rather than a data lake, which is, you know, you're looking for, you're creating a bigger needle stack looking for needles. >> And I'm envisioning almost an index that is super, super fast. I mean, you're talking about sub, well second kind of near real time responses, correct? >> Absolutely. So a lot of what we do in terms of protection is already pushed down to the endpoint , 'cause it has intelligence and the AI model. And then again, the Cloud is always looking for different anomalies, not only on each individual endpoint or workload, but across the entire spectrum of our customer base. And that's all real time. It continually self-learns from all the data we collect. >> So when, yeah, when you've made these architectural decisions over time, there was a time when saying that you needed to run an agent could be a deal killer somewhere for people who argued against that. >> George Kurtz: Right. >> You've made the right decision there, clearly. Having everything be crowdsourced into Cloud makes perfect sense. Has that, though, posed a challenge from a sovereignty perspective? If you were deploying stuff On-Prem all over the place, you don't need to worry about that. Everything is here >> George Kurtz: Yeah. >> in a given country. How do you address the challenges of sovereignty when these agents are sending data into some sort of centralized Cloud space that crosses boundaries? >> Well, yeah, I guess what we would, let me go back to the beginning. So I started company in 2011 and I had to convince people that delivering endpoint security from the Cloud was going to be a good thing. >> Dave Vellante: Right. (chuckles) >> You know, you go into a Swiss bank and a bunch of other places and they're like, you're crazy. Right? >> Dave Nicholson: Right. >> They all became customers afterwards, right? And you have to just look at what they're doing. And the question I would have in the early days is, well, let me ask you are you using Dropbox, Box? Are you using a Microsoft? You know, what are you using? Well, they're all sending data to the Cloud. So good news! You already have a model, you've already approved that, right? So let's talk about our benefit. And you know, you can either have an adversary steal your data or you can send threat data to our Cloud, which by the way is in a lot of sovereign Clouds that are out there. And when you actually break it down to what we're sending to the Cloud, it's threat data, right? It isn't user files and documents and stuff. It's threat data. So, we work through all of that. And the Cloud is bigger than CrowdStrike. So you look at Sales Force, Service Now, Workday, et cetera. That's being used all over the place, Box, Dropbox. We just tagged onto it. Like why shouldn't security be the platform of record, and why shouldn't CrowdStrike be the platform of record and be the pillar of Cloud security? >> Explain your observability strategy, 'cause you acquired Humio for, I mean, I think it was $400 million, which is a song. >> Yeah. >> And then Reposify is the latest acquisition. I see that as an extension, 'cause it gives you visibility. Is that part of your security, of your observability play? Explain where you do play and don't play. >> Sure. Well observability is a big, you know, fluffy word. Where we play is in probably the first two areas of observability, right? There's five, kind of, pillars. We're focused on event collection. Let's get events from the endpoints. Let's get events from really anywhere in the network. And we can do that with Humio is now log scale. And then the second piece is with our agents, let's get an understanding of their, the asset itself. What is the asset? What state is it in? Does it have vulnerabilities? Does it have, you know, is it running out of disc space? Is it have, does it have a performance issue? Those are really the first two, kind of, areas of observability. We're not in application performance, we're in let's collect data from the endpoint and other sources, and let's understand if the thing is working, right? And that's a huge value for customers. And we can do that because we already have a privileged spot on the endpoint with our agent. >> Got it. Question on the TAM. Like I look at your TAMs, your charts, I love it. You know, generally do. Were you taking known data from you know, firms like IDC >> George Kurtz: Yeah. >> and saying, okay we're going to play there, now we're made this acquisition. We're new modules, now we're playing there. Awesome. I think you got a big TAM. And I guess that's, that's the point. There's no lack of market for you. >> George Kurtz: Right. >> But I do feel like there's this unknown unquantifiable piece of your TAM. IDC can't see it, 'cause they're kind of looking back >> George Kurtz: Right. >> seein' what the market do last year and we'll forecast it out. It's almost, you got to be a futurist to see it. How do you think about your total available market and the opportunity that's out there? >> Well, it's well in excess of 120 billion and we've actually updated that recently. So it's even beyond that. But if you look at all the modules each module has a discreet TAM and again, for what, you know, what we're focused on is how do you give an outcome to a customer? So a lot of the modules map back into specific TAM and product categories. When you add 'em all up and when you look at, you know, some of the new things that we're coming out with, again, it's well in excess of 120 billion. So that's why we like to say like, you know, we're not an endpoint company. We're really, truly a security platform company that was born in the Cloud. And I think if you see the growth rates, and one of the things that we've talked about, and I think you might have pointed out in prior podcasts, is we're the second fastest company to 2 billion dollars in annual recurring revenue, only behind Zoom. And you know I would argue- great company, by the way, a customer- but that was a black Swan event in a pandemic, right? >> Dave Vellante: I'll say! >> Yeah. >> So we are rarefied air when you think about the capabilities that we have and the performance and the TAM that's available to us. >> The other thing I said in my breaking analysis was 'cause you guys aspire to be a generational company. And I think you got a really good shot at being one, but to be a generational company, you have to have an ecosystem. So I'd love you to talk about the ecosystem, but where you want to see it in five years. >> Well, it really is a good point and we are a partner first company. Ecosystem is really important. Cameras probably can't see all the vendors that are here that are our partners, right? It's a big part of this show that we're at. You see a lot of, well, you see some vendors behind us. >> Yep. >> We have to realize in 2022, and I think this is something that we did well and it's my philosophy, is we are not the only game in town. We like to be, and we are, for many companies the security platform on record, but we don't do everything. We talked about network in other areas. We can't do everything. You can't be good and try to do everything. So, for customers today, what they're looking at is best of platform. And in the early days of security, I've been in it over 30 years, it used to be best of breed products, then it was best of suite, now it's best of platform. So what do I mean by that? It means that customers don't want to engineer their own solution. They, like Lego blocks, they want to pull the platforms, and they want to stitch 'em together via API. And they want to say, okay, CrowdStrike works with Okta, works with Zscaler, works with Proofpoint, et cetera. And that's what customers want. So, ecosystem is incredibly important for us. >> Explain that. You mentioned Okta, I had another question for you. I was at Reinforce, and I saw this better together presentation, CrowdStrike and Okta talking about identity. You've got an identity module. Explain to people how you're not competing with Okta. You guys complement each other, there. >> Well, an identity kind of broker, if you will, is basically what Okta does in others, right? So you log in single sign on and you get access. They broker access to all these other applications. >> Dave Vellante: Right. >> That's not what we do. What we do is we look at those endpoints and workloads and domain controllers and directory services and we figure out, are there vulnerabilities and are there threats associated with them? And we call that out. The second piece, which is critical, is we prevent lateral movement. So if credentials are stolen we can prevent those credentials from being laundered or used and moved laterally, which is a key part of how breaches happen. We then create a trust score on those endpoints and workloads. And we basically say, okay, do we think the trust on the endpoint and workload is high or low? Do we think the identity, you know, is it George on the endpoint, or not? We give that a score. And we pass that along to Okta or Ping or whoever, and they then use that as part of their calculus in how they broker access to other resources. So it really is better together. >> So your execution has been stellar. This is my competition question. You obviously have competition out there. I think architecturally, you've got some advantages. You have a great relationship with AWS. I don't know what's going on with Google, but Kevin's up on stage. >> George Kurtz: Yeah. >> They're now part of Google. >> George Kurtz: We have a great relationship with them. >> Microsoft obviously, a competitor. You obviously do some things in, >> Right. >> in Azure. Are you building the security Cloud? >> We are. We think we are, because when you look at the amount of data that we actually ingest, when you look at companies using us for critical decisions and critical protection, not only on their On-Prem, but also in their Cloud environment, and the knowledge we have, we think it is a security Cloud. You know, you had, you had Salesforce and Workday and ServiceNow and each of them had their respective Clouds. When I started the company, there was no security Cloud. You know, it wasn't any of the companies that you know. It wasn't the firewall companies, wasn't the AV companies. And I think we really defined ourselves as the security Cloud. And the level of knowledge and insights we have in our Cloud, I think, are world class. >> But you know, it's a difference of being those- 'cause you mentioned those other, you know, seminal Clouds. They, like Salesforce, Workday, they're building their own Clouds. Maybe not so much Workday, but certainly Salesforce and ServiceNow built their own >> Yeah. >> Clouds, their own data centers. You're building on top of hyperscalers, correct? >> Well, >> Well you have your own data centers, too. >> We have our own data centers, yeah. So when we first started, we started in AWS as many do, and we have a great relationship there. We continue to build out. We are a huge customer and we also have, you know, with data sovereignty and those sort of things, we've got a lot of our sort of data that sits in our private Cloud. So it's a hybrid approach and we think it's the best of both worlds. >> Okay. And you mean you can manage those costs and it's, how do you make the decision? Is it just sovereignty or is it cost as well? >> Well, there's an operational element. There's cost. There's everything. There's a lot that goes into it. >> Right. >> And at the end of the day we want to make sure that we're using the right technology in the right Clouds to solve the right problem. >> Well, George, congratulations on being back in person. That's got to feel good. >> It feels really good. >> Got a really good audience here. I don't know what the numbers are but there's many thousands here, >> Thousands, yeah. >> at the ARIA. Really appreciate your time. And thanks for having The Cube here. You guys built a great set for us. >> Well, we appreciate all you do. I enjoy your programs. And I think hopefully we've given the audience a good idea of what CrowdStrike's all about, the impact we have and certainly the growth trajectory that we're on. So thank you. >> Fantastic. All right, George Kurtz, Dave Vellante for Dave Nicholson. We're going to wrap up day one. We'll be back tomorrow, first thing in the morning, live from the ARIA. We'll see you then. (calm music)
SUMMARY :
George Kurtz is the co-founder Boston fan, you know, you know, by three games neutralized it, you know? Anyway, at Fenway, I mean. And the biggest thing for us was that mantra, but you do. So, we talked about the And from our standpoint, Well, and when you dig into You're not a network security specialist, that today. If you look at all the breaches and data is really the I think it was you who said it. And that means you're And most of the On-Prem stuff doesn't even and that's what I think most people Well our agents run wherever. Dave Vellante: Right. And you can't do that if So if you think about why we can actually going, Dave, unless you shove No, no, go ahead. that you made about So you have no context And I'm envisioning almost from all the data we collect. when saying that you you don't need to worry about that. How do you address the and I had to convince people Dave Vellante: Right. You know, you go into a Swiss bank And you know, you can 'cause you acquired Humio for, I mean, 'cause it gives you visibility. And we can do that with you know, firms like IDC And I guess that's, that's the point. But I do feel like there's this unknown and the opportunity that's out there? And I think if you see the growth rates, the capabilities that we have And I think you got a really You see a lot of, well, you And in the early days of security, CrowdStrike and Okta of broker, if you will, Do we think the identity, you know, You have a great relationship with AWS. George Kurtz: We have a You obviously do some things in, Are you building the security Cloud? and the knowledge we have, But you know, it's a of hyperscalers, correct? Well you have your we also have, you know, how do you make the decision? There's a lot that goes into it. And at the end of the day That's got to feel good. I don't know what the numbers are at the ARIA. Well, we appreciate all you do. We'll see you then.
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Breaking Analysis: How CrowdStrike Plans to Become a Generational Platform
>> From theCUBE studios in Palo Alto in Boston bringing you data driven insights from theCUBE and ETR. This is "Breaking Analysis" with Dave Vellante. >> In just over 10 years, CrowdStrike has become a leading independent security firm with more than 2 billion in annual recurring revenue, nearly 60% ARR growth, and approximate $40 billion market capitalization, very high retention rates, low churn, and a path to 5 billion in revenue by mid decade. The company has joined Palo Alto Networks as a gold standard pure play cyber security firm. It has achieved this lofty status with an architecture that goes beyond a point product. With outstanding go to market and financial execution, some sharp acquisitions and an ever increasing total available market. Hello, and welcome to this week's Wikibon Cube Insights powered by ETR. In this "Breaking Analysis" and ahead of Falcon, Fal.Con, CrowdStrike's user conference, we take a deeper look into CrowdStrike, its performance, its platform, and survey data from our partner ETR. Now, the general consensus is that spending on Cyber is non-discretionary and is held up better than other technology sectors. While this is generally true, as this data shows, it's nuanced. Let's explore this a bit. First, this is a year-to-date chart of the stock performance of CrowdStrike relative to Palo Alto, the BUG ETF, which is a Cyber index, the NASDAQ and SentinelOne, a relatively new entrant to the IPO public markets. Now, as you can see the security sector as evidenced by the orange line, that Cyber ETF, is holding up better than the overall NASDAQ which is off 28% year-to-date. Palo Alto has held up incredibly well, the best, being off only around 4% year-to-date. Whereas CrowdStrike is off in the double digits this year. But up as we talked about in one of our last "Breaking Analysis" on Cyber, up from its lows this past May. Now, CrowdStrike had a very nice beat and raise on August 30th. But the stop didn't respond well initially. We asked "Breaking Analysis" contributor, Chip Simonton for his technical take and he stated that CrowdStrike has bounced around for the last three months in its current range. He said that Cyber stocks have held up better than the rest of the market, as we're showing. And now might be a good time to take a shot but he is cautious. FedEx had a warning today of a global recession and that's obvious case for a concern. You know, maybe some of these quality Cyber stocks like Palo Alto and CrowdStrike and Zscaler will outperform in a recession, but that play is not for the faint of heart. In fact, it's feeling like a longer, more drawn out tech lash than many had hoped. Perhaps as much as 12 to 18 months of bouncing around with sellers still in control, is generally the sentiment from Simonton. So in terms of Cyber spending being non-discretionary, we'd say it's less discretionary than other it sectors but the CISO still does not have an open wallet, as we've reported before. We've seen that spending momentum has decelerated in all sectors throughout the year. This is an across the board trend. Now, independent of the stock price, George Kurtz, CEO of CrowdStrike, he's running a marathon, not a sprint. And this company is running at a nice pace despite tough macro headwinds. The company is free cash flow positive and is in the black, or a non-GAAP operating profit basis and yet it's growing ARR at nearly 60%. Frank Slootman uses the term inherent profitability, meaning that the company could drive more profits if it wanted to dial down expenses especially in go to market costs. But that would be a mistake for a company like CrowdStrike, in our opinion. While it has an impressive nearly 20,000 customers, there are hundreds of thousands of customers that CrowdStrike could penetrate. So like Snowflake and Slootman, Kurtz is not taking its foot off the gas. Now, the fundamental strength of CrowdStrike and its secret sauce is its architecture and platform, in our view, so let's take a deeper look. CrowdStrike believes that the unstoppable breach is a myth. Now, CISOs don't agree with that because they assume they're going to get breached, but that's CrowdStrike's point of view, so lofty vision. CrowdStrike's mission is to consolidate the patchwork of solutions by introducing modules that go beyond point products. CrowdStrike has more than 20 modules, I think 22, that span a range of capabilities as shown in this table. Now, there are a few critical aspects of the CrowdStrike architecture that bear mentioning. First is the lightweight agent, that is fundamental. You know, we're used to thinking that agentless is good and agent is bad, but in this case, a powerful but small, slim and easy to install but unobtrusive agent has its advantages because it supports multiple CrowdStrike modules. The second point is CrowdStrike from the beginning has been dogmatic about getting all the telemetry data into the cloud. It sort of shunned doing bespoke on prem so that all the data could be analyzed. So the more agents that CrowdStrike installs around the world, the more data it has access to and the better its intelligence. Few companies have access to more data, perhaps Microsoft given it scale and size is an exception in that endpoint space. CrowdStrike has developed a purpose-built threat graph and analytics platform that allows it to quickly ingest in near real time key telemetry data and detect not only known malware, that's pretty straightforward, pretty much anybody could do that. But using machine intelligence, it can also detect unknown malware and other potentially malicious behavior using indicators of attack, IOC, or IOAs. Humio is shown here as a company that CrowdStrike bought for around 400 million in early 2020, early 2021. It's the company's Splunk killer and will serve as an observability platform. It's really starting to take off, that's a great market for them to go after. CrowdStrike, to try to put it into sort of a summary, uses a three pronged approach. First is it's next generation anti-virus, meaning it's SaaS base. SAS based solution that can do fast lookups to telemetry data and that data lives in the cloud. And this leverages cloud strikes proprietary threat graph. Now, the second is endpoint detection and response. CrowdStrike sends all endpoint activity to the cloud and can process the data in real time. CrowdStrike EDR allows you to search data history and its partners with threat intelligent platforms who push the data into CrowdStrike, the CrowdStrike cloud. This increases CloudStrike's observation space. It also has containment capabilities in EDR to fence off compromised system. Now, the third leg of the stool is CrowdStrike's world class manage hunting approach. Like many firms, CrowdStrike has a crack team of experts that is looking at the data, but CrowdStrike's advantage is the amount of data, that observation space that we just talked about, and near real time capabilities of the architecture thanks to that proprietary database that they've developed. And all this is built in the cloud and so it enables global scale. And of course, agility. Now, let's dig into some of the survey data and take a look at what ETR respondents are saying about the spending momentum for CrowdStrike in context with its peers. Here's a very recent dataset, the October preliminary data from the October dataset in ETR's survey. Eric Bradley shared with us, ETR's head of strategy, and he runs the round tables, he's a frequent "Breaking Analysis" contributor. This is an XY graph with Netcore or spending momentum on the vertical axis and the overlap or pervasiveness in the survey on the horizontal axis. That dotted red line at 40% indicates an elevated level of spending velocity. Anything above that, we consider really impressive. Note the CrowdStrike progression since the pandemic started. The two notable points are one, that CrowdStrike has remained consistently above that 40% mark and two, it has made notable progress to the right. You can see that sort of squiggly line consistently increasing its share with one little anomaly there in the early days of over a two-year period. The other call out here is Microsoft in the upper-right. We circled Microsoft as usual. Microsoft messes up the data because it's such a dominant player and has referenced earlier as a massive scale and very quality telemetry from its endpoints. Unlike AWS, Microsoft is a direct competitor of CrowdStrike's. Nonetheless, the sector remains very strong with lots of players. Cyber is a large and expanding TAM with too many point tools that CrowdStrike is well positioned to consolidate, in our view. Now, here's a more narrow view of that same XY graph. What it does is it takes out Microsoft to kind of normalize the data a bit and it compares a number of firms that specialize in endpoint, along with CrowdStrike such as Tanium which also has a lightweight agent, by the way, and appears to be doing pretty well. SentinelOne did a relatively recent IPO, took off, stock hasn't done as well since, as you saw earlier. Carbon Black which VMware bought for around $2 billion and Cylance which is the Blackberry pivot. Now, we've also for context included Palo Alto and Cisco because they are major players with the big presence in security and they've got solutions that compete with CrowdStrike. But you can see how CrowdStrike looms large with a higher net score than these others. Although Palo Alto is very impressive, as is Cisco, steady. But Palo Alto also, sorry, CrowdStrike also has a very steady posture instead of just looming on that X axis. Let's now take a look at XDR, extended detection and response. XDR is kind of this bit of a buzzword but CrowdStrike seems to be taking the mantle and trying to sort of own the category and define it, in our view. It's a natural evolution of endpoint detection and response, EDR. In a recent ETR Roundtable hosted by our colleague, Eric Bradley, the sentiment among several CIOs is that existing SIEM, security information and event management platforms are inadequate and some see XDR as a replacement for, or at least a strong compliment to SIEM. CISOs want a single view of their data. Hmm, you haven't heard that before. They want help prioritizing potentially high impact breaches and they want to automate the low level stuff because the problem is sometimes too much information becomes information overload and you can't prioritize. So they want to consolidate platforms. They want better co consistency. They have too many dashboards, too many stove pipes. They have difficulty scaling and they have inconsistent telemetry data. As one CISO said, it's a call out here. "If the regulatory requirement isn't there, I absolutely would get rid of my SIEM." So CrowdStrike, we feel, is in a good position to continue to gain, share and disrupt this space. And that's what Dave Nicholson and I will be looking for next week when theCUBE is at Fal.Con, CrowdStrike's user conference. We'll be there for two days at the area in Vegas. In addition to CrowdStrike CEO, we'll hear from government cyber experts. We always hear that at security conferences and the CEO of Mandiant. Google just the other day closed its $5 billion plus acquisition of Mandiant, which is a threat intelligence expert and MSSP. I'm going to hear a lot about MSSPs by the way. CrowdStrike is a growing MSSP base. We think that's a really interesting sector because many companies don't have a SOC. As many as 50% of companies in the United States don't have a security operations center. So they need help, that's where MSPs come in. At the conference, there'll be a real focus on the Falcon platform. And we expect CrowdStrike to educate the audience on its multiple modules and how to take advantage of the capabilities beyond endpoint. And we'll also be watching for the ecosystem conversations. We saw this at reinforced, for example, where CrowdStrike and Okta were presenting together to show how these companies products compliment each other in the marketplace. Sometimes it gets confusing when you hear that CrowdStrike has an identity product. Okta, of course, is the identity specialist. So we'll be helping extract that signal from the noise. Because a generational company must have a strong ecosystem. CrowdStrike is evolving and our belief is that it has some work to do to create a stronger partner flywheel, and we're eager to dig into that next week. So if you're at the event, please do stop by theCUBE, say hello to Dave Nicholson and myself. Okay, we're going to leave it there today. Many thanks to Chip Simonton and Eric Bradley for their input and contributions to today's episode. Thanks to Alex Myerson, who does production, he also manages our podcast, Ken Schiffman as well, in our Boston studios, Kristen Martin and Cheryl Knight help get the word out on social media and our newsletters, and Rob Hof is our editor in chief over at siliconangle.com. He does some wonderful editing and I really appreciate that. Remember, all these episodes are available as podcasts wherever you listen, just search "Breaking Analysis" Podcast. I publish each week on wikibon.com and siliconangle.com and you can email me at david.vellante@siliconangle.com or DM me @DVellante or comment on our LinkedIn post. And please do check out etr.ai for 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)
SUMMARY :
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Super Data Cloud | Supercloud22
(electronic music) >> Welcome back to our studios in Palo Alto, California. My name is Dave Vellante, I'm here with John Furrier, who is taking a quick break. You know, in one of the early examples that we used of so called super cloud was Snowflake. We called it a super data cloud. We had, really, a lot of fun with that. And we've started to evolve our thinking. Years ago, we said that data was going to form in the cloud around industries and ecosystems. And Benoit Dogeville is a many time guest of theCube. He's the co-founder and president of products at Snowflake. Benoit, thanks for spending some time with us, at Supercloud 22, good to see you. >> Thank you, thank you, Dave. >> So, you know, like I said, we've had some fun with this meme. But it really is, we heard on the previous panel, everybody's using Snowflake as an example. Somebody how builds on top of hyper scale infrastructure. You're not building your own data centers. And, so, are you building a super data cloud? >> We don't call it exactly that way. We don't like the super word, it's a bit dismissive. >> That's our term. >> About our friends, cloud provider friends. But we call it a data cloud. And the vision, really, for the data cloud is, indeed, it's a cloud which overlays the hyper scaler cloud. But there is a big difference, right? There are several ways to do this super cloud, as you name them. The way we picked is to create one single system, and that's very important, right? There are several ways, right. You can instantiate your solution in every region of the cloud and, you know, potentially that region could be AWS, that region could be GCP. So, you are, indeed, a multi-cloud solution. But Snowflake, we did it differently. We are really creating cloud regions, which are superimposed on top of the cloud provider region, infrastructure region. So, we are building our regions. But where it's very different is that each region of Snowflake is not one instantiation of our service. Our service is global, by nature. We can move data from one region to the other. When you land in Snowflake, you land into one region. But you can grow from there and you can, you know, exist in multiple cloud at the same time. And that's very important, right? It's not different instantiation of a system, it's one single instantiation which covers many cloud regions and many cloud provider. >> So, we used Snowflake as an example. And we're trying to understand what the salient aspects are of your data cloud, what we call super cloud. In fact, you've used the word instantiate. Kit Colbert, just earlier today, laid out, he said, there's sort of three levels. You can run it on one cloud and communicate with the other cloud, you can instantiate on the clouds, or you can have the same service running 24/7 across clouds, that's the hardest example. >> Yeah. >> The most mature. You just described, essentially, doing that. How do you enable that? What are the technical enablers? >> Yeah, so, as I said, first we start by building, you know, Snowflake regions, we have today 30 regions that span the world, so it's a world wide system, with many regions. But all these regions are connected together. They are meshed together with our technology, we name it Snow Grid, and that makes it hard because, you know, Azure region can talk to a WS region, or GCP regions, and as a user for our cloud, you don't see, really, these regional differences, that regions are in different potentially cloud. When you use Snowflake, you can exist, your presence as an organization can be in several regions, several clouds, if you want, geographic, both geographic and cloud provider. >> So, I can share data irrespective of the cloud. And I'm in the Snowflake data cloud, is that correct? I can do that today? >> Exactly, and that's very critical, right? What we wanted is to remove data silos. And when you insociate a system in one single region, and that system is locked in that region, you cannot communicate with other parts of the world, you are locking data in one region. Right, and we didn't want to do that. We wanted data to be distributed the way customer wants it to be distributed across the world. And potentially sharing data at world scales. >> Does that mean if I'm in one region and I want to run a query, if I'm in AWS in one region, and I want to run a query on data that happens to be in an Azure cloud, I can actually execute that? >> So, yes and no. The way we do it is very expensive to do that. Because, generally, if you want to join data which are in different region and different cloud, it's going to be very expensive because you need to move data every time you join it. So, the way we do it is that you replicate the subset of data that you want to access from one region from other region. So, you can create this data mesh, but data is replicated to make it very cheap and very performing too. >> And is the Snow Grid, does that have the metadata intelligence to actually? >> Yes, yes. >> Can you describe that a little? >> Yeah, Snow Grid is both a way to exchange metadata. So, each region of Snowflake knows about all the other regions of Snowflake. Every time we create a new region, the metadata is distributed over our data cloud, not only region knows all the region, but knows every organization that exists in our cloud, where this organization is, where data can be replicated by this organization. And then, of course, it's also used as a way to exchange data, right? So, you can exchange data by scale of data size. And I was just receiving an email from one of our customers who moved more than four petabytes of data, cross region, cross cloud providers in, you know, few days. And it's a lot of data, so it takes some time to move. But they were able to do that online, completely online, and switch over to the other region, which is very important also. >> So, one of the hardest parts about super cloud that I'm still trying to struggling through is the security model. Because you've got the cloud as your sort of first line of defense. And now we've got multiple clouds, with multiple first lines of defense, I've got a shared responsibility model across those clouds, I've got different tools in each of those clouds. Do you take care of that? Where do you pick up from the cloud providers? Do you abstract that security layer? Do you bring in partners? It's a very complicated. >> No, this is a great question. Security has always been the most important aspect of Snowflake sense day one, right? This is the question that every customer of ours has. You know, how can you guarantee the security of my data? And, so, we secure data really tightly in region. We have several layers of security. It starts by creating every data at rest. And that's very important. A lot of customers are not doing that, right? You hear of these attacks, for example, on cloud, where someone left their buckets. And then, you know, you can access the data because it's a non-encrypted. So, we are encrypting everything at rest. We are encrypting everything in transit. So, a region is very secure. Now, you know, from one region, you never access data from another region in Snowflake. That's why, also, we replicate data. Now the replication of that data across region, or the metadata, for that matter, is really our least secure, so Snow Grid ensures that everything is encrypted, everything is, we have multiple encryption keys, and it's stored in hardware secure modules, so, we bit Snow Grid such that it's secure and it allows very secure movement of data. >> Okay, so, I know we kind of, getting into the technology here a lot today, but because super cloud is the future, we actually have to have an architectural foundation on which to build. So, you mentioned a bucket, like an S3 bucket. Okay, that's storage, but you also, for instance, taking advantage of new semi-conductor technology. Like Graviton, as an example, that drives efficiency. You guys talk about how you pass that on to your customers. Even if it means less revenue for you, so, awesome, we love that, you'll make it up in volume. And, so. >> Exactly. >> How do you deal with the lowest common denominator problem? I was talking to somebody the other day and this individual brought up what I thought was a really good point. What if we, let's say, AWS, have the best, silicon. And we can run the fastest and the least expensive, and the lowest power. But another cloud provider hasn't caught up yet. How do you deal with that delta? Do you just take the best of and try to respect that? >> No, it's a great question. I mean, of course, our software is extracting all the cloud providers infrastructure so that when you run in one region, let's say AWS, or Azure, it doesn't make any difference, as far as the applications are concerned. And this abstraction, of course, is a lot of work. I mean, really, a lot of work. Because it needs to be secure, it needs to be performance, and every cloud, and it has to expose APIs which are uniform. And, you know, cloud providers, even though they have potentially the same concept, let's say block storage, APIs are completely different. The way these systems are secure, it's completely different. There errors that you can get. And the retry mechanism is very different from one cloud to the other. The performance is also different. We discovered that when we starting to port our software. And we had to completely rethink how to leverage block storage in that cloud versus that cloud, because just off performance too. And, so, we had, for example, to stripe data. So, all this work is work that you don't need as an application because our vision, really, is that application, which are running in our data cloud, can be abstracted for this difference. And we provide all the services, all the workload that this application need. Whether it's transactional access to data, analytical access to data, managing logs, managing metrics, all of this is abstracted too, so that they are not tied to one particular service of one cloud. And distributing this application across many region, many cloud, is very seamless. >> So, Snowflake has built, your team has built a true abstraction layer across those clouds that's available today? It's actually shipping? >> Yes, and we are still developing it. You know, transactional, Unistore, as we call it, was announced last summit. So, they are still, you know, work in progress. >> You're not done yet. >> But that's the vision, right? And that's important, because we talk about the infrastructure, right. You mention a lot about storage and compute. But it's not only that, right. When you think about application, they need to use the transactional database. They need to use an analytical system. They need to use machine learning. So, you need to provide, also, all these services which are consistent across all the cloud providers. >> So, let's talk developers. Because, you know, you think Snowpark, you guys announced a big application development push at the Snowflake summit recently. And we have said that a criterion of super cloud is a super paz layer, people wince when I say that, but okay, we're just going to go with it. But the point is, it's a purpose built application development layer, specific to your particular agenda, that supports your vision. >> Yes. >> Have you essentially built a purpose built paz layer? Or do you just take them off the shelf, standard paz, and cobble it together? >> No, we build it a custom build. Because, as you said, what exist in one cloud might not exist in another cloud provider, right. So, we have to build in this, all these components that a multi-application need. And that goes to machine learning, as I said, transactional analytical system, and the entire thing. So that it can run in isolation physically. >> And the objective is the developer experience will be identical across those clouds? >> Yes, the developers doesn't need to worry about cloud provider. And, actually, our system will have, we didn't talk about it, but a marketplace that we have, which allows, actually, to deliver. >> We're getting there. >> Yeah, okay. (both laughing) I won't divert. >> No, no, let's go there, because the other aspect of super cloud that we've talked about is the ecosystem. You have to enable an ecosystem to add incremental value, it's not the power of many versus the capabilities of one. So, talk about the challenges of doing that. Not just the business challenges but, again, I'm interested in the technical and architectural challenges. >> Yeah, yeah, so, it's really about, I mean, the way we enable our ecosystem and our partners to create value on top of our data cloud, is via the marketplace. Where you can put shared data on the marketplace. Provide listing on this marketplace, which are data sets. But it goes way beyond data. It's all the way to application. So, you can think of it as the iPhone. A little bit more, all right. Your iPhone is great. Not so much because the hardware is great, or because of the iOS, but because of all the applications that you have. And all these applications are not necessarily developed by Apple, basically. So, we are, it's the same model with our marketplace. We foresee an environment where providers and partners are going to build these applications. We call it native application. And we are going to help them distribute these applications across cloud, everywhere in the world, potentially. And they don't need to worry about that. They don't need to worry about how these applications are going to be instantiated. We are going to help them to monetize these applications. So, that unlocks, you know, really, all the partner ecosystem that you have seen, you know, with something like the iPhone, right? It has created so many new companies that have developed these applications. >> Your detractors have criticized you for being a walled garden. I've actually used that term. I used terms like defacto standard, which are maybe less sensitive to you, but, nonetheless, we've seen defacto standards actually deliver value. I've talked to Frank Slootman about this, and he said, Dave, we deliver value, that's what we're all about. At the same time, he even said to me, and I want your thoughts on this, is, look, we have to embrace open source where it makes sense. You guys announced Apache Iceberg. So, what are your thoughts on that? Is that to enable a developer ecosystem? Why did you do Iceberg? >> Yeah, Iceberg is very important. So, just to give some context, Iceberg is an open table format. >> Right. >> Which was first developed by Netflix. And Netflix put it open source in the Apache community. So, we embraced that open source standard because it's widely used by many companies. And, also, many companies have really invested a lot of effort in building big data, Hadoop Solutions, or DataX Solution, and they want to use Snowflake. And they couldn't really use Snowflake, because all their data were in open format. So, we are embracing Iceberg to help these companies move through the cloud. But why we have been reluctant with direct access to data, direct access to data is a little bit of a problem for us. And the reason is when you direct access to data, now you have direct access to storage. Now you have to understand, for example, the specificity of one cloud versus the other. So, as soon as you start to have direct access to data, you lose your cloud data sync layer. You don't access data with API. When you have direct access to data, it's very hard to sync your data. Because you need to grant access, direct access to tools which are not protected. And you see a lot of hacking of data because of that. So, direct access to data is not serving well our customers, and that's why we have been reluctant to do that. Because it is not cloud diagnostic. You have to code that, you need a lot of intelligence, why APIs access, so we want open APIs. That's, I guess, the way we embrace openness, is by open API versus you access, directly, data. >> iPhone. >> Yeah, yeah, iPhone, APIs, you know. We define a set of APIs because APIs, you know, the implementation of the APIs can change, can improve. You can improve compression of data, for example. If you open direct access to data now, you cannot evolve. >> My point is, you made a promise, from governed, security, data sharing ecosystem. It works the same way, so that's the path that you've chosen. Benoit Dogeville, thank you so much for coming on theCube and participating in Supercloud 22, really appreciate that. >> Thank you, Dave. It was a great pleasure. >> All right, keep it right there, we'll be right back with our next segment, right after this short break. (electronic music)
SUMMARY :
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PJ Kirner, Illumio | AWS re:Inforce 2022
(upbeat music) >> Hi, everybody. We're wrapping up day two of AWS Re:Inforce 2022. This is theCUBE, my name is Dave Vellante. And one of the folks that we featured, one of the companies that we featured in the AWS startup showcase season two, episode four, was Illumio. And of course their here at the security theme event. PJ Kerner is CTO and Co-Founder of Illumio. Great to see you, welcome back to theCUBE. >> Thanks for having me. >> I always like to ask co-founders, people with co-founder in their titles, like go back to why you started the company. Let's go back to 2013. Why'd you start the company? >> Absolutely. Because back in 2013, one of the things that we sort of saw as technology trends, and it was mostly AWS was, there were really three things. One was dynamic workloads. People were putting workloads into production faster and faster. You talk about auto scale groups and now you talk about containers. Like things were getting faster and faster in terms of compute. Second thing was applications were getting more connected, right? The Netflix architecture is one define that kind of extreme example of hyper connectivity, but applications were, we'd call it the API economy or whatever, they were getting more connected. And the third problem back in 2013 was the problems around lateral movement. And at that point it was more around nation state actors and APTs that were in those environments for a lot of those customers. So those three trends were kind of, what do we need to do in security differently? And that's how Illumio started. >> So, okay, you say nation state that's obviously changed in the ROI of for hackers has become pretty good. And I guess your job is to reduce the ROI, but so what's the relationship PJ between the API economy, you talked about in that lateral movement? Are they kind of go hand in hand? >> They do. I think one thing that we have as a mission is, and I think it's really important to understand is to prevent breaches from becoming cyber disasters, right? And I use this metaphor around kind the submarine. And if you think about how submarines are built, submarines are built with water tight compartments inside the submarine. So when there is a physical breach, right, what happens? Like you get a torpedo or whatever, and it comes through the hall, you close off that compartment, there are redundant systems in place, but you close off that compartment, that one small thing you've lost, but the whole ship hasn't gone down and you sort of have survived. That's physical kind of resiliency and those same kind of techniques in terms of segmentation, compartmentalization inside your environments, is what makes good cyber resiliency. So prevent it from becoming a disaster. >> So you bring that micro segmentation analogy, the submarine analogy with micro segmentation to logical security, correct? >> Absolutely, yes. >> So that was your idea in 2013. Now we fast forward to 2022. It's no longer just nation states, things like ransomware are top of mind. I mean, everybody's like worried about what happened with solar winds and Log4j and on and on and on. So what's the mindset of the CISO today? >> I think you said it right. So ransomware, because if you think about the CIA triangle, confidentiality, integrity, availability, what does ransomware really does? It really attacks the availability problem, right? If you lock up all your laptops and can't actually do business anymore, you have an availability problem, right. They might not have stole your data, but they locked it up, but you can't do business, maybe you restore from backups. So that availability problem has made it more visible to CEOs and board level, like people. And so they've been talking about ransomware as a problem. And so that has given the CISO either more dollars, more authority to sort of attack that problem. And lateral movement is the primary way that ransomware gets around and becomes a disaster, as opposed to just locking up one machine when you lock up your entire environment, and thus some of the fear around colonial pipeline came in, that's when the disaster comes into play and you want to be avoiding that. >> Describe in more detail what you mean by lateral movement. I think it's implied, but you enter into a point and then instead of going, you're saying necessarily directly for the asset that you're going after, you're traversing the network, you're traversing other assets. Maybe you could describe that. >> Yeah, I mean, so often what happens is there's an initial point of breach. Like someone has a password or somebody clicked on a phishing link or something, and you have compromise into that environment, right? And then you might be compromised into a low level place that doesn't have a lot of data or is not worthwhile. Then you have to get from that place to data that is actually valuable, and that's where lateral movement comes into place. But also, I mean, you bring up a good point is like lateral movement prevention tools. Like, one way we've done some research around if you like, segmentation is, imagine putting up a maze inside your data center or cloud, right. So that, like how the attacker has to get from that initial breach to the crown jewels takes a lot longer when you have, a segmented environment, as opposed to, if you have a very flat network, it is just go from there to go find that asset. >> Hence, you just increase the denominator in the ROI equation and that just lowers the value for the hacker. They go elsewhere. >> It is an economic, you're right, it's all about economics. It's a time to target is what some our research like. So if you're a quick time to target, you're much easier to sort of get that value for the hacker. If it's a long time, they're going to get frustrated, they're going to stop and might not be economically viable. It's like the, you only have to run faster than the-- >> The two people with the bear chasing you, right. (laughs) Let's talk about zero trust. So it's a topic that prior to the pandemic, I think a lot of people thought it was a buzzword. I have said actually, it's become a mandate. Having said that others, I mean, AWS in particular kind of rolled their eyes and said, ah, we've always been zero trust. They were sort of forced into the discussion. What's your point of view on zero trust? Is it a buzzword? Does it have meaning, what is that meaning to Illumio? >> Well, for me there's actually two, there's two really important concepts. I mean, zero trust is a security philosophy. And so one is the idea of least privilege. And that's not a new idea. So when AWS says they've done it, they have embraced these privileges, a lot of good systems that have been built from scratch do, but not everybody has least privilege kind of controls everywhere. Secondly, least privilege is not about a one time thing. It is about a continuously monitoring. If you sort of take, people leave the company, applications get shut down. Like you need to shut down that access to actually continuously achieve that kind of least privilege stance. The other part that I think is really important that has come more recently is the assume breach mentality, right? And assume breach is something where you assume the attacker is, they've already clicked on, like stop trying to prevent. Well, I mean, you always still should probably prevent the people from clicking on the bad links, but from a security practitioner point of view, assume this has already happened, right. They're already inside. And then what do you have to do? Like back to what I was saying about setting up that maze ahead of time, right. To increase that time to target, that's something you have to do if you kind of assume breach and don't think, oh, a harder shell on my submarine is going to be the way I'm going to survive, right. So that mentality is, I will say is new and really important part of a zero trust philosophy. >> Yeah, so this is interesting because I mean, you kind of the old days, I don't know, decade plus ago, failure meant you get fired, breach meant you get fired. So we want to talk about it. And then of course that mentality had to change 'cause everybody's getting breached and this idea of least privilege. So in other words, if someone's not explicitly or a machine is not explicitly authorized to access an asset, they are not allowed, it's denied. So it's like Frank Slootman would say, if there's doubt, there's no doubt. And so is that right? >> It is. I mean, and if you think about it back to the disaster versus the breach, imagine they did get into an application. I mean, lamps stacks will have vulnerabilities from now to the end of time and people will get in. But what if you got in through a low value asset, 'cause these are some of the stories, you got in through a low value asset and you were sort of contained and you had access to that low value data. Let's say you even locked it up or you stole it all. Like it's not that important to the customer. That's different than when you pivot from that low value asset now into high value assets where it becomes much more catastrophic for those customers. So that kind of prevention, it is important. >> What do you make of this... Couple things, we've heard a lot about encrypt everything. It seems like these days again, in the old days, you'd love to encrypt everything, but there was always a performance hit, but we're hearing encrypt everything, John asked me the day John Furrier is like, okay, we're hearing about encrypting data at rest. What about data in motion? Now you hear about confidential computing and nitro and they're actually encrypting data in the flow. What do you make of that whole confidential computing down at the semiconductor level that they're actually doing things like enclaves and the arm architecture, how much of the problem does that address? How much does it still leave open? >> That's a hard question to answer-- >> But you're a CTO. So that's why I can ask you these questions. >> But I think it's the age old adage of defense in depth. I mean, I do think equivalent to what we're kind of doing from the networking point of view to do network segmentation. This is another layer of that compartmentalization and we'll sort of provide similar containment of breach. And that's really what we're looking for now, rather than prevention of the breach and rather than just detection of the breach, containment of that breach. >> Well, so it's actually similar philosophy brought to the wider network. >> Absolutely. And it needs to be brought at all levels. I think that's the, no one level is going to solve the problem. It's across all those levels is where you have to. >> What are the organizational implications of, it feels like the cloud is now becoming... I don't want to say the first layer of defense because it is if you're all in the cloud, but it's not, if you're a hybrid, but it's still, it's becoming increasingly a more important layer of defense. And then I feel like the CISO and the development team is like the next layer maybe audit is the third layer of defense. How are you seeing organizations sort of respond to that? The organizational roles changing, the CISO role changing. >> Well there's two good questions in there. So one is, there's one interesting thing that we are seeing about people. Like a lot of our customers are hybrid in their environment. They have a cloud, they have an on-prem environment and these two things need to work together. And in that case, I mean, the massive compute that you can be doing in the AWS actually increases the attack surface on that hybrid environment. So there's some challenges there and yes, you're absolutely right. The cloud brings some new tools to play, to sort of decrease that. But it's an interesting place we see where there's a attack surface that occurs between different infrastructure types, between AWS and on-prem of our environment. Now, the second part of your question was really around how the developers play into this. And I'm a big proponent of, I mean, security is kind of a team sport. And one of the things that we've done in some of our products is help people... So we all know the developers, like they know they're part of the security story, right? But they're not security professionals. They don't have all of the tools and all of the experience. And all of the red teaming time to sort of know where some of their mistakes might be made. So I am optimistic. They do their best, right. But what the security team needs is a way to not just tell them, like slap on the knuckles, like developer you're doing the wrong thing, but they really need a way to sort of say, okay, yes, you could do better. And here's some concrete ways that you can do better. So a lot of our systems kind of look at data, understand the data, analyze the data, and provide concrete recommendations. And there's a virtual cycle there. As long as you play the team sport, right. It's not a us versus them. It's like, how can we both win there? >> So this is a really interesting conversation because the developer all of a sudden is increasingly responsible for security. They got to worry about they're using containers. Now they got to worry about containers security. They got to worry about the run time. They got to worry about the platform. And to your point, it's like, okay, this burden is now on them. Not only do they have to be productive and produce awesome code, they got to make sure it's secure. So that role is changing. So are they up for the task? I mean, I got to believe that a lot of developers are like, oh, something else I have to worry about. So how are your customers resolving that? >> So I think they're up for the task. I think what is needed though, is a CISO and a security team again, who knows it's a team sport. Like some technologies adopted from the top down, like the CIO can say, here's what we're doing and then everybody has to do it. Some technologies adopted from the bottom up, right. It's where this individual team says, oh, we're using this thing and we're using these tools. Oh yeah, we're using containers and we're using this flavor of containers. And this other group uses Lambda services and so on. And the security team has to react because they can't mandate. They have to sort of work with those teams. So I see the best groups of people is where you have security teams who know they have to enable the developers and the developers who actually want to work with the security team. So it's the right kind of person, the right kind of CISO, right kind of security teams. It doesn't treat it as adversarial. And it works when they both work together. And that's where, your question is, how ingrained is that in the industry, that I can't say, but I know that does work. And I know that's the direction people are going. >> And I understand it's a spectrum, but I hear what you're saying. That is the best practice, the right organizational model, I guess it's cultural. I mean, it's not like there's some magic tool to make it all, the security team and the dev team collaboration tool, maybe there is, I don't know, but I think the mindset and the culture has to really be the starting point. >> Well, there is. I just talk about this idea. So however you sort of feel about DevOps and DevSecOps and so on, one core principle I see is really kind of empathy between like the developers and the operations folks, so the developers and the security team. And one way I actually, and we act like this at Illumio but one thing we do is like, you have to truly have empathy. You kind have to do somebody else's job, right. Not just like, think about it or talk about it, like do it. So there are places where the security team gets embedded deep in the organization where some of the developers get embedded in the operations work and that empathy. I know whether they go back to do what they were doing, what they learned about how the other side has to work. Some of the challenges, what they see is really valuable in sort of building that collaboration. >> So it's not job swapping, but it's embedding, is maybe how they gain that empathy. >> Exactly. And they're not experts in all those things, but do them take on those summer responsibilities, be accountable for some of those things. Now, not just do it on the side and go over somebody's shoulder, but like be accountable for something. >> That's interesting, not just observational, but actually say, okay, this is on you for some period of time. >> That is where you actually feel the pain of the other person, which is what is valuable. And so that's how you can build one of those cultures. I mean, you do need support all the way from the top, right. To be able to do that. >> For sure. And of course there are lightweight versions of that. Maybe if you don't have the stomach for... Lena Smart was on this morning, CISO of Mongo. And she was saying, she pairs like the security pros that can walk on water with the regular employees and they get to ask all these Colombo questions of the experts and the experts get to hear it and say, oh, I have to now explain this like I'm explaining it to a 10 year old, or maybe not a 10 year old, but a teenager, actually teenager's probably well ahead of us, but you know what I'm saying? And so that kind of cross correlation, and then essentially the folks that aren't security experts, they absorb enough and they can pass it on throughout the organization. And that's how she was saying she emphasizes culture building. >> And I will say, I think, Steve Smith, the CISO of AWS, like I've heard him talk a number of times and like, they do that here at like, they have some of the spirit and they've built it in and it's all the way from the top, right. And that's where if you have security over and a little silo off to the side, you're never going to do that. When the CEO supports the security professionals as a part of the business, that's when you can do the right thing. >> So you remember around the time that you and you guys started Illumio, the conversation was, security must be a board level topic. Yes, it should be, is it really, it was becoming that way. It wasn't there yet. It clearly is now, there's no question about it. >> No, ransomware. >> Right, of course. >> Let's thank ransomware. >> Right. Thank you. Maybe that's a silver lining. Now, the conversation is around, is it a organizational wide issue? And it needs to be, it needs to be, but it really isn't fully. I mean, how many organizations actually do that type of training, certainly large organizations do. It's part of the onboarding process, but even small companies are starting to do that now saying, okay, as part of the onboarding process, you got to watch this training video and sure that you've done it. And maybe that's not enough, but it's a start. >> Well, and I do think that's where, if we get back to zero trust, I mean, zero trust being a philosophy that you can adopt. I mean, we apply that kind of least privilege model to everything. And when people know that people know that this is something we do, right. That you only get access to things 'cause least privileges, you get access to absolutely to the things you need to do your job, but nothing more. And that applies to everybody in the organization. And when people sort of know this is the culture and they sort of work by that, like zero trust being that philosophy sort of helps infuse it into the organization. >> I agree with that, but I think the hard part of that in terms of implementing it for organizations is, companies like AWS, they have the tools, the people, the practitioners that can bring that to bear, many organizations don't. So it becomes an important prioritization exercise. So they have to say, okay, where do we want to apply that least privilege and apply that technology? 'Cause we don't have the resources to do it across the entire portfolio. >> And I'll give you a simple example of where it'll fail. So let's say, oh, we're least privilege, right. And so you asked for something to do your job and it takes four weeks for you to get that access. Guess what? Zero trust out the door at that organization. If you don't have again, the tools, right. To be able to walk that walk. And so it is something where you can't just say it, right. You do have to do it. >> So I feel like it's pyramid. It's got to start. I think it's got to be top down. Maybe not, I mean certainly bottom up from the developer mindset. No question about that. But in terms of where you start. Whether it's financial data or other confidential data, great. We're going to apply that here and we're not going to necessarily, it's a balance, where's the risk? Go hard on those places where there's the biggest risk. Maybe not create organizational friction where there's less risk and then over time, bring that in. >> And I think, I'll say one of the failure modes that we sort of seen around zero trust, if you go too big, too early, right. You actually have to find small wins in your organization and you pointed out some good ones. So focus on like, if you know where critical assets are, that's a good place to sort of start. Building it into the business as usual. So for example, one thing we recommend is people start in the developing zero trust segmentation policy during the development, or at least the test phase of rolling out a new application as you sort of work your way into production, as opposed to having to retro segment everything. So get it into the culture, either high value assets or work like that, or just pick something small. We've actually seen customers use our software to sort of like lock down RDP like back to ransomware, loves RDP lateral movement. So why can we go everywhere to everywhere with RDP? Well, you need it to sort of solve some problems, but just focus on that one little slice of your environment, one application and lock that down. That's a way to get started and that sort of attacks the ransomware problem. So there's lots of ways, but you got to make some demonstrable first steps and build that momentum over time to sort of get to that ultimate end goal. >> PJ Illumio has always been a thought leader in security generally in this topic specifically. So thanks for coming back on theCUBE. It's always great to have you guys. >> All right. Thanks, been great. >> All right. And thank you for watching. Keep it right there. This is Dave Vellante for theCUBE's coverage of AWS re:Inforce 2022 from Boston. We'll be right back. (upbeat music)
SUMMARY :
And one of the folks that we featured, like go back to why you And the third problem back in 2013 was in the ROI of for hackers And if you think about So that was your idea in 2013. And so that has given the for the asset that you're going after, and you have compromise into and that just lowers the It's like the, you only have into the discussion. And then what do you have to do? And so is that right? and you had access to that low value data. and the arm architecture, you these questions. detection of the breach, brought to the wider network. And it needs to be brought at all levels. CISO and the development team And all of the red teaming time And to your point, it's like, okay, And the security team has to react and the culture has to the other side has to work. So it's not job swapping, Now, not just do it on the side but actually say, okay, this is on you And so that's how you can and they get to ask all And that's where if you have security over around the time that you And it needs to be, it needs to be, to the things you need to do So they have to say, okay, And so you asked for But in terms of where you start. So get it into the culture, It's always great to have you guys. All right. And thank you for watching.
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Ed Walsh, ChaosSearch | AWS re:Inforce 2022
(upbeat music) >> Welcome back to Boston, everybody. This is the birthplace of theCUBE. In 2010, May of 2010 at EMC World, right in this very venue, John Furrier called it the chowder and lobster post. I'm Dave Vellante. We're here at RE:INFORCE 2022, Ed Walsh, CEO of ChaosSearch. Doing a drive by Ed. Thanks so much for stopping in. You're going to help me wrap up in our final editorial segment. >> Looking forward to it. >> I really appreciate it. >> Thank you for including me. >> How about that? 2010. >> That's amazing. It was really in this-- >> Really in this building. Yeah, we had to sort of bury our way in, tunnel our way into the Blogger Lounge. We did four days. >> Weekends, yeah. >> It was epic. It was really epic. But I'm glad they're back in Boston. AWS was going to do June in Houston. >> Okay. >> Which would've been awful. >> Yeah, yeah. No, this is perfect. >> Yeah. Thank God they came back. You saw Boston in summer is great. I know it's been hot, And of course you and I are from this area. >> Yeah. >> So how you been? What's going on? I mean, it's a little crazy out there. The stock market's going crazy. >> Sure. >> Having the tech lash, what are you seeing? >> So it's an interesting time. So I ran a company in 2008. So we've been through this before. By the way, the world's not ending, we'll get through this. But it is an interesting conversation as an investor, but also even the customers. There's some hesitation but you have to basically have the right value prop, otherwise things are going to get sold. So we are seeing longer sales cycles. But it's nothing that you can't overcome. But it has to be something not nice to have, has to be a need to have. But I think we all get through it. And then there is some, on the VC side, it's now buckle down, let's figure out what to do which is always a challenge for startup plans. >> In pre 2000 you, maybe you weren't a CEO but you were definitely an executive. And so now it's different and a lot of younger people haven't seen this. You've got interest rates now rising. Okay, we've seen that before but it looks like you've got inflation, you got interest rates rising. >> Yep. >> The consumer spending patterns are changing. You had 6$, $7 gas at one point. So you have these weird crosscurrents, >> Yup. >> And people are thinking, "Okay post-September now, maybe because of the recession, the Fed won't have to keep raising interest rates and tightening. But I don't know what to root for. It's like half full, half empty. (Ed laughing) >> But we haven't been in an environment with high inflation. At least not in my career. >> Right. Right. >> I mean, I got into 92, like that was long gone, right?. >> Yeah. >> So it is a interesting regime change that we're going to have to deal with, but there's a lot of analogies between 2008 and now that you still have to work through too, right?. So, anyway, I don't think the world's ending. I do think you have to run a tight shop. So I think the grow all costs is gone. I do think discipline's back in which, for most of us, discipline never left, right?. So, to me that's the name of the game. >> What do you tell just generally, I mean you've been the CEO of a lot of private companies. And of course one of the things that you do to retain people and attract people is you give 'em stock and it's great and everybody's excited. >> Yeah. >> I'm sure they're excited cause you guys are a rocket ship. But so what's the message now that, Okay the market's down, valuations are down, the trees don't grow to the moon, we all know that. But what are you telling your people? What's their reaction? How do you keep 'em motivated? >> So like anything, you want over communicate during these times. So I actually over communicate, you get all these you know, the Sequoia decks, 2008 and the recent... >> (chuckles) Rest in peace good times, that one right? >> I literally share it. Why? It's like, Hey, this is what's going on in the real world. It's going to affect us. It has almost nothing to do with us specifically, but it will affect us. Now we can't not pay attention to it. It does change how you're going to raise money, so you got to make sure you have the right runway to be there. So it does change what you do, but I think you over communicate. So that's what I've been doing and I think it's more like a student of the game, so I try to share it, and I say some appreciate it others, I'm just saying, this is normal, we'll get through this and this is what happened in 2008 and trust me, once the market hits bottom, give it another month afterwards. Then everyone says, oh, the bottom's in and we're back to business. Valuations don't go immediately back up, but right now, no one knows where the bottom is and that's where kind of the world's ending type of things. >> Well, it's interesting because you talked about, I said rest in peace good times >> Yeah >> that was the Sequoia deck, and the message was tighten up. Okay, and I'm not saying you shouldn't tighten up now, but the difference is, there was this period of two years of easy money and even before that, it was pretty easy money. >> Yeah. >> And so companies are well capitalized, they have runway so it's like, okay, I was talking to Frank Slootman about this now of course there are public companies, like we're not taking the foot off the gas. We're inherently profitable, >> Yeah. >> we're growing like crazy, we're going for it. You know? So that's a little bit of a different dynamic. There's a lot of good runway out there, isn't there? >> But also you look at the different companies that were either born or were able to power through those environments are actually better off. You come out stronger in a more dominant position. So Frank, listen, if you see what Frank's done, it's been unbelievable to watch his career, right?. In fact, he was at Data Domain, I was Avamar so, but look at what he's done since, he's crushed it. Right? >> Yeah. >> So for him to say, Hey, I'm going to literally hit the gas and keep going. I think that's the right thing for Snowflake and a right thing for a lot of people. But for people in different roles, I literally say that you have to take it seriously. What you can't be is, well, Frank's in a different situation. What is it...? How many billion does he have in the bank? So it's... >> He's over a billion, you know, over a billion. Well, you're on your way Ed. >> No, no, no, it's good. (Dave chuckles) Okay, I want to ask you about this concept that we've sort of we coined this term called Supercloud. >> Sure. >> You could think of it as the next generation of multi-cloud. The basic premises that multi-cloud was largely a symptom of multi-vendor. Okay. I've done some M&A, I've got some Shadow IT, spinning up, you know, Shadow clouds, projects. But it really wasn't a strategy to have a continuum across clouds. And now we're starting to see ecosystems really build, you know, you've used the term before, standing on the shoulders of giants, you've used that a lot. >> Yep. >> And so we're seeing that. Jerry Chen wrote a seminal piece on Castles in The Cloud, so we coined this term SuperCloud to connote this abstraction layer that hides the underlying complexities and primitives of the individual clouds and then adds value on top of it and can adjudicate and manage, irrespective of physical location, Supercloud. >> Yeah. >> Okay. What do you think about that concept?. How does it maybe relate to some of the things that you're seeing in the industry? >> So, standing on shoulders of giants, right? So I always like to do hard tech either at big company, small companies. So we're probably your definition of a Supercloud. We had a big vision, how to literally solve the core challenge of analytics at scale. How are you going to do that? You're not going to build on your own. So literally we're leveraging the primitives, everything you can get out of the Amazon cloud, everything get out of Google cloud. In fact, we're even looking at what it can get out of this Snowflake cloud, and how do we abstract that out, add value to it? That's where all our patents are. But it becomes a simplified approach. The customers don't care. Well, they care where their data is. But they don't care how you got there, they just want to know the end result. So you simplify, but you gain the advantages. One thing's interesting is, in this particular company, ChaosSearch, people try to always say, at some point the sales cycle they say, no way, hold on, no way that can be fast no way, or whatever the different issue. And initially we used to try to explain our technology, and I would say 60% was explaining the public, cloud capabilities and then how we, harvest those I guess, make them better add value on top and what you're able to get is something you couldn't get from the public clouds themselves and then how we did that across public clouds and then extracted it. So if you think about that like, it's the Shoulders of giants. But what we now do, literally to avoid that conversation because it became a lengthy conversation. So, how do you have a platform for analytics that you can't possibly overwhelm for ingest. All your messy data, no pipelines. Well, you leverage things like S3 and EC2, and you do the different security things. You can go to environments say, you can't possibly overrun me, I could not say that. If I didn't literally build on the shoulders giants of all these public clouds. But the value. So if you're going to do hard tech as a startup, you're going to build, you're going to be the principles of Supercloud. Maybe they're not the same size of Supercloud just looking at Snowflake, but basically, you're going to leverage all that, you abstract it out and that's where you're able to have a lot of values at that. >> So let me ask you, so I don't know if there's a strict definition of Supercloud, We sort of put it out to the community and said, help us define it. So you got to span multiple clouds. It's not just running in each cloud. There's a metadata layer that kind of understands where you're pulling data from. Like you said you can pull data from Snowflake, it sounds like we're not running on Snowflake, correct? >> No, complimentary to them in their different customers. >> Yeah. Okay. >> They want to build on top of a data platform, data apps. >> Right. And of course they're going cross cloud. >> Right. >> Is there a PaaS layer in there? We've said there's probably a Super PaaS layer. You're probably not doing that, but you're allowing people to bring their own, bring your own PaaS sort of thing maybe. >> So we're a little bit different but basically we publish open APIs. We don't have a user interface. We say, keep the user interface. Again, we're solving the challenge of analytics at scale, we're not trying to retrain your analytics, either analysts or your DevOps or your SOV or your Secop team. They use the tools they already use. Elastic search APIs, SQL APIs. So really they program, they build applications on top of us, Equifax is a good example. Case said it coming out later on this week, after 18 months in production but, basically they're building, we provide the abstraction layer, the quote, I'm going to kill it, Jeff Tincher, who owns all of SREs worldwide, said to the effect of, Hey I'm able to rethink what I do for my data pipelines. But then he also talked about how, that he really doesn't have to worry about the data he puts in it. We deal with that. And he just has to, just query on the other side. That simplicity. We couldn't have done that without that. So anyway, what I like about the definition is, if you were going to do something harder in the world, why would you try to rebuild what Amazon, Google and Azure or Snowflake did? You're going to add things on top. We can still do intellectual property. We're still doing patents. So five grand patents all in this. But literally the abstraction layer is the simplification. The end users do not want to know that complexity, even though they ask the questions. >> And I think too, the other attribute is it's ecosystem enablement. Whereas I think, >> Absolutely >> in general, in the Multicloud 1.0 era, the ecosystem wasn't thinking about, okay, how do I build on top and abstract that. So maybe it is Multicloud 2.0, We chose to use Supercloud. So I'm wondering, we're at the security conference, >> RE: INFORCE is there a security Supercloud? Maybe Snyk has the developer Supercloud or maybe Okta has the identity Supercloud. I think CrowdStrike maybe not. Cause CrowdStrike competes with Microsoft. So maybe, because Microsoft, what's interesting, Merritt Bear was just saying, look, we don't show up in the spending data for security because we're not charging for most of our security. We're not trying to make a big business. So that's kind of interesting, but is there a potential for the security Supercloud? >> So, I think so. But also, I'll give you one thing I talked to, just today, at least three different conversations where everyone wants to log data. It's a little bit specific to us, but basically they want to do the security data lake. The idea of, and Snowflake talks about this too. But the idea of putting all the data in one repository and then how do you abstract out and get value from it? Maybe not the perfect, but it becomes simple to do but hard to get value out. So the different players are going to do that. That's what we do. We're able to, once you land it in your S3 or it doesn't matter, cloud of choice, simple storage, we allow you to get after that data, but we take the primitives and hide them from you. And all you do is query the data and we're spinning up stateless computer to go after it. So then if I look around the floor. There's going to be a bunch of these players. I don't think, why would someone in this floor try to recreate what Amazon or Google or Azure had. They're going to build on top of it. And now the key thing is, do you leave it in standard? And now we're open APIs. People are building on top of my open APIs or do you try to put 'em in a walled garden? And they're in, now your Supercloud. Our belief is, part of it is, it needs to be open access and let you go after it. >> Well. And build your applications on top of it openly. >> They come back to snowflake. That's what Snowflake's doing. And they're basically saying, Hey come into our proprietary environment. And the benefit is, and I think both can win. There's a big market. >> I agree. But I think the benefit of Snowflake's is, okay, we're going to have federated governance, we're going to have data sharing, you're going to have access to all the ecosystem players. >> Yep. >> And as everything's going to be controlled and you know what you're getting. The flip side of that is, Databricks is the other end >> Yeah. >> of that spectrum, which is no, no, you got to be open. >> Yeah. >> So what's going to happen, well what's happening clearly, is Snowflake's saying, okay we've got Snowpark. we're going to allow Python, we're going to have an Apache Iceberg. We're going to have open source tooling that you can access. By the way, it's not going to be as good as our waled garden where the flip side of that is you get Databricks coming at it from a data science and data engineering perspective. And there's a lot of gaps in between, aren't there? >> And I think they both win. Like for instance, so we didn't do Snowpark integration. But we work with people building data apps on top of Snowflake or data bricks. And what we do is, we can add value to that, or what we've done, again, using all the Supercloud stuff we're done. But we deal with the unstructured data, the four V's coming at you. You can't pipeline that to save. So we actually could be additive. As they're trying to do like a security data cloud inside of Snowflake or do the same thing in Databricks. That's where we can play. Now, we play with them at the application level that they get some data from them and some data for us. But I believe there's a partnership there that will do it inside their environment. To us they're just another large scaler environment that my customers want to get after data. And they want me to abstract it out and give value. >> So it's another repository to you. >> Yeah. >> Okay. So I think Snowflake recently added support for unstructured data. You chose not to do Snowpark because why? >> Well, so the way they're doing the unstructured data is not bad. It's JSON data. Basically, This is the dilemma. Everyone wants their application developers to be flexible, move fast, securely but just productivity. So you get, give 'em flexibility. The problem with that is analytics on the end want to be structured to be performant. And this is where Snowflake, they have to somehow get that raw data. And it's changing every day because you just let the developers do what they want now, in some structured base, but do what you need to do your business fast and securely. So it completely destroys. So they have large customers trying to do big integrations for this messy data. And it doesn't quite work, cause you literally just can't make the pipelines work. So that's where we're complimentary do it. So now, the particular integration wasn't, we need a little bit deeper integration to do that. So we're integrating, actually, at the data app layer. But we could, see us and I don't, listen. I think Snowflake's a good actor. They're trying to figure out what's best for the customers. And I think we just participate in that. >> Yeah. And I think they're trying to figure out >> Yeah. >> how to grow their ecosystem. Because they know they can't do it all, in fact, >> And we solve the key thing, they just can't do certain things. And we do that well. Yeah, I have SQL but that's where it ends. >> Yeah. >> I do the messy data and how to play with them. >> And when you talk to one of their founders, anyway, Benoit, he comes on the cube and he's like, we start with simple. >> Yeah. >> It reminds me of the guy's some Pure Storage, that guy Coz, he's always like, no, if it starts to get too complicated. So that's why they said all right, we're not going to start out trying to figure out how to do complex joins and workload management. And they turn that into a feature. So like you say, I think both can win. It's a big market. >> I think it's a good model. And I love to see Frank, you know, move. >> Yeah. I forgot So you AVMAR... >> In the day. >> You guys used to hate each other, right? >> No, no, no >> No. I mean, it's all good. >> But the thing is, look what he's done. Like I wouldn't bet against Frank. I think it's a good message. You can see clients trying to do it. Same thing with Databricks, same thing with BigQuery. We get a lot of same dynamic in BigQuery. It's good for a lot of things, but it's not everything you need to do. And there's ways for the ecosystem to play together. >> Well, what's interesting about BigQuery is, it is truly cloud native, as is Snowflake. You know, whereas Amazon Redshift was sort of Parexel, it's cobbled together now. It's great engineering, but BigQuery gets a lot of high marks. But again, there's limitations to everything. That's why companies like yours can exist. >> And that's why.. so back to the Supercloud. It allows me as a company to participate in that because I'm leveraging all the underlying pieces. Which we couldn't be doing what we're doing now, without leveraging the Supercloud concepts right, so... >> Ed, I really appreciate you coming by, help me wrap up today in RE:INFORCE. Always a pleasure seeing you, my friend. >> Thank you. >> All right. Okay, this is a wrap on day one. We'll be back tomorrow. I'll be solo. John Furrier had to fly out but we'll be following what he's doing. This is RE:INFORCE 2022. You're watching theCUBE. I'll see you tomorrow.
SUMMARY :
John Furrier called it the How about that? It was really in this-- Yeah, we had to sort of bury our way in, But I'm glad they're back in Boston. No, this is perfect. And of course you and So how you been? But it's nothing that you can't overcome. but you were definitely an executive. So you have these weird crosscurrents, because of the recession, But we haven't been in an environment Right. that was long gone, right?. I do think you have to run a tight shop. the things that you do But what are you telling your people? 2008 and the recent... So it does change what you do, and the message was tighten up. the foot off the gas. So that's a little bit But also you look at I literally say that you you know, over a billion. Okay, I want to ask you about this concept you know, you've used the term before, of the individual clouds and to some of the things So I always like to do hard tech So you got to span multiple clouds. No, complimentary to them of a data platform, data apps. And of course people to bring their own, the quote, I'm going to kill it, And I think too, the other attribute is in the Multicloud 1.0 era, for the security Supercloud? And now the key thing is, And build your applications And the benefit is, But I think the benefit of Snowflake's is, you know what you're getting. which is no, no, you got to be open. that you can access. You can't pipeline that to save. You chose not to do Snowpark but do what you need to do they're trying to figure out how to grow their ecosystem. And we solve the key thing, I do the messy data And when you talk to So like you say, And I love to see Frank, you know, move. So you AVMAR... it's all good. but it's not everything you need to do. there's limitations to everything. so back to the Supercloud. Ed, I really appreciate you coming by, I'll see you tomorrow.
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